畢業(yè)設(shè)計(jì)外文翻譯----基于多數(shù)據(jù)融合傳感器的分布式溫度控制系統(tǒng)-全文預(yù)覽
【正文】 of the intelligent CAN node. So we can obtain eight temperature values in each CAN node at the same time. We arrange the collected temperature data in a sequence from small to large: T1, T2, …, T 8 In the sequence, T1 is the limit inferior and T8 is the limit superior. We define the median—TM as: (1) The upper quartile—Fv is the median of the interval [TM, T8].The lower quartile number—FL is the median of the interval [T1, TM].The dispersion of the quartile is: （ 2） We suppose that the data is an aberration one if the distance from the median is greater than adF, that is, the estimation interval of invalid data is: (3) In the formula, a is a constant, which is dependent on the system measurement error, monly its value is to be , , and so on. The rest values in the measurement column are considered as to be the valid ones with consistency. And the SingleChip in the intelligent CAN node will fuse the consistent measurement value to obtain a fusion result 5. Temperature measurement data fusion experiment By applying the distributed temperature control system to a greenhouse, we obtain an array of eight temperature values from eight sensors as follows The mean value of the eight measurement temperature result is Comparing the mean value (8)T with the true temperature value in the cell of the greenhouse, we can know that the measurement error is +℃ . After we eliminate the careless error from the fifth sensor using the method introduced before, we can obtain the mean value of the rest seven data (7)T=℃ , the measurement error is ℃ . The seven rest consistent sensor can be divided into two groups with sensor S1, S3, S7 in the first group and sensor S2, S4, S6, S8 in the second one. The arithmetical mean of the two groups of measured data and the standard deviation are as follows respectively: According to formula (13), we can educe the temperature fusion value with the seven measured temperature value. The error of the fusion temperature result is ℃ . It is obvious that the measurement result from data fusion is more close to the true value than that from arithmetical mean. In the practical application, the measured temperature value may be very dispersive as the monitoring area bees bigger, data fusion will improve the measuring precision much more obviously. 6. Conclusions The distributed temperature control system based on multisensor data fusion is constructed through CAN bus. It takes full advantage of the characteristics of field bus control systemFDCS. Data acquisition, data fusion and system controlling is carried out in the intelligent CAN node, and system management is implemented in the main controller (host PC). By using CAN bus and data fusion technology the reliability and realtime ability of the system is greatly impr
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