基于ai智能图像的工控火电现场爆炸风险评估
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摘要
对工控火电现场爆炸风险进行评估时,若采用人工识别现场图片信息的方法,容易导致现场图片特征信息采集不准确,存在评估耗时长、评估效率低和评估结果不准确的问题。针对该问题,提出1种基于ai智能图像的工控火电现场爆炸风险评估方法;通过自适应融合方法提取工控火电现场ai智能图像中的特征信息,根据特征信息对工控火电现场ai智能图像进行识别;结合层次分析法和问卷调查法,选取工控火电现场爆炸风险评估指标;在图像识别结果的基础上,通过风险等级集合、评估指标权重,建立工控火电现场爆炸风险评估模型,并与另外2种工控火电现场爆炸风险评估方法进行了对比。研究结果表明:所建方法能够缩短评估时间,且评估效率较高、评估结果准确率较高。
When assessing the explosion risk in the field of industrial control thermal power,the information of field image have been recognized manually,which results in the inaccurate collection of characteristic information in the field image,and there exists the problems of long assessment time,low assessment efficiency and inaccurate assessment results. Aiming at these problems,an assessment method of the explosion risk in the field of industrial control thermal power based on the ai intelligent image was put forward. The characteristic information of the ai intelligent image in the field of industrial control thermal power were extracted by using the adaptive fusion method,and the ai intelligent image was recognized according to the characteristic information. Combined with the analytic hierarchy process method and the questionnaire survey method,the assessment indexes of explosion risk in the field of industrial control thermal power were selected. On the basis of the image recognition results,an assessment model of explosion risk in the field of industrial control thermal power was established through the risk grade set and the weights of assessment indexes,then the assessment of explosion risk in the field of industrial control thermal power was completed. The results showed that the proposed method could shorten the assessment time,with a relatively high assessment efficiency and high accuracy of assessment results.
When assessing the explosion risk in the field of industrial control thermal power,the information of field image have been recognized manually,which results in the inaccurate collection of characteristic information in the field image,and there exists the problems of long assessment time,low assessment efficiency and inaccurate assessment results. Aiming at these problems,an assessment method of the explosion risk in the field of industrial control thermal power based on the ai intelligent image was put forward. The characteristic information of the ai intelligent image in the field of industrial control thermal power were extracted by using the adaptive fusion method,and the ai intelligent image was recognized according to the characteristic information. Combined with the analytic hierarchy process method and the questionnaire survey method,the assessment indexes of explosion risk in the field of industrial control thermal power were selected. On the basis of the image recognition results,an assessment model of explosion risk in the field of industrial control thermal power was established through the risk grade set and the weights of assessment indexes,then the assessment of explosion risk in the field of industrial control thermal power was completed. The results showed that the proposed method could shorten the assessment time,with a relatively high assessment efficiency and high accuracy of assessment results.
引文
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[18]亢永,吕鹏飞,庞磊.城市燃气管道泄漏事故风险场强度评价研究[J].安全与环境工程,2016,23(6):166-169.KANG Yong,LYU Pengfei,PANG Lei. Evaluation of risk field intensity for leakage accidents of urban gas pipelines[J]. Safety and Environmental Engineering,2016,23(6):166-169.
[2]苏秀红. HHT在爆炸振动信号处理中的应用[J].电子设计工程,2016,24(10):156-158.SU Xiuhong. The application of HHT in blasting signal processing[J]. Electronic Design Engineering,2016,24(10):156-158.
[3]苏利红,罗彦.火电厂锅炉节能减排技术分析[J].科技视界,2017,23(2):274-274.SU Lihong,LUO Yan. Analysis on energy saving and emission reduction technology of thermal power plant[J]. Science&Technology Vision,2017,23(2):274-274.
[4]苑举斌.火电厂安全管理的精细化分析研究[J].科技风,2017,14(5):217-218.YUAN Jubin. Refined analysis and research on safety management of thermal power plants[J]. Technology Wind,2017,14(5):217-218.
[5]王晨辰,张盛中,杨晓瑜,等.天津港“8·12”爆炸事件记录波形分析[J].地震工程学报,2018,40(1):130-138.WANG Chenchen,ZHANG Shengzhong,YANG Xiaoyu,et al. Analysis of record waveform of “8·12”explosion event in tianjin port[J]. China Earthquake Engineering Journal,2018,40(1):130-138.
[6]郭二果,李传镇,王俊明,等.火电厂环境风险评估技术要点[J].安全、健康和环境,2016,16(4):30-33.GUO Erguo,LI Chuanzhen,WANG Junming,et al. Technical key points in environment risk evaluation of thermal power plants[J].Safety Health&Environment,2016,16(4):30-33.
[7]吴庭吉,郭可可,陈光秀,等.火电厂环境风险的评估技术[J].中国资源综合利用,2017,35(4):91-92.WU Tingji,GUO Keke,CHEN Guangxiu,et al. Environmental risk assessment technology of thermal power plant[J]. China Resources Comprehensive Utilization,2017,35(4):91-92.
[8]孟宪良,杨莉.火电工程项目施工风险评价指标体系的构建[J].电子制作,2016(20):17.MENG Xianliang,YANG Li. Construction of construction risk evaluation index system for thermal powerengineering projects[J]. Practical Electronics,2016(20):17.
[9]成明涛,林友新,肖志前,等.火力发电厂高温蒸汽管道应力评估与调整[J].广东电力,2016,29(11):8-11.CHENG Mingtao,LIN Youxin,XIAO Zhiqian,et al. Assessment and adjustment for stress of high-temperature steam pipelines in thermal power plants[J]. Guangdong Electric Power,2016,29(11):8-11.
[10]徐年,李伟,陈飞,等.基于模糊理论的地震现场图像增强技术研究[J].地震工程学报,2016,38(S1):134-137.XU Nian,LI Wei,CHEN Fei,et al. Enhancement technology for seismic field images based on fuzzy theory[J]. China Earthquake Engineering Journal,2016,38(S1):134-137.
[11]刘忠军.爆炸危险区域电伴热现场智能控制器的设计及应用[J].防爆电机,2017,52(4):38-42.LIU Zhongjun. Design and application of on-site intelligent controller of electric tracing device for explosive hazardous area[J]. Explosion-Proof Electric Machine,2017,52(4):38-42.
[12]胡向阳.变电站设备失效概率模型及电气主接线风险评估[J].供用电,2017,34(3):78-83.HU Xiangyang. Failure probability model and main electrical wiring risk assessment of substation devices[J]. Distribution&Utilization,2017,34(3):78-83.
[13]赵刚,黄汉明,卢欣欣,等.基于BP-Adaboost方法的天然地震和人工爆炸事件波形信号分类识别研究[J].地震工程学报,2017,39(3):557-563.ZHAO Gang,HUANG Hanming,LU Xinxin,et al. Research on the classification of seismic wave signals of earthquakes and explosion events based on bp-adaboost[J]. China Earthguake Engineering Journal,2017,39(3):557-563.
[14]唐丽华,李山有,宋立军.地震灾害风险评估方法的对比分析——以乌鲁木齐市为例[J].地震工程学报,2016,38(5):838-845.TANG Lihua,LI Shanyou,SONG Lijun. Comparative analysis of earthquake risk assessment methods:a case study on urumqi city[J]. China Earthquake Engineering Journal,2016,38(5):838-845.
[15]陈永杰,覃欣欣,牛国庆.基于区间层次分析法的煤尘爆炸引火源风险评估[J].中州煤炭,2016,50(8):1-4.CHEN Yongjie,TAN Xinxin,NIU Guoqing. Risk assessment of coal dust explosion ignition sources based on interval analytic hierarchy process[J]. Zhongzhou Coal,2016,50(8):1-4.
[16]刘辉.基于ISO价值链的火电企业标准化效益评估案例研究[J].标准科学,2016,14(3):9-14.LIU Hui. Case study on standardization benefit assessment of thermal power enterprise based on iso value chain[J]. Standard Science,2016,14(3):9-14.
[17]周德红,李文,冯豪,等.事故树分析法在LNG储存系统风险评估中的应用[J].工业安全与环保,2016,42(2):63-66.ZHOU Dehong,LI Wen,FENG Hao,et al. Application of fault tree analysis method in risk assessment for lng storage system[J].Industrial Safety and Environmental Protection,2016,42(2):63-66.
[18]亢永,吕鹏飞,庞磊.城市燃气管道泄漏事故风险场强度评价研究[J].安全与环境工程,2016,23(6):166-169.KANG Yong,LYU Pengfei,PANG Lei. Evaluation of risk field intensity for leakage accidents of urban gas pipelines[J]. Safety and Environmental Engineering,2016,23(6):166-169.