Equipment fault diagnosis method and system
A technology of equipment failure and diagnosis system, applied in the field of artificial intelligence, can solve problems such as inability to accurately locate the cause of equipment failure and immature equipment failure diagnosis technology.
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Embodiment 1
[0052] see figure 1 , an embodiment of the present invention provides a device fault diagnosis system, including:
[0053]The data acquisition module 1 is used to acquire the parameter data of each component of the equipment collected by the data sensor in real time. Among them, after obtaining the parameter data of each component of the equipment, edge computing technology is used to preprocess the data, so that the fault detection module can judge whether the component is faulty or not according to the parameter data of each component of the equipment.
[0054] The fault detection module 2 is configured to judge whether a fault occurs in a component according to the spatiotemporal distribution state of the parameter data of each component.
[0055] The fault diagnosis module 3 is used to receive the initial failure probability of the component and the digital twin model of the equipment structure input by the initial multi-fault propagation relationship model 4 based on gra...
Embodiment 2
[0083] The embodiment of the present invention also provides a device fault diagnosis method, including:
[0084] Real-time acquisition of parameter data of each component of the equipment collected by the data sensor;
[0085] According to the spatio-temporal distribution state of the parameter data of each component, it is judged whether the component fails;
[0086] When a component of the equipment is detected to be faulty, the initial failure probability of the component input from the initial multi-fault propagation relationship model and the damage degree of the equipment input from the equipment structure digital twin model are received; wherein, the The initial multi-fault propagation relationship model is constructed based on the historical parameter data of the equipment, using deep learning and combined with expert experience;
[0087] Determine the final failure probability of the component according to the damage degree of the equipment and the initial failure p...
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