Diesel engine fault diagnosis covers the three main parts of signal collection, data processing and feature value extraction, fault diagnosis and classification, but its fault diagnosis technology has integrated a variety of disciplines and theoretical knowledge, and has gone from traditional diagnostic technology to intelligent diagnosis. The history of technology.
Although the diesel engine fault diagnosis technology has made many breakthroughs in engineering applications, due to the complex structure of the diesel engine system, the working conditions of parts and components during operation are interfering with each other and the types of faults are various. So far, there has not been a set of rapid, effective, widely used, and diagnostic methods with ideal results. Its main difficulties are:
1. The diesel engine has a complicated component structure. During operation, the role of each working system is unclear. Second, for different types of diesel engines, the component structure, system composition, and working principle are also different, that is, the fault diagnosis of a diesel engine The method is applied to another diesel engine, and the diagnosis results obtained are not consistent with the current running status.
2. Since the diesel engine is a reciprocating rotary mechanical device and is accompanied by a lot of noise during work, the vibration signal collected at a certain instant does not truly reflect the good or bad condition of the diesel engine.
3. In diesel engine fault diagnosis, it is impossible to accurately determine the correspondence between symptoms and faults, that is, there is not a one-to-one correspondence between the two, but a one-to-many phenomenon.
In the future social development, with the deepening of scientific research, intelligent optimization algorithms and computer technology are constantly updated and integrated with each other, and they will be applied to diesel engine fault diagnosis to improve the speed of the diagnosis process and the accuracy of the diagnosis results. Become the trend of the times progress. Based on this, the future progress is mainly reflected in the following aspects:
1. In terms of signal processing, in view of the non-stationarity, transientity and abruptness of diesel engine vibration signals, further improve and improve signal analysis and processing methods (such as information extraction methods in time-frequency domain analysis), in order to obtain more More information that reflects the state of the machine is an important research breakthrough in future fault diagnosis.
2. In terms of diagnosis results, each intelligent optimization algorithm has its own advantages and disadvantages. Therefore, in order to improve the accuracy of the diagnosis results, a variety of optimization algorithms are integrated with each other, the advantages are complementary, and the diesel engine fault analysis method is used to diagnose, In this paper, the artificial bee colony algorithm optimizes the support vector machine to obtain the best performance parameters, which can be used to obtain higher accuracy in the final diesel engine fault classification.
3. In terms of technical resources, in order to ensure production efficiency and work efficiency, use computer technology to establish fault diagnosis systems and signal data acquisition and analysis systems, use network technology to share information, and realize online diagnosis of information fusion.
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