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A Fault Diagnosis of Wind Power Converter Based on Adaptive Filtering

A wind power converter and adaptive filtering technology, applied in the measurement of electrical variables, instruments, measurement of electricity, etc., can solve problems such as algorithm accuracy or stability impact

Active Publication Date: 2020-09-08
CHONGQING UNIV
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Problems solved by technology

The existence of noise is bound to have a certain degree of impact on the accuracy or stability of the algorithm

Method used

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  • A Fault Diagnosis of Wind Power Converter Based on Adaptive Filtering
  • A Fault Diagnosis of Wind Power Converter Based on Adaptive Filtering
  • A Fault Diagnosis of Wind Power Converter Based on Adaptive Filtering

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Experimental program
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Embodiment Construction

[0051] The fault diagnosis algorithm based on the filter algorithm is given below, and its flow chart is as follows: figure 1 shown.

[0052] Step1: Let k=1, set the initial value of the state estimation and the initial value of the error covariance matrix as Process noise covariance matrix and measurement noise covariance matrix Q k , R k , and set the forgetting factor b and the error covariance matrix reset threshold C, and calculate the state transition matrix F according to the state equation and measurement equation of the discrete system k and the measurement equation coefficient matrix H k . It should be noted that in actual situations, as time goes by, the influence of the initial state and its covariance on the KF algorithm gradually decreases, but the noise covariance matrix Q k , R k will hinder the attenuation of this effect, therefore, the selection of the initial value of the noise covariance matrix should be as close as possible to the actual system, gen...

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Abstract

The invention belongs to the field of fault diagnosis of a wind power converter. Aiming at a permanent-magnet direct-drive wind power generation system converter, the invention designs a fault diagnosis frame based on current normalization and a current mean value. In order to improve the accuracy of current observation, the invention introduces an adaptive Kalman filter algorithm. A Sage-Husa noise estimator is selected for adaptively adjusting the Q and R values in real time, thereby improving the robustness of the algorithm under the noise background with the unknown statistical features. Moreover, a resetting error covariance matrix method is used for improving the tracking and estimation capability of parameter abrupt changes.

Description

technical field [0001] The invention belongs to the field of fault diagnosis of wind power converters, and relates to a fault diagnosis method for wind power converters. Background technique [0002] Precisely forecasting and predicting the three-phase current can not only accurately understand the working status of the converter, but also discover potential safety hazards in the converter in time, so that corresponding measures can be taken in time. However, the working environment of the converter is complex. In the actual observation process, due to the existence of various unknown or uncertain factors, the observation results inevitably contain a variety of random disturbance errors, which affect the accuracy of the prediction results. However, the fault diagnosis based on the observer does not consider the influence of noise, which is different from the actual system. It applies only to cases where the available measurements are not too heavily polluted by noise and yi...

Claims

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Application Information

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IPC IPC(8): G01R31/00
CPCG01R31/00
Inventor 魏善碧柴毅孙秀玲刘文宇刘晓宇尚敖男
Owner CHONGQING UNIV
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