The invention discloses an elevator car anomaly detection method and system for electric vehicle recognition, and the method specifically comprises the following steps: a special training data set isconstructed for an electric motor car, an electric vehicle picture is downloaded on a Baidu search engine, the position of the electric vehicle in the training set is marked through an image marking tool, the data is used as a label of training data; in the model training step, based on the electric vehicle training data set in the first step, 1000 rounds of iterative optimization are carried out,and the accuracy of the electric vehicle recognition model is improved. A self-built electric vehicle data set is used for training a neural network model, the recognition precision for the electricvehicle is improved, the safety of a lift car is guaranteed, and the risk of safety accidents in the later period is reduced; by constructing a special electric vehicle data set, the electric vehiclerecognition and detection precision is improved; an edge computing mode is adopted, and a microcontroller is utilized to solve the problem of time delay depending on a cloud network and even the problem of electric vehicle detection and recognition with an unavailable network.
本发明公开了一种针对电动车识别的电梯轿厢异常检测方法及系统,具体实施包括以下步骤:构建电动动车专用训练数据集,以及在百度搜索引擎上下载电动车图片,并利用图像标注工具,标注出训练集中电动车位置,以作为训练数据的标签;模型训练步骤中,基于第一步中的电动车训练数据集,经过1000轮迭代优化,提升电动车识别模型的准确率。本发明体现在用自建电动车数据集,来训练神经网络模型,提高针对电动车的识别精度,以保证轿厢安全,降低后期发生安全事故风险;利用构建专用电动车数据集,提高电动车识别检测精度;采用边缘计算模式,利用微控制器,解决依赖云端网络时延问题,甚至网络不可用的电动车检测识别问题。
Elevator car anomaly detection method and system for electric vehicle recognition
一种针对电动车识别的电梯轿厢异常检测方法及系统
2021-01-26
Patent
Electronic Resource
Chinese
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