Cloud data analysis method, device and system for air compressor

Abstract

The embodiments of the present application disclose a cloud data analysis method, device and system for an air compressor, wherein the system includes: at least two information collection devices and a server for performing cloud communication with the information collection devices; the information collection device and the air compressor are one-to-one Correspondingly, it is used to collect the operating parameter information and operating environment information of the corresponding air compressor and send it to the server; the server is used to determine the operating state of each wear part of the air compressor according to the operating parameter information, and use the operating state and operating environment information as each loss. The historical operation information of each consumable part is associated and stored; the server is used to construct the performance prediction model of each type of consumable parts according to the historical operation information of each consumable part and the stored historical maintenance information of each consumable part; the server is used to utilize the use performance prediction model, Combined with the currently received operating parameter information and operating environment information, the use performance of the corresponding consumable parts is predicted. The accuracy of prediction is improved by the present application.

Description

technical field [0001] The present application relates to the field of air compressor maintenance, in particular to an air compressor-based cloud data analysis method, device and system. Background technique [0002] An air compressor will involve the use of multiple wear parts, such as air filter, oil filter, oil separator, etc. Each lossy part has a different model, and the performance of different models of lossy parts is different. For example, different types of air filter elements have different service lives under the same operating state, or different types of air filter elements have different failure rates in different weather environments. [0003] However, there are various factors that affect the performance of wear parts, and the manufacturers of wear parts cannot predict various factors to accurately predict the performance of wear parts. Moreover, the actual use environment, such as the weather and the operating state of the air compressor, is changeable, a...

AI Technical Summary

Problems solved by technology

Therefore, the performance parameters of consumable parts given by the manufacturer are less accurate

And further predictions based on these performance parameters are not accurate enough

[0004] For example, the manufacturer will generally give the maintenance cycle of a specific consumable part, that is, the maintenance cycle, but for the same type of consumable parts, the maintenance cycle given is the same, without considering the various operating states of the air compressor Such as overload, various weather conditions such as extremely low temperature and other conditions

Obviously, these factors will have a greater impact on the maintenance cycle of consumable parts

For example, for some filter equipment, the ambient air index obviously has a greater impact on its maintenance cycle

If the maintenance is carried out according to the maintenance cycle given by the manufacturer, it obviously cannot meet the needs, or the consumable parts that do not need maintenance have been maintained in advance or have not been maintained, and the consumable parts have been damaged.

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