基于Adaboost识别算法的电力塔杆拉线防盗报警系统的研究
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摘要
近年来,电力塔杆拉线被盗事件时有发生,针对传统的拉线防盗系统实时性较差,防盗报警误报、漏报率高等问题,设计了一种基于Adaboost识别算法、STM32和uCOSⅡ的电力塔杆拉线防盗报警系统。以STM32微处理器为核心,搭载uCOSⅡ操作系统,实时采集振动、拉力、倾角加速度传感器信号,通过Adaboost算法对拉线状态进行识别判断,将结果以GSM消息方式传递给运行维护人员。实验表明,该系统实时性较强、运行可靠,预警准确率达89.4%以上,报警准确率达100%,具有较高的工程实践意义。
In recent years,power pole line theft usually occurs. To conquer the problem of the traditional cable antitheft system like its poor real-time,false negative and positive in burglar alarm,a new system for power pole line antitheft alarm system based on Adaboost algorithm STM32 and u COS Ⅱ is designed in this paper. The alarm system takes the STM32 microprocessor as a core,and equipped with u COSⅡ operating system,it can collect and process data in real time. We judge the state of line through the Adaboost algorithm,and it can send the result to operation and maintenance personnel by GSM. The practical engineering application shows that the system has good real-time and high reliability,the early warning accuracy rate is achieved 89. 4% or more,and the alarm accuracy rate can reach 100%,which has practical value for product engineering.
In recent years,power pole line theft usually occurs. To conquer the problem of the traditional cable antitheft system like its poor real-time,false negative and positive in burglar alarm,a new system for power pole line antitheft alarm system based on Adaboost algorithm STM32 and u COS Ⅱ is designed in this paper. The alarm system takes the STM32 microprocessor as a core,and equipped with u COSⅡ operating system,it can collect and process data in real time. We judge the state of line through the Adaboost algorithm,and it can send the result to operation and maintenance personnel by GSM. The practical engineering application shows that the system has good real-time and high reliability,the early warning accuracy rate is achieved 89. 4% or more,and the alarm accuracy rate can reach 100%,which has practical value for product engineering.
引文
[1]胡毅,刘凯,等.输电线路运行安全影响因素分析及防治措施[J].高电压技术,2014,40(11):3491-3499.Hu Yi,Liu Kai,et al.Analysis of Influential Factors on Operation Safety of Transmission Line and Countermeasures[J].High Voltage Engineering,2014,40(11):3491-3499.
[2]龚炳伟.输电线路运行安全的影响因素及防治措施[J].科技与创新,2016,(4):99-100.
[3]张文亮,于永清,宿志一,等.湖南电网2008年冰雪灾害调研分析[J].电网技术,2008,38(8):1-5.
[4]陆佳政,蒋正龙,等.湖南电网2008年冰灾事故分析[J].电力系统自动化,2008,32(11):16-19.Lu Jiazheng,Jiang Zhenglong,et al.Analysis of Hunan Power Grid Ice Disaster Accident in 2008[J].Automation of Electric Power Systems,2008,32(11):16-19.
[5]钱进,钱冠军,余刚华.输电线路拉线防盗在线监测研究[J].计算机与数字工程,2008,36(2):146-148.
[6]崔勇,聂新华,刘东海.新型输配电杆塔拉线铝合金防盗管设计及应用[J].水电能源科学,2013,31(4):204-206.
[7]钱进,钱冠军,杜卫华.输电线路拉线防盗告警系统中的GIS应用[J].计算机与数字工程,2008,36(1):125-127.
[8]廉小亲,张阳伟,等.基于Ucos II系统的电气火灾远程监控系统[J].测控技术,2015,34(13):70-73,77.Lian Xiaoqin,Zhang Yangwei,et al.Electrical Fire Remote Monitoring System Based on UcosⅡ[J].Measurement&Control Technology,2015,34(13):70-73,77.
[9]陈磊,林明.基于u COS-II的模糊自适应温度控制系统设计[J].科学技术与工程,2012,12(26):6634-6639.
[10]魏雪倩,黄新波,等.基于Adaboost多分类算法变压器故障诊断[J].西安工程大学学报,2016,30(2):207-211.Wei Xueqian,Huang Xinbo,et al.Fault diagnosis of transformer based on multi-classification algorithm Ada Boost[J].Journal of Xi'an Polytechnic University,2016,30(2):207-211.
[11]周星,丁立新,万润泽,等.分类器集成算法研究[J].武汉大学学报,2015,61(6):503-508.
[12]吕雁飞,侯子骄,张凯.多分类BP-Ada Boost算法研究与应用[J].高技术通讯,2015,25(5):437-444.Lv Yanfei,Hou Zijiao,Zhang Kai.Study of Multi-class BP-Ada Boost and its application[J].Chinese High Technology Letters,2015,25(5):437-444.
[2]龚炳伟.输电线路运行安全的影响因素及防治措施[J].科技与创新,2016,(4):99-100.
[3]张文亮,于永清,宿志一,等.湖南电网2008年冰雪灾害调研分析[J].电网技术,2008,38(8):1-5.
[4]陆佳政,蒋正龙,等.湖南电网2008年冰灾事故分析[J].电力系统自动化,2008,32(11):16-19.Lu Jiazheng,Jiang Zhenglong,et al.Analysis of Hunan Power Grid Ice Disaster Accident in 2008[J].Automation of Electric Power Systems,2008,32(11):16-19.
[5]钱进,钱冠军,余刚华.输电线路拉线防盗在线监测研究[J].计算机与数字工程,2008,36(2):146-148.
[6]崔勇,聂新华,刘东海.新型输配电杆塔拉线铝合金防盗管设计及应用[J].水电能源科学,2013,31(4):204-206.
[7]钱进,钱冠军,杜卫华.输电线路拉线防盗告警系统中的GIS应用[J].计算机与数字工程,2008,36(1):125-127.
[8]廉小亲,张阳伟,等.基于Ucos II系统的电气火灾远程监控系统[J].测控技术,2015,34(13):70-73,77.Lian Xiaoqin,Zhang Yangwei,et al.Electrical Fire Remote Monitoring System Based on UcosⅡ[J].Measurement&Control Technology,2015,34(13):70-73,77.
[9]陈磊,林明.基于u COS-II的模糊自适应温度控制系统设计[J].科学技术与工程,2012,12(26):6634-6639.
[10]魏雪倩,黄新波,等.基于Adaboost多分类算法变压器故障诊断[J].西安工程大学学报,2016,30(2):207-211.Wei Xueqian,Huang Xinbo,et al.Fault diagnosis of transformer based on multi-classification algorithm Ada Boost[J].Journal of Xi'an Polytechnic University,2016,30(2):207-211.
[11]周星,丁立新,万润泽,等.分类器集成算法研究[J].武汉大学学报,2015,61(6):503-508.
[12]吕雁飞,侯子骄,张凯.多分类BP-Ada Boost算法研究与应用[J].高技术通讯,2015,25(5):437-444.Lv Yanfei,Hou Zijiao,Zhang Kai.Study of Multi-class BP-Ada Boost and its application[J].Chinese High Technology Letters,2015,25(5):437-444.