TY - JOUR
T1 - MULTIVARIATE STATISTICS FOR ANOMALY DETECTION
T2 - APPLICATION IN A TURBOJET
AU - Salazar-Martínez, Salma
AU - Takano-De-La-Cruz, Luis
AU - Loboda, Igor
AU - Villarreal-Valderrama, Francisco
AU - Hernandez-Alcantara, Diana
AU - Amézquita-Brooks, Luis
N1 - Publisher Copyright:
© 2024 Publicaciones Dyna Sl. All rights reserved.
PY - 2024/3
Y1 - 2024/3
N2 - Although the computational power of embedded systems has increased in recent years, these systems are increasingly being taxed with more tasks. This raises the interest for computationally lean algorithms which are able of rendering process operation more efficient and reliable. This is particularly relevant in the case of flight computers for autonomous aircraft. Fault detection, isolation and identification assist in management strategies to improve both predictive maintenance and operational safety. This article combines a principal component–based representation with multivariate statistics to detect and isolate anomalies in a process. The resulting algorithm is computationally lean and was validated with respect to experimental measurements in a turbojet before and after years of operation. The results show that the developed algorithm is capable of successfully determining the fouling components in the turbojet.
AB - Although the computational power of embedded systems has increased in recent years, these systems are increasingly being taxed with more tasks. This raises the interest for computationally lean algorithms which are able of rendering process operation more efficient and reliable. This is particularly relevant in the case of flight computers for autonomous aircraft. Fault detection, isolation and identification assist in management strategies to improve both predictive maintenance and operational safety. This article combines a principal component–based representation with multivariate statistics to detect and isolate anomalies in a process. The resulting algorithm is computationally lean and was validated with respect to experimental measurements in a turbojet before and after years of operation. The results show that the developed algorithm is capable of successfully determining the fouling components in the turbojet.
UR - http://www.scopus.com/inward/record.url?scp=85190855698&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85190855698&partnerID=8YFLogxK
U2 - 10.6036/10921
DO - 10.6036/10921
M3 - Article
AN - SCOPUS:85190855698
SN - 0012-7361
VL - 99
SP - 208
EP - 214
JO - Dyna (Spain)
JF - Dyna (Spain)
IS - 2
ER -