Online equipment health state self-detection method and system for tobacco processing equipment

Abstract

The invention discloses an online equipment health state self-detection method and system for tobacco processing equipment. The method comprises the steps that parameters reflecting the state of the tobacco processing equipment in real time are acquired; the tobacco processing equipment state parameters corresponding to an operating state are selected according to the operating state that the tobacco processing equipment is in; an evaluation model for the health state of the tobacco processing equipment is constructed according to the selected tobacco processing equipment state parameters; the parameter weight, a model parameter center value, a model parameter threshold value and a stage key parameter in the evaluation model for the health state of the tobacco processing equipment are determined; the corresponding parameter current value, parameter center value, parameter threshold value, parameter weight and key parameter value of the tobacco processing equipment are substituted into the constructed evaluation model for the health state of the tobacco processing equipment according to the state that the tobacco processing equipment is in, and then the health state of the tobacco processing equipment in a current state is obtained. According to the online equipment health state self-detection method and system for the tobacco processing equipment, the adopted data is real-time online data, and by taking the data as an evaluation basis, more truth is achieved, and quantitative evaluation is more precise.

Description

technical field [0001] The invention relates to the technical field of tobacco processing equipment state health self-inspection, in particular to a method for self-inspection of the equipment health state of tobacco leaf feeder equipment. Background technique [0002] At present, in cigarette manufacturing enterprises, there is generally a lack of evaluation of the health status of tobacco processing equipment. Tobacco processing equipment mostly uses PLC for automatic control. The equipment alarm function is provided in the general control program, which can provide alarm prompts when some parameters of the equipment are abnormal. However, this method covers fewer equipment parameters, and only provides an alarm mechanism for a few key parameters, and the correlation between parameters is not taken into account, so the status of this equipment cannot be evaluated. At the same time, this method only considers the parameters of equipment components, and does not include th...

AI Technical Summary

Problems solved by technology

[0003] In the prior art, a small number of tobacco companies have established the health status evaluation of the tobacco leaf feeder, but the evaluation method is generally a qualitative evaluation in the form of manual scoring, and there is a lack of quantitative analysis of the equipment

The evaluation granularity of this method is relatively coarse, and the subjective influence of the evaluator is relatively large

At the same time, the evaluation method is generally the comprehensive result of the overall evaluation, lacking the positioning and treatment of equipment problems

[0004] In addition, most of the existing methods for evaluating the health status of tobacco leaf feeder equipment are off-line evaluation methods

It is not possible to make an evaluation online through real-time data

Due to the long evaluation cycle and offline data distortion, the evaluation result lags behind in this method, and it cannot accurately reflect the real-time status of the current equipment.

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