Event-driven remote wireless coalbed methane well station abnormal scene safety monitoring method
A coalbed methane well, event-driven technology, applied in the information field
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[0054] In order to verify the effect of the algorithm, it is compared with the classical kernel density estimation (KDE) algorithm and background-based difference kernel density estimation (BS-KDE) detection algorithm in terms of accuracy. Select the live video of coalbed methane mining, the main interference is the reciprocating motion of the water pump; the video resolution is 320*240, and the parameters of the three algorithms are selected as follows:
[0055] KDE algorithm, the number of samples M is 40, the Gaussian kernel function is selected, the threshold value th=0.0005 is selected when calculating the threshold value, and the background update method is blind update.
[0056] BS-KDE algorithm, the first background model update rate α is 0.1, the background difference threshold is 255*0.15, and the counter threshold C T is 50; the number of samples M in the second background model is 40, a Gaussian kernel function is selected, a threshold value th=0.0005 is selected, ...
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