基于12位高精度SAR ADC芯片的电梯运行感知与按需维保预测数据集

数据集由佛山市东桥麓山智能科技有限公司在电梯实际监测与智慧运维业务中产出。数据的底层采集依托于公司核心成果——高性能的非二进制12位SAR ADC技术。通过搭载该专利芯片的运维装置，在电梯曳引机、导向轮、电机等关键部位进行高精度数字化采样，确保了物理信号在数字化过程中的高保真度与抗干扰性，具有显著的技术独创性。数据集由“原始传感层”与“智能特征层”共同构成。基础数据涵盖23个原始字段，实时记录电梯各监测点的振动烈度、机械冲击、轴承状态、电机温度及平衡度等物理量。在此基础上，通过自研的机械振动分析算法进行实质性加工，生成了平均振动烈度、平均机械磨损指数、峰值机械冲击、设备健康综合评分、运行状态等级及温度趋势平滑值共6项关键衍生字段。该数据集实现了从底层物理信号到高阶逻辑特征的转化，有效提升故障预判准确率。通过实时监测与健康量化评价，为物业及维保单位提供精准的预测性维护决策。此外，数据集广泛服务于政府特种设备安全监控、老旧电梯安全性能评估及智慧城市大脑集成，为电梯全生命周期价值管理提供核心数据底座。

This dataset was generated by Foshan Dongqiao Lushan Intelligent Technology Co., Ltd. during its elevator actual monitoring and intelligent operation and maintenance business. The underlying data acquisition of the dataset relies on the company's core achievement: high-performance non-binary 12-bit SAR ADC technology. Through high-precision digital sampling conducted on key elevator components including traction machines, guide wheels and motors via operation and maintenance devices equipped with this patented chip, the dataset ensures high fidelity and anti-interference performance of physical signals during digitization, with remarkable technical originality. The dataset consists of two parts: the "Raw Sensing Layer" and the "Intelligent Feature Layer". The basic data contains 23 original fields, which real-timely record physical quantities such as vibration severity, mechanical shock, bearing condition, motor temperature and balance degree at each elevator monitoring point. On this basis, through substantial processing via the self-developed mechanical vibration analysis algorithm, 6 key derived fields are generated, including average vibration severity, average mechanical wear index, peak mechanical shock, comprehensive equipment health score, operating status level and temperature trend smoothing value. This dataset realizes the transformation from underlying physical signals to high-order logical features, effectively improving the accuracy of fault prediction. Through real-time monitoring and health quantitative evaluation, it provides accurate predictive maintenance decisions for property management and maintenance units. In addition, the dataset is widely applied in government special equipment safety monitoring, safety performance assessment of old elevators and smart city brain integration, providing a core data foundation for full-life-cycle value management of elevators.

搜集汇总

背景与挑战

背景概述

该数据集基于12位高精度SAR ADC芯片技术，通过电梯关键部位的高保真采样，采集振动、温度等物理信号，并加工生成平均振动烈度、设备健康综合评分等衍生特征，实现了从底层数据到智能特征的转化。它支持电梯故障预判和按需维保，提升安全性和效率，并应用于智慧城市管理和设备全生命周期评估，具有显著的技术独创性和实用价值。