Method and system for monitoring field maintenance of special device
A special equipment and maintenance technology, applied in general control systems, control/regulation systems, program control, etc., can solve the lack of effective monitoring methods, poor monitoring accuracy, and difficult to guarantee maintenance quality for special equipment on-site maintenance. question
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Embodiment 1
[0061] Embodiment one, take the project maintenance of elevator car door opening / closing as an example, the project maintenance of elevator car door opening / closing is carried out according to the following method: E1, on the big data server 100 at least store the information of the target special equipment The following data, as the file data of the target special equipment: a) elevator model, b) elevator car door model, c) image feature data of the car door, d) image feature data of devices related to car door opening / closing, e ) the speed curve of the normal switch of the car door, f) the normal movement speed curve of the device related to the opening / closing of the car door (in the form of a function or the parameter of the function), g) the data of the acceleration sensor installed on the car door, h) The failure prediction result of the big data server 100 (judgment based on the data that has been sent back from the site), i) the last maintenance time, maintenance resul...
Embodiment 2
[0062]Embodiment 2, for the project maintenance of the hoisting machinery traction wheel, adopt on-site maintenance monitoring to carry out as follows: F1, store the following data of the target special equipment on the big data server 100, as the file data of the target special equipment: a) The model of the hoisting machine, b) the model of the traction sheave, c) the image feature data of the traction sheave, d) the image feature data of the components related to the operation of the traction sheave, e) the speed curve of the normal operation of the traction sheave , f) the normal motion speed curve of the device related to the operation of the traction wheel, f) the failure prediction result of the big data server 100, g) the last maintenance time, maintenance result and device replacement record; wherein the image feature data includes: Pulley color, pulley texture, number of corners of polygonal pulley outline, corner smoothness of polygonal pulley outline, all or part of...
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