Signal envelope generation based on Matlab

Content introduction

The signal envelope refers to the curve formed by connecting the maximum amplitude of the signal as time changes. It can be used to describe the overall change trend of the signal and is often used in signal processing and communication systems.

Signal envelope plays an important role in signal processing. It represents the trend of the amplitude of the signal changing with time, that is, the envelope of the signal. By extracting the envelope of the signal, applications such as signal amplitude modulation demodulation, signal analysis, and signal compression can be realized.

Specifically, the functions of the signal envelope include the following aspects:

  1. AM demodulation: In AM communication, the original modulated signal can be restored by extracting the signal envelope. This has important applications in radio and television, wireless communications and other fields.

  2. Signal analysis: By analyzing the envelope of the signal, important characteristics of the signal, such as frequency, amplitude, phase and other information, can be obtained. This is of great significance for signal processing and fault diagnosis.

  3. Signal compression: In some cases, the envelope of a signal can represent the main information of the signal, while ignoring the details. By extracting the envelope of the signal and compressing it, storage and transmission overhead can be reduced.

  4. Speech recognition: In speech processing, important features of speech, such as intonation and pitch, can be obtained by extracting the envelope of the speech signal, thereby realizing technologies such as speech recognition and speech synthesis.

    Signal envelopes have many applications in signal processing. Here are some common ones:

1. Medical field: In electrocardiogram (ECG) signal processing, the signal envelope can be used to detect the R-wave peak of the heart, thereby helping doctors diagnose heart disease. It can also be used for respiratory signal processing to monitor the patient’s breathing.

2. Audio processing: Signal envelopes can be applied to audio signal processing to extract notes in music or semantic information in human voices. By extracting the envelope of the signal, applications such as audio denoising, music analysis, and speech recognition can be realized.

3. Vibration analysis: In mechanical engineering and structural engineering, signal envelopes can be used for vibration analysis and fault diagnosis. By extracting the envelope of vibration signals, faults of rotating machinery can be detected, fatigue life of structures can be predicted, etc.

4. Communication system: In wireless communication systems, the signal envelope can be used to estimate the dynamic range of the signal, thereby helping to adjust the gain and dynamic range of the receiving end. It can also be applied to areas such as radio spectrum sensing and adaptive modulation.

5. Image processing: Signal envelopes can be applied to edge detection and contour extraction in image processing. By extracting the envelope of the image gray value, the edge information of the image can be enhanced to achieve tasks such as target detection and image segmentation.

To sum up, signal envelope generation is an important signal processing technology, which can help us better understand and analyze the characteristics and trends of signals. Peak detection, low-pass filtering and envelope tracking are commonly used signal envelope generation methods, and they can be selected according to actual needs. Signal envelope generation technology has wide applications in communication systems, audio processing, vibration analysis and other fields. By mastering signal envelope generation technology, we can better process and analyze various signals, providing strong support for practical applications.

Part of the code

?MOENVELOPE shows how to use function envelope to obtain the </code>
<code>clc;</code><code>close all</code><code>% Load a signal waveform</code><code>%---------------- ----------------------------</code><code>load data.txt data;</code><code>t = data(:,1); % time series</code><code>y = data(:,2); % signal data</code><code>figure(1);</code><code>plot( t,y,'b-'); </code><code>title('The original signal waveform','FontSize',18);</code>


<code>% Call function envelope to </code><code>% obtain the envelope data</code><code>%---------------------- -----------------------</code><code>[up,down] = envelope(t,y,'linear');</code>


<code>% Show the envelope alone</code><code>%---------------------------------- ----------</code><code>figure(2)</code><code>plot(t,up); hold on;</code><code>plot(t,down );</code><code>title('The envelope of the given signal data','FontSize',18);</code><code>hold off;</code>


<code>% Show the original signal and its envelope</code><code>%---------------------------------- -------------</code><code>figure(3)</code><code>plot(t,y,'g-'); hold on;</code> <code>plot(t,up,'r-.');</code><code>plot(t,down,'r-.');</code><code>title('The envelope vs the given signal data','FontSize',18);</code><code>hold off;</code>

<code>

  • Part of the code

Operation results

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References

[1] Zhang Yongsheng. Research on LCR wave ultrasonic stress detection system based on Hilbert envelope signal extraction technology [D]. University of Electronic Science and Technology of China [2023-09-19]. DOI: CNKI: CDMD: 2.1013.331017.

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