机器人产品安全性随机器人数量增长和应用范围扩大而越受重视。为解决机器人安全数据缺乏导致机器人产品质量监管形式及方法受制约问题，设计了以数据为核心、应用为导向的预警系统架构，构建了机器人安全指标库、产品类型库、安全风险库等机器人产品属性和安全属性数据库，研究了基于抽样检测数据、网络舆情数据、消费投诉数据的多源数据处理流程和方法，开发了机器人产品质量安全监测预警平台。该平台实现了机器人质量安全事件和信息的实时采集、智能评估、系统监测和及时预警，为其他工业产品基于大数据的质量监督提供方法参考。

The safety of robot products is getting more and more attention with the increase of the number of robots and the expansion of their application scope. In order to solve the problem that the lack of robot safety data restricts the form and method of robot product quality supervision, a data driven and application oriented early warning system architecture was designed, and robot product attribute and safety attribute databases such as robot safety index database, product type database, and safety risk database were constructed. Based on sampling inspection data, network public opinion data, the multi-source data processing process and method of consumer complaint data, a robot product quality and safety monitoring and early warning platform was developped. The platform realizes real-time collection, intelligent evaluation, system monitoring and timely early warning of robot quality and safety events and information, and provides method reference for quality supervision of other products based on big data.