Similar waveform based digital signal end data continuation method

A digital signal, similar waveform technology, applied in electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as large prediction errors, low algorithm efficiency, and reduced algorithm speed.

Inactive Publication Date: 2006-10-25
CHANGAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the time series forecasting method has high requirements for the order determination of the time series model. If the order determination is not accurate, it will cause large prediction errors and also produce endpoint effects.
However, when using the neural network prediction method t

Method used

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  • Similar waveform based digital signal end data continuation method
  • Similar waveform based digital signal end data continuation method
  • Similar waveform based digital signal end data continuation method

Examples

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Embodiment 1

[0086] Figure 3 is a set of industrial field measured data, which is the vibration signal waveform at a bearing bush of a fan in a heavy oil catalytic cracking unit of a domestic oil refinery. The sensor used for signal acquisition is an eddy current (displacement) sensor with a data length of 1024. in Figure 3a is the original signal waveform, Figure 3b It is a local refinement of the original signal, and it can be found that similar components appear repeatedly in the signal, indicating that the signal has cyclostationary characteristics. Figure 5 It is a schematic diagram of the unit of the heavy oil catalytic cracking unit, Figure 3a The signal shown is the vibration signal collected in the X direction of the No. 1 bearing bush of the fan. In order to check the accuracy of the method of the present invention, 50 data points are cut off at both ends of the group of signals to form the signal before the extension, and the most similar waveform extension method proposed...

Embodiment 2

[0088] figure 1 To analyze the signal x(t) using the Empirical Mode Decomposition (EMD) method

[0089] The result of x(t)=0.5·cos(2π·20·t+150°)+cos(2π·100·t) (1), in the figure x(t) is the signal waveform, c 1 , c 2 , r 2 are the first and second intrinsic mode function (intrinsic mode function, IMF) and the remainder obtained after empirical mode decomposition, respectively. Intrinsic mode function c 1 Reflects the cosine signal component with a frequency of 100Hz in the signal x(t), c 2 It reflects the cosine component of the signal with a frequency of 20Hz and an initial phase of 150°. Ideally, c 2 It should be a cosine waveform with an initial phase of 150°, but when actually decomposed, c 2 Severe distortion occurs at the left endpoint, the endpoint effect. remainder r 2 There are also endpoint effects that do not turn into ideal zero vectors. figure 2 is the Hilbert-Huang Transform (HHT) result of the signal x(t). Ideally, it is two straight lines para...

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Abstract

The present invention includes 1, searching waveform in signal most similar with signal end point waveform and used as end point waveform estimation; 2, using outboard waveform in said most similar waveform as outer end point signal data estimation and continuing said waveform to outer signal end point. Said invention has advantages of high continuation data precision, eliminating end effect to both of circulation smoothness signal periodic signal and non-circulation smoothness signal.

Description

technical field [0001] The invention belongs to the technical field of digital signal processing, and in particular relates to a digital signal endpoint data extension method based on similar waveforms for extending one-dimensional digital signal endpoint data to eliminate endpoint effects. Background technique [0002] In addition to the useful components we need, the signals collected in the actual engineering environment are usually mixed with various noise components. In many cases, the noise can be so strong that it can even overwhelm useful information. If not processed, these signals are actually of little use value. The core of signal processing technology is to separate the useful information from the actual collected signal mixed with various noise interference. Since noise is unavoidable and ubiquitous in the engineering environment, signal processing technology is particularly important. At present, signal processing technology (including digital signal proces...

Claims

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Application Information

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IPC IPC(8): G06F17/00
Inventor 高强王婉秦曹建明边耀璋蹇小平吴克刚祁东辉赵伟何正嘉
Owner CHANGAN UNIV
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