电缆RFID定位技术的新型优化算法

doi:10.16265/j.cnki.issn1003-3033.2023.S2.0024

摘要/Abstract

摘要：

为解决露天煤矿电缆智能化管理中的射频识别(RFID)定位问题,提出一种基于改进的鲸鱼优化算法(IWOA)优化RFID定位精确度的方法。首先,采用RFID技术定位电子标签的位置,并进行信息读取;然后,利用接收信号接收强度(RSSI)值计算出阅读器与标签之间的测量距离;最后,通过改进的鲸鱼算法优化距离误差,以迭代寻优选取的位置坐标误差值反应系统的定位精度。结果表明:利用IWOA优化后的系统平均定位误差为0.024 1 m,与传统LANDMARC、差分进化(DE-RFID)、鲸鱼优化(WOA-RFID)定位方法相比平均误差更小,定位精度提高到97.8%,能够更加精准地确定电子标签的位置。

关键词: 射频识别(RFID), 定位技术, 优化算法, 改进的鲸鱼优化算法(IWOA), 信号接收强度(RSSI), 参考标签, 自适应度

Abstract:

To solve the RFID positioning problem in the intelligent management of cables in the open-pit coal mine, a method to optimize the RFID positioning accuracy based on the IWOA was proposed. RFID technology was used to locate the electronic tag and read the information, and RSSI value was utilized to calculate the measurement distance between the reader and the tag. Then the distance error was optimized through the improved whale algorithm, and the positioning accuracy of the system was reflected by the position coordinate error value selected by iterative search. The results show that the average positioning error of the system optimized by the IWOA is 0.024 1 m. Compared with the traditional LANDMARC, differential evolution (DE)-RFID, and whale optimization algorithm (WOA)-RFID positioning methods, the average error is smaller, and the positioning accuracy is increased to 97.8%, which can more accurately locate the electronic tag.

Key words: radio frequency identification (RFID), positioning technology, optimization algorithm, improved whale optimization algorithm (IWOA), received signal strength indication (RSSI), reference tags, adaptability

中图分类号:

X936

焦晓亮, 郭安斌, 张建宇, 苏红俊. 电缆RFID定位技术的新型优化算法[J]. 中国安全科学学报, 2023, 33(S2): 182-187.

JIAO Xiaoliang, GUO Anbin, ZHANG Jianyu, SU Hongjun. Novel optimization algorithm for cable RFID positioning technology[J]. China Safety Science Journal, 2023, 33(S2): 182-187.

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相关参数名称	参数取值
鲸鱼个体总数SearchAgents_no	36
迭代次数Max_iteration	50
鲸鱼搜索区域	10 m×10 m

定位算法	MSE	RMSE	MAE
LANDMARC 算法	1.115 8	1.197 1	3.446 4
WOA算法	0.325 3	0.337 0	2.735 2
DE算法	0.046 3	0.050 6	2.626 5
IWOA算法	0.001 3	0.001 7	2.431 6