摘要
为解决皮带式检重分级装备,在高速工作时检重精度低的问题,首先对检重系统进行建模,研究检重秤在静止、空载运行、加载工作下的系统状态,对检重秤采集的信号进行时频分析,找出干扰源和干扰频段,分析其产生原因及变化趋势,确定滤波指标。依指标,设计FIR数字滤波器提高数据信噪比。降噪后采用2种方式进行重量值估计:(1)非对称切尾均值(Trimmed-mean mass estimator,TME),取去噪后的最后N个采样数据按大小排序,对排序后的数据进行非对称切尾,找出准确的观测区间,然后对该区间取平均值;(2)算数平均重量估计(Average mass estimation,AME),截取最后N个数据取平均值。结果表明:TME方式所得检重误差低于0.3%,平均误差0.155%;AME平均误差为0.758%。FIR滤波可快速去噪,TME重量估计能令检重精度更高。
In order to solve the problem of low weight detection preci- sion of belt type weight detection equipment at high speed. Firstly, the model of weight detection system was modeled, and then the checkweigher in static, no-load operation, the normal work of the state of the system was checked to analyze time frequency signals. The source of interference and its frequency were found out, then an analysis of its causes and changes were analyzed, determining the in- dex filtering. According to the index, the FIR digital filter was de- si.gaed to dertoise tb.e data. After fiiterl.ng, two methods were adopted as follows. The weight estimation of asymmetric trimmed mean （Trimmed-mean mass estimator, referred to as TME） was investiga- ted. After taking the last N data and sorting by size, this sequence was cut in an asymmetrical way for average. Moreover, the arithmetic average weight estimation （A^eragemassest^mat^cm, re- ferred to as AME） u^ed to intercept the last N data, and the average was adopted, The results showed that the weight error of TME was less than 0,3%, and the average error is 0.155%, with the average error of AME 0.758%, It was concluded that the FIR filtering could fast denoise the wave, and the TME weight estimation had higher detection accuracy.
出处
《食品与机械》
CSCD
北大核心
2017年第11期96-99,共4页
Food and Machinery
基金
国家科技支撑计划项目(编号:2015BAF12B00)
关键词
动态检重系统
时频分析
FIR滤波
非对称切尾均值
dynamic weighing
time-frequency analysis
FIR filter- ing
sorting-based trimmed mean
