2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC)最新文献_第7页

Classifying Mangrove Crub Images for Growth Stages Detection and Monitoring 红树林碎石图像分类用于生长阶段检测与监测

2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC) Pub Date : 2019-08-01 DOI: 10.1109/SDPC.2019.00134

Jasmin Almarinez, Alexander A. Hernandez

引用次数: 0

State Assessment Method of Fire Control System Based on Fusion of Grey Relational and D-S Evidence Theory 基于灰色关联与D-S证据理论融合的火控系统状态评估方法

2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC) Pub Date : 2019-08-01 DOI: 10.1109/SDPC.2019.00034

Li Yingshun, Min Zheng, Weiyan Tong, X. Yi

{"title":"State Assessment Method of Fire Control System Based on Fusion of Grey Relational and D-S Evidence Theory","authors":"Li Yingshun, Min Zheng, Weiyan Tong, X. Yi","doi":"10.1109/SDPC.2019.00034","DOIUrl":"https://doi.org/10.1109/SDPC.2019.00034","url":null,"abstract":"A state assessment method based on fusion of grey correlation analysis and D-S evidence theory is proposed by taking the fire control computer and sensor subsystem of armored equipment as the research object. Firstly, the state evaluation model based on information fusion is established, and the basic knowledge of information fusion technology, D-S evidence theory and grey correlation degree are briefly introduced. Because there are many indicators in the research object and the signals are complicated to process. Therefore, the gray correlation analysis method is used to reduce the redundant index and optimize the index system. Then, the credibility distribution of each index in the reduction set is obtained, and the D-S evidence theory is used to fuse the results of the reduction to obtain the state assessment result. Finally, the gray correlation analysis method and D-S evidence theory constitute a complete information fusion system. The test results of the actual fire control system status data prove that the results are consistent with the prior knowledge, which proves the credibility of the method.","PeriodicalId":403595,"journal":{"name":"2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134256884","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}

引用次数: 0

Determination of Easy Parking Points of Train Driving Interval Based on UAS and BP Neural Network Linear Grey system 基于UAS和BP神经网络线性灰色系统的列车行驶区间易停车点确定

2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC) Pub Date : 2019-08-01 DOI: 10.1109/SDPC.2019.00031

Jun Shen, Hongyu Zhou, Jiahui Feng, Yang Chai, Qingyuan Wang

引用次数: 0

The Research of New Black Box Control Method Based on Conjugate Gradient Algorithm 基于共轭梯度算法的新型黑盒控制方法研究

2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC) Pub Date : 2019-08-01 DOI: 10.1109/SDPC.2019.00065

Weiwei Ma, Yong Zhou, Jiakuan Gao

{"title":"The Research of New Black Box Control Method Based on Conjugate Gradient Algorithm","authors":"Weiwei Ma, Yong Zhou, Jiakuan Gao","doi":"10.1109/SDPC.2019.00065","DOIUrl":"https://doi.org/10.1109/SDPC.2019.00065","url":null,"abstract":"With the development of artificial neutral network and control science, black box control has become one of the most popular topics for the researchers because of its good performance of the self-adaptivity, robustness and antidisturbance in recent years. Since there are lots of drawbacks for the BP neutral networks such as low converging speed and uncertainly of network structure and weight factors. This paper develops a new modified F-R algorithm to improve converging speed of back propagation neutral network and tries to eliminate the bad effect to the whole control system caused by uncertainty. The topology structure and weight factor of the neutral network are optimized by using GA (Genetic Algorithm) offline. This paper introduces servo control system, network optimization algorithm, gradient descent algorithm, and modified Fletcher- Reeves algorithm. The black box algorithm is programed in MATLAB and simulated in the Simulink for control system. During the simulating experiment, the load disturbance is added to test the capability to withstand the disturbance. The results show that the modified Fletcher-Reeves algorithm has the better performance in the response time, overshooting and antidisturbance ability compared with other two methods. In the end, the experiment is carried out based on the successful simulation. The control program is finished in LabVIEW and applied to the servo-control systems of EMA (Electron-mechanic Actuator). The results indicate the response of the system has the better stability and rapidity, which can meet the requirements of engineering application greatly.","PeriodicalId":403595,"journal":{"name":"2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131990301","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}

引用次数: 0

Integrated Group Method of Data Handing Framework for Remaining Useful Life Prediction 剩余使用寿命预测数据处理框架的集成成组方法

2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC) Pub Date : 2019-08-01 DOI: 10.1109/SDPC.2019.00160

Xin Ge, Shunjie Zhang, Q. Cheng, Xuejun Zhao, Yong Qin

引用次数: 0

A Joint Model of Virtual and Actual Maintenance Time with Covariates 带协变量的虚拟与实际维修时间联合模型

2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC) Pub Date : 2019-08-01 DOI: 10.1109/SDPC.2019.00054

Xiaoyue Xie, Jian Shi, X. Yi, Shulin Liu

引用次数: 0

On-board Sensor Data Monitoring System For Unmanned Aerial Vehicle PHM 无人机PHM机载传感器数据监测系统

2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC) Pub Date : 2019-08-01 DOI: 10.1109/SDPC.2019.00102

Mingxi Jiang, Benkuan Wang, Datong Liu, Yu Peng

{"title":"On-board Sensor Data Monitoring System For Unmanned Aerial Vehicle PHM","authors":"Mingxi Jiang, Benkuan Wang, Datong Liu, Yu Peng","doi":"10.1109/SDPC.2019.00102","DOIUrl":"https://doi.org/10.1109/SDPC.2019.00102","url":null,"abstract":"Due to the excellent performance and cost-effective, unmanned aerial vehicle (UAV) has been widely used in civil and military fields. But the accident rate of UAV is much higher than that of manned aircraft. Therefore, the sensor data monitoring of UAV has become a research hotspot, which can further support UAV Prognostics and Health Management (PHM). However, the on-board computing resources and power are limited, and most state-of-the-art sensor data monitoring methods can only be operated on ground. A huge challenge is presented to UAV real-time condition monitoring. In this paper, an on-board system is developed for real-time fixed-wing UAV sensor monitoring. Firstly, an LSTM network is designed to fulfill accurate estimation of UAV sensor data. Secondly, the sensor data estimation model with high computational complexity is accelerated by utilizing High Level Synthesis (HLS). Finally, the calculation optimized model is deployed in an on-board embedded hardware platform. The simulated fixed-wing UAV flight data are used to verify the performance of the proposed system. The experimental results show that the proposed system is effective for fixed-wing UAV real-time sensor data estimation.","PeriodicalId":403595,"journal":{"name":"2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128090402","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}

引用次数: 2

A Fault Diagnosis Method for Valve Train of Diesel Engine Considering Incomplete Feature Set 考虑不完全特征集的柴油机配气机构故障诊断方法

2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC) Pub Date : 2019-08-01 DOI: 10.1109/SDPC.2019.00161

Zhinong Jiang, Y. Lai, Zijia Wang, Jinjie Zhang

{"title":"A Fault Diagnosis Method for Valve Train of Diesel Engine Considering Incomplete Feature Set","authors":"Zhinong Jiang, Y. Lai, Zijia Wang, Jinjie Zhang","doi":"10.1109/SDPC.2019.00161","DOIUrl":"https://doi.org/10.1109/SDPC.2019.00161","url":null,"abstract":"Abnormal valve clearance is a common fault of diesel engine, and early warning of abnormal valve clearance plays an important role in the condition based maintenance of diesel engine. Although information fusion technology can improve the accuracy of fault diagnosis, it cannot guarantee that the fused features can perfectly represent the required key information. For the incomplete feature set, a method combining multi-domain feature and improved support vector machine is proposed. Firstly, the extraction of multi-domain feature is carried out to deeply explore the state information of valve train contained in the original vibration signal. The statistical characteristics and waveform characteristics are extracted from time domain vibration signals, and the frequency domain feature similar to time-domain feature is extracted after the Fourier transform of the vibration signal. What’s more, according to the working principle of diesel engine, the energy characteristics in angular frequency domain are extracted. Then, an improved support vector machine method based on multi-domain feature is proposed to further reduce the diagnostic errors caused by incomplete feature set. Finally, the proposed method is compared with other traditional methods about the fault diagnosis of valve train of diesel engine. The results show that the proposed method is applicable to the fault diagnosis of valve train of diesel engine with good accuracy, and the generalization ability of diagnostic model is greatly improved.","PeriodicalId":403595,"journal":{"name":"2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134325247","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}

引用次数: 0

Prediction of Photovoltaic Power Generation Based on PSO-RNN and SVR Model 基于PSO-RNN和SVR模型的光伏发电预测

2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC) Pub Date : 2019-08-01 DOI: 10.1109/SDPC.2019.00174

Z. Luo, F. Fang

引用次数: 0

Influence of the debris trajectory on output inductive signal in large-diameter particle detector 碎片轨迹对大直径颗粒探测器输出感应信号的影响

2019 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC) Pub Date : 2019-08-01 DOI: 10.1109/SDPC.2019.00117

Leng Han, Xinyu Wang, Song Feng, Dewei Yang, Hong Xiao

引用次数: 0