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RSS2023 Vol. 42, No. 7
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2023, 42(7): 985-992.
doi: 10.13433/j.cnki.1003-8728.20220053
PDF 5712KB
Abstract:
The most widely used noise-separating methods are transfer function method and multiple linear regression method. Both methods consider that the total engine′s noises include two categories, combustion and mechanical noises, by which the motor noise are hypothetically considered as mechanical noise. However noises from these two methods still comprise indirect combustion noise as a result of piston slapping as well. This research is conducted under the condition of 4 500 r/min and 2 000 r/min to acquire the total noises, cylinder pressure and vibration data of a gasoline engine, which also uses the time window of -15-85 ℃A ATDC to cut out the target signal and then separate the mechanical noise under motor test. The signal of cylinder pressure and combustion noise help to develop Wiener filter to apply to combustion noise so that it can achieve the separation between indirect and direct combustion noises. The result proves that most of the indirect noise are in the region of 500-8 000 Hz.
The most widely used noise-separating methods are transfer function method and multiple linear regression method. Both methods consider that the total engine′s noises include two categories, combustion and mechanical noises, by which the motor noise are hypothetically considered as mechanical noise. However noises from these two methods still comprise indirect combustion noise as a result of piston slapping as well. This research is conducted under the condition of 4 500 r/min and 2 000 r/min to acquire the total noises, cylinder pressure and vibration data of a gasoline engine, which also uses the time window of -15-85 ℃A ATDC to cut out the target signal and then separate the mechanical noise under motor test. The signal of cylinder pressure and combustion noise help to develop Wiener filter to apply to combustion noise so that it can achieve the separation between indirect and direct combustion noises. The result proves that most of the indirect noise are in the region of 500-8 000 Hz.
2023, 42(7): 993-999.
doi: 10.13433/j.cnki.1003-8728.20230215
Abstract:
In order to solve the difficulty of achieving low energy consumption and high efficiency operation in the separation process of hydrocyclones, a conical overflow pipe slit structure is proposed, and the design and analysis of the number of slit layers, seam position and seam angle of the conical overflow pipe are optimized by studying the test and response surface model, taking the separation efficiency and pressure drop of the hydrocyclone as the objective function. For the Ø100 mm hydrocyclone, the fine powder of glass beads with a median particle size of 41.52 μm was used, and the test results showed that the slit positioning size within a certain range had little effect on the separation performance of the hydrocyclone, and the slit angle and number of layers had a significant effect on the separation performance of the hydrocyclone. The optimal parameter combination of improved hydrocyclone is 3 slit-layers, 5.3 mm slit positioning size and 58° slit angle of the overflow pipe. Compared with the conventional hydrocyclone, after the inlet flow rate is optimized at 920 mL/s, the separation efficiency of the hydrocyclone reaches the highest, with an increase rate of 0.26% and a pressure drop reduction rate of 24.88%, which shows that the energy-saving effect is remarkable.
In order to solve the difficulty of achieving low energy consumption and high efficiency operation in the separation process of hydrocyclones, a conical overflow pipe slit structure is proposed, and the design and analysis of the number of slit layers, seam position and seam angle of the conical overflow pipe are optimized by studying the test and response surface model, taking the separation efficiency and pressure drop of the hydrocyclone as the objective function. For the Ø100 mm hydrocyclone, the fine powder of glass beads with a median particle size of 41.52 μm was used, and the test results showed that the slit positioning size within a certain range had little effect on the separation performance of the hydrocyclone, and the slit angle and number of layers had a significant effect on the separation performance of the hydrocyclone. The optimal parameter combination of improved hydrocyclone is 3 slit-layers, 5.3 mm slit positioning size and 58° slit angle of the overflow pipe. Compared with the conventional hydrocyclone, after the inlet flow rate is optimized at 920 mL/s, the separation efficiency of the hydrocyclone reaches the highest, with an increase rate of 0.26% and a pressure drop reduction rate of 24.88%, which shows that the energy-saving effect is remarkable.
2023, 42(7): 1000-1008.
doi: 10.13433/j.cnki.1003-8728.20220073
Abstract:
Underground pipeline detection robot (UPDR) equipped with ground penetrating radar (GPR) can effectively realize the comprehensive detection of underground pipeline′s internal and external diseases. In order to improve its performance and mechanical structure, dynamic analysis should be firstly operated. In this paper, dynamic simulation analysis of GPR-UPDR for 600 mm pipeline based on Adams and experimental verification of simulation results are carried out. In detail, the stress of robot′s key components, such as rolling wheels, torsional springs, axles of rocker and antenna shells are analyzed, when it works in the underground pipeline with obstacles on inner wall. The results show that the stress in the whole process and its variation amplitude at the stage of passing through obstacles of bottom detectors′ key components are greater than those of top detector. The stress of bottom detectors′ rolling wheels has great differences. Specifically, the upper rolling wheels of bottom detectors don′t work when they don′t contact with obstacles, and the whole force is concentrated on lower rolling wheels. In addition, when robot collides with raised obstacles, the stress of the mentioned key components increase immediately by 3~60 times with simulated traction of 500 N, and the antenna shell bears a great impact force of 1 700 N. The analysis results provide scientific basis for optimal design, material selection and machining process of GPR-UPDR, especially key components of detectors.
Underground pipeline detection robot (UPDR) equipped with ground penetrating radar (GPR) can effectively realize the comprehensive detection of underground pipeline′s internal and external diseases. In order to improve its performance and mechanical structure, dynamic analysis should be firstly operated. In this paper, dynamic simulation analysis of GPR-UPDR for 600 mm pipeline based on Adams and experimental verification of simulation results are carried out. In detail, the stress of robot′s key components, such as rolling wheels, torsional springs, axles of rocker and antenna shells are analyzed, when it works in the underground pipeline with obstacles on inner wall. The results show that the stress in the whole process and its variation amplitude at the stage of passing through obstacles of bottom detectors′ key components are greater than those of top detector. The stress of bottom detectors′ rolling wheels has great differences. Specifically, the upper rolling wheels of bottom detectors don′t work when they don′t contact with obstacles, and the whole force is concentrated on lower rolling wheels. In addition, when robot collides with raised obstacles, the stress of the mentioned key components increase immediately by 3~60 times with simulated traction of 500 N, and the antenna shell bears a great impact force of 1 700 N. The analysis results provide scientific basis for optimal design, material selection and machining process of GPR-UPDR, especially key components of detectors.
2023, 42(7): 1009-1015.
doi: 10.13433/j.cnki.1003-8728.20220072
Abstract:
Supporting type tubular busbars often encounter wind-induced vibration problems during long-term service in the field. Numerical simulation methods are used to analyze the wind vibration characteristics of the supported tubular busbar and the influence of damping on vibration. The natural frequency and mode shape of the busbar under ideal conditions and the deformation characteristics when subjected to wind load are calculated. The static algorithm and the dynamic algorithm are respectively used analyze the effect of the damping line on the wind resistance of the busbar. Furthermore, the dynamic characteristics of the full-scale supported tubular busbar structure under wind load are calculated, and the influence of the damping line and the busbar structural damping against wind vibration is analyzed. The results show that in an ideal state, the damping line can effectively reduce the deformation of the busbar after wind load. However, in the real full-size tubular bus structure, the structural damping formed by structural connections is more significant than the effect of the damping wire on the wind vibration of the busbar.
Supporting type tubular busbars often encounter wind-induced vibration problems during long-term service in the field. Numerical simulation methods are used to analyze the wind vibration characteristics of the supported tubular busbar and the influence of damping on vibration. The natural frequency and mode shape of the busbar under ideal conditions and the deformation characteristics when subjected to wind load are calculated. The static algorithm and the dynamic algorithm are respectively used analyze the effect of the damping line on the wind resistance of the busbar. Furthermore, the dynamic characteristics of the full-scale supported tubular busbar structure under wind load are calculated, and the influence of the damping line and the busbar structural damping against wind vibration is analyzed. The results show that in an ideal state, the damping line can effectively reduce the deformation of the busbar after wind load. However, in the real full-size tubular bus structure, the structural damping formed by structural connections is more significant than the effect of the damping wire on the wind vibration of the busbar.
2023, 42(7): 1016-1020.
doi: 10.13433/j.cnki.1003-8728.20220003
Abstract:
According to the characteristics of acoustic emission signal with high sensitivity to early damage and frequency bandwidth, a method coupling with acoustic emission signal and convolutional neural network was proposed to realize the RUL prediction of rolling bearings. The bearing RUL prediction method mainly includes: sub-band filtering and feature value extraction of the original signal to obtain a high-dimensional feature set; combining with the high-dimensional feature set into a two-dimensional neuron as the input of a convolutional neural network, and constructing and training the network to achieve the prediction of remaining life. The feasibility of the prediction method is verified by using the experimental, and it has high accuracy. The coupling use of convolutional neural networks not only solves the problem of large number of eigenvalues and how to reasonably use high-dimensional features, but also obtains the better RUL prediction results.
According to the characteristics of acoustic emission signal with high sensitivity to early damage and frequency bandwidth, a method coupling with acoustic emission signal and convolutional neural network was proposed to realize the RUL prediction of rolling bearings. The bearing RUL prediction method mainly includes: sub-band filtering and feature value extraction of the original signal to obtain a high-dimensional feature set; combining with the high-dimensional feature set into a two-dimensional neuron as the input of a convolutional neural network, and constructing and training the network to achieve the prediction of remaining life. The feasibility of the prediction method is verified by using the experimental, and it has high accuracy. The coupling use of convolutional neural networks not only solves the problem of large number of eigenvalues and how to reasonably use high-dimensional features, but also obtains the better RUL prediction results.
2023, 42(7): 1021-1028.
doi: 10.13433/j.cnki.1003-8728.20220050
Abstract:
Aiming at the fact that rolling bearing signal has a lot of noise and its fault features are difficult to extract, and the dual-tree complex wavelet packet (DCWP) can reduce the loss of useful information, a fault diagnosis method combining DCWP and permutation entropy (PE) is proposed in this paper. Firstly, the average permutation entropy of the components of different layers is calculated by combining DCWP and PE, and the optimal number of layers is determined. Secondly, the kurtosis value is used as the index to select the optimal component after decomposition of the noise signal. Finally, the optimal component is analyzed by envelope analysis to extract the fault characteristic frequency. The combination of DCWP and PE to determine the best number of layers avoids the over-decomposition and under-decomposition of the original signal and can effectively extract the fault features of rolling bearings.
Aiming at the fact that rolling bearing signal has a lot of noise and its fault features are difficult to extract, and the dual-tree complex wavelet packet (DCWP) can reduce the loss of useful information, a fault diagnosis method combining DCWP and permutation entropy (PE) is proposed in this paper. Firstly, the average permutation entropy of the components of different layers is calculated by combining DCWP and PE, and the optimal number of layers is determined. Secondly, the kurtosis value is used as the index to select the optimal component after decomposition of the noise signal. Finally, the optimal component is analyzed by envelope analysis to extract the fault characteristic frequency. The combination of DCWP and PE to determine the best number of layers avoids the over-decomposition and under-decomposition of the original signal and can effectively extract the fault features of rolling bearings.
2023, 42(7): 1029-1034.
doi: 10.13433/j.cnki.1003-8728.20220046
Abstract:
Due to the long training time of the rotating machinery fault diagnosis model, it is easy to overfit and the traditional extreme learning machine can only handle batch data, and the effectiveness is poor. A fault diagnosis method for rotating machinery based on deep online wavelet extreme learning machine is proposed. Introducing the idea of autoencoder into the wavelet extreme learning machine, stacking to form WELM-AE converts the underlying fault features to more abstract and advanced features. And the online extreme learning machine is used as the top-level classifier for fault identification. The experimental results verify the feasibility of the method in the fault diagnosis of rotating machinery, inheriting the characteristics of the fast training speed of the extreme learning machine, and having a higher accuracy rate than BP, SVM, SAE and CNN.
Due to the long training time of the rotating machinery fault diagnosis model, it is easy to overfit and the traditional extreme learning machine can only handle batch data, and the effectiveness is poor. A fault diagnosis method for rotating machinery based on deep online wavelet extreme learning machine is proposed. Introducing the idea of autoencoder into the wavelet extreme learning machine, stacking to form WELM-AE converts the underlying fault features to more abstract and advanced features. And the online extreme learning machine is used as the top-level classifier for fault identification. The experimental results verify the feasibility of the method in the fault diagnosis of rotating machinery, inheriting the characteristics of the fast training speed of the extreme learning machine, and having a higher accuracy rate than BP, SVM, SAE and CNN.
2023, 42(7): 1035-1043.
doi: 10.13433/j.cnki.1003-8728.20220061
Abstract:
Due to advantages of simple structure and large starting torque of switched reluctance motor (SRM), it has been used in many fields. However, SRM shows lower torque density and larger vibration noise compared with permanent magnet(PM) motor. In this paper, a novel segmentation stator SRM is proposed, which had PMs located on both sides of stator block to form segmented stator hybrid excitation SRM (SSHESRM). Firstly, the topology structure and working principle of SSHESRM was introduced, and proven the intensified effect of PMs to air-gap flux density based on magnetic equivalent circuit. Meanwhile, the finite element method was used to analyze impact of PMs on torque density and obtained the optimal thickness of PMs. Then, the model of rectangular slot of ex-rotor teeth was established to analyze principle of reducing the radial electromagnetic force, meanwhile, the optimal size is obtained by FEM to different width and depth. Finally, it is proved that the average torque of SSHESRM is increased by 34.2% and torque ripple is decreased by 19.3% as well as the radial force wave in the overlap area between stator and rotor is reduced by 12.5%, which can effectively reduce radial electromagnetic force and improved vibration and noise.
Due to advantages of simple structure and large starting torque of switched reluctance motor (SRM), it has been used in many fields. However, SRM shows lower torque density and larger vibration noise compared with permanent magnet(PM) motor. In this paper, a novel segmentation stator SRM is proposed, which had PMs located on both sides of stator block to form segmented stator hybrid excitation SRM (SSHESRM). Firstly, the topology structure and working principle of SSHESRM was introduced, and proven the intensified effect of PMs to air-gap flux density based on magnetic equivalent circuit. Meanwhile, the finite element method was used to analyze impact of PMs on torque density and obtained the optimal thickness of PMs. Then, the model of rectangular slot of ex-rotor teeth was established to analyze principle of reducing the radial electromagnetic force, meanwhile, the optimal size is obtained by FEM to different width and depth. Finally, it is proved that the average torque of SSHESRM is increased by 34.2% and torque ripple is decreased by 19.3% as well as the radial force wave in the overlap area between stator and rotor is reduced by 12.5%, which can effectively reduce radial electromagnetic force and improved vibration and noise.
2023, 42(7): 1044-1049.
doi: 10.13433/j.cnki.1003-8728.20220064
Abstract:
Aiming at the difficulty of extracting the encoder signal feature order of the sun gear with root crack at low speed, a feature extraction detection method is proposed based on the difference of the fault feature index in this paper. First, the obtained encoder signal is processed into an instantaneous angular speed(IAS)signal through forward difference, and the obtained IAS signal is divided into subbands according to the 1/3-binary tree. Then, the envelope analysis of each narrowband signal is carried out, and the harmonic significance index(HSI)of each subband of IAS signal in normal and fault states is obtained respectively, from which the relative ratio r can be calculated. And, the value of r is used to select the frequency band with rich fault information. Finally, the processed signal is filtered in the selected frequency band, and the spectrum analysis is performed after the envelope is extracted to extract the fault features. The analysis of the measured encoder signal of the sun gear with root crack fault shows that the method can effectively extract the features of the sun gear faults.
Aiming at the difficulty of extracting the encoder signal feature order of the sun gear with root crack at low speed, a feature extraction detection method is proposed based on the difference of the fault feature index in this paper. First, the obtained encoder signal is processed into an instantaneous angular speed(IAS)signal through forward difference, and the obtained IAS signal is divided into subbands according to the 1/3-binary tree. Then, the envelope analysis of each narrowband signal is carried out, and the harmonic significance index(HSI)of each subband of IAS signal in normal and fault states is obtained respectively, from which the relative ratio r can be calculated. And, the value of r is used to select the frequency band with rich fault information. Finally, the processed signal is filtered in the selected frequency band, and the spectrum analysis is performed after the envelope is extracted to extract the fault features. The analysis of the measured encoder signal of the sun gear with root crack fault shows that the method can effectively extract the features of the sun gear faults.
2023, 42(7): 1050-1054.
doi: 10.13433/j.cnki.1003-8728.20220057
Abstract:
Aiming at the common primary steel spring fracture fault of metro vehicle bogie, the parameter change after steel spring fracture is analyzed, and then the dynamic simulation model for the metro vehicle is established. Considering two failure types of spring end support ring fracture and spring middle effective ring fracture, the safety indexes of fault vehicle and normal vehicle passing through the twisted track are compared and analyzed. The results show that the steel spring fracture has obvious influence on the vertical related safety indexes of vehicles, mainly the wheel unloading ratio and the derailment coefficient, and has slight impact on the wheel axle lateral force. In addition, different types of steel spring fracture have similar influence on the vehicle safety index, but the values are different. The steel spring fracture can worsen the vehicle safety index, but all safety indexes are smaller than the corresponding limit values, which meet the requirements of the standard.
Aiming at the common primary steel spring fracture fault of metro vehicle bogie, the parameter change after steel spring fracture is analyzed, and then the dynamic simulation model for the metro vehicle is established. Considering two failure types of spring end support ring fracture and spring middle effective ring fracture, the safety indexes of fault vehicle and normal vehicle passing through the twisted track are compared and analyzed. The results show that the steel spring fracture has obvious influence on the vertical related safety indexes of vehicles, mainly the wheel unloading ratio and the derailment coefficient, and has slight impact on the wheel axle lateral force. In addition, different types of steel spring fracture have similar influence on the vehicle safety index, but the values are different. The steel spring fracture can worsen the vehicle safety index, but all safety indexes are smaller than the corresponding limit values, which meet the requirements of the standard.
2023, 42(7): 1055-1062.
doi: 10.13433/j.cnki.1003-8728.20220010
Abstract:
Reasonable injection process is of great significance to improve the production efficiency and reduce the defects of die casting. In this paper, a decision method based on grey correlation and D-S evidence theory is proposed for selecting injection parameters in die casting. which is more scientific than the trial-and-error method relying on expert experience in the past. The experimental results show that the present method is not only accurate but also efficient.
Reasonable injection process is of great significance to improve the production efficiency and reduce the defects of die casting. In this paper, a decision method based on grey correlation and D-S evidence theory is proposed for selecting injection parameters in die casting. which is more scientific than the trial-and-error method relying on expert experience in the past. The experimental results show that the present method is not only accurate but also efficient.
2023, 42(7): 1063-1069.
doi: 10.13433/j.cnki.1003-8728.20220045
Abstract:
Abrasive water jet milling technology has large flexibility and complex processing parameters, so its machining performance is difficult to effectively control. To solve this problem, firstly, the influence of the typical process parameters on the milling depth and surface roughness in abrasive water jet milling of titanium alloy is investigated with the response surface methodology (RSM). Then an empirical model is established with the traditional regression method. Secondly, a semi empirical model for milling depth and surface roughness is established in terms of the abrasive wear theory, Gaussian profile model and surface forming analysis. Thirdly, the coefficients are calibrated by using the experimental data. Eventually the two models are verified and compared with the experiments. The results show that the average error of the two prediction models is below 15%. Comparing with the empirical model, the semi empirical model can not only explain the influence of the parameters and milling mechanism, but also ensure the accuracy and stability of prediction, which is of great value for controlling the milling depth and surface quality.
Abrasive water jet milling technology has large flexibility and complex processing parameters, so its machining performance is difficult to effectively control. To solve this problem, firstly, the influence of the typical process parameters on the milling depth and surface roughness in abrasive water jet milling of titanium alloy is investigated with the response surface methodology (RSM). Then an empirical model is established with the traditional regression method. Secondly, a semi empirical model for milling depth and surface roughness is established in terms of the abrasive wear theory, Gaussian profile model and surface forming analysis. Thirdly, the coefficients are calibrated by using the experimental data. Eventually the two models are verified and compared with the experiments. The results show that the average error of the two prediction models is below 15%. Comparing with the empirical model, the semi empirical model can not only explain the influence of the parameters and milling mechanism, but also ensure the accuracy and stability of prediction, which is of great value for controlling the milling depth and surface quality.
2023, 42(7): 1070-1080.
doi: 10.13433/j.cnki.1003-8728.20230241
Abstract:
In the Web2.0 environment, more and more consumers are purchasing products on online platforms and expressing their feelings through online reviews. A large amount of online review data contains valuable information, and enterprises can use online reviews to identify and analyze user requirements for subsequent product improvement. This article takes review data from Lenovo laptops as the research object and proposes a user requirements identification and evolution analysis model based on online reviews mining. The SnowNLP model, Kano model, and LDA model are used to classify, identify, analyze feature sentiment pairs, and analyze time series of user reviews. The results show that according to the sentimental trend prediction, customers′ sentiment values for type 1, type 2, and type 3 show an upward trend, while the sentiment values for type 4 show a downward trend; In addition, users pay more attention to the appearance of the product and the gaming experience. The research has improved the research methods and models of online reviews from a time perspective, providing reference value for analyzing user requirements for products and predicting user sentimental trends towards products.
In the Web2.0 environment, more and more consumers are purchasing products on online platforms and expressing their feelings through online reviews. A large amount of online review data contains valuable information, and enterprises can use online reviews to identify and analyze user requirements for subsequent product improvement. This article takes review data from Lenovo laptops as the research object and proposes a user requirements identification and evolution analysis model based on online reviews mining. The SnowNLP model, Kano model, and LDA model are used to classify, identify, analyze feature sentiment pairs, and analyze time series of user reviews. The results show that according to the sentimental trend prediction, customers′ sentiment values for type 1, type 2, and type 3 show an upward trend, while the sentiment values for type 4 show a downward trend; In addition, users pay more attention to the appearance of the product and the gaming experience. The research has improved the research methods and models of online reviews from a time perspective, providing reference value for analyzing user requirements for products and predicting user sentimental trends towards products.
2023, 42(7): 1081-1087.
doi: 10.13433/j.cnki.1003-8728.20220059
Abstract:
Since the occurrence of chatter in milling may greatly reduce the machining quality of workpieces, the efficient and accurate identification of milling vibration state has always been one of the hot issues in chatter research. Based on the LetNet-5 classical convolution network, a one-dimensional convolution network model is proposed, which can directly process and identify milling force signals in the time domain. To solve the problems such as less semaphore and unbalanced data, the overlapping-random collaborative sampling method is adopted to process data. The T-distribution random neighborhood embedding technology is applied to visualize the learning process of the training set model and verify the end-to-end learning objectives. Comparing the recognition strategy of the standard support vector machine (SVM) with that of the convolution neural network, the proposed model achieves the highest accuracy of 96.17% on the test set. The recognition results show that the proposed model is simple, fast and accurate.
Since the occurrence of chatter in milling may greatly reduce the machining quality of workpieces, the efficient and accurate identification of milling vibration state has always been one of the hot issues in chatter research. Based on the LetNet-5 classical convolution network, a one-dimensional convolution network model is proposed, which can directly process and identify milling force signals in the time domain. To solve the problems such as less semaphore and unbalanced data, the overlapping-random collaborative sampling method is adopted to process data. The T-distribution random neighborhood embedding technology is applied to visualize the learning process of the training set model and verify the end-to-end learning objectives. Comparing the recognition strategy of the standard support vector machine (SVM) with that of the convolution neural network, the proposed model achieves the highest accuracy of 96.17% on the test set. The recognition results show that the proposed model is simple, fast and accurate.
2023, 42(7): 1088-1097.
doi: 10.13433/j.cnki.1003-8728.20220062
Abstract:
The cognitive characteristics of the perceptual product form were analyzed and designed on the objective physiological level. The experiments on the cognitive characteristics, combined with eye-tracking (ET) and electroencephalogram (EEG), were designed and carried out with the household charging piles′ forms as the stimulation. The results were collected wirelessly with the experiments on cognitive characteristics. The E-prime programming was used to measure the eye fixation time under the five perceptual cognitive characteristics: extremely "non-conforming", a little "non-conforming", "uncertain", a little "conforming" and extremely "conforming". The results show that when the product form is extremely "conforming" to the subject′s cognitive characteristics, the response time is shorter and the first fixation time is reduced. The product form can produce stronger P3 and LPP amplitudes in the central-parietal area associated with cortex and the parietal area. For the "non-conforming" cognitive characteristic, the subject′s behavioral response time and first fixation time increase, and the amplitude of the N2 component in the posterior temporal area increases. When the product form is "uncertain" whether it meets the subject′s perceptual cognition, the subject′s N4 wave amplitude generated in the central brain area increases. The analysis of the neural processing mechanism of perceptual image cognition, the behavior, ET and EEG data can objectively and effectively reflect the cognitive process of the user′s perceptual image and provide cognitive support for the design.
The cognitive characteristics of the perceptual product form were analyzed and designed on the objective physiological level. The experiments on the cognitive characteristics, combined with eye-tracking (ET) and electroencephalogram (EEG), were designed and carried out with the household charging piles′ forms as the stimulation. The results were collected wirelessly with the experiments on cognitive characteristics. The E-prime programming was used to measure the eye fixation time under the five perceptual cognitive characteristics: extremely "non-conforming", a little "non-conforming", "uncertain", a little "conforming" and extremely "conforming". The results show that when the product form is extremely "conforming" to the subject′s cognitive characteristics, the response time is shorter and the first fixation time is reduced. The product form can produce stronger P3 and LPP amplitudes in the central-parietal area associated with cortex and the parietal area. For the "non-conforming" cognitive characteristic, the subject′s behavioral response time and first fixation time increase, and the amplitude of the N2 component in the posterior temporal area increases. When the product form is "uncertain" whether it meets the subject′s perceptual cognition, the subject′s N4 wave amplitude generated in the central brain area increases. The analysis of the neural processing mechanism of perceptual image cognition, the behavior, ET and EEG data can objectively and effectively reflect the cognitive process of the user′s perceptual image and provide cognitive support for the design.
2023, 42(7): 1098-1102.
doi: 10.13433/j.cnki.1003-8728.20220002
Abstract:
For the rotating machinery of fault noise has complexity, it is difficult to extract the fault information contained in the noise source from microphone array collected signals. In this paper, beamforming is used to identify and locate the noise source of experimental equipment. The blocking matrix in the generalized sidelobe canceller algorithm (GSC) is constructed with directivity according to the point of noise source, then the sound signal of the fault point is reconstructed by GSC, making diagnose the fault by extracting the fault characteristics from signal. To verify the effectiveness of the signal processing method, simulation and experiment results show that this method can effectively reduce the signal leakage generated by the traditional beamforming algorithm and improve the signal noise to ratio of the output signal.
For the rotating machinery of fault noise has complexity, it is difficult to extract the fault information contained in the noise source from microphone array collected signals. In this paper, beamforming is used to identify and locate the noise source of experimental equipment. The blocking matrix in the generalized sidelobe canceller algorithm (GSC) is constructed with directivity according to the point of noise source, then the sound signal of the fault point is reconstructed by GSC, making diagnose the fault by extracting the fault characteristics from signal. To verify the effectiveness of the signal processing method, simulation and experiment results show that this method can effectively reduce the signal leakage generated by the traditional beamforming algorithm and improve the signal noise to ratio of the output signal.
2023, 42(7): 1103-1108.
doi: 10.13433/j.cnki.1003-8728.20220004
Abstract:
Correntropy is a kind of similarity measure method based on information theoretic learning and kernel function. Correntropy can not only effectively describe the time and statistical characteristics of the signal, but also include the high-order statistics of the signal, therefore, it is an effective technique to deal with non-Gaussian and nonlinear signals. Combining the correntropy with the cyclostationary signal analysis, a bearing fault diagnosis method based on cyclostationary correntropy is proposed. Firstly, the basic concept of correntropy is introduced, and the formulas of cyclostationary correntropy function and cyclostationary correntropy spectral density function are derived. Secondly, the steps of bearing fault diagnosis based on cyclostationary correntropy are put forward. Finally, the cyclostationary correntropy technique is applied to the analysis and processing of vibration signals of bearing inner race or outer race localized crack defect. The outcomes confirm that the correntropy can efficaciously extract the periodic components of bearing fault vibration signal, and the cyclostationary correntropy function and cyclostationary correntropy spectral density can effectively characterize the spectrum characteristics of bearing fault, which is convenient for fault feature extraction and recognition. The superiority of the proposed method is further verified.
Correntropy is a kind of similarity measure method based on information theoretic learning and kernel function. Correntropy can not only effectively describe the time and statistical characteristics of the signal, but also include the high-order statistics of the signal, therefore, it is an effective technique to deal with non-Gaussian and nonlinear signals. Combining the correntropy with the cyclostationary signal analysis, a bearing fault diagnosis method based on cyclostationary correntropy is proposed. Firstly, the basic concept of correntropy is introduced, and the formulas of cyclostationary correntropy function and cyclostationary correntropy spectral density function are derived. Secondly, the steps of bearing fault diagnosis based on cyclostationary correntropy are put forward. Finally, the cyclostationary correntropy technique is applied to the analysis and processing of vibration signals of bearing inner race or outer race localized crack defect. The outcomes confirm that the correntropy can efficaciously extract the periodic components of bearing fault vibration signal, and the cyclostationary correntropy function and cyclostationary correntropy spectral density can effectively characterize the spectrum characteristics of bearing fault, which is convenient for fault feature extraction and recognition. The superiority of the proposed method is further verified.
2023, 42(7): 1109-1113.
doi: 10.13433/j.cnki.1003-8728.20220087
Abstract:
Array gain-phase errors significantly degrade the performance of the sound source localization algorithms based on microphone array. An active broadband near-field calibration method is studied for microphone array gain-phase errors. This method uses only one calibration source, and uses a linear sinusoidal sweep signal as the excitation signal. Firstly, it performs amplitude and phase compensation on the signals received by the array. One element in the array is used as the reference element, and the reference element and the element to be calibrated are regarded as a single-input-single-output linear system. Then, several FIR filters for channel calibration are obtained by the recursive least squares (RLS) system identification algorithm. The calibration and sound source localization experiments were carried out with a three-dimensional sound intensity probe array, and the proposed calibration method was verified to be practical and effective.
Array gain-phase errors significantly degrade the performance of the sound source localization algorithms based on microphone array. An active broadband near-field calibration method is studied for microphone array gain-phase errors. This method uses only one calibration source, and uses a linear sinusoidal sweep signal as the excitation signal. Firstly, it performs amplitude and phase compensation on the signals received by the array. One element in the array is used as the reference element, and the reference element and the element to be calibrated are regarded as a single-input-single-output linear system. Then, several FIR filters for channel calibration are obtained by the recursive least squares (RLS) system identification algorithm. The calibration and sound source localization experiments were carried out with a three-dimensional sound intensity probe array, and the proposed calibration method was verified to be practical and effective.
2023, 42(7): 1114-1119.
doi: 10.13433/j.cnki.1003-8728.20220079
Abstract:
Pressure-actuated V-shaped metal seal has been widely used in liquid rocket engine. However, there are lots of variations of structural style, geometrical parameter and material selection for different service environments. A V-shaped metal seal has been designed based on the working and spatial constraints. Based on ABAQUS code, a FE model for assembling-pressuring-unloading-disassembling through-process of V-shaped metal seal has been developed. The sealing characteristics and influences of the controllable geometrical parameter during working through-process have been studied. The results indicated that the sealing lip yields and the plastic deformation progressively increases after pressure bearing with high temperature, and the plastic deformation on cantilever increases firstly and then is almost unchanged during the working through-process, so the structure of seal has a well self-tightening feature; there is not obvious local indentation on sealing lip after disassembling, and the resilience rate is about 88.4%; thus the seal has well sealing performance and reusable performance; the resilience rate increases with increasing inner angle (α) between two cantilevered legs and angle (β) between inside and outside of cantilevered leg, and the influences of β on the contact pressure and resilience rate is more than that of α; so the resilience rate can be further improved by optimizing the geometrical parameters.
Pressure-actuated V-shaped metal seal has been widely used in liquid rocket engine. However, there are lots of variations of structural style, geometrical parameter and material selection for different service environments. A V-shaped metal seal has been designed based on the working and spatial constraints. Based on ABAQUS code, a FE model for assembling-pressuring-unloading-disassembling through-process of V-shaped metal seal has been developed. The sealing characteristics and influences of the controllable geometrical parameter during working through-process have been studied. The results indicated that the sealing lip yields and the plastic deformation progressively increases after pressure bearing with high temperature, and the plastic deformation on cantilever increases firstly and then is almost unchanged during the working through-process, so the structure of seal has a well self-tightening feature; there is not obvious local indentation on sealing lip after disassembling, and the resilience rate is about 88.4%; thus the seal has well sealing performance and reusable performance; the resilience rate increases with increasing inner angle (α) between two cantilevered legs and angle (β) between inside and outside of cantilevered leg, and the influences of β on the contact pressure and resilience rate is more than that of α; so the resilience rate can be further improved by optimizing the geometrical parameters.
2023, 42(7): 1120-1128.
doi: 10.13433/j.cnki.1003-8728.20220066
Abstract:
Based on the computational fluid dynamics (CFD) model for YN33 diesel engine, three key structural parameters of helical intake port direct current (DC) section are optimized by using the orthogonal optimization design. Those three parameters are the upper deflection angle of DC section, the lower deflection angle of DC section and the length of DC section. In addition, swirl ratio and air input are used as evaluation indexes. The results show that the length of the DC section has the greatest influence on the swirl ratio and air input. When the upper deflection angle of the DC section, the lower deflection angle of the DC section and the length of the DC section are 82°, 85° and 69 mm, respectively, the in-cylinder swirl ratio and intake air volume can be increased by 26.02% and 5.50%, respectively, comparing with the original machine. Under the present condition, the peak heat release rate and accumulated heat release increased by 4.92% and 8.29% respectively comparing with the original machine.
Based on the computational fluid dynamics (CFD) model for YN33 diesel engine, three key structural parameters of helical intake port direct current (DC) section are optimized by using the orthogonal optimization design. Those three parameters are the upper deflection angle of DC section, the lower deflection angle of DC section and the length of DC section. In addition, swirl ratio and air input are used as evaluation indexes. The results show that the length of the DC section has the greatest influence on the swirl ratio and air input. When the upper deflection angle of the DC section, the lower deflection angle of the DC section and the length of the DC section are 82°, 85° and 69 mm, respectively, the in-cylinder swirl ratio and intake air volume can be increased by 26.02% and 5.50%, respectively, comparing with the original machine. Under the present condition, the peak heat release rate and accumulated heat release increased by 4.92% and 8.29% respectively comparing with the original machine.
2023, 42(7): 1129-1139.
doi: 10.13433/j.cnki.1003-8728.20220074
Abstract:
For improving the operating safety of high-speed gear shafts, the parametric design and response surface optimization model of the high-speed gear shaft were established by the modal analysis, parameter sensitivity analysis and DOE. The MOGA was used to optimize the first and second critical speed and their corresponding maximum amplitudes, and the Pareto optimal solution set was obtained. The optimization design under the multi-parameter coupling was realized, and the rotor structure with high operation safety was obtained. The optimized results show that the intervals between the first and second order critical speeds and the working speed are reduced by 22.9% and 10.8% respectively, which meet the requirements of rotor safety design. Through reliability verification, the optimized reliability of the first and second order critical speeds are 100% and 99.02% respectively, which further proves the correctness of the optimal method.
For improving the operating safety of high-speed gear shafts, the parametric design and response surface optimization model of the high-speed gear shaft were established by the modal analysis, parameter sensitivity analysis and DOE. The MOGA was used to optimize the first and second critical speed and their corresponding maximum amplitudes, and the Pareto optimal solution set was obtained. The optimization design under the multi-parameter coupling was realized, and the rotor structure with high operation safety was obtained. The optimized results show that the intervals between the first and second order critical speeds and the working speed are reduced by 22.9% and 10.8% respectively, which meet the requirements of rotor safety design. Through reliability verification, the optimized reliability of the first and second order critical speeds are 100% and 99.02% respectively, which further proves the correctness of the optimal method.
2023, 42(7): 1140-1149.
doi: 10.13433/j.cnki.1003-8728.20220012
Abstract:
Because the path of a distributed electric vehicle is difficult to track, a path tracking strategy was proposed based on the layered coordinated control method. Based on the structural advantage of the electric vehicle′s independent steering/driving, the four-wheel Ackerman steering theory is designed to establish the layered kinematics model of the electric vehicle′s path following and to apply it to the path following control strategy. The strategy is divided into two layers of control. In the upper layer control, the upper-layer kinematics model is used as the prediction model of the model predictive control algorithm. By setting the optimal objective function and constraint conditions, the solution of the future control increment problem is transformed into the optimal quadratic programming solution problem. The optimal rotation angle and velocity control quantity are calculated. In the lower layer control, through the lower layer kinematics, the control quantity obtained with the upper layer control is mapped to the angle and speed control quantity of the four wheels of the electric vehicle. The fuzzy PID algorithm is used to realize the path tracking control of the electric vehicle. The circular path tracking is simulated with the CarSim/Simulink simulation platform. The simulation results show that the controller can accurately track the path of the distributed electric vehicles. The comparison between the simple MPC data and the layered coordinated control data shows that the layered coordinated control method can effectively improve the control performance, accuracy and stability of the path tracking.
Because the path of a distributed electric vehicle is difficult to track, a path tracking strategy was proposed based on the layered coordinated control method. Based on the structural advantage of the electric vehicle′s independent steering/driving, the four-wheel Ackerman steering theory is designed to establish the layered kinematics model of the electric vehicle′s path following and to apply it to the path following control strategy. The strategy is divided into two layers of control. In the upper layer control, the upper-layer kinematics model is used as the prediction model of the model predictive control algorithm. By setting the optimal objective function and constraint conditions, the solution of the future control increment problem is transformed into the optimal quadratic programming solution problem. The optimal rotation angle and velocity control quantity are calculated. In the lower layer control, through the lower layer kinematics, the control quantity obtained with the upper layer control is mapped to the angle and speed control quantity of the four wheels of the electric vehicle. The fuzzy PID algorithm is used to realize the path tracking control of the electric vehicle. The circular path tracking is simulated with the CarSim/Simulink simulation platform. The simulation results show that the controller can accurately track the path of the distributed electric vehicles. The comparison between the simple MPC data and the layered coordinated control data shows that the layered coordinated control method can effectively improve the control performance, accuracy and stability of the path tracking.
2023, 42(7): 1150-1157.
doi: 10.13433/j.cnki.1003-8728.20230228
Abstract:
A two-dimensional numerical simulation model for a metal hydride hydrogen storage tank was established, and the accuracy of the model was verified by using the temperature curve of the tank from experiment. An external cooling channel was added to the tank, the temperature and hydrogen storage amount of the model were analyzed under the different type and flow rate of cooling fluid. The results show that the reaction rate in the center area of the tank is lower than that in wall area under the action of cooling water. With the increasing of cooling water flow rate, the total time of reaction is reduced to a fixed value. At the same flow rate, the variation tendency for water and oil is similar. However, the cooling time and the hydrogen storage time of water are shorter nearly 20% and 15%, respectively. Because of the buoyancy effect, the air velocity closed to the wall decreases and higher than initial temperature, so that the temperature difference between the air and alloy is reduced, the heat transfer capacity is reduced, and the hydrogen absorption time is obviously prolonged.
A two-dimensional numerical simulation model for a metal hydride hydrogen storage tank was established, and the accuracy of the model was verified by using the temperature curve of the tank from experiment. An external cooling channel was added to the tank, the temperature and hydrogen storage amount of the model were analyzed under the different type and flow rate of cooling fluid. The results show that the reaction rate in the center area of the tank is lower than that in wall area under the action of cooling water. With the increasing of cooling water flow rate, the total time of reaction is reduced to a fixed value. At the same flow rate, the variation tendency for water and oil is similar. However, the cooling time and the hydrogen storage time of water are shorter nearly 20% and 15%, respectively. Because of the buoyancy effect, the air velocity closed to the wall decreases and higher than initial temperature, so that the temperature difference between the air and alloy is reduced, the heat transfer capacity is reduced, and the hydrogen absorption time is obviously prolonged.
2023, 42(7): 1158-1164.
doi: 10.13433/j.cnki.1003-8728.20220068
Abstract:
The measurement of blade tip clearance is an effective parameter to monitor the running state of aeroengine. The existing clearance measurement methods are difficult to meet the Nyquist sampling rate of clearance distance under ultra-high rotating speed, so the accurate tip clearance value cannot be effectively extracted. In terms of the principle of compressed sensing, a data reconstruction method by using K-SVD(K-singular value decomposition) dictionary to train the sparse base according to the gap distance data features is proposed. In this method, the sparse base of K-SVD dictionary is firstly constructed to perform the sparse representation of the data. Then, the m-sequence Gaussian random matrix was used to compress the data. Finally, the orthogonal matching pursuit algorithm was used to reconstruct the data based on the compressed observations, and then the tip clearance values were accurately extracted. The experimental results show that the gap distance data can be accurately reconstructed under the condition of under-sampling, and the reconstruction error is below 0.02 mm comparing with the gap data under the condition of high sampling rate.
The measurement of blade tip clearance is an effective parameter to monitor the running state of aeroengine. The existing clearance measurement methods are difficult to meet the Nyquist sampling rate of clearance distance under ultra-high rotating speed, so the accurate tip clearance value cannot be effectively extracted. In terms of the principle of compressed sensing, a data reconstruction method by using K-SVD(K-singular value decomposition) dictionary to train the sparse base according to the gap distance data features is proposed. In this method, the sparse base of K-SVD dictionary is firstly constructed to perform the sparse representation of the data. Then, the m-sequence Gaussian random matrix was used to compress the data. Finally, the orthogonal matching pursuit algorithm was used to reconstruct the data based on the compressed observations, and then the tip clearance values were accurately extracted. The experimental results show that the gap distance data can be accurately reconstructed under the condition of under-sampling, and the reconstruction error is below 0.02 mm comparing with the gap data under the condition of high sampling rate.
2023, 42(7): 1165-1170.
doi: 10.13433/j.cnki.1003-8728.20230194
Abstract:
Aiming at the high requirement of flight test for large refitted structure of test aircraft, the flow chart of static strength digital simulation and experimental verification of large refitted structure was designed. Based on the analysis of error sources of digital simulation and static experiment of segmental assembly structure, the finite element model was modified by using a sensitive-based multi-points search algorithm according to the static strength test results, which ensures the static strength requirements of test aircraft in the test envelope were meted. The process and method were applied to design the frame structure of an engine test nacelle, and the work such as structural design and optimization, design and implementation of static strength test, data processing and finite element model revision, and checking calculation of non-test load cases were carried out. The effectiveness of the above-mentioned process and method is verified, and the closed loop of the whole process of digital simulation and experimental verification of the static strength of large refitted structure is realized.
Aiming at the high requirement of flight test for large refitted structure of test aircraft, the flow chart of static strength digital simulation and experimental verification of large refitted structure was designed. Based on the analysis of error sources of digital simulation and static experiment of segmental assembly structure, the finite element model was modified by using a sensitive-based multi-points search algorithm according to the static strength test results, which ensures the static strength requirements of test aircraft in the test envelope were meted. The process and method were applied to design the frame structure of an engine test nacelle, and the work such as structural design and optimization, design and implementation of static strength test, data processing and finite element model revision, and checking calculation of non-test load cases were carried out. The effectiveness of the above-mentioned process and method is verified, and the closed loop of the whole process of digital simulation and experimental verification of the static strength of large refitted structure is realized.
