JPS62118263A - Signal analyzing system - Google Patents

Abstract

PURPOSE:To analyze the frequency component of a band exceeding a Nyquist frequency, by bringing a time series data to a sampling extraction through a BPF to which the upper limit and the lower limit frequencies are set, executing an FFT processing by an analytic processing part, and bringing a data in which the coefficient of an analytic range of an obtained analytic data is an odd number, to a rearrangement processing. CONSTITUTION:A control part 7 sets the cut-off frequencies FH, FL of a BPF 5 to FH=m.fs/2, and FL=(m+1).fs/2 with respect to the sampling frequency fs of an A/D converter 2, and gives them to the terminals HP, LP of the BPF 5. A time series data A is brought to a sampling extraction by the A/D converter 2 through the BPF 5, and stored in a memory 3 by a processor 6. An FFT processing part 8 fetches a data D in the memory 3, executes an FFT processing, calculates a power spectrum P(n) from a complex Fourier component X(n) and stores it in the memory 3. A discrimination processing part 9 fetches the P(n) from the memory 3, and when (m) is an odd number, the ascending sequence is reversed by executing a rearrangement.

Description

[Detailed Description of the Invention] [Summary] In a processing system that samples vibration and noise data with an AD converter and performs Fourier analysis on the data, it is possible to analyze frequency components in a band equal to or higher than the Nyquist frequency determined by the sampling frequency of the AD converter. And so.

[Industrial application field]

The present invention relates to seven improved signal analysis methods for digitizing and analyzing analog stroke signals.

In signal analysis processing, it is desired to extract and analyze components higher than the Nyquist frequency of an AD converter.

[Conventional technology]

A conventional example will be explained using figures. FIG. 7 is a diagram of a conventional example.

In FIG. 7, when performing spectrum analysis on time series data A such as vibration noise data, time series data A as shown in FIG. 8 is passed through a low-pass filter and an AD converter 2,
After being taken out, the processing section 4 performs analysis processing.

In this case, the cutoff frequency f of the low-pass filter is relative to the sampling frequency fs of the time series data A. is fc
= -f3 or less. Therefore, as shown in FIG. 9, the time series data B after passing through the low-pass filter has components having a frequency higher than the cutoff frequency fc removed.

This time-series data B is converted into digital data C by an AD converter (sampling extraction circuit with a frequency of 7 fs) 2, and then converted into digital data C, which is stored in memory and subjected to fast Fourier transform (FFT) processing. Time series data, (k=0.1...+'-1)
N: Number of data X(n): Complex Fourier component Based on the obtained complex Fourier component data
X(nJI+! When analyzing time series data using the sampling extraction method as described above, the cutoff frequency fc of the low-pass filter 1 is determined by the sampling frequency f8. Therefore, the time series data B after passing through the low-pass filter 1
Vc is the upper limit frequency, that is, the Nyquist frequency (NY(
Components higher than luiat frequency) will not be included.

fmaX (Nyquist frequency) = 1/2TT: Sampling period (seconds) [Problem to be solved by the invention 3 As is clear from the above, when analyzing time series data using the sampling extraction method, the sampling theorem Therefore, there is a problem in that the upper limit of frequency components that can be analyzed is limited to the Nyquist frequency.

[Means for solving problems]

FIG. 1 is a block diagram of the principle of the present invention. In the present invention, a bandpass filter 5, an AD converter 2 having a sampling extraction means with a sampling frequency of f3, and an analysis processing section 8 having a Fourier transform processing means are connected to convert analog time series data into digital time series. Extract it as data,
In a system that analyzes the extracted data by full Fourier transform processing, an upper limit cutoff frequency 11 and a lower limit cutoff frequency 1 are set.
2, a control unit 7 having a means for setting an off frequency 12, a means for determining whether m is an odd number or an even number, and a means for rearranging data when m is an odd number. It is equipped with a processing section 9 and gold.

[Effect]

The control unit 7 sets the upper limit cutoff frequency 11 to the bandpass filter 5.
After setting the lower limit cutoff frequency 12, the analog time series data 14 is input to the bandpass filter 5, the output time series data 15t is sampled and extracted by the AD converter 2, and the extracted data 16 is subjected to Fourier processing by the analysis processing unit 8. When the analysis process is performed, data in which the coefficient m of the analysis range of the obtained analysis data 13 is an odd number is rearranged.

〔Example〕

Hereinafter, the present invention will be explained with reference to the drawings.
The figure is a block diagram explaining one embodiment of the present invention, FIG. 3 is a waveform diagram explaining one embodiment of the present invention, and FIG. 4 is a frequency characteristic diagram explaining one embodiment of the present invention. The figure is a frequency component diagram illustrating one embodiment of the present invention.

In FIG. 2, when the sampling frequency of the AD converter 2 that samples and extracts the time series data A is f8, the control unit 7 of the processing device 6 sets the cut 17 frequencies Fm and Ft of the bandpass filter 5 as follows. Set the value of

Fsi (cutoff frequency on the bypass side tX) FL (cutoff frequency on the low-pass side) = (m+1)・-f8
(The cutoff frequency FH is set to the terminal HP of the bandpass filter 5, and the cutoff frequency FL is set to the other terminal P, so that the output signal, that is, the time series data B is the frequency band FH to Ft,
The data consists of the following components. Note that (1) and (2) above
) The value of the coefficient m in the equation is f, where fl is the lower limit of the frequency to be analyzed.

It is determined by

When time series data A as shown in FIG. 3 is manually input to the bandpass filter 5, the time series data B on the output side
The data includes bandwidth components as shown in the figure. This time series data B is processed by an AD converter (sampling extraction circuit)
2, where it is sampled at a sampling frequency fs, and the extracted data D is stored in the memory 3 by the processing device 6. Therefore, this extracted data D is
The data contains the above frequency components.

The FFT (Fast 7-FFT) process 8X8 takes out the data D in the memory 3 and performs the high-speed to-IJ conversion process shown in the following equations (3) and (4).

X (Company): Sampled time series data, (k=0.
1. . . ., N-1) N: Number of data

P (n) = a X (n) n″
(4) The obtained analysis data, that is, the power spectrum data P(n) is stored in the memory 3.

The discrimination processing unit 9 takes out the power spectrum data P (n) from the memory 3 and performs the following processing.

Distinguish odd/even.

(2) When m is an odd number, rearrange the spectrum data P (n)' as shown in FIG. Sorting is done by reversing the ascending order.

When m is an odd number in the above 0 term, the reason for rearranging is as follows. When data is sampled at the sampling frequency flI, it is folded back onto the Nyquist frequency wavenumber component. Therefore, when m is an odd number, it is necessary to rearrange the order of the data. Generally, when mm is an odd number, data is folded in reverse order, and when m is an even number, data is folded in normal order.

As described above, in a system that analyzes sampling extraction using an AD converter with a sampling frequency fa, even an ADf converter that operates only at a low sampling frequency @fs can perform spectrum calculation in a high frequency band. It becomes easier.

〔Effect of the invention〕

The present invention has the advantage of facilitating spectrum analysis in high frequency bands even with a low frequency AD converter.

[Brief explanation of drawings]

Fig. 1 is a block diagram of the principle of the present invention, Fig. 2 is a block diagram illustrating an embodiment of the present invention, Fig. 3 is a waveform diagram illustrating an embodiment of the present invention, and Fig. 4 is a block diagram of the principle of the present invention. FIG. 5 is a data block diagram explaining one embodiment of the present invention. FIG. 6 is a frequency characteristic diagram explaining one embodiment of the present invention. FIG. 7 is a conventional example. 8 is a waveform diagram that fully explains the conventional example. Figure 9 is a frequency characteristic diagram that fully explains the conventional example. In the figure, 1-digit low-pass filter, 2 is an AD converter, 3 is a memory,
4Fi processing section, 5 is a bandpass filter, 6 is a processing device, 7 is a control section, 8 is an FFT processing section, 9 is a discrimination processing section, 10 is an output section, 11°F'F+ is an upper limit cut Off frequency, 12.Ft is the lower limit) #7 frequency, 13. P(n) $i analysis data, 14°15, A, B
is time series data (analog), 16. D indicates extracted data. etc. 1. One sentence in 4 months ℃υ month υ J agent, υ month month pro, 72 countries
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Claims (1)

[Claims] A bandpass filter 5, an AD converter 2 having a sampling extraction means with a sampling frequency of f_s, and an analysis processing section 8 having a Fourier transform processing means are connected to convert analog time series data into digital data. In a system that extracts time series data and analyzes the extracted data by Fourier transform processing, an upper limit cutoff frequency 11 and a lower limit cutoff frequency 1 are provided.
2 is set, an upper limit cutoff frequency 11 that is an integer (m+1) times 1/2·f_s, and a lower limit cutoff frequency 12 that is (m) times 1/2·f_s are set. and a discrimination processing section 9 having means for determining whether the integer m is an odd number or an even number, and a means for rearranging data when the integer m is an odd number. Upper cutoff frequency 11 for instrument 5
After setting the lower limit cutoff frequency 12, the analog time series data 14 is input to the bandpass filter 5, the output time series data 15 is sampled and extracted by the AD converter 2, and the extracted data 16 is sent to the analysis processing section 8. A signal analysis method characterized by determining the coefficient m of the analysis range of the obtained analysis data 13 when subjected to Fourier analysis processing, and performing rearrangement processing for data in which the coefficient m is an odd number.