Fuzzy evaluation method based on primary and secondary hierarchies under joint learning framework

A fuzzy evaluation and framework technology, applied in the field of fuzzy evaluation based on primary and secondary levels, can solve problems such as incomplete judgment, inaccurate direct use thresholds, and rough equipment health, and achieve refined equipment health levels and strong decision-making processing capabilities. , clear results

Pending Publication Date: 2022-07-29
ENNEW DIGITAL TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a fuzzy evaluation method based on primary and secondary levels under the framework of joint learning to solve the problems in the above-mentioned background technology that the judgment of equipment health is too rough, the judgment is not comprehensive enough, and the threshold value is not used directly.

Method used

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  • Fuzzy evaluation method based on primary and secondary hierarchies under joint learning framework
  • Fuzzy evaluation method based on primary and secondary hierarchies under joint learning framework
  • Fuzzy evaluation method based on primary and secondary hierarchies under joint learning framework

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Effect test

Embodiment 1

[0052] The invention discloses a fuzzy evaluation method based on primary and secondary levels under a joint learning framework, the steps of which are as follows:

[0053] Step 1: When evaluating, first select a time period in which you want to evaluate the equipment, and each data point collects data on operating years, historical maintenance data, current operating data and energy consumption data;

[0054] Step 2: The system sets the corresponding thresholds in advance, and then judges whether the data collected in step 1 exceeds the thresholds through the thresholds set in advance, so as to directly judge whether the equipment parameters are faulty. If it is judged that there is no fault, go to the next step;

[0055] Step 3: On-site personnel and experts evaluate the data, give the weights of each parameter, and construct a single-factor fuzzy evaluation matrix:

[0056] There are 3 main factors affecting the new and old equipment, physical wear and tear, functional d...

Embodiment 2

[0085] The invention discloses a fuzzy evaluation method based on primary and secondary levels under a joint learning framework, the steps of which are as follows:

[0086] Step 1: When evaluating, first select a time period in which you want to evaluate the equipment, and each data point collects data on operating years, historical maintenance data, current operating data and energy consumption data;

[0087] Step 2: The system sets the corresponding thresholds in advance, and then judges whether the data collected in step 1 exceeds the thresholds through the thresholds set in advance, so as to directly judge whether the equipment parameters are faulty. If it is judged that there is no fault, go to the next step;

[0088] Step 3: On-site personnel and experts evaluate the data, give the weights of each parameter, and construct a single-factor fuzzy evaluation matrix:

[0089] There are 3 main factors affecting the new and old equipment, physical wear and tear, functional d...

Embodiment 3

[0116] The invention discloses a fuzzy evaluation method based on primary and secondary levels under a joint learning framework, the steps of which are as follows:

[0117]Step 1: When evaluating, first select a time period in which you want to evaluate the equipment, and each data point collects data on operating years, historical maintenance data, current operating data and energy consumption data;

[0118] Step 2: The system sets the corresponding thresholds in advance, and then judges whether the data collected in step 1 exceeds the thresholds according to the thresholds set in advance, so as to directly judge whether the equipment parameters are faulty. If it is judged that there is no fault, go to the next step;

[0119] Step 3: On-site personnel and experts evaluate the data, give the weights of each parameter, and construct a single-factor fuzzy evaluation matrix:

[0120] There are 3 main factors affecting the new and old equipment, physical wear and tear, function...

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Abstract

The invention discloses a fuzzy evaluation method based on primary and secondary hierarchies under a joint learning framework. The method comprises the following steps: collecting data, judging whether equipment has a fault or not, constructing a matrix, calculating expert set weight, carrying out comprehensive evaluation, fusing results and carrying out health evaluation on factory equipment. According to the primary and secondary hierarchy-based fuzzy evaluation method under the joint learning framework, the fuzzy set theory is introduced, the membership degree of the health state of the equipment parameters is determined, the health state evaluation of the equipment is a multi-attribute decision problem, and the purpose of judging the target attribute can be achieved only by fusing the health states of the parameters; the method solves the problem that traditional non-standard equipment health degree judgment is too rough, expert experience and fuzzy concepts are combined and introduced, energy for processing uncertainty problems is provided, independent evidence information from different information sources can be fused, a multi-factor and multi-factor evaluation system is utilized, all parameter indexes are synthesized for judgment, and the method is high in practicability and high in practicability. And the judgment is more comprehensive.

Description

technical field [0001] The invention relates to the technical field of comprehensive energy systems, in particular to a fuzzy evaluation method based on primary and secondary levels under a joint learning framework. Background technique [0002] The integrated energy system is a system that is connected by a variety of equipment and pipelines, and has a variety of energy input, conversion, and can supply a variety of energy to different users. The equipment in the integrated energy system includes: gas internal combustion engine, waste heat boiler, Steam boilers, bromine coolers, photovoltaic equipment, ground source heat pumps, wind energy equipment, energy storage equipment, etc., for a large number of integrated energy equipment, the premise of maintenance is based on the health status of the equipment. What method is used to maintain the equipment, so evaluating the health status of the equipment and determining the degradation of the equipment health status is of great ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q10/00G06Q50/06G06F17/16G06F17/18G06N20/00
CPCG06Q10/0639G06Q10/20G06Q50/06G06F17/16G06F17/18G06N20/00
Inventor 张燧
Owner ENNEW DIGITAL TECH CO LTD
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