CN107355686A - A kind of detection method of drain line blockage failure - Google Patents
A kind of detection method of drain line blockage failure Download PDFInfo
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- CN107355686A CN107355686A CN201710431959.4A CN201710431959A CN107355686A CN 107355686 A CN107355686 A CN 107355686A CN 201710431959 A CN201710431959 A CN 201710431959A CN 107355686 A CN107355686 A CN 107355686A
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- 238000001514 detection method Methods 0.000 title claims abstract description 31
- 238000000034 method Methods 0.000 claims abstract description 22
- 239000011159 matrix material Substances 0.000 claims abstract description 17
- 238000000354 decomposition reaction Methods 0.000 claims abstract description 11
- 238000000605 extraction Methods 0.000 claims abstract description 10
- 238000007637 random forest analysis Methods 0.000 claims abstract description 9
- 230000006698 induction Effects 0.000 claims abstract description 6
- 230000000903 blocking effect Effects 0.000 claims description 12
- 239000004744 fabric Substances 0.000 claims description 8
- 230000004044 response Effects 0.000 claims description 6
- 239000004020 conductor Substances 0.000 claims description 5
- 238000000205 computational method Methods 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 4
- 239000010865 sewage Substances 0.000 claims description 4
- 230000003321 amplification Effects 0.000 claims description 3
- 238000003199 nucleic acid amplification method Methods 0.000 claims description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 2
- 238000012360 testing method Methods 0.000 abstract description 9
- 238000012549 training Methods 0.000 description 8
- 230000004927 fusion Effects 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 230000002776 aggregation Effects 0.000 description 3
- 238000004220 aggregation Methods 0.000 description 3
- 239000000284 extract Substances 0.000 description 3
- 230000004888 barrier function Effects 0.000 description 2
- 238000005303 weighing Methods 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000004927 clay Substances 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000007499 fusion processing Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000012212 insulator Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000010926 purge Methods 0.000 description 1
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- 230000007480 spreading Effects 0.000 description 1
- 238000003892 spreading Methods 0.000 description 1
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Classifications
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/02—Preventing, monitoring, or locating loss
- F17D5/06—Preventing, monitoring, or locating loss using electric or acoustic means
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/12—Classification; Matching
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- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Investigating Or Analyzing Materials By The Use Of Ultrasonic Waves (AREA)
Abstract
The invention discloses a kind of detection method of drain line blockage failure.Method is：Fix a drainpipe the detection means of plugging fault；Pipeline fault-free section/pipeline fault section is detected known to selection, and computer obtains the signal under two kinds of operating modes from receiving terminal；Obtain the sound induction signal under two kinds of operating modes of drainage pipeline；Sound induction signal carries out SVD decomposition；Energy-Entropy index and approximate entropy index are extracted, the extraction result of two kinds of indexs is incorporated as initial characteristicses vector set；Obtained Energy-Entropy characteristic vector set, the set of approximate entropy characteristic vector, initial characteristicses vector set use are obtained into class discrete matrix between discrete matrix and class apart from Separability Criterion method；Calculate weight, the weight of approximate entropy index of Energy-Entropy index；Each characteristic vector set is weighted to obtain new characteristic vector set；Random forest grader is trained into characteristic vector set, obtains Fault Identification model.The present invention improves the accuracy and reliability of testing result.
Description
Technical field
The present invention relates to a kind of detection method of drain line blockage failure, belong to pipeline fault detection field.
Background technology
The horizontal positive continuous improvement of Chinese Urbanization, with urban economy development, drainage pipeline length is presented acceleration and increased every year
Long trend, but due to initial design existing defects or usage time are long, the fault rate of drainage pipeline also ten
The height divided.Wherein, the blocking of pipeline belongs to the hidden danger for threatening urban safety draining, if can not find in time and purging line event
Barrier, the normal operation of city water supply and sewage will be influenceed.Therefore the drain line blockage detection method of efficiently and accurately is for pipeline fault
Detection is very necessary.
The content of the invention
In order to solve the problems, such as drain line blockage fault detect, the invention provides a kind of drain line blockage failure
Detection method.
The technical scheme is that：A kind of detection method of drain line blockage failure, methods described specific steps are such as
Under：
S1, the plugging fault that fixes a drainpipe detection means；
Pipeline fault-free section known to S2, selection is detected, and signal X (t) is through power caused by computer control sound card
Amplifier, transmitting terminal, loudspeaker are received by hydrophone, and computer obtains the signal Y of normal pipeline from receiving terminal1(t)；
S3, in the artificial placement tamper of above-mentioned known pipeline fault-free section, signal X caused by computer control sound card
(t) received through power amplifier, transmitting terminal, loudspeaker by hydrophone, computer obtains the signal for blocking pipeline from receiving terminal
Y2(t)；
Sound induction signal G (t) under S4, acquisition two kinds of operating modes of drainage pipeline, computational methods areIts reclaimed water
The pipeline acoustical signal for listening device to collect is Y (t), and the sinusoidal signal of sound card transmitting is X (t)；According to response signal computational methods, divide
The response signal of normal pipeline is not obtainedBlock the response signal of pipeline
S5, SVD decomposition is carried out to the sound induction signal under normal pipeline, blocking two kinds of operating modes of pipeline respectively, after decomposition
Component of signal under normal pipeline, blocking two kinds of operating modes of pipeline；
S6, Energy-Entropy index and approximate entropy index, the Energy-Entropy index that will be obtained are extracted to component of signal under two states
As characteristic vector set A, using obtained approximate entropy index as characteristic vector set B, the extraction result of two kinds of indexs is closed
And as the vectorial set C of initial characteristicses1；
S7, by Energy-Entropy characteristic vector set A uses that step S6 is obtained apart from Separability Criterion method obtain in class from
Dissipate matrix SW1The discrete matrix S between classB1；
S8, by approximate entropy characteristic vector set B uses that step S6 is obtained apart from Separability Criterion method obtain in class from
Dissipate matrix SW2The discrete matrix S between classB2；
S9, the vectorial set C of the initial characteristicses for obtaining step S61It is discrete in class using being obtained apart from Separability Criterion method
Matrix SW3The discrete matrix S between classB3；
S10, the weight for calculating Energy-Entropy indexThe weight of approximate entropy index isEach characteristic vector set is weighted to obtain new characteristic vector set C2, C2=A × w1+B ×
w2；Tr () represents to take the mark of matrix；
S11, using characteristic vector set C2Random forest grader is trained, obtains Fault Identification model；
S12, other sections for pipeline obtain characteristic vector set using step S4~step S10 method, use
The random forest grader trained in Step11 carries out the identification of failure to other sections of pipeline.
SVD decomposition is carried out by building Hankel matrixes.
The detection means of the drain line blockage failure include two expansion links, sound card, amplifier, loudspeaker, screen cloth,
Hydrophone, wave filter and computer；
Two expansion links stretch to shaft bottom from two different Sewage well covers, and pallesthesiometer is fixed on expansion link I
Lower end, the ground surface end of expansion link I passes through amplifier, sound card connects computer；Place screen cloth and facilitate sound to believe in the bottom of expansion link II
Number aggregation, hydrophone are fixed on the lower end of expansion link II and above the screen clothes, and the ground surface end of expansion link II is connected by wave filter
Connect computer；
Signal caused by computer control sound card amplifies through power amplifier, and the signal after amplification is via in expansion link I
Put wire and be transferred to the transmitting that pallesthesiometer carries out sound；Voice signal inner conductors in hydrophone receiving pipeline it is flexible
Bar II reaches wave filter and is filtered, and filtered signal is input in computer and carries out data processing.
The loudspeaker, hydrophone are to place one on the other apart from bottom hole location.
The beneficial effects of the invention are as follows：
Detection method is extracted two kinds of features of signal, compensate for the situation of single feature failure extraction deficiency, can be more complete
The characteristic of the reflection pipeline in face, reaches and more reliably extracts result than traditional single failure extracting mode.This method is by special
Weighted Fusion and grader recognition training are levied, can be with the detect line clogging failure of efficiently and accurately, therefore there is Practical valency
Value.
In summary, the actual conditions of the invention based on drainage pipeline fault detect, introduce acoustic conductance wave detecting method, coordinate
Detection means, the detection acoustical signal for extracting drainage pipeline carry out Fault Identification, optimize testing process.Detection proposed by the present invention
Method, carried out failure multi-feature extraction, and carried out the Weighted Fusion of feature, improve the accuracy of testing result with can
By property.
Brief description of the drawings
Fig. 1 is a kind of detection means of drain line blockage failure；
Fig. 2 is the inventive method flow chart；
Fig. 3 is 0.1s normal pipeline time domain waveform；
Fig. 4 is 0.1s blocking pipeline time domain waveform；
Fig. 5 is normal pipeline SVD decomposition results；
Fig. 6 is blocking pipeline SVD decomposition results.
Embodiment
Embodiment 1：A kind of detection method of drain line blockage failure, tested using Bradford of Britain pipeline
The number of chambers is according to progress case verification.Duct length is 15.4 meters, and pipe material is clay pipeline, a diameter of 150mm.Choose 0.1s's
Experimental data carries out illustration, and (due to signal, can to have come and gone pipeline in 0.1s multiple back and forth, carry in abundant pipeline and believe
Breath, has met testing requirements).
The detailed process of Computer signal processing is as follows：
Extract signal：Experiment flow is as shown in Figure 2.Before detection, in order to obtain normal pipeline, block pipeline, two kinds
Training data under operating mode, a segment pipe fault-free section is selected to be detected.Computer obtains the training signal of normal pipeline, such as
Shown in Fig. 3.Then barrier is artificially placed among the normal pipeline of this section, is detected.So as to obtain the instruction for blocking pipeline
Practice signal, as shown in Figure 4.Normal pipeline training signal is 52 groups, 62 groups of jam signal.
Carry out Signal Pretreatment：Signal under two kinds of operating modes is input in MATLAB and analyzed, two kinds of signals are made
SVD decomposition is carried out with 6 rank Hankel matrixes.The SVD decomposition results of one group of normal pipeline are as shown in figure 5, one group of blocking pipeline
SVD decomposes as shown in Figure 6.
Feature extraction：Then the characteristic extraction procedure of signal is carried out, carrying out feature to the component signal under two kinds of operating modes carries
Take, extract its Energy-Entropy, approximate entropy two indices, obtained Energy-Entropy index is as characteristic vector set A, the approximation that will be obtained
Entropy index is as characteristic vector set B, using extraction result joint as characteristic vector set C1, partial results (its as shown in table 1
In one group of signal whole extraction results).
1 one groups of normal pipelines of table and the feature extraction result for blocking pipeline
Characteristic weighing fusion process：And then the characteristic weighing fusion of signal is carried out, calculate the identification power of each characteristic index
Weight.By A, B, C1Characteristic vector set uses apart from Separability Criterion respectively, obtains spreading between scatter matrix and class in three groups of classes
Matrix.Then the identification weight of Energy-Entropy index and approximate entropy approximate entropy in total characteristic vector set is calculated, by calculating
The weight calculation result of Energy-Entropy is 0.41, and approximate entropy index weights are calculated as 0.59.In order to obtain the feature of Weighted Fusion to
Duration set；Two characteristic vector set weighted arrays are obtained into new characteristic vector set C2, combined method C2=A × 0.41+
B×0.59。
Training random forest grader is identified：By characteristic vector set C250% be used as training sample, 50% makees
Random forest grader is trained for test sample, obtains Fault Identification model；(the characteristic vector set after dimensionality reduction is inputted,
By characteristic vector set C257 groups of samples as training sample, 57 groups of samples are as test sample training random forest classification
Device, obtain Fault Identification model.) as shown in table 2 (by embodiment with the discrimination power obtained by the characteristic vector set of embodiment
The characteristic vector set that known pipeline obtains, as test group part, it is identified using Fault Identification model, by what is obtained
Classification contrasts with the good known class of model mark, and the same is correct.).
The discrimination table that table 2 inputs characteristic vector set after random forest
| Correctly | Mistake | Recognition correct rate | |
| Normal pipeline | 26 | 2 | 92.31% |
| It is big to block pipeline | 31 | 1 | 96.77% |
Detect remaining unknown situation duct section：Last experimenter detects the duct section of remaining unknown situation, and repeats
(detection of the present invention for unknown segment is equivalent to the part of test group to above-mentioned detection process, to unknown duct section, collection letter
Number, and double faults detection process obtains characteristic vector set, is input in grader, and grader will recognise that a class
Not, this classification is exactly testing result.).
As shown in Figure 1, the detection means of drain line blockage failure can be experimental provision：
The detection means of the drain line blockage failure include two expansion links, sound card, amplifier, loudspeaker, screen cloth,
Hydrophone, wave filter and computer；
Two expansion links stretch to shaft bottom from two different Sewage well covers, and pallesthesiometer is fixed on expansion link I
Lower end, the ground surface end of expansion link I passes through amplifier, sound card connects computer；Place screen cloth and facilitate sound to believe in the bottom of expansion link II
Number aggregation, hydrophone are fixed on the lower end of expansion link II and above the screen clothes, and the ground surface end of expansion link II is connected by wave filter
Connect computer；
Signal caused by computer control sound card amplifies through power amplifier, and the signal after amplification is via in expansion link I
Put wire and be transferred to the transmitting that pallesthesiometer carries out sound；Voice signal inner conductors in hydrophone receiving pipeline it is flexible
Bar II reaches wave filter and is filtered, and filtered signal is input in computer and carries out data processing.
The loudspeaker, hydrophone can be to place one on the other apart from bottom hole location, can also be apart from the same.
When it is implemented, needing to open two well cover for sewer on ground, two expansion links are stretched into well.Two flexible
Bar gos deep into pipeline and bottomed out simultaneously.Screen cloth is placed in the bottom of expansion link II, and facilitating acoustical signal aggregation, (screen cloth can guarantee that sound produces
Certain resilience, and then facilitate hydrophone to collect signal).The pallesthesiometer model can select Wei Shatong companies (Germany)
K50WP models；Hydrophone can be the SQ31 model hydrophones produced by sensor technology Co., Ltd (Canada)；It is flexible
Bar kernel is metallic conductor, and shell is insulator, can transmit signal.During detection, controlled by the computer equipped with WinMLS softwares
Sound card produces the sine sweep acoustical signal of 20 seconds, and the frequency range of signal is 100-6000 hertz.Sound caused by sound card is believed
Number it need to be amplified by power amplifier, being transferred to pallesthesiometer via the inner conductors of expansion link I by transmitting terminal enters
The transmitting of row sound.The amplifier of selection is the power amplifier of 2708 models of Konstanze Bachmann-Wayne Kramer company (Germany) production,
Power amplifier drives pallesthesiometer sounding.After pallesthesiometer work, hydrophone is reception state.Hydrophone is via stretching
The receiving terminal connection wave filter of contracting bar I, is filtered from Kemo VBF 10M wave filters, is by signal frequency range control
It is input to after 100-4000 hertz among computer and carries out subsequent treatment.
Above in conjunction with accompanying drawing to the present invention embodiment be explained in detail, but the present invention be not limited to it is above-mentioned
Embodiment, can also be before present inventive concept not be departed from those of ordinary skill in the art's possessed knowledge
Put that various changes can be made.
Claims (4)
- A kind of 1. detection method of drain line blockage failure, it is characterised in that：Methods described comprises the following steps that：S1, the plugging fault that fixes a drainpipe detection means；Pipeline fault-free section known to S2, selection is detected, and computer controls signal X (t) caused by sound card through amplifier, raised Sound device is received by hydrophone, and computer obtains the signal Y of normal pipeline from receiving terminal1(t)；S3, in the artificial placement tamper of above-mentioned known pipeline fault-free section, signal X (t) caused by computer control sound card Received through amplifier, loudspeaker by hydrophone, computer obtains the signal Y for blocking pipeline from receiving terminal2(t)；Sound induction signal G (t) under S4, acquisition two kinds of operating modes of drainage pipeline, computational methods areWherein hydrophone The pipeline acoustical signal collected is Y (t), and the sinusoidal signal of sound card transmitting is X (t)；According to response signal computational methods, obtain respectively To the response signal of normal pipelineBlock the response signal of pipelineS5, SVD decomposition is carried out to the sound induction signal under normal pipeline, blocking two kinds of operating modes of pipeline respectively, obtained just after decomposition Component of signal under Chang Guandao, blocking two kinds of operating modes of pipeline；S6, Energy-Entropy index and approximate entropy index are extracted to component of signal under two states, using obtained Energy-Entropy index as Characteristic vector set A, using obtained approximate entropy index as characteristic vector set B, the extraction result of two kinds of indexs is merged and made For the vectorial set C of initial characteristicses1；S7, the Energy-Entropy characteristic vector set A uses that step S6 is obtained are obtained into discrete square in class apart from Separability Criterion method Battle array SW1The discrete matrix S between classB1；S8, the approximate entropy characteristic vector set B uses that step S6 is obtained are obtained into discrete square in class apart from Separability Criterion method Battle array SW2The discrete matrix S between classB2；S9, the vectorial set C of the initial characteristicses for obtaining step S61Discrete matrix in class is obtained using apart from Separability Criterion method SW3The discrete matrix S between classB3；S10, the weight for calculating Energy-Entropy indexThe weight of approximate entropy index isEach characteristic vector set is weighted to obtain new characteristic vector set C2, C2=A × w1+B×w2； Tr () represents to take the mark of matrix；S11, using characteristic vector set C2Random forest grader is trained, obtains Fault Identification model；S12, other sections for pipeline obtain characteristic vector set using step S4~step S10 method, using Step11 In the random forest grader that trains other sections of pipeline are carried out with the identification of failure.
- 2. the detection method of drain line blockage failure according to claim 1, it is characterised in that：By building Hankel Matrix carries out SVD decomposition.
- 3. the detection method of drain line blockage failure according to claim 1, it is characterised in that：The drainage pipeline blocks up The detection means of plug failure includes two expansion links, sound card, amplifier, loudspeaker, screen cloth, hydrophone, wave filter and computer；Two expansion links stretch to shaft bottom from two different Sewage well covers, and pallesthesiometer is fixed under expansion link I End, the ground surface end of expansion link I connect computer by amplifier, sound card；Place screen cloth and facilitate acoustical signal to gather in the bottom of expansion link II Collection, hydrophone are fixed on the lower end of expansion link II and above screen clothes, and the ground surface end of expansion link II is connected by wave filter to be counted Calculation machine；Signal caused by computer control sound card amplifies through power amplifier, and the signal after amplification is led via built in expansion link I Line is transferred to the transmitting that pallesthesiometer carries out sound；The expansion link II of voice signal inner conductors in hydrophone receiving pipeline Reach wave filter to be filtered, filtered signal is input in computer and carries out data processing.
- 4. the detection method of drain line blockage failure according to claim 3, it is characterised in that：The loudspeaker, water Device is listened apart from bottom hole location one on the other to place.
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| CN108958301A (en) * | 2018-06-27 | 2018-12-07 | 北京小米移动软件有限公司 | Control the method, apparatus and storage medium of equipment draining |
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| CN112198232A (en) * | 2020-09-14 | 2021-01-08 | 昆明理工大学 | Drainage pipeline working condition detection and identification method |
| CN112902029A (en) * | 2021-01-19 | 2021-06-04 | 昆明理工大学 | U-shaped pipe running state voiceprint recognition method based on VMD and PNCC |
| CN118194142A (en) * | 2024-05-17 | 2024-06-14 | 中电科大数据研究院有限公司 | Post-earthquake repair engineering analysis method and system for intelligent pipe network |
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| CN112902029B (en) * | 2021-01-19 | 2022-03-18 | 昆明理工大学 | U-shaped pipe running state voiceprint recognition method based on VMD and PNCC |
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