Pub Date : 2024-04-15DOI: 10.1177/00202940241227814
Tahir Munir, Fahad M. Alqahtani, A. Alrashidi, Abdu R Rahman, S. A. Cheema, Yi Li
The precision of process monitoring often encounters challenges in determining the exact shift size. Therefore, combined control charts have gained considerable attention because of their excellent speed to detect simultaneously small-to-moderate and large-size shifts. The effectiveness of the applied quality control methods strongly depends on the performance of the measurement system. Measurement error presence contributes significantly negatively toward the performance of the usual control charting schemes. This article proposes novel two-sided combined Shewhart-Cumulative EWMA-sum (Shewhart-CUESUM) control charts designed to efficiently monitor the mean of normally distributed processes. In addition, to address measurement errors, the M-Shewhart-CUESUM chart is proposed, incorporating an additive measurement error model. Evaluation of the charts through Monte-Carlo simulations, considering metrics such as average run length (ARL), extra quadratic loss, relative ARL, and performance comparison index. It is found that the combined Shewhart-CUESUM outperforms than CUESUM chart. The results show that the presence of measurement errors can significantly diminish the charts’ performance, which can be mitigated by utilizing a multiple measurements scheme. Among the different well-established combined charts examined, the M-Shewhart-CUESUM chart shows considerably more sensitive to detecting simultaneously detect small and large size shifts. To employ simulated datasets to illustrate the impact of measurement errors and demonstrate the implications of the proposed charts on process mean shifts.
{"title":"Novel combined Shewhart-CUmulative EWMA-SUM mean charts without- and with measurement error","authors":"Tahir Munir, Fahad M. Alqahtani, A. Alrashidi, Abdu R Rahman, S. A. Cheema, Yi Li","doi":"10.1177/00202940241227814","DOIUrl":"https://doi.org/10.1177/00202940241227814","url":null,"abstract":"The precision of process monitoring often encounters challenges in determining the exact shift size. Therefore, combined control charts have gained considerable attention because of their excellent speed to detect simultaneously small-to-moderate and large-size shifts. The effectiveness of the applied quality control methods strongly depends on the performance of the measurement system. Measurement error presence contributes significantly negatively toward the performance of the usual control charting schemes. This article proposes novel two-sided combined Shewhart-Cumulative EWMA-sum (Shewhart-CUESUM) control charts designed to efficiently monitor the mean of normally distributed processes. In addition, to address measurement errors, the M-Shewhart-CUESUM chart is proposed, incorporating an additive measurement error model. Evaluation of the charts through Monte-Carlo simulations, considering metrics such as average run length (ARL), extra quadratic loss, relative ARL, and performance comparison index. It is found that the combined Shewhart-CUESUM outperforms than CUESUM chart. The results show that the presence of measurement errors can significantly diminish the charts’ performance, which can be mitigated by utilizing a multiple measurements scheme. Among the different well-established combined charts examined, the M-Shewhart-CUESUM chart shows considerably more sensitive to detecting simultaneously detect small and large size shifts. To employ simulated datasets to illustrate the impact of measurement errors and demonstrate the implications of the proposed charts on process mean shifts.","PeriodicalId":510299,"journal":{"name":"Measurement and Control","volume":"58 44","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140701394","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 : 2024-04-15DOI: 10.1177/00202940241229633
Guisheng Zhang, Qingyi Tu, Jian Xie
The issue of quality-related fault detection in the industrial process has attracted much attention in recent years. The partial least squares (PLS) is considered an efficient tool for predicting and monitoring. The modified partial least squares (MPLS) is an extended algorithm for solving the oblique decomposition of PLS, however, the study indicated that the loss of quality variable information may affect the prediction of quality information in the decomposition process of the MPLS algorithm. Furthermore, the detection rate of traditional statistics and static control limit is low, and the existing dynamic control limit has certain limitations. Therefore, a new PLS space-decomposition algorithm called advanced partial least squares (APLS) is proposed. APLS avoids the loss of quality information by orthogonal decomposition of process variables according to their relationship with quality. APLS has a more accurate prediction of quality when process variables contain more noise; the fault false alarm rates (FAR) of quality-related faults are reduced by using the new statistics and thresholds combined with local information increment technology in the process variable principal component subspace. Finally, the effectiveness of the proposed approach is verified by a numerical example and an industrial benchmark problem.
{"title":"Study on advanced partial least squares for quality-related fault detection","authors":"Guisheng Zhang, Qingyi Tu, Jian Xie","doi":"10.1177/00202940241229633","DOIUrl":"https://doi.org/10.1177/00202940241229633","url":null,"abstract":"The issue of quality-related fault detection in the industrial process has attracted much attention in recent years. The partial least squares (PLS) is considered an efficient tool for predicting and monitoring. The modified partial least squares (MPLS) is an extended algorithm for solving the oblique decomposition of PLS, however, the study indicated that the loss of quality variable information may affect the prediction of quality information in the decomposition process of the MPLS algorithm. Furthermore, the detection rate of traditional statistics and static control limit is low, and the existing dynamic control limit has certain limitations. Therefore, a new PLS space-decomposition algorithm called advanced partial least squares (APLS) is proposed. APLS avoids the loss of quality information by orthogonal decomposition of process variables according to their relationship with quality. APLS has a more accurate prediction of quality when process variables contain more noise; the fault false alarm rates (FAR) of quality-related faults are reduced by using the new statistics and thresholds combined with local information increment technology in the process variable principal component subspace. Finally, the effectiveness of the proposed approach is verified by a numerical example and an industrial benchmark problem.","PeriodicalId":510299,"journal":{"name":"Measurement and Control","volume":"68 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140702629","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 : 2024-04-14DOI: 10.1177/00202940241240896
Lei Liu, Chunzhong Li, Haiyi Bian, Ahmed N Abdalla, Hua Yao, Wen Li
The accurate determination of sugar content in tangerines plays a pivotal role in assessing their quality, nutritional value, and marketability. Traditional methods for sugar quantification often involve time-consuming and resource-intensive processes. In this paper, we introduce a novel approach for sugar determination in tangerines utilizing fluorescence spectroscopy in conjunction with an improved Partial Least Squares (iPLS) algorithm. A robust testing model was developed, incorporating a diverse dataset of tangerine samples with known sugar concentrations. Fluorescence spectra were acquired for 80 samples, of which 37 were used to build the iPLS model and were considered as the training dataset. The remaining 43 samples served as the validation dataset and were used to show the model’s efficacy. The training dataset was evaluated using cross-validation, and F-values were computed to determine how many main components should be utilized to build the model. The result approved validation dataset’s R-square and root-mean-square error were 0.9777 and 0.002992, respectively. These findings open the door to broader applications in the citrus industry and beyond, with the potential for automating the analysis process and improving overall quality control.
{"title":"Determination of sugar in tangerines by fluorescence with an Improved partial least squares (PLS) algorithm","authors":"Lei Liu, Chunzhong Li, Haiyi Bian, Ahmed N Abdalla, Hua Yao, Wen Li","doi":"10.1177/00202940241240896","DOIUrl":"https://doi.org/10.1177/00202940241240896","url":null,"abstract":"The accurate determination of sugar content in tangerines plays a pivotal role in assessing their quality, nutritional value, and marketability. Traditional methods for sugar quantification often involve time-consuming and resource-intensive processes. In this paper, we introduce a novel approach for sugar determination in tangerines utilizing fluorescence spectroscopy in conjunction with an improved Partial Least Squares (iPLS) algorithm. A robust testing model was developed, incorporating a diverse dataset of tangerine samples with known sugar concentrations. Fluorescence spectra were acquired for 80 samples, of which 37 were used to build the iPLS model and were considered as the training dataset. The remaining 43 samples served as the validation dataset and were used to show the model’s efficacy. The training dataset was evaluated using cross-validation, and F-values were computed to determine how many main components should be utilized to build the model. The result approved validation dataset’s R-square and root-mean-square error were 0.9777 and 0.002992, respectively. These findings open the door to broader applications in the citrus industry and beyond, with the potential for automating the analysis process and improving overall quality control.","PeriodicalId":510299,"journal":{"name":"Measurement and Control","volume":"193 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140704521","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}
Sparse regularization has been successfully applied to equivalent source method (ESM) in order to improve the acoustic imaging resolution. However, the application is not always feasible, especially at low frequencies. To overcome the problem, this paper proposes a high-resolution acoustic imaging method. In this method, reweighted l1 minimization is introduced to ESM to deal with the ill-posed inverse problems. Then the obtained equivalent source strengths are used to locate the sound sources. Compared to the sparse regularization-based ESM, the proposed method can provide a low side lobe and higher spatial resolution of acoustic imaging. Meanwhile, by arranging equivalent sources in three-dimensional space, the proposed method can also realize the acoustic imaging in three-dimensional sound field with high resolution. The results of the simulation and experiment demonstrate the validations.
{"title":"High-resolution acoustic imaging method based on equivalent source method and reweighted l1 minimization","authors":"Yuan Liu, Wenqiang Liu, Yongchang Li, Dingyu Hu, Wenqian Jing","doi":"10.1177/00202940241245031","DOIUrl":"https://doi.org/10.1177/00202940241245031","url":null,"abstract":"Sparse regularization has been successfully applied to equivalent source method (ESM) in order to improve the acoustic imaging resolution. However, the application is not always feasible, especially at low frequencies. To overcome the problem, this paper proposes a high-resolution acoustic imaging method. In this method, reweighted l1 minimization is introduced to ESM to deal with the ill-posed inverse problems. Then the obtained equivalent source strengths are used to locate the sound sources. Compared to the sparse regularization-based ESM, the proposed method can provide a low side lobe and higher spatial resolution of acoustic imaging. Meanwhile, by arranging equivalent sources in three-dimensional space, the proposed method can also realize the acoustic imaging in three-dimensional sound field with high resolution. The results of the simulation and experiment demonstrate the validations.","PeriodicalId":510299,"journal":{"name":"Measurement and Control","volume":"10 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140706016","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}
An uncontrolled fire poses severe threats to both humans and the environment, making firefighting a perilous and complex task. Traditional fire suppression methods are inefficient, costly, and without thorough testing, leading to delays in gaining control over fire outbreaks. This paper presents a novel firefighting drone aimed at mitigating risks to firefighters by extinguishing fires and providing real-time imaging, gas concentration and fire location data monitoring. The proposed intelligent quadcopter utilizes the Pixhawk PX4 microcontroller for precise control and the Pixhawk Telemetry system for data processing. The proposed device is constructed from an ultra-strength S500 Quadcopter frame, NodeMCU, Arduino Nano, various gas sensors, a servo motor to extinguish the fire and a camera to detect fire events in real time. Equipped with an FPV camera and a video transmitter, it transmits live video feed to the ground, enabling efficient navigation using the Flysky I6X controller. The intended position and height of the drone are controlled using an adaptive optimization technique known as fuzzy-based backstepping control. This article demonstrates the effectiveness of the device by collecting and analyzing gas emissions data from controlled burns of various materials. The drone successfully measured concentrations of CO, CO2, O3, SO2, and NO2 in affected areas, providing valuable insights for firefighting operations. Different levels of gases have been measured depending on the concentration from burning alcohol, clothes, plastic materials, paper, leaves, and so on. The novelty of this work lies in the development and comprehensive analysis of an IoT-based firefighting drone conducting extensive real-time experiments.
{"title":"Development of an IoT-based firefighting drone for enhanced safety and efficiency in fire suppression","authors":"Nusrat Jahan, Tawab Bin Maleque Niloy, Jannatul Fahima Silvi, Mahdi Hasan, Ishrat Jahan Nashia, Riasat Khan","doi":"10.1177/00202940241238674","DOIUrl":"https://doi.org/10.1177/00202940241238674","url":null,"abstract":"An uncontrolled fire poses severe threats to both humans and the environment, making firefighting a perilous and complex task. Traditional fire suppression methods are inefficient, costly, and without thorough testing, leading to delays in gaining control over fire outbreaks. This paper presents a novel firefighting drone aimed at mitigating risks to firefighters by extinguishing fires and providing real-time imaging, gas concentration and fire location data monitoring. The proposed intelligent quadcopter utilizes the Pixhawk PX4 microcontroller for precise control and the Pixhawk Telemetry system for data processing. The proposed device is constructed from an ultra-strength S500 Quadcopter frame, NodeMCU, Arduino Nano, various gas sensors, a servo motor to extinguish the fire and a camera to detect fire events in real time. Equipped with an FPV camera and a video transmitter, it transmits live video feed to the ground, enabling efficient navigation using the Flysky I6X controller. The intended position and height of the drone are controlled using an adaptive optimization technique known as fuzzy-based backstepping control. This article demonstrates the effectiveness of the device by collecting and analyzing gas emissions data from controlled burns of various materials. The drone successfully measured concentrations of CO, CO2, O3, SO2, and NO2 in affected areas, providing valuable insights for firefighting operations. Different levels of gases have been measured depending on the concentration from burning alcohol, clothes, plastic materials, paper, leaves, and so on. The novelty of this work lies in the development and comprehensive analysis of an IoT-based firefighting drone conducting extensive real-time experiments.","PeriodicalId":510299,"journal":{"name":"Measurement and Control","volume":"58 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140705149","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 : 2024-04-06DOI: 10.1177/00202940241241917
Guanran Wang, Xiaojun Sun
For fractional order systems with colored process noise, the discretization fractional order system model is used to construct the augmented vector defined by the state vector and colored process noise vector. Based on the augmented equation of fractional order systems, the robust local Kalman filtering algorithm for fractional order systems with colored process noise is derived. The matrix weighted fusion, weighted measurement fusion and centralized fusion methods were used to fuse and estimate the state of multi-sensor fractional order system. Simulation results show the effectiveness of the proposed algorithm.
{"title":"Robust Kalman filter for fractional order systems with uncertain colored noise variance","authors":"Guanran Wang, Xiaojun Sun","doi":"10.1177/00202940241241917","DOIUrl":"https://doi.org/10.1177/00202940241241917","url":null,"abstract":"For fractional order systems with colored process noise, the discretization fractional order system model is used to construct the augmented vector defined by the state vector and colored process noise vector. Based on the augmented equation of fractional order systems, the robust local Kalman filtering algorithm for fractional order systems with colored process noise is derived. The matrix weighted fusion, weighted measurement fusion and centralized fusion methods were used to fuse and estimate the state of multi-sensor fractional order system. Simulation results show the effectiveness of the proposed algorithm.","PeriodicalId":510299,"journal":{"name":"Measurement and Control","volume":"17 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140734678","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}
Ball screw is widely used in the engineering field, and accurate estimation of their state is crucial for the reliability of system operation. However, existing methods often overlook the time series characteristics and spatial correlation of vibration signals, unable to provide complete degradation information and divide the degradation process, resulting in limited prediction accuracy. Therefore, a state estimation method for ball screw based on Convolutional Neural Networks (CNN) and Long Short-Term Memory Neural Networks (LSTM) is proposed. An experiment of ball screw transmission equipment was conducted to collect vibration signals throughout the entire life cycle and verify the proposed method. Firstly, the frequency domain amplitude signal of the transformed ball screw is normalized to eliminate scale differences, which serves as the input for CNN feature extraction. Then, these deep features are input into the LSTM network to capture the fault evolution patterns that reveal the degradation of ball screw performance, and achieve accurate estimation of ball screw state. The final prediction accuracy was 97.87%, verifying the effectiveness of the proposed method.
{"title":"A state estimation method based on CNN-LSTM for ball screw","authors":"Jianxin Lei, Zhinong Jiang, Zhilong Gao, Zhang Wenbo","doi":"10.1177/00202940241241924","DOIUrl":"https://doi.org/10.1177/00202940241241924","url":null,"abstract":"Ball screw is widely used in the engineering field, and accurate estimation of their state is crucial for the reliability of system operation. However, existing methods often overlook the time series characteristics and spatial correlation of vibration signals, unable to provide complete degradation information and divide the degradation process, resulting in limited prediction accuracy. Therefore, a state estimation method for ball screw based on Convolutional Neural Networks (CNN) and Long Short-Term Memory Neural Networks (LSTM) is proposed. An experiment of ball screw transmission equipment was conducted to collect vibration signals throughout the entire life cycle and verify the proposed method. Firstly, the frequency domain amplitude signal of the transformed ball screw is normalized to eliminate scale differences, which serves as the input for CNN feature extraction. Then, these deep features are input into the LSTM network to capture the fault evolution patterns that reveal the degradation of ball screw performance, and achieve accurate estimation of ball screw state. The final prediction accuracy was 97.87%, verifying the effectiveness of the proposed method.","PeriodicalId":510299,"journal":{"name":"Measurement and Control","volume":"62 173","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140735041","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 : 2024-04-02DOI: 10.1177/00202940231212871
R. Rascón, Luis Moreno-Ahedo, Andrés Calvillo-Téllez
The major contribution of this study is the feedback design of a finite-time convergence sliding mode control to solve the trajectory-tracking problem in a class of mechanical systems. Some advantages are that the controller presents a continuous signal by integration of the high-frequency switching term. Another benefit is the design and implementation of an uncertainty and disturbance estimator (UDE) to robustify the closed-loop system. We use Lyapunov tools to develop the closed-loop stability analysis and to give an expression of the convergence time [Formula: see text] t through this, we can reduce the convergence time by tuning the gains of the controller. We illustrate the performance of the proposed control structure via numerical simulations conducted for a mass-spring-damper system and experiments developed in a pendular system.
{"title":"Continuous finite-time terminal sliding mode to solve the tracking problem in a class of mechanical systems","authors":"R. Rascón, Luis Moreno-Ahedo, Andrés Calvillo-Téllez","doi":"10.1177/00202940231212871","DOIUrl":"https://doi.org/10.1177/00202940231212871","url":null,"abstract":"The major contribution of this study is the feedback design of a finite-time convergence sliding mode control to solve the trajectory-tracking problem in a class of mechanical systems. Some advantages are that the controller presents a continuous signal by integration of the high-frequency switching term. Another benefit is the design and implementation of an uncertainty and disturbance estimator (UDE) to robustify the closed-loop system. We use Lyapunov tools to develop the closed-loop stability analysis and to give an expression of the convergence time [Formula: see text] t through this, we can reduce the convergence time by tuning the gains of the controller. We illustrate the performance of the proposed control structure via numerical simulations conducted for a mass-spring-damper system and experiments developed in a pendular system.","PeriodicalId":510299,"journal":{"name":"Measurement and Control","volume":"38 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140752037","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 : 2024-03-28DOI: 10.1177/00202940241241217
C. Su, Dunning Liu, Huanyu Zhao, Yanling Yuan, Tingbin Song
This paper introduces a method to quickly and accurately identify the sound quality of automatic transmission in a vehicle by testing the objective vibration parameters on automatic transmission EOL (end of line) test bench. In this study, 50 automatic transmissions serve as the research object, and the vibration parameters of each gear of the transmission are measured on the EOL bench. Then, the transmission is mounted on a vehicle, the vibration parameters and acoustic parameters of corresponding working conditions are measured, and the subjective evaluation of the noise quality of the vehicle is carried out by using a grade scoring method. After this data is collected, the specific vibration parameters and acoustic parameters that are the dominant factors of sound quality are determined by correlation analysis. Based on the multiple linear regression method, the following mathematical models are formulated: the vibration parameters and the subjective evaluation of a vehicle, and the acoustic parameters and the subjective evaluation of a vehicle. Among these models, the mathematical models of the vibration parameters and the subjective evaluation of a vehicle were verified to be more accurate. The consistency between the vibration value in a vehicle and the vibration value on EOL test bench is analyzed and the EOL vibration value is determined to be the most objective evaluation of the data. After batch testing of 100 sets, the effectiveness of this model is within 95%. Finally, the value of critical amplitude of the condition of each gear of transmission is analyzed to form the judgment standard of transmission EOL vibration to ensure better sound quality for the vehicle.
{"title":"Correlation of the sound quality and vibration of end of line testing for automatic transmission","authors":"C. Su, Dunning Liu, Huanyu Zhao, Yanling Yuan, Tingbin Song","doi":"10.1177/00202940241241217","DOIUrl":"https://doi.org/10.1177/00202940241241217","url":null,"abstract":"This paper introduces a method to quickly and accurately identify the sound quality of automatic transmission in a vehicle by testing the objective vibration parameters on automatic transmission EOL (end of line) test bench. In this study, 50 automatic transmissions serve as the research object, and the vibration parameters of each gear of the transmission are measured on the EOL bench. Then, the transmission is mounted on a vehicle, the vibration parameters and acoustic parameters of corresponding working conditions are measured, and the subjective evaluation of the noise quality of the vehicle is carried out by using a grade scoring method. After this data is collected, the specific vibration parameters and acoustic parameters that are the dominant factors of sound quality are determined by correlation analysis. Based on the multiple linear regression method, the following mathematical models are formulated: the vibration parameters and the subjective evaluation of a vehicle, and the acoustic parameters and the subjective evaluation of a vehicle. Among these models, the mathematical models of the vibration parameters and the subjective evaluation of a vehicle were verified to be more accurate. The consistency between the vibration value in a vehicle and the vibration value on EOL test bench is analyzed and the EOL vibration value is determined to be the most objective evaluation of the data. After batch testing of 100 sets, the effectiveness of this model is within 95%. Finally, the value of critical amplitude of the condition of each gear of transmission is analyzed to form the judgment standard of transmission EOL vibration to ensure better sound quality for the vehicle.","PeriodicalId":510299,"journal":{"name":"Measurement and Control","volume":"138 48","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140369381","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 : 2024-03-27DOI: 10.1177/00202940241233504
Mingjun Deng, Pengyi Li, Xinxia Hu, Liping Xu
The fixed green wave speed and staged statistical flow used in arterial signal coordination are not adaptable to the fluctuations in vehicle travel speed and traffic flow on roads, resulting in a mismatch between the signal scheme and the optimal green wave speed and traffic flow demand. This discrepancy negatively impacts the efficiency of intersection traffic. In traditional signal control systems, the cycle and green light timing are typically set independently. However, such a setting method poses problems in practical operation. In this paper, we combine vehicle arrival and vehicle location information, and consider the interaction of speed guidance and dynamic signal optimization to construct a model. This study is developed along the following steps: in the vehicle-road coordination environment, based on the MAXBAND model, a global coordination scheme is obtained, incorporating the speed guidance method; then, based on the vehicle saturation of the inlet lane of the arterial intersection, a multi-objective optimization model for arterial signal coordination under vehicle speed guidance is established based on global coordination with the maximum green wave bandwidth and the minimum delay of arterial vehicles, the minimum number of arterial stops and the minimum delay in the minor direction road as the optimization objectives. Based on global coordination, adopting an integrated control mechanism of cycle and green light timing allows for dynamic adjustments according to real-time traffic conditions. The improved multi-objective particle swarm algorithm is chosen to solve the model, and the simulation environment is built based on the COM interface of VISSIM software and C# platform. Three adjacent intersections of Ganjiang Middle Road in Nanchang are selected as case studies, and the methods in this paper are compared with the current timing scheme, the MAXBAND method and the optimization scheme under speed guidance only, respectively. The results show that the model proposed in this paper achieves significant optimization effects on the indicators of arterial delay, arterial stopping times and the delay of minor roads.
干道信号协调采用的固定绿波速度和分阶段统计流量无法适应道路上车辆行驶速度和交通流量的波动，导致信号方案与最佳绿波速度和交通流量需求不匹配。这种差异对交叉口的交通效率产生了负面影响。在传统的信号控制系统中，周期和绿灯配时通常是独立设置的。然而，这种设置方法在实际操作中存在问题。本文结合车辆到达和车辆位置信息，考虑速度引导和动态信号优化的相互作用，构建了一个模型。本研究按照以下步骤展开：在车路协调环境下，基于 MAXBAND 模型，结合车速引导方法，得到全局协调方案；然后，基于干道交叉口进口车道的车辆饱和度，以全局协调为基础，以最大绿波带宽和干道车辆最小延误、干道最小停车次数和小方向道路最小延误为优化目标，建立车速引导下的干道信号协调多目标优化模型。在全局协调的基础上，采用周期和绿灯配时的综合控制机制，可根据实时交通状况进行动态调整。选用改进的多目标粒子群算法对模型进行求解，并基于 VISSIM 软件的 COM 接口和 C# 平台搭建了仿真环境。选取南昌市赣江中路三个相邻交叉口作为案例，分别与现行配时方案、MAXBAND 方法和仅速度诱导下的优化方案进行比较。结果表明，本文提出的模型在干道延误、干道停车时间和小路延误等指标上都取得了显著的优化效果。
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