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Design and Analysis of High-Precision Weighted Linear Least-Squares Fitting Algorithm for Fluorescent Optical Fiber Temperature Sensor
Journal of Circuits, Systems and Computers ( IF 0.9 ) Pub Date : 2021-08-27 , DOI: 10.1142/s0218126622500311
Jian Yang 1 , Xiangliang Jin 1 , Yan Peng 2 , Jun Luo 2
Affiliation  

Microwave hyperthermia is a new method of treating cancer, where the therapeutic effect is determined by the heating temperature. Traditional active temperature sensors are interfered by high frequency so that the accuracy of temperature measurement cannot be guaranteed. It is of great significance to study the high-precision fluorescent optical fiber temperature sensor with complete insulation. This paper has realized a compact and practical fluorescent optical fiber temperature sensor after studying the optical path, circuit, data processing algorithm. In order to improve the accuracy of the system, the weighted linear least-squares fitting algorithm is improved in this paper. Through experimental tests, compared with the standard linear least-squares fitting algorithm and the unimproved weighted linear least-squares fitting algorithm, the accuracy of the algorithm is improved by about 98% and 65.5%, respectively. In addition, the response time is reduced by about 36.5%, compared with the unimproved weighted linear least-squares fitting algorithm. This algorithm fully meets the precision requirements of microwave hyperthermia.

中文翻译:

荧光光纤温度传感器高精度加权线性最小二乘拟合算法设计与分析

微波热疗是一种治疗癌症的新方法,其治疗效果由加热温度决定。传统的有源温度传感器受高频干扰,无法保证测温的准确性。研究完全绝缘的高精度荧光光纤温度传感器具有重要意义。本文在对光路、电路、数据处理算法进行研究后,实现了一款小巧实用的荧光光纤温度传感器。为了提高系统的精度,本文对加权线性最小二乘拟合算法进行了改进。通过实验测试,与标准线性最小二乘拟合算法和未改进的加权线性最小二乘拟合算法相比,算法的准确率分别提高了约 98% 和 65.5%。此外,与未改进的加权线性最小二乘拟合算法相比,响应时间减少了约 36.5%。该算法完全满足微波热疗的精度要求。
更新日期:2021-08-27
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