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Generating Indicators for Diagnosis of Fault Levels by Integrating Information from Two or More Sensors

Generating Indicators for Diagnosis of Fault Levels by Integrating Information from Two or More Sensors

Xiaomin Zhao, Ming J. Zuo, Ramin Moghaddass
Copyright: © 2013 |Pages: 24
ISBN13: 9781466620957|ISBN10: 1466620951|EISBN13: 9781466620964
DOI: 10.4018/978-1-4666-2095-7.ch004
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MLA

Zhao, Xiaomin, et al. "Generating Indicators for Diagnosis of Fault Levels by Integrating Information from Two or More Sensors." Diagnostics and Prognostics of Engineering Systems: Methods and Techniques, edited by Seifedine Kadry, IGI Global, 2013, pp. 74-97. https://doi.org/10.4018/978-1-4666-2095-7.ch004

APA

Zhao, X., Zuo, M. J., & Moghaddass, R. (2013). Generating Indicators for Diagnosis of Fault Levels by Integrating Information from Two or More Sensors. In S. Kadry (Ed.), Diagnostics and Prognostics of Engineering Systems: Methods and Techniques (pp. 74-97). IGI Global. https://doi.org/10.4018/978-1-4666-2095-7.ch004

Chicago

Zhao, Xiaomin, Ming J. Zuo, and Ramin Moghaddass. "Generating Indicators for Diagnosis of Fault Levels by Integrating Information from Two or More Sensors." In Diagnostics and Prognostics of Engineering Systems: Methods and Techniques, edited by Seifedine Kadry, 74-97. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2095-7.ch004

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Abstract

Diagnosis of fault levels is an important task in fault diagnosis of rotating machinery. Two or more sensors are usually involved in a condition monitoring system to fully capture the health information on a machine. Generating an indicator that varies monotonically with fault propagation is helpful in diagnosis of fault levels. How to generate such an indicator integrating information from multiple sensors is a challenging problem. This chapter presents two methods to achieve this purpose, following two different ways of integrating information from sensors. The first method treats signals from all sensors together as one multi-dimensional signal, and processes this multi-dimensional signal to generate an indicator. The second method extracts features obtained from each sensor individually, and then combines features from all sensors into a single indicator using a feature fusion technique. These two methods are applied to the diagnosis of the impeller vane trailing edge damage in slurry pumps.

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