人工智能的电力物资仓库无人驾驶行吊技术

Unmanned Crane Control Scheme in Energy Power Generation by Using Artificial Intelligence

针对现有技术中电力物资仓库无人驾驶行吊运行在存在避障灵敏性差、故障诊断能力薄弱等问题,设计了一种新型的电力物资仓库无人驾驶行吊控制方案。构建了新型的人工智能控制系统,能够实现无人驾驶行吊运行状态的智能化、自动化监控。还设计了行波定位算法模型,对无人驾驶行吊运行过程中障碍点以及故障点进行监测,并构建长短时记忆神经网络模型,实现无人驾驶行吊运行过程中的故障诊断。试验表明,所提出的方法定位精度高,故障诊断能力强。

Aiming at the problems of poor obstacle avoidance sensitivity and weak fault diagnosis ability in the unmanned crane operation of electric power material warehouse, a new type of unmanned crane control scheme for electric power material warehouse is designed. This technology constructs a new type of artificial intelligence control system to realize the intelligent and automatic monitoring of the operating status of unmanned cranes. This research also designs a traveling wave positioning algorithm model to monitor obstacles and fault points during the operation of unmanned traveling cranes, and builds a long and short-term memory neural network model to realize fault diagnosis during the operation of unmanned traveling cranes. Experiments show that the method in this study has high positioning accuracy and strong fault diagnosis capabilities.