Fault diagnosis method for stamping equipment and computer storage medium

Abstract

The invention provides a fault diagnosis method for stamping equipment, and belongs to the technical field of fault diagnosis of heavy equipment. The method comprises the following steps: acquiring basic data, current operation data and historical fault data of a hydraulic system of the stamping equipment, and transmitting and storing the data to terminal equipment; carrying out time-series processing on the current operation data; building a deep-learning network model based on an LSTM (Long Short-Term Memory) and a RNN (Recurrent Neural Network); training a network model by adopting an improved particle swarm POS algorithm according to the basic data and the historical fault data, optimizing parameters of the network model, and acquiring an oil leakage feature set; inputting the preprocessed current operation data into the network model to extract performance state features of the hydraulic system; and inputting the performance state features into a classifier to judge whether hydraulic equipment has an oil leakage risk or not. The method can quickly and accurately forecast whether the stamping equipment has the oil leakage risk or not, guarantee safe and reliable operation of the stamping equipment and reduce the operation and maintenance cost of the stamping equipment.

Description

technical field [0001] The invention relates to fault diagnosis of heavy equipment, in particular to a fault diagnosis method and computer storage medium for stamping equipment. Background technique [0002] Most stamping equipment is heavy equipment, with many components and complex structure, which can complete blank processing such as free forging and die forging, and its core is the hydraulic system. The hydraulic system is not only used for the transmission and force transmission of the main mechanism, but also for various auxiliary tasks such as forging hammer lifting, hammer head positioning, material feeding, and overload protection. Forging machinery driven by hydraulic system, such as hydraulic press, hydraulic shearing machine, hydraulic bending machine, etc., are all high-power, high-pressure and high-speed machines. Once these heavy equipment leaks, it will not only pollute the environment, but also directly affect the performance of the equipment, and even cau...

AI Technical Summary

Problems solved by technology

Once these heavy equipment leaks, it will not only pollute the environment, but also directly affect the performance of the equipment, and even cause personal accidents, so it must be paid enough attention

At present, in the factory production, the abnormality of the working status of the equipment is mainly discovered and reported by the staff, and the fault type is initially determined by the monitor on duty. The cost of manual maintenance and repair is high, and the processing efficiency is low.

Images