A Fault Detection Method for Coal Milling System in Thermal Power Plant Based on Accurate Classification of Data Types in Mixed Regions
A technology of regional data and pulverizing system, applied in general control system, control/regulation system, test/monitoring control system, etc., can solve the problem that fault data cannot be accurately classified, aliased regional data is not easy to accurately classify, thermal power plant pulverizing The system operating conditions are changing and other problems, to achieve the effect of improving the effect of fault classification
Active Publication Date: 2022-04-15
陕西工业职业技术学院
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[0005] The purpose of the present invention is to provide a fault detection method for the pulverizing system of a thermal power plant, which solves the problem that the data in the aliasing area is difficult to accurately classify
[0006] The working conditions of the pulverizing system in thermal power plants are changeable, and the data of different working conditions will inevitably overlap, resulting in some fault data that may not be accurately classified
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[0039] The present invention specifically discloses a fault detection method for a coal-fired power plant pulverizing system that accurately divides the data categories of the aliasing area, and the steps are as follows:
[0040]Step 1: First, the pulverizing system of the thermal power plant collects 4 types of process data including normal state, full mill fault, coal cut fault and powder return pipe blockage fault; each type of process data contains 200 sets of data, and 800 sets of data are formed On-site historical database D, the database D includes six variables: mill load, mill inlet and outlet pressure difference, mill inlet negative pressure, mill outlet temperature, coarse powder separator outlet negative pressure and fine powder separator outlet negative pressure; In this way, database D is used as a training sample, and part of the data is shown in Table 1. The serial numbers corresponding to the four types of process data in the table are 1-15, 16-30, 31-45, and 4...
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The invention discloses a fault classification method for the pulverization system of a thermal power plant that can accurately classify the data categories of the aliasing area; In different hyperspheres, k is selected to determine the neighbor data of the data, by calculating the density of the neighbor data in the different hyperspheres in which the sample falls, and according to the similarity between the sample density and the neighbor data density in different hyperspheres, the sample pairs are calculated. degree of class belonging. The invention improves the fault classification effect of the coal-fired power plant's pulverizing system on the basis of accurately judging the category of samples in the mixing area.
Description
technical field [0001] The invention discloses a method for fault detection of a coal-fired power plant pulverizing system, in particular to a method for classifying data of aliasing regions in the coal-fired power plant pulverizing system data. Background technique [0002] The pulverizing system is one of the main auxiliary systems of thermal power plants. In order to ensure its operation safety and efficiency, fault detection technology is applied in the pulverizing system to detect and identify the abnormal state of the system, so as to ensure the continuous and stable operation of the system as planned. Due to the complex structure and changing working conditions of the pulverizing system, the fault data inevitably belong to different categories, resulting in the decline of fault detection performance. Therefore, we need to accurately classify the data of different fault aliasing areas of the pulverizing system. [0003] At present, there are four commonly used processi...
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IPC IPC(8): G05B23/02
CPCG05B23/0262G05B2219/24065Y04S10/52
Inventor 白蕾侯伟夏东盛
Owner 陕西工业职业技术学院