中圖分類號：TN79 文獻標志碼：A DOI: 10.16157/j.issn.0258-7998.246172 中文引用格式： 吳衛(wèi)堃，鄭耀華，曾彥超，等. 一種電纜終端頭紅外識別算法的FPGA實現(xiàn)研究[J]. 電子技術應用，2025，51(7)：95-100. 英文引用格式： Wu Weikun，Zheng Yaohua，Zeng Yanchao，et al. Research on FPGA implementation of an infrared identification algorithm for cable terminals[J]. Application of Electronic Technique，2025，51(7)：95-100.
Research on FPGA implementation of an infrared identification algorithm for cable terminals
1.Zhaoqing Power Supply Bureau， Guangdong Power Grid Co.， Ltd.；2.School of Electrical and Information Engineering， Hunan University
Abstract： To address the issues of low identification accuracy and poor real-time performance of cable terminal heads during power station inspections, a field programmable gate array (FPGA) infrared recognition system based on particle swarm optimization (PSO) to optimize back propagation (BP) neural networks has been designed. The infrared recognition algorithm includes the use of an improved region growing algorithm for segmenting infrared images, followed by the calculation of Hu invariant moments as input features for the neural network. For the PSO-BP neural network, a 7-10-1 network structure was chosen, achieving a mean squared error of 0.085 after training, which is better than the 0.136 of the BP neural network. When implemented on the FPGA, fixed-point data quantization, pipelined architecture, and parallel computing methods were employed, along with a piecewise quadratic fitting for the Sigmoid activation function. Ultimately, through simulation verification, the system achieved a recognition rate of 92% and improved the algorithm's speed by approximately six times.
