2016 IEEE International Conference on Prognostics and Health Management (ICPHM)最新文献

Integrated Hilbert Huang technique for bearing defects detection 轴承缺陷检测的集成希尔伯特黄技术

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-08-15 DOI: 10.1109/ICPHM.2016.7542877

Shazali Osman, Wilson Q. Wang

{"title":"Integrated Hilbert Huang technique for bearing defects detection","authors":"Shazali Osman, Wilson Q. Wang","doi":"10.1109/ICPHM.2016.7542877","DOIUrl":"https://doi.org/10.1109/ICPHM.2016.7542877","url":null,"abstract":"Nowadays, the modern rotating machinery industries, such as automotive industries, aerospace turbo machinery, chemical plants, and power stations, are rapidly increasing in complexity and in their everyday operations, which demand the system to operate in higher reliability, extreme safety, and with lower cost of production and maintenance. Therefore accurate fault diagnosis of machine failure is vital to the operation and production departments. The majority of Machine imperfections and malfunctions have been related to bearings faults. Many researchers are still exploring to find suitable diagnosis strategies and techniques to detect incipient bearing faults. A new integrated Hilbert-Huang technique (iHT) is proposed in this paper for bearing fault detection. The iHT takes two processes; firstly: representative signatures are extracted and secondly the resulting selected features are employed to highlight defect-related impulses for incipient bearing fault detection. A novel Jarque-Bera analysis method is suggested to select most prominent characteristic feature functions and the signals are integrated to enhance the features of the condition related function. The effectiveness of the proposed iHT technique is verified by a series of experimental tests corresponding to different bearing health conditions.","PeriodicalId":140911,"journal":{"name":"2016 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116866689","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: 1

Correlation analysis for impedance-based health monitoring of electromagnetic coils 基于阻抗的电磁线圈健康监测相关分析

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-08-15 DOI: 10.1109/ICPHM.2016.7542842

N. J. Jameson, M. Azarian, M. Pecht

{"title":"Correlation analysis for impedance-based health monitoring of electromagnetic coils","authors":"N. J. Jameson, M. Azarian, M. Pecht","doi":"10.1109/ICPHM.2016.7542842","DOIUrl":"https://doi.org/10.1109/ICPHM.2016.7542842","url":null,"abstract":"Electromagnetic coils are widely used components in a variety of industries and systems, including electric motors and solenoids. The failure of electromagnetic coil insulation can lead to catastrophic failure of the coil and subsequently, the component and system in which the coil is used. In this paper, a method of locating frequencies in the impedance spectrum that are not only useful for health monitoring, but reveal the changing electrical behavior of coil due to degraded wire insulation is demonstrated. The Spearman rank correlation coefficient can be used to measure linear or non-linear monotonic relationships between two variables. Hence, the measure is more general than the Pearson correlation coefficient, which measures only the linear correlation between two variables. First, experiments were performed where electromagnetic coils were subjected to degrading environments while measuring the impedance spectra of the coils. These complex impedance spectrum measurements are split into real and imaginary parts, resistance and reactance, respectively. The values of resistance and reactance at each frequency constitute a set of features, each of which is a potential health indicator. Second, the impedance time series at each frequency is correlated with degradation time using Spearman correlation. Next, the Spearman correlation coefficient is plotted against frequency to construct an impedance frequency-correlation diagram, providing an understanding of the extent to which each frequency can be used to monitor the health of the coil, and whether the impedance at each frequency increases or decreases over the aging period. The results indicate that the Spearman correlation coefficient is a tool that can be utilized to identify the frequencies at which to monitor the coil for health monitoring purposes. Furthermore, comparisons between environmental aging tests show the impedance frequency-correlation diagrams can be applied in understanding the mechanisms of degradation.","PeriodicalId":140911,"journal":{"name":"2016 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125710304","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: 1

Frequency analysis on vibration signatures for gearbox spalling defect detection 齿轮箱剥落缺陷检测的振动特征频率分析

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542869

Weidong Li, A. Dadouche, Jie Liu

{"title":"Frequency analysis on vibration signatures for gearbox spalling defect detection","authors":"Weidong Li, A. Dadouche, Jie Liu","doi":"10.1109/ICPHM.2016.7542869","DOIUrl":"https://doi.org/10.1109/ICPHM.2016.7542869","url":null,"abstract":"Gearboxes are widely used in rotary machinery for mechanical power transmission and are prone to faults. Vibration signature analysis usually provides a good potential for gearbox incipient fault detection. This article presents an application of frequency analysis on vibration signatures obtained from a faulty gearbox. Experiments were carried out on an accessory gearbox of a J85 engine, which serves on several aircrafts such as Canadair CT-114 Tutor. Real operating system of the gearbox is reconstructed on a test rig located at the National Research Council of Canada. A spalling defect was artificially introduced to a flank of one of the pinions of the gearbox at the meshing section. Vibrations of the gearbox under various operating conditions are measured by an accelerometer mounted on the gearbox housing. Raw signals are first time synchronous-averaged (TSA) to reduce noise and then the averaged signals are transformed into frequency domain for analysis. Order analysis, which represents all frequencies in terms of shafts' rotating frequency, is employed instead of traditional frequency analysis in this investigation. Testing results demonstrate that the fundamental and the second gear mesh frequency (GMF) contain the major features of the gearbox health condition. Analysis results also show that at a constant operating speed, the spalling defect attenuates the power of the fundamental GMF while strengthens the power of the second GMF. Accordingly, the magnitude ratio between the fundamental and the second GMF is introduced as an indicator for spalling defect detection. The fault indicator is capable of clearly distinguishing the normal pinion from the defected one. It is also observed that the proposed fault indicator is robust and is consistent as the load on the gear is varied.","PeriodicalId":140911,"journal":{"name":"2016 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115431920","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: 5

An improved fault diagnosis approach based on support vector machine 基于支持向量机的改进故障诊断方法

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542827

Qi Zhao, Bingqian Wang, Gan Zhou, Wenfeng Zhang, XiuMei Guan, W. Feng

引用次数: 1

Data-driven prognostic techniques for estimation of the remaining useful life of lithium-ion batteries 锂离子电池剩余使用寿命估算的数据驱动预测技术

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542870

R. Razavi-Far, Maryam Farajzadeh-Zanjani, Shiladitya Chakrabarti, M. Saif

引用次数: 22

A prediction method for aero-engine health management based on nonlinear time series analysis 基于非线性时间序列分析的航空发动机健康管理预测方法

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542816

Qiang Huang, Haixia Su, Jian Wang, Weixing Huang, Guigang Zhang, Jiayang Huang

引用次数: 5

Application of PSO-ELM in electronic system fault diagnosis PSO-ELM在电子系统故障诊断中的应用

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542818

Shaowei Chen, Y. Shang, Minhua Wu

{"title":"Application of PSO-ELM in electronic system fault diagnosis","authors":"Shaowei Chen, Y. Shang, Minhua Wu","doi":"10.1109/ICPHM.2016.7542818","DOIUrl":"https://doi.org/10.1109/ICPHM.2016.7542818","url":null,"abstract":"Extreme Learning Machine (ELM) has many advantages, such as fast learning speed, good generalization performance and high diagnostic accuracy when it is applied in fault diagnosis, but its classification performance is affected by the two network random parameters-input weights and thresholds. Particle swarm optimization (PSO) algorithm has the characteristics of simple, easy to implement and found the local optimum quickly. This paper proposes the Particle Swarm Optimization algorithm (PSO) to optimize the two parameters and to obtain the electronics system fault diagnosis based on PSO-ELM. Two analog circuits, one is complex; the other is simple, are designed to obtain the original data in the essay. Then, wavelet transform and PCA are combined to extract the feature of samples information. Take the processed data into the PSO-ELM to get the diagnosis results, meanwhile, compared the optimal performance of PSO, glowworm swarm optimization (GSO)and bat algorithm (BA) to ELM, experiments show that PSO is the most efficient to improve the diagnostic accuracies of the two circuits, the results obtained with PSO-ELM reach to 98.89% and 99.46% respectively.","PeriodicalId":140911,"journal":{"name":"2016 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122502398","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: 10

Failure simulation and identification of shock absorber in carrier-based aircraft landing gear 舰载机起落架减振器失效仿真与辨识

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542833

Hui Yang, Fangyi Wan, W. Cui

{"title":"Failure simulation and identification of shock absorber in carrier-based aircraft landing gear","authors":"Hui Yang, Fangyi Wan, W. Cui","doi":"10.1109/ICPHM.2016.7542833","DOIUrl":"https://doi.org/10.1109/ICPHM.2016.7542833","url":null,"abstract":"The gas-oil leakage in the shock absorber of carrier-based aircraft landing gear is a frequent and common failure, which can deteriorate the absorbing performance. However rarely research is done to quantitatively analysis the coupling effect of gas-oil leakage on the absorbing performance. In this paper, the failure simulation and identification of shock absorber is studied by numerical modeling and simulation experiment. To analyze the effect of gas-oil leakage on the shock absorber, the equivalent air spring stiffness is deduced. And Kringing model is introduced to surrogate gas-oil leakage to further present the relation of corresponding shock absorber time to residual gas quantity and oil volume. Then an efficient method is proposed to identify the failure of gas-oil leakage. The simulation experiment is designed to verify the theory presented in this paper. The result of numerical model explains that the gas cushioning property is influenced by both gas and oil property. The simulation model is used to obtain the coupling effect curve of gas-oil leakage on the absorbing time. Eventually the analytical results show that the shock absorber performance varies with different gas-oil ratio caused by gas-oil leakage.","PeriodicalId":140911,"journal":{"name":"2016 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122074618","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: 3

Model-based fault diagnosis and prognosis for Electric Power Steering systems 基于模型的电动助力转向系统故障诊断与预测

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542840

Wen-Chiao Lin, Y. Ghoneim

{"title":"Model-based fault diagnosis and prognosis for Electric Power Steering systems","authors":"Wen-Chiao Lin, Y. Ghoneim","doi":"10.1109/ICPHM.2016.7542840","DOIUrl":"https://doi.org/10.1109/ICPHM.2016.7542840","url":null,"abstract":"Electric Power Steering (EPS) is an advanced steering system that consists of two subsystems: electrical and mechanical subsystems. EPS systems not only provide steering assist to drivers but they are also actuators for recently developed active safety features, such as lane keeping and lane changing assist. Failure of some component of the EPS system can lead to walk-home situations and increased warranty costs. Hence, for the improvement of reliability, safety, and efficiency of EPS systems, fault detection, diagnosis, and prognosis become increasingly important. This paper provides fault detection for EPS systems through model-based techniques using parameter estimation to determine the current electric parameters of the EPS motor. In addition, by monitoring the deviation of the self-aligning torque (SAT) estimated from two different methods, changes in EPS mechanical parameters can be detected. The progression of this deviation can be fed into a health state estimator which can give an indication of state of health and remaining useful life. Computer simulations as well as hardware-in-the-loop (HIL) experiments are provided to illustrate this method. Finally, for integrated system diagnosis and fault isolation, a fault signature table is constructed based on estimations of motor parameters, calculations of road SAT, and residuals of parity equations. This table can be used to detect and isolate considered electrical, mechanical, and sensor faults in the EPS system and simulation results are shown to verify the developed ideas.","PeriodicalId":140911,"journal":{"name":"2016 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130608840","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: 9

Aviation PHM system research framework based on PHM big data center 基于PHM大数据中心的航空PHM系统研究框架

2016 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2016-06-20 DOI: 10.1109/ICPHM.2016.7542824

Lu Yang, Jian Wang, Guigang Zhang

引用次数: 14