Due to the importance of bearings in modern machinery, the prediction of the remaining useful life (RUL) of rolling bearings has been widely studied. When predicting the RUL of rolling bearings in engineering practice, the RUL is usually predicted based on historical data, and as the historical data increases, the prediction results should be more accurate. However, the existing methods usually have the shortcomings of low prediction accuracy, large cumulative error and failure to dynamically give prediction results with the increase of historical data, which are not suitable for engineering practice.To address the above problems, a novel RUL prediction method is proposed. The proposed method consists of 3 parts: First, the multi-scale entropy-based feature -namely "average multi-scale morphological gradient power spectral information entropy (AMMGPSIE)"from the rolling bearings as the Health indicator (HI) is extracted to ensure all the fault-related information is well-included; Then, the HI is processed with the enhanced Hodrick Prescott trend-filtering with boundary lines (HPTF-BL) to ensure good performance and small fluctuation on the HI; Finally, the deterioration curve is predicted using an LSTM neural network and the improved Particle Filter algorithm that we proposed. The proposed method is validated using the experimental bearing degradation dataset and the casing data of a centrifugal pump bearing from an actual industrial site. Comparing the results with other recent RUL prediction methods, the proposed method achieved state-ofthe-art feasibility and effectiveness, conform to the needs of practical application of the project.
By establishing the motion equation of the air valve under the condition of air volume adjustment, the motion law of the air valve in the process of expansion, compression, suction and exhaust of the reciprocating compressor under different loads is calculated, and the reciprocating compressor with stepless air volume adjustment is used. The compressor unit verifies the calculation results. The maximum stress of the valve plate under different loads is analyzed, and the results show that in the ideal state where the fork pressure disappears instantaneously, the adjustment method of the partial stroke pressure opening suction valve has a greater influence on the stress concentration of the valve plate than the normal condition; in the partial stroke pressure opening suction valve adjustment method, the free retraction speed and stress of the valve plate will increase as the compressor load decreases.
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