摘要
粮温异常严重影响粮食储藏状态,准确探测到粮堆内高温异常是各项工作的基础,合理布置温度传感器是保障探测准确性的关键。以华北地区某平房仓粮温监测数据为基础,利用聚类模型对粮温空间分布、时间段聚类,探索粮堆温度场空间分布规律。结合多重响应分析结果,提出传感器优化布置方案。采用时间序列模型预测未来粮温变化,对布置方案进行检验和修正,得出最终优化布置方案:测温点位根据风险级别可分为6类,其中0级风险经检验不会出现高温异常,则可不再布控传感器。测温点位从240处减少至124处,重点布控在粮面、粮堆四周靠墙部位及粮堆底面,保证了测量准确性。经过以上优化布置,可有效减少测温传感器数量,降低企业储粮成本。
Grain temperature anomalies seriously affect the state of grain storage.Accurate detection of high temperature anomalies in grain piles is the basis of all work.Reasonable placement of temperature sensors is the key to ensuring the accuracy of detection.Based on the temperature monitoring data of a grain warehouse in North China,a model of clustering algorithmwasused to cluster spatial distribution and time distribution of grain temperature,and to explore the rules of spatial distribution of temperature in a grain warehouse.Combined with the results of multiple response analysis,a sensor optimal layout scheme was proposed.The time series model was used to predict the future grain temperature change,and the layout plan was tested and corrected to obtain the final optimized layout plan:thetemperature monitoring positions could be divided into 6 categories according to the risk level,and the 0-level risk was tested without high temperature abnormality.The sensor could no longer be placed in the positions of 0-level risk.The temperature monitoring positions could be reduced from 240 to 124,and the monitoring focus on the surface of grain warehouse,the wall around the grain pile and the bottom of the grain pile to ensure the accuracy of measurement.Based on the optimized arrangement above,the number of temperature sensors could be effectively reduced,and the cost of grain storage of enterprises could be reduced.
作者
郝山山
赵欣然
石宇佳
Hao Shanshan;Zhao Xinran;Shi Yujia(China Academy of Safety Science and Technology,Beijing 100012;Key Laboratory of Major Hazard Control and Accident Emergency Technology,Ministry of Emergency Management,Beijing 100012)
出处
《中国粮油学报》
EI
CAS
CSCD
北大核心
2019年第S02期64-70,共7页
Journal of the Chinese Cereals and Oils Association
基金
国家科技支撑计划(2017YFC0805900)
中国安全生产科学院基本科研课题(2016JBKY13).
