Adaptive fuzzy neural network gear remaining life prediction method

Abstract

The invention provides an improved adaptive fuzzy neural network gear remaining life prediction method, and belongs to the technical field of mechanical reliability. The method is characterized by comprising the following implementation steps: 1, gear degradation is monitored in real time by using a vibration sensor; 2, feature extraction of the gear fatigue state is performed, and degradation assessment is performed on the gear wear degradation performance; 3, the fuzzy system and the neural network are combined, the defects of the fuzzy control system are compensated by using the neural network self-learning mechanism and a fuzzy information fuzzy neural network is established; 4, the memory unit is added to all the nodes of the fuzzy processing layer, the information of the last momentis memorized and applied to the output of the present moment and the information is constantly saved, information forward and backward correlation is enhanced, the deviation between the prediction value and the actual value is reduced and the improved adaptive fuzzy neural network prediction system is established; and 5, the gear remaining life is predicted according to the trained improved adaptive fuzzy neural network. The advantages are that the gear degradation state and the real-time remaining life can be effectively predicted so as to provide the basis for gear preventive maintenance.

Description

technical field [0001] The invention belongs to the technical field of mechanical reliability, and in particular relates to a method for predicting the remaining life of a gear. Background technique [0002] Gear is a mechanical component that transmits motion and power. It relies on the motor to drive the gear teeth to gradually mesh to change the size and direction of motion and then transmit the power between the rollers. It is mostly used in mechanical equipment in a closed form such as a gearbox. Compared with Other forms of transmission mechanism, gear transmission has the advantages of wide range of peripheral speed and power, high efficiency, constant transmission ratio, safety and reliability, etc. Nowadays, the performance of products is constantly improving, and the structure of mechanical equipment systems is also exquisite and complex. Gears are prone to failures such as high vibration frequency, wear or broken teeth, and cracks when they are in long-term load o...

AI Technical Summary

Problems solved by technology

[0002] Gear is a mechanical component that transmits motion and power. It relies on the motor to drive the gear teeth to gradually mesh to change the size and direction of motion and then transmit the power between the rollers. It is mostly used in mechanical equipment in a closed form such as a gearbox. Compared with Other forms of transmission mechanism, gear transmission has the advantages of wide range of peripheral speed and power, high efficiency, constant transmission ratio, safety and reliability, etc. Nowadays, the performance of products is constantly improving, and the structure of mechanical equipment systems is also exquisite and complex. Gears are prone to failures such as high vibration frequency, wear or broken teeth, and cracks when they are in long-term load operation. Research has found that most gearbox failures are caused by gears, and the operating status of the gearbox directly affects the normal operation of machinery and equipment. Once the equipment parts fail to operate normally, it may damage the entire equipment or even affect the entire production process, causing economic losses such as downtime, and even catastrophic casualties. Important Measures for Efficient Operation and Improving Product Quality

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