With the advent of the Internet of things era, power equipment is gradually connected to the network, and its intelligent fault detection function provides greater help for the power industry. The purpose of this study is to design the power equipment fault information acquisition system of the Internet of things. This research is based on the equipment fault information collection system of the Internet of things and mainly studies the fault information collection method based on the Internet of things technology. Equipment fault data are generally time series data. In the analysis of equipment failure, the data before and after fault and before and after fault are analyzed. The abnormal state of equipment is associated with the data before and after the fault. Therefore, by analyzing the characteristics of the fault data and the equipment before and after the fault, a bidirectional recurrent neural network model based on LSTM is constructed. The method designed in this paper can not only improve the efficiency and speed of collection, but also can compare and collect fault information. The overall operation state of the power unit is improved accurately. The research results show that the company's low-voltage user acquisition success rate has reached more than 99%. With the increase of time, the fault information collection efficiency can approach 99%. It shows that the function of this research system is better, the economic loss of the company is reduced, and the management is optimized.

随着物联网时代的到来，电力设备逐渐连接到网络，其智能故障检测功能为电力行业提供了更大的帮助。本研究的目的是设计物联网的电力设备故障信息采集系统。本研究基于物联网的设备故障信息采集系统，主要研究基于物联网技术的故障信息采集方法。设备故障数据通常是时间序列数据。在设备故障分析中，分析了故障前后，故障前后的数据。设备的异常状态与故障前后的数据有关。所以，通过分析故障前后数据和设备的特征，建立了基于LSTM的双向递归神经网络模型。本文设计的方法不仅可以提高收集效率和速度，而且可以比较和收集故障信息。功率单元的整体操作状态被精确地改善。研究结果表明，该公司的低压用户获取成功率已达到99％以上。随着时间的增加，故障信息的收集效率可以达到99％。结果表明，该研究系统的功能较好，减少了企业的经济损失，并优化了管理。本文设计的方法不仅可以提高收集效率和速度，而且可以比较和收集故障信息。功率单元的整体操作状态被精确地改善。研究结果表明，该公司的低压用户获取成功率已达到99％以上。随着时间的增加，故障信息的收集效率可以达到99％。结果表明，该研究系统的功能较好，减少了企业的经济损失，并优化了管理。本文设计的方法不仅可以提高收集效率和速度，而且可以比较和收集故障信息。功率单元的整体操作状态被精确地改善。研究结果表明，该公司的低压用户获取成功率已达到99％以上。随着时间的增加，故障信息的收集效率可以达到99％。结果表明，该研究系统的功能较好，减少了企业的经济损失，并优化了管理。低压用户获取成功率已达到99％以上。随着时间的增加，故障信息的收集效率可以达到99％。结果表明，该研究系统的功能较好，减少了企业的经济损失，并优化了管理。低压用户获取成功率已达到99％以上。随着时间的增加，故障信息的收集效率可以达到99％。结果表明，该研究系统的功能较好，减少了企业的经济损失，并优化了管理。