Cancam Condition Monitoring for Dry Friction Buildup in an Industrial Hydraulic System Using Unscented Kalman Filter
نویسندگان
چکیده
This paper presents a method for on-line fault monitoring and diagnosis, which is implemented in the hydraulic control system in the cutter module of an industrial fish processing machine. Raw data from the pressure sensors and displacement sensors of the machine are analyzed on line, and residual values are generated using an Unscented Kalman Filter (UKF). By comparing these values against a set thresholds and estimated state of the system, the specific faults are detected when they occur, and are properly diagnosed. In particular, faults related to dry friction in the moving components are detected using residual moving average errors (MAE). This fault is manually introduced to the supporting tables of the sliding cutter. The effectiveness of the method is evaluated experimentally, for the induced faults.
منابع مشابه
Condition Monitoring in a Hydraulic System of an Industrial Machine Using Unscented Kalman Filter
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