2012 Prognostics and System Health Management Conference (PHM)

Conference Information
Name: 2012 Prognostics and System Health Management Conference (PHM)
Location: Beijing, China
Date: 2012-5-23 - 2012-5-25

Latest articles from this conference

Yizhou He, Lin Ma
Proceedings of the IEEE 2012 Prognostics and System Health Management Conference (PHM-2012 Beijing) pp 1-6; https://doi.org/10.1109/phm.2012.6228813

Prognostics and Health Management(PHM) is a support technology on the base of equipment Integrated Diagnostics and there are many authors have researched the PHM architecture with the object of mechanical equipment. This paper is aim to construct the PHM architecture in the area of electrical equipment. In order to solve this problem, this paper firstly review the history of PHM briefly and then analyzes the main elements of general PHM system. By the research of these elements and design process, the PHM system architecture is given for electronic equipment.
Feng Wang, Jianguo Zhang, Xianchao Wang, Cancan Wang, Zhan Liu
Proceedings of the IEEE 2012 Prognostics and System Health Management Conference (PHM-2012 Beijing) pp 1-5; https://doi.org/10.1109/phm.2012.6228861

This paper is concerned with the non-probabilistic methods to deal with uncertainties problems. First, this paper analyzes the difference between non-probabilistic reliability methods and traditional probabilistic reliability methods, which makes the comparative analysis on aspects of the application scope of methods, the use of processes and the complexity of employment. Second, this paper introduces the basic concept of the convex model, as the interval model, the ellipsoid model and the multidimensional ellipsoid model are briefly presented. Third, this paper analyzes the use of information gap model of uncertainty, including the basic application of the model and the way to use. Finally, numerical example is given to illustrate the validity and efficiency of non-probabilistic reliability method. The example used herein is reliability analysis of fatigue strength of turbine blade, but it is also an important reference of other types of uncertainties systems. Compared with the probability approach, the non-probabilistic information gap model only requires a small amount of samples to obtain the variation bounds of the imprecise parameters, and whereby makes the reliability analysis very convenient and economical.
Qingbo He, Xiangxiang Wang
Proceedings of the IEEE 2012 Prognostics and System Health Management Conference (PHM-2012 Beijing) pp 1-6; https://doi.org/10.1109/phm.2012.6228867

For rotating machines, the localized faults of key components generally represent as periodic transient impulses in vibrations. The existence of background noise will submerge the transient impulses in practice, and will thus increase the difficulty to identify specific faults. This paper proposes a novel fault demodulation method based on time-frequency manifold (TFM) to solve the aforementioned problem. This method uses the TFM base to demodulate the periodic impulses from raw signals. It mainly includes two following steps: first, the TFM is obtained by addressing manifold learning on the time-frequency distributions (TFD); second, a short TFM is adopted as a template to do correlation analysis with the original TFD. The proposed demodulation method can achieve a high resolution for identifying interesting impulse components. The novel method is verified to be superior to traditional enveloping demodulation method by means of simulation signal analysis and application to gearbox fault detection.
Jianshe Kang, Xinghui Zhang, Jianmin Zhao, Hongzhi Teng, Duanchao Cao
Proceedings of the IEEE 2012 Prognostics and System Health Management Conference (PHM-2012 Beijing) pp 1-13; https://doi.org/10.1109/phm.2012.6228866

This paper presents an intelligent method for gear fault diagnosis based on wavelet packet analysis and support vector machine (SVM). For this purpose, two experiments were selected to verify the proposed method. One is a spur gear of the motorcycle gearbox system. Slight-worn, medium-worn, and broken-tooth were selected as the faults. In fault simulating, two very similar models of worn gear have been considered with partial difference for evaluating the preciseness of the proposed method. The other one is a helical gear of a gearbox system. Broken-tooth and crack in root of gear were selected as the faults. Raw vibration signals were segmented into the signals recorded during one complete revolution of the input shaft using tachometer information and then synchronized using cubic spline interpolation to construct the sample signals with the same length. Next, standard deviations of wavelet packet coefficients of the vibration signals which have been normalized and dimension deducted using principal component analysis (PCA) were considered as the feature vector for training purposes of the SVM. The parameters of SVM are optimized using particle swarm optimization (PSO). Its effectiveness is verified by experimental results.
Yu Pei, Wei Pan, Lifeng Wu, Yong Guan, Shengzhen Jin
Proceedings of the IEEE 2012 Prognostics and System Health Management Conference (PHM-2012 Beijing) pp 1-4; https://doi.org/10.1109/phm.2012.6228950

The power supply is a typical equipment. It is used widely. At the same time, it is difficult to solve its fault diagnosis problem by using general or traditional fault diagnosis theory and method, because of its uncertainty, fuzzy and other questions. Rough Set (RS) represents the uncertainly technology which provides an effective approach to resolve these issues, receives more academic attention nowadays. During the process of fault diagnosis, people always face incomplete information systems due to data measurement, obtaining restrictions and other reasons. However, the classical RS theory is based on the complete system. So we proposed a new method about data filling on the basis of discrepancy relation. Experiment shows that this method can effectively increase the precision and decrease the conflict rate.
Jianmin Zhao, Chang'an Xu
Proceedings of the IEEE 2012 Prognostics and System Health Management Conference (PHM-2012 Beijing) pp 1-7; https://doi.org/10.1109/phm.2012.6228941

A condition-based order-replacement policy is presented for a single-unit system, in order to optimize the maintenance and the spare parts inventory jointly. In this policy, equipment degradation is modeled using a continuous gamma process and degradation information may be obtained from continuous state monitoring. A simulation model is developed by integrating the process of deterioration, condition monitoring, replacement activities and spare provisioning. On this basis, the Monte-Carlo method and the iterative method are utilized to get the best preventive maintenance threshold Dpm and maximum stock level S. Numerical experiments have shown that a reasonable optimal solution can be obtained by employing a decision-making on maintenance and spare parts inventory under the promise of satisfy specified stockout probability.
Guohui Wang, Yong Guan, Jie Zhang, Lifeng Wu, Xueyuan Zheng, Wei Pan
Proceedings of the IEEE 2012 Prognostics and System Health Management Conference (PHM-2012 Beijing) pp 1-6; https://doi.org/10.1109/phm.2012.6228949

Aluminum electrolytic capacitors are usually used in DC-DC converters as smoothing capacitors. According to the statistics data, they are the weakest among various power components in the DC-DC converter. With the increase of the running time, the performance degradation of electrolytic capacitors reflects in electrical parameters, mainly the Equivalent Series Resistance (ESR) and capacitance. The best indicator of the output filter capacitor failure is the increase of ESR. And the output ripple voltage of the converter increases with respect to ESR. Monitoring the ESR variation of the electrolytic capacitor, achieving by voltage and current ripple, can estimate the health state of the converter.
Hua Wang, Xianyu Li, Jianqun Zheng, Peitao Liu, Zhengmao Chen, Rua Wang
Proceedings of the IEEE 2012 Prognostics and System Health Management Conference (PHM-2012 Beijing) pp 1-4; https://doi.org/10.1109/phm.2012.6228943

Based upon the summarization of system availability engineering, this paper sets forth the availability management works, such as the development demonstration, the technical reviews, the question eliminating and configuration management of the Information Processing System, and depicts the measures taken in the system reliability, maintainability and supportability design, and then the system availability models are deduced of full functions, main functions and lowest functions, moreover the system availability is quantitatively analyzed. Thenceforth the further prospect of the availability engineering of Information Processing System is presented.
H. Zhang, J. Zhou, S. S. Ang, J. C. Balda, H. A. Mantooth
Proceedings of the IEEE 2012 Prognostics and System Health Management Conference (PHM-2012 Beijing) pp 1-6; https://doi.org/10.1109/phm.2012.6228948

The reliability assessment for a 10 kV, wire-bondless power electronics module with a double-sided cooling was investigated. A direct solder attachment was employed to minimize parasitic circuit elements and increase current handling capability as well as to enable double-sided cooling capability with mechanical robustness. Finite element simulations were performed to investigate the reliability of the power module in terms of the thermal, electrical and mechanical performance. To further enhance the high-voltage reliability, a polyamide imide (PAI) nano material as a high-voltage passivation was employed. Wire bondless power modules have been fabricated and passivated using the PAI hybrid nano material. These power modules were tested up to 10 kV.
Alexandr Kirillov, Sergey Kirillov,
Proceedings of the IEEE 2012 Prognostics and System Health Management Conference (PHM-2012 Beijing) pp 1-11; https://doi.org/10.1109/phm.2012.6228771

This work describes mathematical models and computing cluster for early failure prognosis and accurate estimates of remaining useful life (RUL) for technical objects: internal combustion engines, gas turbine, hydroelectric turbines, wind turbines, etc. The hierarchy of mathematical models for prognosis (CH&P) is based on a hierarchy of degrees of developed failure, and solves the problem of accurate assessment of RUL; determines the required physical parameters for the prediction and risk assessment; classifies the signs and their evolution at all stages of development. In the absence of early incipient fault the mathematical model identifies incipient of fault cause, the time evolution of which leads to the appearance of early incipient fault. In the absence of incipient of fault cause the hierarchical mathematical model analyzes the state of the system using the methods of symbolic and topological dynamics to identify the evolution of symbolic hidden trajectories of the observed signals, which leads to Incipient of hidden fault cause. Thus, the hierarchical mathematical model provides the earliest prognosis of occurrence of failure causes. It is also noted that in the analysis stage of hidden trajectories (preventive prognosis) is possible a physical reversibility in the technical system. There is a legitimate question about the implementation of the automatic stochastic management by system in real time in order to avoid failure at the stage of the appearance of their hidden causes.
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