Fault diagnosis of a nonlinear hybrid system using adaptive unscented Kalman filter bank

被引：13

作者：

Sadhukhan, Chandrani ^{[1
]}

Mitra, Swarup Kumar ^{[2
]}

Naskar, Mrinal Kanti ^{[3
]}

Sharifpur, Mohsen ^{[4
,5
]}

机构：

[1] MCKV Inst Engn, Dept Elect Engn, Howrah 711204, W Bengal, India

[2] MCKV Inst Engn, Elect & Telecommun Engn Dept, Howrah 711204, W Bengal, India

[3] Jadavpur Univ, Elect & Telecommun Engn Dept, Jadavpur 700032, W Bengal, India

[4] Univ Pretoria, Dept Mech & Aeronaut Engn, ZA-0002 Pretoria, South Africa

[5] Duy Tan Univ, Inst Res & Dev, Da Nang 550000, Vietnam

来源：

ENGINEERING WITH COMPUTERS | 2022年 / 38卷 / 03期

关键词：

Model-based fault diagnosis; Adaptive unscented Kalman filter (AUKF); Adaptive extended Kalman filter (AEKF); Residual signal; Discrete mode; 3-TANK SYSTEM; ION BATTERIES; ACCOMMODATION; SENSOR;

D O I：

10.1007/s00366-020-01235-0

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, a model-based fault diagnosis scheme of a nonlinear hybrid system using an adaptive unscented Kalman filter (AUKF) bank is proposed. The hybrid system is an amalgamation of discrete dynamics and continuous states. Fault diagnosis for simultaneous occurrences of multiple faults such as leakage fault, clogging fault, sensor fault, and actuator fault on a benchmark three-tank system are simulated. The residual signal based output generates some discrete modes that guarantee the uniqueness of the concerning fault. The efficacy of the proposed scheme is compared with that of the adaptive extended Kalman filter (AEKF) bank on the same system to prove its better response over AEKF.

引用

页码：2717 / 2728

页数：12

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