A monitoring method for sensor data quality
A technology for data quality and data monitoring, applied in the fields of electrical digital data processing, digital data information retrieval, special data processing applications, etc., to achieve the effect of good versatility, strong robustness, and guaranteed reliability
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Embodiment 1
[0047] Such as figure 1 As shown, the sensor data quality online and trusted monitoring method includes algorithm initialization, reading sensor data and time stamp, detection and isolation of sensor data abnormal format, sensor data abnormal timing detection and isolation, sensor data abnormal format and abnormal timing Recovery and detection, isolation and recovery of outliers in sensor data.
Embodiment 2
[0049] Such as figure 2 As shown, the specific implementation of the above six steps is as follows:
[0050] step 1:
[0051] According to the real-time requirements of the sensor system, the requirements for computational complexity, and the theoretical basis and conditional assumptions of the algorithm, determine the initial monitoring window length L1 = 3, the maximum monitoring window length L2 = 50, and the length of each adjustment of the window size is Num = 1. The monitoring threshold Th, the absolute value of the front and rear data Var, the time stamp corresponding to the data to be monitored is t, the data is represented as data, the flag format is a space, the initial number of spaces Num1=0, and the two data and the corresponding the time stamp.
[0052] Step 2:
[0053] The read sensor data and time stamp are used as the input of the algorithm, and the sensor data and time stamp are data(t-2), data(t-1), data(t). Where data(t) is the data to be monitored. d...
Embodiment 3
[0064] Such as image 3 As shown, the data monitoring example of sensor abnormal format and abnormal timing, step1 is to convert all abnormal formats into blanks, and supplement the lost data according to the data timestamp, and the timestamp unit depends on the output frequency of the data; step2 is to make full use of Data around spaces Fill those spaces with appropriate data. Here is to use the interpolation method to take the average value of the data at both ends of the space and fill it into the space.
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