基于改进狼群算法与时序特征融合的多元化安全生产预警系统设计  

Design of Diversified Safety Production Early Warning System Based on Improved Wolf Pack Algorithm and Timing Feature Fusion

作　　者：和洪宽 HE Hongkuan(CSD Water Service Co.,Ltd.,Beijing 100192,China)

机构地区：[1]中持水务股份有限公司,北京100192

出　　处：《微型电脑应用》2025年第1期313-316,共4页Microcomputer Applications

摘　　要：受到安全生产信息多元化复杂程度较高的影响,现阶段预警系统无法在既定时间指标范围内准确识别安全异常数据,不能对其进行同步预警。在单位时间内降低系统的识别效率与准确率,不利于维持正常生产秩序。为了解决上述问题,从系统硬件与软件算法两方面入手,构建全新功能硬件,增设专项处理单元。根据硬件特点及系统预警缺陷,引入改进狼群算法与时序特征融合算法,共同优化安全异常特征数据,实现多元化异常数据的高精度识别。对所提系统的数据调试证明,所提系统能够有效提升对安全异常数据的识别灵敏度及其准确度,确保系统满足实际生成要求。Affected by the higher complexity coefficient of safety production information diversification,the early warning system at this stage is unable to accurately identify the safety abnormal data within the established time index range and conduct synchronous early warning for it.The recognition efficiency and accuracy of the system are reduced in a unit time,which is not conducive to the maintenance of normal production order.In order to solve the above problems,this paper builds new functional hardware and adds special processing units from system hardware and software algorithm.According to the characteristics of hardware and the early warning defects of the system,the improved wolf pack algorithm and the timing feature fusion algorithm are introduced to jointly optimize the safety anomaly feature data and realize the high-precision identification of diversified anomaly data.Through the data debugging of the proposed system,it is proved that the proposed system can effectively improve the identification sensitivity and accuracy of safety anomaly data,and ensure that the system meets the actual production requirements.

关 键 词：改进狼群算法 时序特征融合 多元化 预警系统 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]