Pub Date : 2023-06-01DOI: 10.1051/jnwpu/20234130471
Yan Huang, Feixiang Ren, Puhui Chen
In order to study the mechanical properties of ZT7G/LT-03A carbon fiber reinforced composite bolted joints, the single-bolt double-lap joints tests were carried out with 3 kinds of ply and 3 kinds of width, and the effects of the different ply ratios, width to diameter ratios on the failure load and failure mode were analyzed. Then, the failure process of the specimens was simulated by using the progressive damage and failure analysis method. The failure mode and failure load of the model are consistent with that of the specimen, which verified the accuracy of the model. On this basis, the stress and damage status of each ply during initial load shedding were studied, and the influence of the ply ratios and width to diameter ratios on the performance of laminates was further studied. The results show that when the width to diameter ratio of laminates increases, the failure mode changes from tensile failure to bearing failure, and to change the ply ratios does not affect the failure mode in a certain range.
{"title":"Study on failure of single-bolt double-lap composite joints based on test and numerical emulation","authors":"Yan Huang, Feixiang Ren, Puhui Chen","doi":"10.1051/jnwpu/20234130471","DOIUrl":"https://doi.org/10.1051/jnwpu/20234130471","url":null,"abstract":"In order to study the mechanical properties of ZT7G/LT-03A carbon fiber reinforced composite bolted joints, the single-bolt double-lap joints tests were carried out with 3 kinds of ply and 3 kinds of width, and the effects of the different ply ratios, width to diameter ratios on the failure load and failure mode were analyzed. Then, the failure process of the specimens was simulated by using the progressive damage and failure analysis method. The failure mode and failure load of the model are consistent with that of the specimen, which verified the accuracy of the model. On this basis, the stress and damage status of each ply during initial load shedding were studied, and the influence of the ply ratios and width to diameter ratios on the performance of laminates was further studied. The results show that when the width to diameter ratio of laminates increases, the failure mode changes from tensile failure to bearing failure, and to change the ply ratios does not affect the failure mode in a certain range.","PeriodicalId":39691,"journal":{"name":"西北工业大学学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57899191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-01DOI: 10.1051/jnwpu/20234130510
Peng Li, Juanni Yin, Jiaolong Zhang, Z. Gao, Heng Huang
In order to realize the reliable unlocking of solar arrays of a CubeSat under the strict constraints of space and power dissipation, a shape memory alloy(SMA) wire linear actuation unlocking mechanism is developed. Through using a spring-SMA structure, relying on the spring force locking, heating the SMA wire and producing a recovery stress drive pin movement, the solar arrays are unlocked. The mathematical model of the unlocking mechanism is established, and the relationship among stroke, unlocking time, power, alloy wire diameter and working voltage of the SMA unlocking mechanism is obtained through simulation. In order to optimize its overall unlocking time and power, the particle swarm optimization algorithm is used to optimize the diameter and working voltage of the alloy wire. The simulation results show that the SMA unlocking mechanism with the wire whose diameter is 0.5 mm has the best working performance when the driving voltage is 1.2 V. Finally, the experimental study of the design results shows that the unlocking time of the actuation unlocking mechanism is 3.2 s, its power is 3.55 W and that its pin-pulling stroke is 1.8 mm, being consistent with the simulation results. The unlocking mechanism has a high reliability, consistent working performance and good adaptability, therefore having passed various environmental tests and being successfully applied to a CubeSat in orbit.
{"title":"Optimal design of SMA linear actuation unlocking mechanism for CubeSat","authors":"Peng Li, Juanni Yin, Jiaolong Zhang, Z. Gao, Heng Huang","doi":"10.1051/jnwpu/20234130510","DOIUrl":"https://doi.org/10.1051/jnwpu/20234130510","url":null,"abstract":"In order to realize the reliable unlocking of solar arrays of a CubeSat under the strict constraints of space and power dissipation, a shape memory alloy(SMA) wire linear actuation unlocking mechanism is developed. Through using a spring-SMA structure, relying on the spring force locking, heating the SMA wire and producing a recovery stress drive pin movement, the solar arrays are unlocked. The mathematical model of the unlocking mechanism is established, and the relationship among stroke, unlocking time, power, alloy wire diameter and working voltage of the SMA unlocking mechanism is obtained through simulation. In order to optimize its overall unlocking time and power, the particle swarm optimization algorithm is used to optimize the diameter and working voltage of the alloy wire. The simulation results show that the SMA unlocking mechanism with the wire whose diameter is 0.5 mm has the best working performance when the driving voltage is 1.2 V. Finally, the experimental study of the design results shows that the unlocking time of the actuation unlocking mechanism is 3.2 s, its power is 3.55 W and that its pin-pulling stroke is 1.8 mm, being consistent with the simulation results. The unlocking mechanism has a high reliability, consistent working performance and good adaptability, therefore having passed various environmental tests and being successfully applied to a CubeSat in orbit.","PeriodicalId":39691,"journal":{"name":"西北工业大学学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48885970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-01DOI: 10.1051/jnwpu/20234120303
Xinzhe Chen, Hong Liang, Weiyu Xu
Due to the low resolution and the small number of samples of sonar images, the existing class incremental learning networks have a serious problem of catastrophic forgetting of historical task targets, resulting in a low average recognition rate of all task targets. Based on the framework model of generated replay, an improved class incremental learning network is proposed in this paper, and a new deep convolution generative adversarial network is designed and built to replace the variational autoencoder as the reconstruction model of generated replay incremental network to improve the effect of image reconstruction; a new convolution neural network is constructed to replace the multi-layer perception as the recognition network of generated replay incremental network to improve the performance of image classification and recognition. The results show that the improved generated replay incremental network alleviates the problem of catastrophic forgetting of historical task targets, and the average recognition rate for all task targets is significantly improved.
{"title":"Research on a class-incremental learning method based on sonar images","authors":"Xinzhe Chen, Hong Liang, Weiyu Xu","doi":"10.1051/jnwpu/20234120303","DOIUrl":"https://doi.org/10.1051/jnwpu/20234120303","url":null,"abstract":"Due to the low resolution and the small number of samples of sonar images, the existing class incremental learning networks have a serious problem of catastrophic forgetting of historical task targets, resulting in a low average recognition rate of all task targets. Based on the framework model of generated replay, an improved class incremental learning network is proposed in this paper, and a new deep convolution generative adversarial network is designed and built to replace the variational autoencoder as the reconstruction model of generated replay incremental network to improve the effect of image reconstruction; a new convolution neural network is constructed to replace the multi-layer perception as the recognition network of generated replay incremental network to improve the performance of image classification and recognition. The results show that the improved generated replay incremental network alleviates the problem of catastrophic forgetting of historical task targets, and the average recognition rate for all task targets is significantly improved.","PeriodicalId":39691,"journal":{"name":"西北工业大学学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43124991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-01DOI: 10.1051/jnwpu/20234120264
Yunwen Feng, Rui Wang, Tao Lu, Jun-Yu Chen, Cheng Lu
To effectively monitor the operation state of landing gear, a back propagation neural network-based on multi-strategy cooperative optimization(MSCO-BPNN) is proposed. The multi-strategy optimization algorithm is composed of chaotic mapping strategy, adaptive spiral capture strategy, crossover mutation strategy and whale optimization algorithm(WOA). WOA is applied to find the optimal hyperparameters of back propagation neural network(BPNN). The search efficiency, multi-local search ability and global search performance of model can be improved by using chaotic mapping strategy, adaptive spiral capture strategy and crossover mutation strategy. The BPNN with optimal hyperparameters is introduced to establish the implicit model of input parameters and output responses. Based on quick access recorder(QAR) data, landing gear left side brake temperature is act as the monitoring objective of this paper. The validity and applicability of MSCO-BPNN are verified by compared with WOA-BPNN, particle swarm optimization BPNN and traditional BPNN. The results show that MSCO-BPNN can monitor the operation status of landing gear with high efficiency and accuracy. The efforts of this paper provide a promising insight for the precise condition monitoring of complex structures.
{"title":"Landing gear condition monitoring based on back propagation neural network-based on multi-strategy cooperative optimization","authors":"Yunwen Feng, Rui Wang, Tao Lu, Jun-Yu Chen, Cheng Lu","doi":"10.1051/jnwpu/20234120264","DOIUrl":"https://doi.org/10.1051/jnwpu/20234120264","url":null,"abstract":"To effectively monitor the operation state of landing gear, a back propagation neural network-based on multi-strategy cooperative optimization(MSCO-BPNN) is proposed. The multi-strategy optimization algorithm is composed of chaotic mapping strategy, adaptive spiral capture strategy, crossover mutation strategy and whale optimization algorithm(WOA). WOA is applied to find the optimal hyperparameters of back propagation neural network(BPNN). The search efficiency, multi-local search ability and global search performance of model can be improved by using chaotic mapping strategy, adaptive spiral capture strategy and crossover mutation strategy. The BPNN with optimal hyperparameters is introduced to establish the implicit model of input parameters and output responses. Based on quick access recorder(QAR) data, landing gear left side brake temperature is act as the monitoring objective of this paper. The validity and applicability of MSCO-BPNN are verified by compared with WOA-BPNN, particle swarm optimization BPNN and traditional BPNN. The results show that MSCO-BPNN can monitor the operation status of landing gear with high efficiency and accuracy. The efforts of this paper provide a promising insight for the precise condition monitoring of complex structures.","PeriodicalId":39691,"journal":{"name":"西北工业大学学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43826665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-01DOI: 10.1051/jnwpu/20234120282
Yang Liu, Chunna Li, Yuan Fang, Chun-lin Gong
In order to solve the problem that some test data cannot be measured or the measurement is difficult, a combined aerodynamic parameters identification method for missing test data is proposed. In this method, the aerodynamic parameter identification problem is modified into an optimization problem. The initial value of the flight state and the aerodynamic parameter interpolation table are used as design variables, and the motion equation of the aircraft including all aerodynamic parameters is used as a model to construct an objective function containing multiple pieces of test data information. In the optimization, the aerodynamic parameter database and the identification results of the existing methods are used as the prior knowledge. The initial value of the unmeasured data is fitted as the reference value. Then, the feasible sample selection method is designed. Finally, the differential evolution algorithm is used to solve the problem. The proposed method is used to process 264 pieces of test data, and the results show that compared with the existing aerodynamic parameter identification methods, the proposed identification method can obtain all aerodynamic parameters with higher accuracy and can inversely calculate and obtain unmeasured flight test data practical engineering significance.
{"title":"A combined aerodynamic parameter identification method for missing test data","authors":"Yang Liu, Chunna Li, Yuan Fang, Chun-lin Gong","doi":"10.1051/jnwpu/20234120282","DOIUrl":"https://doi.org/10.1051/jnwpu/20234120282","url":null,"abstract":"In order to solve the problem that some test data cannot be measured or the measurement is difficult, a combined aerodynamic parameters identification method for missing test data is proposed. In this method, the aerodynamic parameter identification problem is modified into an optimization problem. The initial value of the flight state and the aerodynamic parameter interpolation table are used as design variables, and the motion equation of the aircraft including all aerodynamic parameters is used as a model to construct an objective function containing multiple pieces of test data information. In the optimization, the aerodynamic parameter database and the identification results of the existing methods are used as the prior knowledge. The initial value of the unmeasured data is fitted as the reference value. Then, the feasible sample selection method is designed. Finally, the differential evolution algorithm is used to solve the problem. The proposed method is used to process 264 pieces of test data, and the results show that compared with the existing aerodynamic parameter identification methods, the proposed identification method can obtain all aerodynamic parameters with higher accuracy and can inversely calculate and obtain unmeasured flight test data practical engineering significance.","PeriodicalId":39691,"journal":{"name":"西北工业大学学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47479812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To coordinate the conflict between the high-altitude task and long-term energy efficiency of high-altitude long endurance solar UAV, it is one of the core issues of UAV control. A strategy combining the energy management with the route tracking is presented. Firstly, based on the three-dimensional particle motion model, energy storage battery model and solar energy acquisition model for the solar UAV, according to the aerodynamic parameters of the solar UAV and the typical horizontal flight, climb, descent and other motion processes of the solar UAV, the energy management strategy of the solar UAV is designed, and the allocation mechanism and optimal flight parameters of the energy acquisition, storage and consumption of the solar UAV in different flight stages are determined. The surplus solar energy is stored by using the gravitational potential energy, and then the energy management based on height adjustment is carried out to realize the longitudinal tracking control of the solar UAV under different lighting and energy conditions. Then based on the task requirements of the lateral movement of the solar UAV, a track tracking control method based on the feedback linearization method is established by decoupling the particle dynamics equation of the solar UAV, and the track tracking control of the solar UAV in the lateral direction is realized. Finally, a simulation throughout 24 hours is implemented and illustrated the effectiveness of the energy management strategy and route tracking control law.
{"title":"Path tracking control of solar-powered UAV based on energy management strategy","authors":"Lin Guo, Fei Liu, Jiayu Li, Pei He, Qingdong Li, Jiwei Wang, Yangming Guo","doi":"10.1051/jnwpu/20234120409","DOIUrl":"https://doi.org/10.1051/jnwpu/20234120409","url":null,"abstract":"To coordinate the conflict between the high-altitude task and long-term energy efficiency of high-altitude long endurance solar UAV, it is one of the core issues of UAV control. A strategy combining the energy management with the route tracking is presented. Firstly, based on the three-dimensional particle motion model, energy storage battery model and solar energy acquisition model for the solar UAV, according to the aerodynamic parameters of the solar UAV and the typical horizontal flight, climb, descent and other motion processes of the solar UAV, the energy management strategy of the solar UAV is designed, and the allocation mechanism and optimal flight parameters of the energy acquisition, storage and consumption of the solar UAV in different flight stages are determined. The surplus solar energy is stored by using the gravitational potential energy, and then the energy management based on height adjustment is carried out to realize the longitudinal tracking control of the solar UAV under different lighting and energy conditions. Then based on the task requirements of the lateral movement of the solar UAV, a track tracking control method based on the feedback linearization method is established by decoupling the particle dynamics equation of the solar UAV, and the track tracking control of the solar UAV in the lateral direction is realized. Finally, a simulation throughout 24 hours is implemented and illustrated the effectiveness of the energy management strategy and route tracking control law.","PeriodicalId":39691,"journal":{"name":"西北工业大学学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41513232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-01DOI: 10.1051/jnwpu/20234120389
Penglin Hu, Q. Pan, Yaning Guo, Chunhui Zhao
Considering the obstacle avoidance and collision avoidance for multi-agent cooperative formation in multi-obstacle environment, a formation control algorithm based on transfer learning and reinforcement learning is proposed. Firstly, in the source task learning stage, the large storage space required by Q-table solution is avoided by using the value function approximation method, which effectively reduces the storage space requirement and improves the solving speed of the algorithm. Secondly, in the learning phase of the target task, Gaussian clustering algorithm was used to classify the source tasks. According to the distance between the clustering center and the target task, the optimal source task class was selected for target task learning, which effectively avoided the negative transfer phenomenon, and improved the generalization ability and convergence speed of reinforcement learning algorithm. Finally, the simulation results show that this method can effectively form and maintain formation configuration of multi-agent system in complex environment with obstacles, and realize obstacle avoidance and collision avoidance at the same time.
{"title":"Study on learning algorithm of transfer reinforcement for multi-agent formation control","authors":"Penglin Hu, Q. Pan, Yaning Guo, Chunhui Zhao","doi":"10.1051/jnwpu/20234120389","DOIUrl":"https://doi.org/10.1051/jnwpu/20234120389","url":null,"abstract":"Considering the obstacle avoidance and collision avoidance for multi-agent cooperative formation in multi-obstacle environment, a formation control algorithm based on transfer learning and reinforcement learning is proposed. Firstly, in the source task learning stage, the large storage space required by Q-table solution is avoided by using the value function approximation method, which effectively reduces the storage space requirement and improves the solving speed of the algorithm. Secondly, in the learning phase of the target task, Gaussian clustering algorithm was used to classify the source tasks. According to the distance between the clustering center and the target task, the optimal source task class was selected for target task learning, which effectively avoided the negative transfer phenomenon, and improved the generalization ability and convergence speed of reinforcement learning algorithm. Finally, the simulation results show that this method can effectively form and maintain formation configuration of multi-agent system in complex environment with obstacles, and realize obstacle avoidance and collision avoidance at the same time.","PeriodicalId":39691,"journal":{"name":"西北工业大学学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47336947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-01DOI: 10.1051/jnwpu/20234120344
Guangwei YU, Li YAN
In view of the problem that the generalization ability of traditional data-driven fault diagnosis model declines or even fails in mechanical system diagnosis, a fault diagnosis method based on multi-scale transfer symbolic dynamic entropy and support vector machine is proposed based on the idea of transfer learning. Firstly, multi-scale symbolic dynamic entropy is used to extract fault features from measured vibration signals. And then a feature projection technique based on transfer learning is proposed, which reduces the data distribution difference. Secondly, the parameters of the multi-scale transfer symbol dynamic entropy method are optimized to improve the final fault identification rate. Then, the support vector machine can implement the fault identification. Finally, through the test of bearing fault experimental signals, the rolling bearing diagnosis method based on multi-scale transfer symbol dynamic entropy can effectively improve the generalization ability of data-driven model and realize accurate identification of different fault types of rolling bearing under a small number of samples.
{"title":"A novel bearing fault diagnosis method based on multi-scale transfer symbolic dynamic entropy and support vector machine","authors":"Guangwei YU, Li YAN","doi":"10.1051/jnwpu/20234120344","DOIUrl":"https://doi.org/10.1051/jnwpu/20234120344","url":null,"abstract":"In view of the problem that the generalization ability of traditional data-driven fault diagnosis model declines or even fails in mechanical system diagnosis, a fault diagnosis method based on multi-scale transfer symbolic dynamic entropy and support vector machine is proposed based on the idea of transfer learning. Firstly, multi-scale symbolic dynamic entropy is used to extract fault features from measured vibration signals. And then a feature projection technique based on transfer learning is proposed, which reduces the data distribution difference. Secondly, the parameters of the multi-scale transfer symbol dynamic entropy method are optimized to improve the final fault identification rate. Then, the support vector machine can implement the fault identification. Finally, through the test of bearing fault experimental signals, the rolling bearing diagnosis method based on multi-scale transfer symbol dynamic entropy can effectively improve the generalization ability of data-driven model and realize accurate identification of different fault types of rolling bearing under a small number of samples.","PeriodicalId":39691,"journal":{"name":"西北工业大学学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135673703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-01DOI: 10.1051/jnwpu/20234120293
Shan Lu, Shiyuan Zhang
The univariate non-stationary growth model (UNGM) is widely used in the verification of nonlinear filters, and the unscented Kalman filter (UKF) is often used as the reference filter for comparative analysis when using this model to evaluate the filter performance. However, due to the strong nonlinearity of UNGM and the change of model properties with different parameter settings, the estimation misalignment problem due to different reasons will occur when UKF is used for filtering. To solve these problems, this paper analyzes the complex characteristics of UNGM in filtering process, and proposes an UKF with sliding sampling module(SSUKF). The algorithm is optimized on the basis of UKF, and can effectively deal with the complex characteristics of UNGM by sampling and analyzing the filtering information in the filtering process and correcting the distribution of Sigma points in real time. SSUKF is applied to UNGM under different parameters and compared with UKF and bootstrap particle filter(BPF). The simulation results show that SSUKF can effectively solve the misalignment problem when UKF is applied to UNGM, and the calculation speed is better than BPF. Compared with UKF, SSUKF is suitable as a benchmark filter for evaluating the performance of nonlinear filters using UNGM.
{"title":"Characteristic analysis and filtering algorithm design for UNGM model","authors":"Shan Lu, Shiyuan Zhang","doi":"10.1051/jnwpu/20234120293","DOIUrl":"https://doi.org/10.1051/jnwpu/20234120293","url":null,"abstract":"The univariate non-stationary growth model (UNGM) is widely used in the verification of nonlinear filters, and the unscented Kalman filter (UKF) is often used as the reference filter for comparative analysis when using this model to evaluate the filter performance. However, due to the strong nonlinearity of UNGM and the change of model properties with different parameter settings, the estimation misalignment problem due to different reasons will occur when UKF is used for filtering. To solve these problems, this paper analyzes the complex characteristics of UNGM in filtering process, and proposes an UKF with sliding sampling module(SSUKF). The algorithm is optimized on the basis of UKF, and can effectively deal with the complex characteristics of UNGM by sampling and analyzing the filtering information in the filtering process and correcting the distribution of Sigma points in real time. SSUKF is applied to UNGM under different parameters and compared with UKF and bootstrap particle filter(BPF). The simulation results show that SSUKF can effectively solve the misalignment problem when UKF is applied to UNGM, and the calculation speed is better than BPF. Compared with UKF, SSUKF is suitable as a benchmark filter for evaluating the performance of nonlinear filters using UNGM.","PeriodicalId":39691,"journal":{"name":"西北工业大学学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42449945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-01DOI: 10.1051/jnwpu/20234120310
Haojie Yang, Kai Luo, Chuang Huang, Zhao Liu, Xu He, Qian Wang
Water ramjet is the most ideal power propulsion device for high-speed underwater weapons. However, failure to start it at low-speed makes it hard for the engine to be widely used. In order to solve the problem of starting water ramjet at low-speed, a configuration scheme of water ramjet pressurized water intake system of the micro-turbine driving micro-mixed-flow pump is proposed. The design method of micro-turbine and micro-mixed-flow pump is perfected. And the simulation model of turbine and mixed-flow pump is established. The rationality of the design results was verified by numerical simulation. The matching design of the turbine and the mixed-flow pump is completed. And the working performance of the pressurized water inlet system is analyzed. The results show that the maximum relative deviation between the design results of the turbine and the pump and the target value is less than 3.2%, and the booster system can increase the fluid pressure by 2.0 MPa, reducing the starting speed of the ramjet from 90 to 63 m/s. The research results of this paper have reference value for the engineering application of water ramjet technology.
{"title":"Research on configuration and performance of water ramjet pressurized water intake system","authors":"Haojie Yang, Kai Luo, Chuang Huang, Zhao Liu, Xu He, Qian Wang","doi":"10.1051/jnwpu/20234120310","DOIUrl":"https://doi.org/10.1051/jnwpu/20234120310","url":null,"abstract":"Water ramjet is the most ideal power propulsion device for high-speed underwater weapons. However, failure to start it at low-speed makes it hard for the engine to be widely used. In order to solve the problem of starting water ramjet at low-speed, a configuration scheme of water ramjet pressurized water intake system of the micro-turbine driving micro-mixed-flow pump is proposed. The design method of micro-turbine and micro-mixed-flow pump is perfected. And the simulation model of turbine and mixed-flow pump is established. The rationality of the design results was verified by numerical simulation. The matching design of the turbine and the mixed-flow pump is completed. And the working performance of the pressurized water inlet system is analyzed. The results show that the maximum relative deviation between the design results of the turbine and the pump and the target value is less than 3.2%, and the booster system can increase the fluid pressure by 2.0 MPa, reducing the starting speed of the ramjet from 90 to 63 m/s. The research results of this paper have reference value for the engineering application of water ramjet technology.","PeriodicalId":39691,"journal":{"name":"西北工业大学学报","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45720553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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