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
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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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