Sensor Fault Diagnosis Method of Double Closed Loop Ratio Control System

doi:10.12382/bgxb.2022.0969

Abstract

Abstract:

The fault diagnosis of double closed loop ratio control system is more complicated due to the lag effect of master slave loop and the regulating effect of closed loop. Aiming at the problem that sensor faults are difficult to be identified in this system, a data-driven fault diagnosis method is proposed by analyzing the real-time data reflecting the dynamic characteristics of the system. In this method, a fault detection model is established by calibrating the detection threshold using Pauta criterion; A fault location model is established based on the hysteresis characteristic of sensor fault propagation; a fault estimation model is established based on the amplitude characteristics of abrupt faults; a fault separation model is established by using the change trend of dynamic process of fault regulation; and a dynamic model of fault diagnosis is obtained by online data calibration. The effectiveness and high precision of the proposed method are verified by experiments. The results show that the proposed method is suitable for the real-time fault diagnosis of sensors in general double closed loop ratio control system. The accuracy of fault detection can reach 98.5%, the accuracy of fault location can reach 98.5%, the accuracy of fault estimation can reach 99.28%, and the accuracy of fault separation can reach 98%.

Key words: sensor, fault diagnosis, double closed loop ratio control system, data driven, liquid-level system

CLC Number:

TP277

WANG Jiahao, NA Wenbo, LIU Zhiwei, ZAN Qi, WANG Zheng. Sensor Fault Diagnosis Method of Double Closed Loop Ratio Control System[J]. Acta Armamentarii, 2024, 45(4): 1252-1263.

Figures/Tables 20

References 21

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序号	主传感器最大波动值/cm	从传感器最大波动值/cm
1	0.0868	0.1357
2	0.1032	0.1121
3	0.0957	0.1032
4	0.1023	0.0953
5	0.1229	0.1418
6	0.1321	0.1231
7	0.0957	0.0957
8	0.0822	0.0872
9	0.0752	0.0621
10	0.1012	0.0912

序号	主传感器最大波动值/cm	从传感器最大波动值/cm
1	0.0868	0.1357
2	0.1032	0.1121
3	0.0957	0.1032
4	0.1023	0.0953
5	0.1229	0.1418
6	0.1321	0.1231
7	0.0957	0.0957
8	0.0822	0.0872
9	0.0752	0.0621
10	0.1012	0.0912

强度/%	真实值	预测值	强度/%	真实值	预测值
1.5	加性	加性	1.5	乘性	乘性
2	加性	乘性	2	乘性	乘性
4	加性	加性	4	乘性	乘性
6	加性	加性	6	乘性	乘性
8	加性	加性	8	乘性	乘性
10	加性	加性	10	乘性	乘性
14	加性	加性	14	乘性	乘性
16	加性	加性	16	乘性	乘性
20	加性	加性	20	乘性	乘性

强度/%	真实值	预测值	强度/%	真实值	预测值
1.5	加性	加性	1.5	乘性	乘性
2	加性	乘性	2	乘性	乘性
4	加性	加性	4	乘性	乘性
6	加性	加性	6	乘性	乘性
8	加性	加性	8	乘性	乘性
10	加性	加性	10	乘性	乘性
14	加性	加性	14	乘性	乘性
16	加性	加性	16	乘性	乘性
20	加性	加性	20	乘性	乘性

强度/%	真实值	预测值	强度/%	真实值	预测值
1.5	加性	乘性	1.5	乘性	乘性
2	加性	乘性	2	乘性	乘性
4	加性	加性	4	乘性	乘性
6	加性	加性	6	乘性	乘性
8	加性	加性	8	乘性	乘性
10	加性	加性	10	乘性	乘性
14	加性	加性	14	乘性	乘性
16	加性	加性	16	乘性	乘性
20	加性	加性	20	乘性	乘性