ASQ - Electronics and Communications Division

Sensor Recovery for Robust Multivariate Condition Monitoring

Abstract: 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must first be obtained from the IEEE.

The ability to predict and prevent equipment failures is essential to various industrial processes and military operations. In recent years, Condition Monitoring (CM) has been recognized as an effective paradigm in this regard. CM can be performed via several sensor channels with broad coverage to enhance monitoring capabilities. However, loss of sensor readings due to malfunction of connectors and/or sensor abnormalities is the hurdle to reliable fault diagnosis and prognosis in multichannel CM systems. The problem becomes more challenging when the sensor channels are not synchronized because of different and/or time-varying sampling/transmission rates. This paper provides a new sensor recovery technique to improve the robustness of multichannel CM systems. Specifically, the associated sensor signals are modeled through Functional Principal Component Analysis (FPCA). Based on the FPCA results obtained from historical data, the relationships among the signals can be constructed.

Keywords: RAMS 2011 Proceedings - Software Reliability - Failure Analysis

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