共 34 条
- [1] LIU II, PI D C, QIU S Y, Et al., Data-driven identification model for associated fault propagation path, Measurement, 188, (2022)
- [2] AMIN M T, KUAN F, IMTIAZ S., Fault detection and pathway analysis using a dynamic bayesian network, Chemical Engineering Science, 195, 23, pp. 777-790, (2019)
- [3] OIILEF II, BINROTII W, IIABOUSII R., Statistical model for a failure mode and effects analysis and its application to computer fault-tracing, IEEE Trans. on Reliability, 27, 1, pp. 16-22, (1978)
- [4] HUANG X L, GAO J M, JIANG II Q, Et al., Fault root cause tracing of complicated equipment based on fault graph, Proceedings of Institution of Mechanical Engineers Part E: Journal of Process Mechanical Engineering, 227, 1, pp. 17-32, (2012)
- [5] YU J, RASIIID M M., A novel dynamic Bayesian network-based networked process monitoring approach for fault detection, propagation identification, and root cause diagnosis, AIChE Journal, 59, 7, pp. 2348-2365, (2013)
- [6] DUAN S Y, ZHAO C II, WU M., Multiscale partial symbolic transfer entropy for time-delay root cause diagnosis in nonstationary industrial processes, IEEE Trans, on Industrial Electronics, 70, 2, pp. 2015-2025, (2022)
- [7] OLIVEIRA E E, MIGUEIS V L, BORGES J L., Automatic root cause analysis in manufacturing: an overview &- conceptualizat i o n ^ ], Journal of Intelligent Manufacturing, 3 4, 5, pp. 2061-2078, (2023)
- [8] MA L, PENG K X, DONG J., Review of root cause diagnosis and propagation path identification techniques for faults in industrial processes, Ada Automatica Sinica, 48, 7, pp. 1650-1663, (2022)
- [9] ALI II, MAULUD A S, ZABIRI II, Et al., Multiscale principal component analysis-signed directed graph based process monitoring and fault diagnosis, ACS Omega, 7, 11, pp. 9496-9512, (2022)
- [10] TANG P, PENG K X, DONG J., A novel method for deep ca-suality graph modeling and fault diagnosis[J], Acta Automatica Sinica, 48, 6, pp. 1616-1624, (2022)