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??????本文目錄如下：??????
目錄
??1 概述
??2 運行結果
??3?參考文獻
??4 Matlab代碼及文獻
??1 概述
文獻來源：
摘要:本文提出了一種基于“條件局部峰值率”(CLPR)的信號變化/事件/異常檢測方法。首先對CLPR特征進行了描述，并在此基礎上介紹了該方法。CLPR計算算法作為用戶自定義函數(shù)在Matlab?軟件環(huán)境中實現(xiàn)，并使用實際數(shù)據(jù)進行了多次數(shù)值實驗以進行驗證和驗證。將該方法與基于短時能量、短時過零率和短時峰度的三種經(jīng)典檢測方法進行了性能比較，結果表明了該方法的優(yōu)越性。Matlab?實現(xiàn)的可訪問性允許實驗的可重復性，并促進該方法的實際應用。
關鍵詞:時域，信號，數(shù)據(jù)，變化，事件，異常，檢測。
原文摘要：
Abstract – In this paper, we present a method for signal change/event/anomaly detection based on a novel time-domain feature termed “conditional local peaks rate” (CLPR). First, the CLPR feature is described and further the method is introduced based on it. The CLPR calculation algorithm is implemented in the Matlab? software environment as a user-defined function and several numerical experiments are conducted with real-world data for sake of verification and validation. The performance of the proposed method is compared with three other classic detection methods based on the short-time energy, short-time zero-crossing rate and short-time kurtosis and the obtained results indicate its advantages. The accessibility of the Matlab? implementation allows repeatability of the experiments and facilitates the real practical application of the method. Keywords: time domain, signal, data, change, event, anomaly, detection.
?本文使用逐幀方法和名為“條件局部峰值速率”（CLPR） 的新穎信號特征實現(xiàn)了一種新的基于時域的信號變化檢測方法——本地信號峰值的速率高于其鄰居的某個預定義閾值水平。所提出的特征的基本單位是“每個樣品的局部峰”（lpps）。
為了闡明函數(shù)的用法，給出了幾個實際示例。它們表明，CLPR可以作為數(shù)據(jù)中各種異常或事件的良好檢測過程。這些例子表明，在大多數(shù)情況下，CLPR優(yōu)于經(jīng)典的變化檢測方法——短時間能量、短時間過零率和短時間峰度。
??2 運行結果
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%% 最后一個運行結果圖主函數(shù)?
clear, clc, close all
%% load data file
load data_5.mat ? ? ? ? ? ? ? ? ? ? ? ? ? ? % load data
fs = 16000; ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? % sampling frequency?
x = x/max(abs(x)); ? ? ? ? ? ? ? ? ? ? ? ? ?% normalize the signal
N = length(x); ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?% signal length
t = (0:N-1)/fs; ? ? ? ? ? ? ? ? ? ? ? ? ??? ?% time vector%% signal framing
frlen = round(50e-3*fs); ? ? ? ? ? ? ? ? ? ?% frame length
hop = round(frlen/2); ? ? ? ? ? ? ? ? ? ? ? % hop size
[FRM, tfrm] = framing(x, frlen, hop, fs); ? % signal framing%% determine the Short-time Energy
STE = sum(abs(FRM).^2);%% determine the Short-time Zero-crossing Rate
STZCR = crossrate(FRM, 0);%% determine the Short-time Kurtosis
STK = kurtosis(FRM);%% determine the Short-time Conditional Local Peaks Rate
% minimum height difference between a peak and its neighbors
mindiff = 50e-3;?% CLPR measurement
STCLPR = conlocpksrate(abs(FRM), mindiff);%% plot the results
% plot the signal waveform
figure(1)
subplot(5, 1, 1);
plot(t, x, 'r')
grid minor
hold on
xlim([0 max(t)])
ylim([-1.1*max(abs(x)) 1.1*max(abs(x))])
set(gca, 'FontName', 'Times New Roman', 'FontSize', 14)
xlabel('Time, s')
ylabel('Amplitude, V')
title('The signal in the time domain')% plot the STE
subplot(5, 1, 2)
plot(tfrm, STE, 'r')
grid minor
xlim([0 max(t)])
ylim([0 1.1*max(abs(STE))])
set(gca, 'FontName', 'Times New Roman', 'FontSize', 14)
xlabel('Time, s')
ylabel('Value, V^2')
title('Short-time Energy')% plot the STZCR
subplot(5, 1, 3)
plot(tfrm, STZCR, 'r')
grid minor
xlim([0 max(t)])
ylim([0 1.1*max(abs(STZCR))])
set(gca, 'FontName', 'Times New Roman', 'FontSize', 14)
xlabel('Time, s')
ylabel('Value, cps')
title('Short-time ZCR')% plot the STK
subplot(5, 1, 4)
plot(tfrm, STK, 'r')
grid minor
xlim([0 max(t)])
ylim([0 1.1*max(abs(STK))])
ylim([0 10])
set(gca, 'FontName', 'Times New Roman', 'FontSize', 14)
xlabel('Time, s')
ylabel('Value, /')
title('Short-time Kurtosis')% plot the STLPR
subplot(5, 1, 5)
plot(tfrm, STCLPR, 'r')
grid minor
xlim([0 max(t)])
ylim([0 1.1*max(STCLPR)])
set(gca, 'FontName', 'Times New Roman', 'FontSize', 14)
xlabel('Time, s')
ylabel('Value, lpps')
title('Short-time CLPR')%% mark the signal
DF = STCLPR > 1.5*mean(STCLPR);
subplot(5, 1, 1)
plot(tfrm, DF, 'k', 'LineWidth', 1)
legend('Signal', 'Detection flag', 'Location', 'SouthEast')
??3?參考文獻
部分理論來源于網(wǎng)絡，如有侵權請聯(lián)系刪除。文章來源：http://www.zghlxwxcb.cn/news/detail-467041.html
[1] H. Zhivomirov, N. Kostov. A Method for Signal Change Detection via Short-Time Conditional Local Peaks Rate Feature. Journal of Electrical and Electronics Engineering, ISSN: 1844-6035, Vol. 15, No. 2, Oct. 2022, pp. 106-109, 2022.文章來源地址http://www.zghlxwxcb.cn/news/detail-467041.html
??4 Matlab代碼及文獻
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