Fault Detection of Permanent Magnet Synchronous Motor Based on SVD-RF

Zhao, Dongnan; Shi, Hengliang

doi:10.1109/iccc54389.2021.9674703

Cited by 1 publication

(1 citation statement)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The detrended fluctuation analysis (DFA) method can describe the irregularity and self-similarity of the signal locally and as a whole and extract the features of the multifractal spectrogram as signal features. Zhao et al [66] proposed an equipment fault feature extraction method based on improved DFA and linear discriminant analysis.…”

Section: Fault Feature Extractionmentioning

confidence: 99%

Research Progress and Development Trend of Prognostics and Health Management Key Technologies for Equipment Diesel Engine

Liu

Zhang²,

Dong

et al. 2023

Processes

View full text Add to dashboard Cite

The diesel engine, as the main power source of equipment, faces practical problems in the maintenance process, such as difficulty in fault location and a lack of preventive maintenance techniques. Currently, breakdown maintenance and cyclical preventive maintenance are the main means of maintenance support after a diesel engine failure, but these methods require professional maintenance personnel to carry out manual fault diagnosis, which is time-consuming. Prognostics and health management (PHM), as a new technology in the field of equipment maintenance support, has significant advantages in improving equipment reliability and safety, enhancing equipment maintenance support capability, and reducing maintenance support costs. In view of this, when introducing PHM into diesel engine maintenance support, the research progress and development trend of the key technologies of PHM for diesel engines are carried out with the objective of achieving precise maintenance and scientific management of diesel engines, and the key technologies demand traction. Firstly, the development history of PHM technology is reviewed, and its basic concept and main functions are introduced. Secondly, the system architecture of PHM for diesel engines is constructed, and its key technologies are summarized. Then, the research progress in the field of PHM for diesel engines is reviewed from four aspects: data acquisition, data processing, fault diagnosis, and health status assessment. Finally, the challenges faced by diesel engine PHM in engineering applications are analyzed, effective solutions to address these challenges are explored, and the future development trend is foreseen.

show abstract

Section: Fault Feature Extractionmentioning

confidence: 99%