Failure analysis of variable inlet guide vane and compressor rotor blade of helicopter engine

Sharma, Rohit; Manda, Premkumar; Singh, Satyapal; Singh, A. K.

doi:10.1016/j.matpr.2017.12.093

Cited by 5 publications

(1 citation statement)

References 2 publications

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“…For this type of signal, if you need to understand its waveform, you can consider it as a time domain signal. A higher sampling rate is required in this case [17][18]. For example, motor pulse signals require that the sample period signal must be smaller than the pulse period.…”

Section: Engine Signal Analysismentioning

confidence: 99%

Engine Fault Diagnosis Based on Virtual Instrument Technology

2020

KME

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With the development of automobile technology, the function of engine detection device is more and more obvious. The introduction of virtual instrument can build a general testing system with simple hardware. The purpose of this paper is to study engine fault diagnosis with virtual instrument technology. In view of the fact that the electronic and integrated level of automobile products is constantly improving, the basic theory and technical methods of fault self-diagnosis of automobile electronic injection system are studied. BP neural network theory and virtual instrument technology are comprehensively applied to the field of engine fault self-diagnosis. By analyzing the characteristic parameters containing rich engine status information, fault characteristics are extracted, A general platform of engine intelligent fault diagnosis based on virtual instrument technology is proposed and designed. The experimental results show that the system improves the diagnosis speed and accuracy.

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Section: Engine Signal Analysismentioning

confidence: 99%