2017 Prognostics and System Health Management Conference (PHM-Harbin)最新文献

{"title":"A roadmap for modeling and feature extraction of energy storage battery pack for marine energy power station","authors":"Liqiang Zhang, Lan-jun Liu, Rui Yang, Kun Wang, Zhen Chen, Ming Li","doi":"10.1109/PHM.2017.8079289","DOIUrl":"https://doi.org/10.1109/PHM.2017.8079289","url":null,"abstract":"This paper introduces the entire roadmap and detailed research methods of our NSFC project. A three-stage roadmap is proposed for energy store application of marine power station, and called upon to solve the key issues of health feature rapid extraction and modeling for battery pack. Efficient numerical modeling, rapid ICA and EIS testing and degradation of key features investigating makes the acquirement of the key features much faster. Graph theory and data mining method will be applied in the preparation of the performance and health relationship between cells and pack. A double-layer model will be finally proposed to describe the performance and health behavior of the battery pack. This project can provide a systematic method for extracting health features of energy store battery pack, the findings will enrich the theoretical understanding of battery pack health and its degradation mechanisms, and provide strong support for health status evaluation in further.","PeriodicalId":281875,"journal":{"name":"2017 Prognostics and System Health Management Conference (PHM-Harbin)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134234801","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}

{"title":"Dynamic response of steam seal rubbing in steam turbine considering thermal effect","authors":"Jingming Chen, D. Jiang","doi":"10.1109/PHM.2017.8079242","DOIUrl":"https://doi.org/10.1109/PHM.2017.8079242","url":null,"abstract":"Steam seal rubbing is a common problem bothering the power plant. Usually the rubbing happens during the process of start-up or shut-down. Some of the rubbings would cause the failure of start-up or even greatly damage the rotor, but some would not. This paper presents the dynamic response of steam seal rubbing rotor by simulation. The rubbing problem was a thermal/mechanical problem, which was decoupled by sequenced method in the simulation, i.e. the rotordynamics equation was solved in frequency domain and the heat conduction equation was solved in the time domain. The simulated results showed that the stiffness and the preload of the steam seal structure would greatly influence the amplitude and phase of the 1× vibration for a rubbing rotor. The dynamic response with a big stiffness would develop into spiraling state, and the rotor would fail to start up due to rubbing. What's worse, the partial of the rotor would be heated and bowed permanently. Therefore, it is very important to adjust the steam seal structure to reduce the stiffness of rubbing.","PeriodicalId":281875,"journal":{"name":"2017 Prognostics and System Health Management Conference (PHM-Harbin)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134428210","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}

{"title":"Reliability allocation for aircraft engines","authors":"Li Ming, W. Peng, Shangguan Xingjian, W. Lulu","doi":"10.1109/PHM.2017.8079162","DOIUrl":"https://doi.org/10.1109/PHM.2017.8079162","url":null,"abstract":"This paper studies reliability allocation methods for aircraft engines. The objective of the research is to develop an effective reliability allocation method for complex systems when only limited data can be obtained. A practical approach is proposed by considering complexity of the engine and data availability. Using this method, MTBF and Dispatch Reliability targets can be decomposed from higher to lower levels. It is based on reliability data of similar engines. Through deep-dive analysis on engine repair reports, reliability and maintenance data on similar engine models can be used as a baseline for reliability allocation of the new design. This method can be extended to other types of products.","PeriodicalId":281875,"journal":{"name":"2017 Prognostics and System Health Management Conference (PHM-Harbin)","volume":"66 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114049672","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}

{"title":"UAV engine fault and diagnosis with parameter models based on telemetry data","authors":"Huanzhen Fan, Hongzheng Fang, Yunfan Dong, Hui Shi, Shuai Ren","doi":"10.1109/PHM.2017.8079278","DOIUrl":"https://doi.org/10.1109/PHM.2017.8079278","url":null,"abstract":"It takes time to do feedback and control for the outer loop UAV system from failure to determine in the outer loop which will affect the stability of the system if not handled in time. As a large hysteresis delay complex systems it is the only way for UAV to master craft condition telemetry and remote data. UAV's prognostics and health management (PHM) technology, is to predict, monitor and manage the condition of UAV by using advanced sensor integration, real-time telemetry downlink data, and various algorithms and intelligent models. Based on the telemetry data and combined with actual engineering application demands UAVs, this paper analyzed the typical fault modes, established three UAV typical fault detection models, such as particle filter, K-Means cluster, Multi Layered Perceptron neural network.","PeriodicalId":281875,"journal":{"name":"2017 Prognostics and System Health Management Conference (PHM-Harbin)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121232638","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}

{"title":"A warranty period optimization strategy considering the change point of infant failure rate","authors":"Yi Wei, Yihai He, Chunling Zhu, Zhaoxiang Chen","doi":"10.1109/PHM.2017.8079229","DOIUrl":"https://doi.org/10.1109/PHM.2017.8079229","url":null,"abstract":"The point that the failure rate of a product tends to be steady and low from the high infant period is called change point. An ideal starting time of a warranty period should be exactly set as this point. The infant period of a life cycle is usually believed to be highly relative with the defects and failures which originated in production. However, due to the lack of studies on the mechanism of product infant failures, existing warranty policies usually assign the warranty periods without considering the change point of infant failure rate. To optimize the warranty policy and reduce the cost of product providers, the impacts of the usually overlooked manufacturing potential defects in the lifetime of a product is introduced in this paper at first. Second, a method to detect the change point by monitoring the tendency of the shape parameter of Weibull distributed products is introduced. Third, based on the identified change points of the infant failure rate, an optimization strategy of the warranty policy and the corresponding warranty cost model is derived. Finally, the model is verified by a warranty optimization example.","PeriodicalId":281875,"journal":{"name":"2017 Prognostics and System Health Management Conference (PHM-Harbin)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129337990","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}

{"title":"Rolling bearing fault diagnosis based on multipoint optimal minimum entropy deconvolution adjusted technique and direct spectral analysis","authors":"Yitian Wang, N. Hu, Lei Hu, Zhe Cheng","doi":"10.1109/PHM.2017.8079265","DOIUrl":"https://doi.org/10.1109/PHM.2017.8079265","url":null,"abstract":"This paper introduces a new idea of bearing fault diagnosis, which is to use the Multipoint Optimal Minimum Entropy Deconvolution Adjusted (MOMEDA) Technique to filter the vibration signal, getting the output signal and directly to do spectral analysis, then to observe the fault characteristics for fault diagnosis. MOMEDA technique is an improved MED algorithm proposed by McDonald in 2016, which can enhance the repetition of pulses in the signal. In this paper, MOMEDA is applied to the fault signal processing of rolling bearing. For bearing fault signal with constant speed, we firstly use MOMEDA technology to filter the signal, then do the frequency spectrum analysis. In addition, for variable speed bearing fault signal, this paper uses MOMEDA technology combined with resampling order analysis technology to analyze variable speed signal. The simulation signals and the bearing experimental data of Case Western Reserve University were processed, from the results, the direct spectral analysis after MOMEDA processing can obtain the fault characteristic without traditional envelope analysis, for fault diagnosis of bearing is simple and effective.","PeriodicalId":281875,"journal":{"name":"2017 Prognostics and System Health Management Conference (PHM-Harbin)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128560179","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}

{"title":"Real-time life prediction of equipment based on optimized ARMA model","authors":"Yangbo Tan, jinjun Cheng, Haizhen Zhu, Zewen Hu, Bowen Li, Shuai Liu","doi":"10.1109/PHM.2017.8079318","DOIUrl":"https://doi.org/10.1109/PHM.2017.8079318","url":null,"abstract":"Prediction with large error by traditional Autoregressive Moving Average (ARMA) theory has long been hampering accuracy in the life prediction. In this paper, methodology based on optimized ARMA model is proposed to provide real-time life prediction for equipment by utilizing information of degradation of similar equipment. Firstly, average relative change is used to optimize the orders of ARMA model, and the optimal model parameters are obtained. Afterwards, the ARMA model for similar equipment is established to get its degradation path sets. Then we get the degradation path sets of similar equipment that has the maximum similarity with specific equipment degradation path by K-means clustering. After that we get the specific equipment degradation path by weighting the equipment degradation path sets which are obtained by figuring out K-means clustering center with least similarity. By this algorithm, we can update the degradation path through real-time measured value, so as to predict the life of equipment timely. To test the model, operating current degenerating data of a laser is applied in this case study, and our study revealed that predicting accuracy using optimized model is evidently better than using model based on function degradation data of single equipment.","PeriodicalId":281875,"journal":{"name":"2017 Prognostics and System Health Management Conference (PHM-Harbin)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116770220","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}

{"title":"Construction of emergency response assistant system based on risk analysis for petrochemical unit","authors":"Zhao Zhang, Yankun Zhao, Lei Shi, Feng Wang","doi":"10.1109/PHM.2017.8079121","DOIUrl":"https://doi.org/10.1109/PHM.2017.8079121","url":null,"abstract":"Petrochemical hydrogenation unit has often been operated under high-temperature, high-pressure or critical hydrogen condition, probably resulting in severe accident such as leaking, fire and explosion. The reasonable emergency response program is an important guarantee for controlling the spread of risk and reducing the consequence of accident. There are a lot of database files in petrochemical units, and it is urgent to put forward a method of data classification and fast positioning for effective management. When the abnormal condition occurs, it can respond in time to find the data document needed to deal with the problems. The lacks of emergency response plans, difficulties in rescue information location and improper rescue measures have severe impact on the promptness and validity of the emergency response. The construction method of emergency response assistant system based on risk analysis was proposed and applied on residual oil hydrogenation unit. First, Hazard and Operability Analysis (HAZOP) was applied on qualitatively analyze the potential risks of the entire process. The probability of events of risk spread path was quantitatively calculated through establishing a Bayesian network model for the whole process. The consequence effect and the damage area could be acquired by conducting PHAST simulation. Secondly, equipment technical data was classified by using process safety document management (PSM) method, and established a knowledge database of emergency response information. Units risk analysis result can be matched up with emergency response document and emergency response information integrated management and knowledge remote network share could be achieved due to this database. Finally, the emergency response assistant system based on risk analysis was established. When the unit worked under an abnormal condition, the required technical information for risk event or accident treatment could be obtained at first time. According to clear emergency response step description and reasonable evacuation route and distance, emergency workers could deal with accidental problem efficiently and orderly.","PeriodicalId":281875,"journal":{"name":"2017 Prognostics and System Health Management Conference (PHM-Harbin)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116279038","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}

{"title":"Wavelet transform based convolutional neural network for gearbox fault classification","authors":"Yixiao Liao, Xueqiong Zeng, Weihua Li","doi":"10.1109/PHM.2017.8079274","DOIUrl":"https://doi.org/10.1109/PHM.2017.8079274","url":null,"abstract":"As a valid method of time-frequency analysis, Wavelet transform (WT) can offer great help for gearbox fault diagnosis. However, it requires much human expertise and prior knowledge to diagnose the faulty conditions of gearbox according to the time-frequency distribution. In addition, the coupling of different failures and noise makes it hard to accurately diagnose the running conditions of the gearbox. In this paper, the convolutional neural network (CNN) is applied for the classification of gearbox health conditions with the time-frequency image generated by WT. As a typical model of deep learning, CNN has distinguished capacity in image recognition. It can automatically extract faulty features from time-frequency images, which can depress the uncertainty of artificial feature extraction. For comparison, S-transform (ST) and short time Fourier transform (STFT) are combined with CNN for the same classification task. Experimental result indicates that the combination of WT and CNN is superior to other methods.","PeriodicalId":281875,"journal":{"name":"2017 Prognostics and System Health Management Conference (PHM-Harbin)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114442961","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}

{"title":"Modeling and simulation analysis of pressure-sensing characteristics for piezoresistive pressure sensor based on graphene/hexagonal boron nitride heterostructures","authors":"Zhongzheng Fang, Yong Zhang, J. Qiu, Guanjun Liu","doi":"10.1109/PHM.2017.8079174","DOIUrl":"https://doi.org/10.1109/PHM.2017.8079174","url":null,"abstract":"Small and high-precision piezoresistive pressure sensor based on graphene/hexagonal boron nitride (h-BN) heterostructures can be embedded in aircraft airborne equipment, allowing for potential application involving fault diagnosis, prognostics and health management. In this paper, the pressure-sensing characteristics of graphene/h-BN heterostructures membrane — the relationship between pressure and strain were studied by finite element modeling and simulation method. On the one hand, the pressure-sensing characteristics models of circular, rectangular and square graphene/h-BN heterostructures membrane were established by finite element simulation software COMSOL. On the other hand, h-BN/graphene/h-BN heterostructures and monolayer graphene also have been selected for comparative analysis. The above results provide an effective quantitative guidance for the structure and performance designing of piezoresistive pressure sensors based on graphene/h-BN heterostructures.","PeriodicalId":281875,"journal":{"name":"2017 Prognostics and System Health Management Conference (PHM-Harbin)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126730837","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}