Incipient sensor fault isolation based on augmented Mahalanobis distance

被引:50
作者
Ji, Hongquan [1 ]
Huang, Keke [2 ]
Zhou, Donghua [1 ,3 ]
机构
[1] Shandong Univ Sci & Technol, Coll Elect Engn & Automat, Qingdao 266590, Shandong, Peoples R China
[2] Cent S Univ, Sch Automat, Changsha 410083, Peoples R China
[3] Tsinglum Univ, Dept Automat, Beijing 100084, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Statistical process monitoring (SPM); Incipient fault; Fault detection and isolation; Augmented Mahalanobis distance (AMD); Contribution analysis; RECONSTRUCTION-BASED CONTRIBUTION; KULLBACK-LEIBLER DIVERGENCE; DIAGNOSIS;
D O I
10.1016/j.conengprac.2019.03.013
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Incipient sensor fault diagnosis is important to an efficient and optimal operating condition for modern industrial systems. Recently, a new fault detection index called augmented Mahalanobis distance (AMD) has been proposed in our previous work for incipient fault detection. Following detection, fault isolation is also quite desired so as to investigate root causes of the occurred fault. In the present work, the AMD statistic is first revisited and a geometric illustration of AMD is provided, which intuitively shows its superiority for incipient fault detection. Then, with available fault direction information, an incipient sensor fault isolation approach is proposed. Its fault isolability condition is analyzed theoretically and compared with that of the conventional method. For complex sensor faults whose fault direction information is unknown, a corresponding fault isolation strategy is also briefly discussed. Case studies on a high-speed train air brake system and the continuous stirred tank reactor (CSTR) process are carried out, which demonstrate the effectiveness of the AMD based fault detection and isolation methods, in comparison with conventional approaches.
引用
收藏
页码:144 / 154
页数:11
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