CN111476137B - Novel pipeline leakage early warning online relevant positioning data compression method and device - Google Patents
Novel pipeline leakage early warning online relevant positioning data compression method and device Download PDFInfo
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Abstract
The invention discloses a novel pipeline leakage early warning online relevant positioning data compression method and device, wherein the method comprises the following steps: collecting a noise sample; performing FFT (fast Fourier transform) operation on the acquired noise samples to obtain noise frequency domain information; recombining the frequency spectrum in the frequency domain by a frequency band migration method, reserving an effective pipeline noise frequency band, and discarding out-of-band noise; performing an IFFT (inverse fourier transform) transformation operation to obtain a frequency domain compressed time domain signal; and finally, ADPCM compression coding is carried out to output compressed code stream. The invention has the advantages of good selectivity, good anti-interference performance, high compression ratio, no phase distortion, simple algorithm and the like.
Description
Technical Field
The invention relates to the field of signal and information processing, in particular to a novel pipeline leakage early warning online relevant positioning data compression method and device.
Background
When a pipe leaks, the fluid medium passes through the leak gap at high speed, and due to vibration, friction, deceleration, expansion, impact, etc., the fluid generates reynolds stress or shear force, forming leakage noise. Leaky sound waves propagate in the form of non-dispersive plane waves and dispersive higher-order acoustic modes in pipes and pipe fluids, and are affected by the fluid and pipe attenuation characteristics, with increasing propagation distance, the noise intensity is rapidly reduced. By utilizing the characteristic that noise is generated when a pipeline leaks, various pipe network leakage detection/monitoring devices (such as a leakage detector, a correlator, leakage early warning and the like) have been developed at home and abroad, and the noise detection method is also a current main use method of a water supply pipe network.
The common leakage early warning equipment is an important equipment applying a noise detection method and adopts noise intensityThe characteristic distinguishing method generally selects to collect noise data in the period of 2:00-4:00 at night, and aims to reduce the interference of environmental noise and reduce the false alarm and false alarm probability. During acquisition, noise data are acquired at fixed intervals of T seconds (generally 5-10 seconds, different manufacturers are slightly different), the noise intensity is calculated, and the total number of times of acquisition is N times (generally N>For ease of analysis, define the noise intensity discrete sequence acquired N times as F (t), while defining the intensity range threshold V th (generally about 5db is set, different manufacturers have slightly different) and cut-off value V cut (generally about 20db is set, and different manufacturers slightly differ), and the leakage judging method comprises the following steps:
1. when MIN (F (t))>＝V cut And MAX (F (t)) -MIN (F (t))<＝V th When leakage occurs;
2. when MIN (F (t))<V cut Or MAX (F (t)) -MIN (F (t))>V th When the leakage occurs, no leakage occurs;
wherein MAX () takes the maximum value of the sequence and MIN () takes the minimum value of the sequence. The method mainly judges whether leakage occurs according to the characteristic that the leakage noise intensity is relatively stable and the randomness of the environmental noise is high.
Although the common leakage early warning equipment can early warn pipeline faults, the leakage points cannot be accurately positioned on line, and when leakage occurs, engineers are required to use professional instruments (a leakage hearing instrument, a correlation instrument and the like) to position the leakage points on site. In order to solve the problem, the development of leakage early warning supporting an online positioning function is scheduled, and the online positioning plate leakage early warning realizes online automatic leakage point positioning while realizing leakage early warning. The device collects pipeline noise data of not less than 3 seconds at night, the data are transmitted to a central server through the Internet of things after being compressed, and the server completes cross correlation operation of adjacent monitoring points and automatically positions leakage points.
The leakage early warning equipment is arranged underground for a long time, is powered by a battery, and belongs to micro-power consumption and micro-strip wide application equipment. Practice proves that the data transmission loss electric quantity accounts for more than 70% of the total electric quantity of the equipment, if the data transmission loss electric quantity accounts for more than 70% of the total electric quantity of the equipment, namely the total data quantity of 3 seconds of collected samples is 10KHz by 3 seconds by 2B (bytes) by 60KB, the data must be transmitted after being compressed in order to reduce the transmission data quantity and the equipment power consumption. Although current audio compression techniques are mature and have a large variety of compression, there are still a number of drawbacks to the application of pipeline leak-site related localization. The pipeline leakage noise and the leakage point positioning have the unique characteristics, and particularly show the following aspects:
1. the frequency bands are different: the sound propagation characteristics of different pipes are different, and the audio transmission characteristics of the common pipe are shown in fig. 3 (pipe noise propagation frequency band table): the frequency band of leakage noise of the spheroidal graphite cast iron pipeline is distributed in the range of 200 Hz-800 Hz, the leakage noise of the polyvinyl chloride pipeline is distributed in the range of 100 Hz-600 Hz, the leakage noise of the cement pipeline is distributed in the range of 200 Hz-1200 Hz, and the leakage noise of the galvanized steel pipeline is distributed in the range of 400 Hz-1200 Hz. The compression is required according to the specific frequency band characteristics of different pipes, so that the compression ratio is improved, the data volume is reduced, and the out-of-band noise interference is suppressed.
2. Low frequency band and high sampling rate: as can be seen from fig. 3 (pipe noise propagation band table), different pipe noise bands are distributed between 100Hz and 1200Hz, and according to the sampling theorem, the sampling rate is not lower than 2400Hz, and according to the industry requirement, the positioning accuracy error is not greater than 1m, and the correlation resolution is not greater than 0.1ms (millisecond), so the minimum 10KHz sampling rate (resolution: 1000 ms/10k=0.1 ms) is generally taken. The higher sampling rate increases the data volume, is unfavorable for micro-power consumption and micro-strip width application, so that the compression is required by combining the sound propagation characteristics of different pipes, only the effective noise bandwidth is reserved, and the invalid out-of-band noise is abandoned. Taking a polyvinyl chloride pipeline as an example, if the sampling rate is 10KHz, the frequency band range after Fourier transform is 0-5 KHz, as shown in FIG. 4 (the effective frequency spectrum range of the polyvinyl chloride pipeline). The leakage noise of the pipeline is distributed between 100Hz and 600Hz, the proportion of the effective leakage noise in the whole frequency spectrum is very small, and the noise below 100Hz and above 600Hz belongs to the environmental noise, and the practice shows that the environmental noise is a main factor affecting the relative positioning precision and must be filtered by a technical means.
3. Phase sensitivity: unlike conventional speech compression algorithms, the cross-correlation operation is known to be phase sensitive according to the cross-correlation theory, so that the compression algorithm is required to be phase lossless. The cross-correlation function is as follows:
f1 (t), f2 (t) is a cross-correlation function of the energy signals, f1 (t) and f2 (t);
4. high compression ratio: the leakage early warning equipment is powered by a battery and is arranged underground for a long time, micro-power consumption work and extremely small transmission bandwidth are required, and practical application shows that: when the device is in standby operation, the electric quantity is only consumed by a few microamps, the average electric quantity is more than 250 milliamperes in transmission, the instantaneous electric quantity is up to 800 milliamperes or even higher, and the electric quantity of the transmission loss accounts for more than 70 percent of the total electric quantity of the loss, so that the compression ratio is provided as much as possible, the data quantity is reduced, and the purposes of reducing the electric quantity consumption of the transmission and prolonging the service life are achieved.
5. The algorithm is simple: the complexity of the compression algorithm should be reduced as much as possible because the terminal device adopts a lower-rate MCU in order to reduce the power consumption and has limited operation capability.
Disclosure of Invention
The invention aims to provide a novel pipeline leakage early warning online relevant positioning data compression method and device, which aim at the application requirement of online leakage point positioning according to the pipeline noise propagation characteristics, solve the problem of a data compression technology suitable for online leakage point positioning of a pipe network, and have the characteristics of good selectivity, good anti-interference performance, high compression rate, no phase distortion, simple algorithm and the like.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
a method of pipeline noise compression, the method comprising: collecting pipeline noise data and performing analog-to-digital conversion; collecting noise data, and performing FFT (fast Fourier transform) operation to obtain noise frequency domain information; the frequency spectrum is recombined in the frequency domain according to the sound propagation characteristics of the pipeline by a frequency band migration method, only an effective pipeline noise frequency band is reserved, and out-of-band interference noise is discarded; then reduced to time domain signal through IFFT (inverse fast Fourier transform); and finally, outputting a compressed code stream in the time domain through ADPCM coding.
To achieve the above object, there is also provided a data compression apparatus comprising: the acquisition unit is used for acquiring pipeline noise data and performing analog-to-digital conversion; FFT operation unit: performing FFT (fast Fourier transform) operation on the acquired pipeline noise data to obtain pipeline noise frequency domain information; the frequency band migration unit is used for recombining the frequency spectrum in the frequency domain according to the sound propagation characteristics of the pipeline by a frequency band migration method, only preserving the effective noise frequency band of the pipeline, and discarding out-of-band interference noise; an IFFT operation unit performing IFFT (inverse fast fourier transform) conversion operation on the frequency spectrum data after the band migration to obtain a time domain signal after the frequency domain compression; ADPCM encoding unit: and performing compression coding on the output signals of the IFFT operation unit by using an ADPCM algorithm, and outputting compressed code streams.
To achieve the above object, there is also provided a pipe noise decompression method, the method comprising: receiving the compressed code stream; ADPCM decoding is carried out on the compressed code stream; then obtaining frequency domain information through FFT (fast Fourier transform) operation; performing reverse migration on the frequency spectrum in a frequency domain through a frequency band recovery method, and recovering the original position of an effective pipeline noise frequency band; and finally, performing IFFT (inverse fast Fourier transform) operation to restore the time domain signal after decompression.
To achieve the above object, there is also provided a pipe noise decompression apparatus including: a receiving unit configured to receive the compressed code stream; an ADPCM decoding unit for decoding the compressed code stream by using an ADPCM algorithm; FFT operation unit: performing FFT (fast Fourier transform) operation on the data decoded by the ADPCM to obtain frequency domain information; band recovery unit: reversely shifting the frequency spectrum in the frequency domain to restore the original position of the effective frequency band of the pipeline noise; IFFT operation unit: spread spectrum and recover the decompressed pipe noise time domain signal.
The invention has the advantages and positive effects that:
compared with the prior art, the invention adopts the frequency domain and time domain dual compression technology, comprehensively considers the noise propagation characteristics of the pipeline and the actual application scene requirements, can be suitable for pipelines with different materials, has the characteristics of high compression rate, good anti-interference performance, meeting the phase sensitivity application, simple algorithm and the like, and is described in detail below.
1. The invention has the advantages of flexible selectivity and anti-out-of-band interference
The transmission of the pipeline leakage noise is influenced by the attenuation characteristic of the pipeline material, different pipelines show different frequency band characteristics (see figure 3), and the algorithm can selectively reserve the frequency band of the pipeline leakage noise according to the on-site pipelines and shield out-of-band noise interference. If the ductile cast iron pipeline only selects and retains the frequency band information in the range of 200 Hz-800 Hz; the polyvinyl chloride pipeline only selects and reserves the frequency band information in the range of 100 Hz-600 Hz; the cement material pipeline only selects and reserves the frequency band information in the range of 200 Hz-1200 Hz; the galvanized steel pipeline only selectively reserves the frequency band information in the range of 400 Hz-1200 Hz. In practical pipe applications, leakage noise comes from inside the pipe, while ambient noise comes mainly from outside the pipe. Practice proves that the environmental noise is a main factor influencing the relative positioning precision, and the problem is well solved by adopting selective compression, so that the data volume is reduced, and the out-of-band noise interference is inhibited.
2. The invention has the advantage of high compression ratio
Taking a polyvinyl chloride pipeline as an example, if the sampling rate is 10KHz and the sampling bit is 16 bits wide, 1 second of original data volume=10 khz×1 second×2b (byte) =20kb. As can be seen from FIG. 3, the noise frequency band of the polyvinyl chloride pipeline is distributed in the range of 100 Hz-600 Hz, and the bandwidth is 500Hz. The original acquisition data is subjected to FFT conversion to obtain a frequency spectrum in a range of 0-5 KHz, and the compression ratio of the original data and an effective pipeline noise frequency band is=5 KHz/500 Hz=10:1. If ADPCM adopts a common 16:4 compression rate, the total compression rate=40:1, and the compressed data is only 512B (bytes). The higher sampling rate ensures the accuracy of relevant positioning, and the high compression ratio reduces the transmission data volume, reduces the power consumption of equipment, prolongs the service life of the equipment and saves precious bandwidth resources.
3. The invention satisfies the phase sensitive application
In the application of accurate positioning of pipeline leakage points, the current common pipeline network leakage point accurate positioning equipment mainly comprises a correlator, a multi-probe correlator and other equipment, and is based on cross-correlation operation, wherein the cross-correlation operation is sensitive to phase, and the change of the phase directly influences the operation result, so that the problems of large leakage point positioning error or incapability of positioning and the like are caused. The algorithm completes the compression process in the frequency domain through frequency domain migration based on frequency domain and time domain double compression, thereby not only ensuring that the phase of effective leakage noise is lossless, but also inhibiting the interference of out-of-band noise. ADPCM compression and decompression are adopted in the time domain, the ADPCM coding utilizes the correlation of adjacent audio data in time, the audio data of adjacent sampling points have similar characteristics, the difference correlation well describes the phase characteristics of signals, and the practice proves that the consistency result can be obtained by adopting the direct correlation operation of the ADPCM coding and the original data.
Drawings
FIG. 1 is a schematic flow chart of the coding algorithm of the present invention;
FIG. 2 is a schematic flow chart of a decoding algorithm of the present invention;
FIG. 3 is a table of common pipe noise propagation characteristics bands;
FIG. 4 is an illustration of the effective spectral range of a PVC pipe;
FIG. 5 is a graph of the noise spectrum of polyvinyl chloride pipe;
FIG. 6 is a schematic diagram of band shifting of the present invention;
FIG. 7 is a flow chart of band migration of the present invention;
fig. 8 is a band recovery flow chart of the present invention;
fig. 9 is an ADPCM encoding framework diagram.
Detailed Description
The following describes specific embodiments of the present invention in detail with reference to the drawings. It should be understood that the detailed description and specific examples, while indicating and illustrating the invention, are not intended to limit the invention.
Overview:
the leakage noise is formed by the fact that fluid medium passes through a leakage gap at a high speed to generate Reynolds stress or shearing force, and is influenced by the damping characteristics of water fluid and pipelines, the damping speed of the leakage noise in the propagation process is far higher than that of the leakage noise in the low frequency, and the damping characteristics of pipelines made of different materials on sound are different, and the leakage noise is particularly shown in fig. 3. By comprehensively considering the frequency band characteristics of all the common pipelines, the leakage noise frequency is mainly distributed in the range of 100-1.2 KHz, and the sampling frequency is not lower than 2.4KHz according to the shannon sampling theorem. And the positioning error is not more than 1m, and the related resolution is not more than 0.1ms (millisecond) according to the requirements of the industry, so the minimum sampling rate of 10KHz is generally adopted. The higher sampling rate increases the data volume, and is unfavorable for leakage early warning, such as micro-power consumption and micro-strip wide application equipment which are arranged underground throughout the year and are powered by batteries.
From the perspective of the pipeline noise composition, the pipeline noise comprises two parts of pipeline leakage noise and environmental noise, the leakage noise is from the inside of the pipeline, the environmental noise is from the outside of the pipeline, the environmental noise belongs to Gaussian white noise, and the spectral power distribution accords with Gaussian distribution. Practice has shown that ambient noise is a major factor affecting the accuracy of the associated positioning, so in pipe leak location applications, shielding ambient noise effects must be maximized.
The algorithm comprehensively considers the sound propagation characteristics of pipelines with different materials and the characteristics of actual application scenes, has the characteristics of being capable of selectively compressing according to the characteristics of different pipe frequency bands, good in anti-interference performance, high in sampling rate, low in phase distortion, high in compression ratio, simple in algorithm and the like, and meets the pipeline leakage positioning application requirements. The algorithm compression coding process flow is shown in fig. 1, and the decompression process flow is shown in fig. 2.
The coding process comprises the following steps: collecting a pipeline noise sample and performing analog-to-digital conversion; collecting noise data, and performing FFT (fast Fourier transform) operation to obtain noise frequency domain information; the frequency spectrum is recombined in the frequency domain according to the sound propagation characteristics of the pipeline by a frequency band migration method, only the effective pipeline leakage noise frequency band is reserved, and out-of-band interference noise is discarded; then reduced to time domain signal through IFFT (inverse fast Fourier transform); and finally, outputting a compressed code stream in the time domain through ADPCM coding.
The decoding process comprises the following steps: receiving the compressed code stream; ADPCM decoding is carried out on the compressed code stream; then obtaining frequency domain information through FFT (fast Fourier transform) operation; performing reverse migration on the frequency spectrum in a frequency domain through a frequency band recovery method, and recovering the original position of the effective pipeline leakage noise frequency band; finally, the time domain signals are restored into decompressed time domain signals through IFFT (inverse fast Fourier transform) operation.
For a better illustration of the invention, the following detailed description of the various parts is provided:
principle of band selective compression:
the leakage noise frequency bands of different pipes are distributed differently and out-of-band noise is a main factor affecting the accuracy of the correlation and must be filtered by a technical means. Therefore, during compression, effective pipeline leakage noise frequency bands are selectively reserved in the frequency domain according to the current pipeline materials, and ineffective out-of-band noise is discarded. As shown in fig. 3: the ductile iron pipeline reserves the frequency band information in the range of 200 Hz-800 Hz; the polyvinyl chloride pipeline reserves the frequency band information in the range of 100 Hz-600 Hz; the cement material pipeline reserves the frequency band information in the range of 200 Hz-1200 Hz; the galvanized steel pipeline retains the frequency band information in the range of 400 Hz-1200 Hz. The selectively compressed data only contains effective leakage noise information, so that the compression ratio is improved, the data volume is reduced, and meanwhile, the data has better filtering performance and is beneficial to improving the correlation accuracy. In order to achieve the band-selective compression, the present algorithm performs a band-selective compression process and a band-selective recovery process through "band migration" and "band recovery", which will be described in detail below.
Band shift principle:
the frequency band migration is a specific implementation process of frequency band selective compression, and according to noise frequency band characteristics of different pipes, the frequency domain is recombined, an effective leakage noise frequency band is selectively reserved, and out-of-band interference noise is discarded. Band migration process: let the lower limit frequency point of the current pipe noise be f low The upper frequency limit point is f top The leakage noise frequency band of the current pipe can be marked as F log (f low ，f top ). If the current sampling frequency is fs (the value is greater than or equal to 10 KHz), the frequency band after FFT (fast Fourier transform) operation can be marked as F fft (0, fs/2). As can be seen from fig. 3 and 4, the leakage noise band F log (f low ，f top ) Far smaller than the original frequency band F fft (0,fs/2)，Will F log (f low ，f top ) The range spectrum data is migrated to the original band 0 start position and discarded (f top -f low ) All the above spectrum data form a new frequency band F new (0,f top -f low ). And then to F new (0,f top -f low ) An IFFT (inverse fast fourier transform) operation is performed with a minimum number of points, resulting in a time domain signal containing only pipe leakage noise.
For the convenience of explanation of the frequency band shift principle, a polyvinyl chloride pipe will be taken as an example, and as can be seen from fig. 3, the lower limit frequency point f of leakage noise of the polyvinyl chloride pipe low =100 Hz, upper frequency limit point f top =600 Hz, the band is then denoted as F log (100 Hz,600 Hz). The upper limit frequency is fs/2=5khz, the frequency band is marked as F, which is known according to shannon's sampling theorem fft (0 Hz,5 KHz). The leakage noise spectrum of the polyvinyl chloride pipe is shown in fig. 5, in which the abscissa represents frequency, unit Hz, and the ordinate represents amplitude, unit db. Will F log The spectrum data in the (100 Hz,600 Hz) range is migrated to the initial position of the spectrum 0, and the interference noise data content above 600Hz is discarded to form a new frequency band F new (0,500 hz), the band shift procedure is shown in fig. 6, 7. Finally, to F new An IFFT (inverse fast fourier transform) operation is performed with a minimum number of points to obtain a time domain signal containing only pipe leakage noise. If the number of FFT operation points before band migration is 10240, the minimum number of IFFT operation is 1024.
Band recovery principle:
the frequency band recovery is the inverse process of frequency band migration, the frequency domain recovery of effective pipeline leakage noise is completed, and the original frequency spectrum is reconstructed. Band recovery process: let FFT point number in spectrum migration be P fft Let the number of IFFT points in the spectrum migration process be P ifft . First with P ifft Performing FFT conversion on the points to obtain band data F after band migration new (0,f top -f low ). Then use P fft Point spread spectrum, spread part filled with 0, and F new (0,f top -f low ) Migration of spectral data to F log (f low ，f top ) Corresponding positions. Finally by P fft And performing IFFT operation on the points to obtain the restored pipeline leakage noise time domain signal. The band recovery process diagram is shown in fig. 8.
The polyvinyl chloride pipeline is adopted, the sampling rate fs=10KHz is set, and P is set fft ＝10240，P ifft =1024. Firstly, FFT operation is carried out on the time domain signal after frequency band migration by 1024 points to obtain frequency domain data F after frequency band migration new (0,500 Hz). Spreading the spectrum to 10240 points, filling the spread with 0, and then F new (0,500 Hz) spectral data migration to F log (100 Hz,600 Hz). The original position of the pipeline leakage noise is restored in the frequency domain, and a new frequency spectrum F is obtained fft (0 Hz,5 KHz). And finally, performing IFFT operation at 10240 points to obtain the restored pipeline leakage noise time domain signal.
ADPCM codec principle:
ADPCM (Adaptive Differential Pulse Code Modulation) the adaptive differential pulse code modulation, the G.726 audio coding algorithm is also essentially an ADPCM algorithm, and the coding block diagram is shown in FIG. 9. ADPCM coding is essentially a predictive coding algorithm that uses a variable step quantizer for predictive coding, taking advantage of the temporal correlation of adjacent audio data. The encoding process of ADPCM can be divided into three steps: the first step is to calculate the error between the current actual value and the predicted value; the second step carries on the quantization coding to the error; and thirdly, updating the predictor. ADPCM decoding is the inverse of ADPCM encoding, and the decoding process can be divided into three steps: firstly, obtaining a predicted value; a second step of executing a decoding process; and thirdly, updating the predicted value.
The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to the specific details of the above embodiments, and various simple modifications can be made to the technical solution of the present invention within the scope of the technical concept of the present invention, and all the simple modifications belong to the protection scope of the present invention.
In addition, the specific features described in the above embodiments may be combined in any suitable manner without contradiction.
Moreover, any combination of the various embodiments of the invention can be made without departing from the spirit of the invention, which should also be considered as disclosed herein.
Claims (2)
1. The novel pipeline leakage early warning online relevant positioning data compression method is characterized by comprising two steps of pipeline noise compression and decompression:
pipeline noise compression: collecting a pipeline noise sample and performing analog-to-digital conversion; obtaining noise frequency domain information through FFT conversion operation; the frequency spectrum is recombined in the frequency domain through a frequency band migration method, the frequency domain information of effective pipeline leakage noise is reserved, and out-of-band interference noise is discarded; then the time domain signals are restored by IFFT conversion operation; finally, outputting compressed code stream by ADPCM compression coding;
pipeline noise decompression: ADPCM decoding is carried out on the received compressed code stream; then obtaining frequency domain information through FFT conversion operation; performing reverse migration on the frequency spectrum in a frequency domain through a frequency band recovery method, and recovering the original position of the effective pipeline leakage noise frequency band; and finally, restoring the time domain signals into decompressed time domain signals through IFFT operation.
2. The novel pipeline leakage early warning online relevant positioning data compression device is characterized by comprising two parts, namely pipeline noise compression and pipeline noise decompression:
the pipeline noise compression comprises an acquisition unit, a sampling unit and a sampling unit, wherein the acquisition unit is used for acquiring pipeline noise samples and completing analog-to-digital conversion; the FFT operation unit performs FFT conversion operation on the pipeline noise samples subjected to analog-to-digital conversion to obtain noise frequency domain information; the frequency band migration unit is used for reserving effective pipeline leakage noise frequency domain information according to sound propagation characteristics of pipelines made of different materials and discarding out-of-band interference noise; an IFFT operation unit for performing IFFT conversion operation on the frequency domain data after frequency band migration to obtain a time domain signal after frequency domain compression; an ADPCM encoding unit which applies an ADPCM algorithm to perform compression encoding on the compressed time domain signal and outputs a compressed code stream;
the pipeline noise decompression comprises a receiving unit for receiving the compressed code stream; an ADPCM decoding unit for decoding the compressed code stream by using an ADPCM algorithm; an FFT operation unit for performing FFT operation on the ADPCM decoded data to obtain frequency domain information; the frequency band recovery unit reversely shifts the frequency band in the frequency domain to recover the original position of the effective pipeline leakage noise frequency band; and the IFFT operation unit restores the decompressed pipeline noise time domain signal.
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