基于曳引电机动态模型的电梯故障在线监测关键技术研究

More than 3.5 million elevators are operating in China, about twenty five percent of which are ten years old elevators. With the growing number of elevators and the rise of the proportion of old elevators, elevator accidents are gradually increasing, and the elevator safety issue has become the focus of public attention. Many domestic and foreign experts have done deep research on elevator safety in the fields of theory, standard, technology, product and management. Fruitful results have been achieved, providing systematic guarantee for the safe operation of the elevators. Elevator safety is determined by all the critical components. Any critical component fault may lead to serious accidents, and the occurrence of the fault may be coincidental. The existing fault monitoring technologies are inadequate with its incapability of online monitoring, emphasis on qualitative assessment rather than quantitative assessment, poor performance in monitoring critical components and so on. In this project, we carry out new research on online elevator fault monitoring based on traction motor dynamic model, which can execute the main key parameters in real-time identification and self-correction. Based on the dynamic model and input parameters of the traction motor and the dynamic parameters of the elevator, we apply basic principles of dynamics to reveal their intrinsic functional relationship. The embedded intelligent devices will be developed based on traction motor dynamic model and diagnose arithmetic to realize online real-time fault monitoring and performance evaluation of the critical devices, such as traction motors, traction drive devices, brakes and so on. The achievement of this project will help establish the Prognostics and Health Management (PHM) system of the elevators and provide technical support for the formulation of relevant standards of elevators. The research of this project will greatly improve the real-time performance, selectivity, accuracy and reliability of the elevator safety protection, and has important theoretical significance and application prospects.

我国电梯保有量已超过350万台，梯龄超过十年的老旧电梯占比约为25%。随着电梯保有量和老旧电梯占比的提升，电梯事故逐渐增多，电梯安全问题已成为民众关注的焦点。电梯故障具有一定的偶发性，现有故障监测技术手段无法实时在线监测，对于故障数据多定性分析而少定量评估，特别对于制动系统等关键部位的监测手段不足，直接影响了电梯的运行安全性。本项目从曳引电机的本征动态模型出发，通过对电机关键参数的实时辨识和自校正，建立曳引驱动器电参数和电梯传动系统及制动器关键参数的关系映射，进而通过研究确定判别阈，实现电梯主要故障的定量判别和实时在线监测。在此基础上研发嵌入式智能诊断仪器，并建立系统的电梯健康度诊断评估理论，为相关标准制定提供支撑。本项目的研究将大幅提高电梯安全保护的快速性、选择性、准确性和可靠性，具有重要的理论意义和应用前景。

我国电梯保有量已达到700万台，梯龄超过十年的老旧电梯占比逐年提升。随着电梯保有量和老旧电梯占比的提升，电梯事故逐渐增多，电梯安全问题已成为民众关注的焦点，实现电梯故障在线实时监测具有非常重要的意义。本项目研究了基于曳引电机动态模型、无线传感网络、无线数据传输以及实时数据库技术的电梯故障在线监测等关键技术，解决了曳引电机模型适配、电梯关键设备状态感知、高可靠无线传感网络与低功耗等技术难点，形成了电梯健康管理系统。项目采用了微信号提取与处理技术、高效硬件算法逻辑运算技术、桥路补偿技术等解决了温度及受力信号的可靠及高精度测量问题，研发出了温度采集模块以及应变信号采集模块。项目采用了多轴传感及多算法融合技术，实现了电梯轿箱运动学参数的高精度采集，研发出了电梯动力学参数传感与采集模块。项目采用RF433、NBIOT、GPRS/4G无线射频技术、物联网技术以及移动通信技术，构建了可靠无线传感及无线通信数据传输网络，研发了相关传感设备及网关设备，为运动中的传感信号传输提供了可靠的解决方案。项目进行了基于永磁同步曳引电机的软件模型仿真，为嵌入式应用移植、建立与电梯运动表征参数的映射关系提供了基础，进而实现故障诊断，为电梯健康管理提供了技术保障。系统采用开放性系统接口，可方便快捷地实现第三方设备系统集成，可应用于电梯维保、特种设备检测等物理信号的采集及状态监控。项目组共发表论文26篇，申请发明专利5项。项目负责人发表论文14篇，其中SCI收录论文5篇（IEEE TRANSACTIONS 1篇IF 7.351，COMPEL录用1篇）、EI检索论文7篇（含2篇录用），其他论文2篇，申请发明专利3项（授权2项）。项目培养博士研究生1名，硕士研究生5名，本科生4名。通过该项目培养了教授1名，副教授2名。