Matlab 过滤加速度数据中的电尖峰 [英] Matlab filter electical spikes in accelerometric data

问题描述

我有一个受电尖峰影响的加速度数据数据集.

I have a dataset of accelerometric data that is affected by electical spikes.

我正在寻找一种很好的方法来过滤掉或减少这些尖峰，因为需要根据这些数据计算 FFT 的滚动窗口和其他统计指标，例如峰态和偏度.我不能简单地删除这些异常值或用 NaN 替换它们.采样 2000[hz]

I'm looking for a good method to filter out or reduce these spikes as need to calculate on these data a rolling window of FFT and other statistical indicators such as kurtosis and skewness. I can't simply delete these outliers or replace them with NaN. Sampling 2000[hz]

直到现在我都在 MATLAB 2012b 上试过:

Until now I've tried on MATLAB 2012b:

• 小波去噪(Haar小波)
• 中值过滤器
• Despike 和迭代方法

您能提出一种处理这些数据的适当方法吗?

Can you suggest a proper approach to deal with these data?

下载示例数据集

推荐答案

我建议进行一些局部平滑处理.通过定义阈值和平均所有低于和高于的值.

I would suggest some local smoothing. By defining thresholds and averaging all values below and above.

Af = data.example1;
% Thresholds
Tl = -0.6;
To = 0.6;

peaks = find( Af < Tl | Af > To);
Af(peaks) = ( Af(peaks-1) + Af(peaks+1) ) / 2;

这种方法的问题在于，您的大纲有时最多包含 6 个样本.因此，您需要使用 while 循环在多个步骤中进行平滑处理:

The problem with this approach is that your outliners sometimes consist of up to 6 samples. So you need to smooth in multiple steps using a while loop:

Af = data.example1;
% Thresholds
Tl = -0.6;
To = 0.6;

% initialisation
peaks = find( Af < Tl | Af > To);
counter = 0;

while ~isempty(peaks)
    peaks = find( Af < Tl | Af > To);
    Af(peaks) = ( Af(peaks-1) + Af(peaks+1) ) / 2;
    counter=counter+1;
end

经过 6 次迭代后，您会得到以下结果:

after 6 iterations you get the following result:

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