Online Fault Detection of Dry Reactor Based on Improved Kalman Filter

Abstract

In order to meet the requirements of online fault detection for dry reactor, an online fault detection technology based on improved Kalman filter is proposed. The main content of the technology is based on the dry reactor detection technology, through the study of improved Kalman filter, the use of fault diagnosis and other methods, and finally through the experiments and analysis to build improved Kalman filter dry reactor online fault detection research means. The experimental results show that the maximum relative error of the improved Kalman filter is 6.039%, and the average relative error is 2.388%. The improved algorithm is very effective and greatly improves the prediction accuracy. The research based on improved Kalman filter can meet the demand of online fault detection of reactor.

A Digital Lock‐in Amplifier Based on Adaptive Kalman Filter for Rail Defect Detection

“…In Equation (7), l belongs to the set {0, 1} and represents a sign of operation. Then, using the averaging filter, one that has uniform coefficients at each sampling point [15], filters out the undesired terms as follows:…”

“…In order to further obtain a better balance between demodulation speed and accuracy, this paper proposes an improved lock-in amplifier integrated with adaptive Kalman filter (AKF). AKF has been applied in many fields, such as fault detection [15], sensor fusion [16], underwater navigation [17], and signal tracking [18][19][20]. AKF is an optimal linear filter in a statistical sense and a more adaptive filter.…”

Retracted: Online Fault Detection of Dry Reactor Based on Improved Kalman Filter

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This article has been retracted by Hindawi, as publisher, following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of systematic manipulation of the publication and peer-review process.

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