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| Research on Method of Data Optimization for 2D Laser Measurement of the Mining Ventilator Blade |
| LI Xuezhe,SHEN Yao,CAO Ai,WANG Yanxin,HUA Zhongxu,TIAN Wenyu |
| Hebei Key Laboratory of Safety Monitoring of Mining Equipment, College of Emergency Equipment, North China Institute of Science and Technology, Sanhe,Hebei 065201, China |
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Abstract The extraction of measurement model is the key issue to detecting the geometric deformation of mining ventilator blades.In order to improve the accuracy of measurement model for the blade,a method of data optimization based on least squares principle for the 2D laser measurement is proposed.Firstly,the raw measurement data of the 2D laser sensor is processed based on Kalman filter algorithm in real-time,the accuracy of coordinate measurement is improved and the authentic data for subsequent model construction is provided.Then,three measurement models are solved respectively using methods of cubic polynomial,cubic B-spline,high-order Bessel,and the significance level of each model is evaluated based on the least squares principle,the measurement model suitable for the geometric characteristics of the ventilator blades is determined.Finally,the experimental research is implemented,and the results show that the best fitting effect can be achieved by establishing the measurement model of blade using cubic B-spline function,with the smallest significance evaluation factor (less than 0.05).The accuracy of the blade measurement model is effectively improved through data optimization, and provides an effective technical solution for subsequent geometric evaluation of fan blades.
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Received: 16 October 2023
Published: 25 March 2024
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2024, Vol. 45 
