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基于FOA-BP的风电运维人员不安全行为风险评价

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为评价风电运维人员不安全行为风险,减少行为安全事故的发生,在确定不安全行为风险因素集合的基础上构建不安全行为风险评价指标体系,利用果蝇优化算法调整BP神经网络权值和阈值,建立基于FOA-BP的不安全行为风险评价模型.以某风电场为例收集数据对模型进行测试,实现不安全行为风险评价并计算风险评价指标权重.结果表明:该模型预测性能较好,能够评价不安全行为风险,企业可依据评价指标、指标权重值及风险等级制定针对性的防控措施.
Risk Evaluation of Unsafe Behavior of Wind Power Operation Personnel Based on FOA-BP
In order to evaluate the risk of unsafe behavior of wind power operation and maintenance personnel and reduce the occurrence of behavioral safety accidents.On the basis of determining the set of risk factors of unsafe behavior,the risk evaluation index system of unsafe behavior is constructed.The weight and threshold of BP neural network were adjusted by fruit fly optimiza-tion algorithm,and an unsafe behavior risk assessment model based on FOA-BP was established.Taking a wind farm as an example to collect data,test the model,realize the risk evaluation of unsafe behavior,and calculate the weight of risk evaluation index.This model has good predic-tive performance and can evaluate the risk of unsafe behavior.Enterprises can develop targeted prevention and control measures according to the evaluation index,index weight value and risk level.

fruit fly optimization algorithmwind power operationsunsafe behaviorrisk evalua-tionprediction and evaluation

常丁懿、石娟、瞿丽莉、何子春、张银龙、郑鹏

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天津理工大学管理学院,天津 300384

天津体育学院体育经济与管理学院,天津 301617

西安热工研究院有限公司,西安 710054

华电电力科学研究院有限公司,杭州 310030

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果蝇优化算法 风电运维 不安全行为 风险评价 预测评价

国家自然科学基金中国华电集团有限公司科技项目天津市研究生科研创新项目天津市科学技术普及项目天津市教委社会科学重大项目

71603181CHDKJ21-01-072021YJSB24321KPXMRC000802021JWZD15

2024

10.13306/j.1672-3813.2024.01.015

复杂系统与复杂性科学
青岛大学

复杂系统与复杂性科学

CSTPCD北大核心
影响因子：0.798
ISSN：1672-3813
年,卷(期)：2024.21(1)
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