基于模型优化预测与温度场分析的温室传感器故障识别
Greenhouse Sensor Fault Recognition Based on Model Optimization Prediction and Temperature Field Analysis
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摘要: 在温室高温高湿的工作环境下,传感器易出现故障,会对温室的智能管理造成一定的资源浪费,为保证智能化温室管理系统的有效运行,需要及时准确地对温室内故障传感器做出识别。通过试验对云南地区温室在夏季不同通风状态下室内场域的变化情况进行分析,以云南地区大型玻璃连栋温室作为研究对象,建立夏季不同通风方式下温室的三维稳态CFD模型,并结合试验对模型的有效性进行验证。根据实际的外界条件,对温室内部场域进行分析,预测出传感器节点位置处的环境数值,通过与实际读数进行对比,找出传感器读数异常位置。为进一步提高故障传感器识别的准确性,结合基于中值策略的传感器故障节点检测算法,能够及时准确地识别出温室故障传感器,为温室的智能化管理决策提供了准确的温室内环境数据。Abstract: In working environment of greenhouse with high temperature and humidity,the sensors are prone to failure,which causes a certain waste of resources for intelligent management of greenhouse.To ensure effective operation of intelligent greenhouse management system,it is necessary to identify faulty sensors in greenhouse in a timely and accurate manner.Through experiments,changes in the indoor field of Yunnan greenhouses under different ventilation conditions in summer were analyzed.Taking large glass multi-span greenhouses in Yunnan as research object,a three-dimensional steady-state CFD model of greenhouses under different ventilation modes in summer was established and combined with experiments.Validity of the model was verified by experiments.According to actual external conditions,internal field of greenhouse was analyzed to predict environmental value at sensor node position,and abnormal position of sensor reading was found by comparing with actual reading.In order to further improve accuracy of fault sensor identification,combined with sensor fault node detection algorithm based on median strategy,it could accurately identify greenhouse fault sensor in time and provide accurate greenhouse environmental data for intelligent management of greenhouse.
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Keywords:
- greenhouse /
- CFD /
- temperature field /
- sensor /
- fault identification
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