Online detection and diagnosis of sensor faults for a non-linear system

Swetha Rajkumar, Subasree Palanisamy
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Abstract

In systems, the fault is an internal occurrence. It becomes a failure if the defect is not detected and corrected. Sensors have been widely employed as a vital component of data collection systems, particularly in the industrial and agricultural sectors. Sensors are prone to failure due to their harsh operating environment. As a result, early detection of sensor faults is crucial for taking corrective action to reduce the impact. In this paper, faults in generator speed and wind turbine velocity have been investigated. The Extended Kalman Filter is utilized to identify the sensor faults in wind turbine model. The residual generation is used to detect the fault. The residual is the discrepancy between the real and estimated outputs. A Linear Quadratic Regulator controller is used for the stabilization of an unstable system.
非线性系统传感器故障的在线检测与诊断
在系统中,故障是内部发生的。如果不检测和纠正缺陷,它将成为一个失败。传感器已被广泛用作数据收集系统的重要组成部分,特别是在工业和农业部门。传感器工作环境恶劣,容易出现故障。因此,早期发现传感器故障对于采取纠正措施以减少影响至关重要。本文研究了发电机转速和风力机转速的故障。利用扩展卡尔曼滤波对风力机模型中的传感器故障进行识别。残差产生用于检测故障。残差是实际输出和估计输出之间的差异。线性二次型调节器控制器用于不稳定系统的镇定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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