Research On Fault Diagnosis Methods Of Reciprocating Compressor Based On HHT

Reciprocating compressor is widely used in the area of petroleum and chemical industry and so on. The important thing about equipment maintenance is to guarantee it operate safely, therefore the development of research work on the fault diagnosis of reciprocating compressor will have an important actual significance and economic value. In recent years the research of mechanical equipment failure diagnosis technology has got a great development at home and abroad, but the technology of malfunction diagnosis research of reciprocating compressor is not still practical because of a reciprocating compressor having the feature of complication and multi-driving source, which makes the test signal more nonstationary, while the existing signal processing methods have lowly time-frequency resolution in processing nonstationary signal. While the emergence of Hilbert-Huang transformation (HHT) provides a new method for the analysis of non-stationary signal, also provides a new means for the malfunction diagnosis research of reciprocating compressor, but the existing defects are still unable to meet the actual application. In order to apply HHT to fault diagnosis of reciprocating compressor effectively, this paper will study 2D12 reciprocating compressor, together with the advantages and drawbacks of HHT, carrying out a series of research work aiming at the malfunction diagnosis technology of reciprocating compressor.Firstly, the elementary working principle of reciprocating compressor, the kinematics and dynamics analysis of main moving parts are analyzed, the testing signals for reciprocating compressor have strong nonstationarity are given, and choosing principle for vibration data of driving mechanism and gas valve are proposed.Secondly, through the comparisons for lots of simulated signals included the common amplitude modulation, frequency modulation signal of reciprocating compressor testing signal between HHT and wavelets analysis, this paper points out that HHT method is more suitable for processing non-steady signal and could be used in malfunction diagnosis of reciprocating compressor.Then, according to the further analysis of the existing defect of HHT method and the features of reciprocating compressor actual signal, this paper points out the cause of end effect, modality aliasing, modality disintegrate and false modality, and brings the corresponding solve methods, which mainly represent that:(1) bringing the method of setting pollution isolation region on both ends of analysis data according to the feature of practical test data point being too many; (2) according to one phenomenon that reciprocating compressor testing data cause modality aliasing with the closeness of frequency component, this paper brings a method that we use a method of piecewise cubic Hermite interpolation polynomial to structure extreme value enveloping line to seek for local means; (3) according to one phenomenon that reciprocating compressor testing signal makes inherent modality function arise modality disintegrate because of the influence of high-frequency factor, this paper brings a way of local signal glitch elimination; (4) according to false modality phenomenon which is caused by experiential modality decomposition algorithm and non-stationary of the testing signal of reciprocating compressor, it puts in this paper false modality elimination way of local correlation analysis. The simulation analysis shows that the four methods above all solve efficiently the defects of HHT, which promotes its practical application in fault diagnosis reciprocating compressor.Finally, from above research results, we apply HHT to the fault diagnosis for drive mechanism of reciprocating compressor, and diagnose efficiently three kinds of fault from the view of time-frequency analysis, and prove the accuracy of analysis data taking crosshead measured data as the malfunction diagnosis of drive mechanism, and reduce the difficulty of fault diagnosis because the measurement station being too many; according to the advantage of maximum entropy spectrum analysis being suitable for short data analysis and the influence of noise to the method, together with the advantage of self-adapting denoising for HHT, a method based HHT and maximum entropy spectrum analysis is pointed out, which acquires good application in fault diagnosis of gas valves in reciprocating compressor. The result shows that the feature frequency of gas valve varies clearly with valve's conditions.