FPGA-based all-fiber current transformer denoising method and device
A current transformer and all-fiber technology, which is applied in measuring devices, voltage/current isolation, measuring current/voltage, etc., can solve problems such as the lack of control of overall system noise, avoid the occupation of a large number of resources, and solve complex matrix operations , the effect of improving the accuracy
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Embodiment 1
[0054] This embodiment provides an FPGA-based all-fiber-optic current transformer denoising method. This embodiment adopts the spartan6 series FPGA of XILINX, and utilizes the rich DSP, RAM resources and floating-point computing IP cores to complete the algorithm. complex matrix operations. Such as image 3 As shown, when the system is working, the state variable data x in 1 should be initialized first i ,in, here x 1 、x 2 、x 3 Respectively represent the amplitude, frequency and phase of the AC current signal. Calculate the average value x of each state variable by the mean value module 2 i , the covariance matrix P is calculated by the covariance module 3 xx After resampling module 4, obtain according to the following formula:
[0055]
[0056] x i =x i , i=4;
[0057]
[0058] Among them, n=7, λ=α 2 n-n, 0.0001≤α≤1, the weight is
[0059] Then the prior value calculation module 6 utilizes The calculated prior point set 7{y i}. The u obtained by ADC ...
Embodiment 2
[0061] This embodiment provides a FPGA-based all-fiber-optic current transformer denoising device to implement the denoising method in Embodiment 1, such as Figure 4 As shown, the denoising device includes: a preprocessing module 101, a weight calculation module 102, a nonlinear processing module 103, a covariance calculation module 104 and a posteriori value calculation module 105, wherein,
[0062] The preprocessing module 101 is used to collect the state signal of the current transformer and preprocess the state signal to obtain the state variable data x i ;
[0063] Weighted calculation module 102, for the obtained state variable data x i Perform weighting calculations to obtain a weighted dataset {χ i};
[0064] The nonlinear processing module 103 is used to obtain weighted data set {χ i} Perform nonlinear data processing to obtain the dataset {y i};
[0065] Covariance calculation module 104, for according to the data set {y i}, dataset {y i} mean value calculat...
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