Random forest-based fan high-temperature capacity reduction state evaluation method

• Main Authors: GAO DELAN, SHI RUXIN, CAO QINGCAI, WANG JUAN, TADAO, ZHANG JIANXIN, LIU XIANRONG, TANG HONGFEN, CAO SHANQIAO, ZHANG SHUXIANG, XUN JIAMENG, ZHANG SHUXIAO, XU ZHIXUAN, GUO XUFENG, ZHANG LIXING
• Format: Patent
• Language: Chinese; English
• Published: 13.05.2022
• Subjects: BLASTING; CALCULATING; COMPUTING; COUNTING; HANDLING RECORD CARRIERS; HEATING; LIGHTING; MACHINES OR ENGINES FOR LIQUIDS; MECHANICAL ENGINEERING; OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR; PHYSICS; PRESENTATION OF DATA; PRODUCING MECHANICAL POWER; RECOGNITION OF DATA; RECORD CARRIERS; WEAPONS; WIND MOTORS; WIND, SPRING WEIGHT AND MISCELLANEOUS MOTORS

The invention discloses a fan high-temperature capacity reduction state evaluation method based on a random forest. The fan high-temperature capacity reduction state evaluation method comprises the following specific steps: step 1, a data acquisition module acquires data of a working environment of a wind turbine generator; 2, the data transmission module transmits the current operation environment temperature data collected in the data collection module to the data comparison module through the control module, and the current operation environment temperature data is compared with a preset environment temperature range in the data comparison module; 3, the control module carries out random forest generation training on the obtained training set and the test set, and generates a random forest intelligent agent of the high-temperature capacity increasing and decreasing state of the fan; and 4, an analysis module performs real-time operation risk judgment analysis by using the random forest intelligent agent me