CN103742794A - Simulating device and simulating method for pipeline leakage acoustic emission signals - Google Patents
Simulating device and simulating method for pipeline leakage acoustic emission signals Download PDFInfo
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Abstract
The invention relates to a simulating device and a simulating method for pipeline leakage acoustic emission signals, and belongs to the technical field of acoustic emission inspection. One end of a pipeline is sealed, and the other end of the pipeline is connected with the pressurized air charging device. A leakage hole capable of adjusting air leakage quantity is formed in the surface of the pipeline. A waveguide rod with a sensor is mounted on the surface of the pipeline and is away from the air leakage hole by certain distance. One end of the waveguide rod is connected with an acoustic emitter. Leakage acoustic emission signals detected by the simulating device are decomposed by an HHT and then subjected to BP network training to acquire classification results, so that simulation of the pipeline leakage acoustic emission signals is realized. By the simulation method and the simulation device, organization structure and operation mechanism of human brains are simulated in terms of microstructure and function, so that nonlinear systems and uncertain systems can be described well.
Description
Technical field
The simulator and the method that the present invention relates to a kind of pipe leakage acoustic emission signal, belong to acoustic emission testing technology field.
Background technique
Along with the fast development of national economy, industrial exhaust heat boiler more and more appears in industrial production, brings people and greatly facilitates; Meanwhile, because industrial exhaust heat boiler is extremely to work under rugged environment, pipeline very easily leaks, and has a strong impact on safe, reliable, stable, the economic operation of manufacturing mechanism.Traditional monitoring method hysteresis is very large, can not accomplish Real-Time Monitoring, more and more can not adapt to modern production demand, in the urgent need to utilizing the means of science accurately to monitor the application technology of the early stage leakage of pipeline.
At present, the method for real-time that China mainly adopts is acoustic monitoring technology, and the method is on boiler tubing, to open air-borne sound to propagate hole, welds air-borne sound waveguide and air borne sensor is installed on hole, also has soot blower.Although the method has realized on-line monitoring, solved to a certain extent the technical problem of additive method, but the sensitivity, validity, reliability of monitoring and easy to use on still exist some problems, especially acoustic noise during boiler operatiopn with leak the acoustic noise frequency producing and approach, only in the situation that leakage is stronger, just can detect, and be wherein mingled with many undesired signals, the leakage signal producing with source of leaks superposes mutually, this can bring very large difficulty to the processing of follow-up signal, often can not reach desirable effect.
Summary of the invention
In view of above conventional pipelines Leak testtion and signal are processed the problem facing, the present invention proposes a kind of simulator and method of pipe leakage acoustic emission signal, the one, proposed a kind ofly based on solid coupled wave guide rod diagnostic tube, to say transmit leakage technology, build the auxiliary acoustic emission testing pipe leakage experiment porch of waveguide rod; The 2nd, the energy after HHT processes is proposed using acoustic emission signal as characteristic vector input neural network classifier diagnosis pipe leakage, show that accurate analysis result verifies the feasibility of said method.
The structure of simulator of the present invention is: the inflator that one end sealing of pipeline, the other end connect pressurization, there is the Leak hole of adjustable air leakage on the surface of pipeline, on pipeline, with leak holes certain distance, the waveguide rod with sensor is installed, one end of waveguide rod is connected with Acoustic radiating instrument.
Described inflating device is the gas tank of being controlled by air compressor.
Described pipeline is provided with pressure gauge detected pressures.
Described Leak hole is provided with the screw with leakage hole, and screw is controlled the size of air leakage by needle type valve adjustment aperture.
Described waveguide rod be according to installing apart from the distance of Leak hole 1000～6500mm.For example, apart from Leak hole 1000,3000,4500,5500, the waveguide rod of the position of 6500mm welding equal-specification.Distance between Fig. 1 middle tube body and wall column does not have clear and definite restriction (as long as while testing, wall is not encountered in body vibrations), and this is for not impact of experimental result.
The analogy method of simulator of the present invention is: (as shown in Fig. 2～3)
(1), to the air that is filled with pressurization in pipeline, by Leak hole adjutage internal pressure, the Acoustic radiating instrument filtering then connecting by each waveguide rod exceeds reveals the high-frequency noise that signal frequency domain occurs, and obtains revealing acoustic emission signal;
(2) by reveal acoustic emission signal with HHT by its decomposition and extract the signal characteristic that in decomposition layer, each frequency layer is divided
, then and obtain the total energy of each node signal:
, construct characteristic vector
;
(3) characteristic vector is inputted to BP network training, obtained classification results, realize the simulation of pipe leakage acoustic emission signal.
The pressure range of described inner air tube is 0.1～3MPa.
Described exceed the high-frequency noise that signal frequency domain reveal to occur refer to flow through undesired signal outside the high-frequency signal of removing regulation sensor send sound.Noise, refers to the energy field that undesired signal is propagated, and scope is 20HZ～2000KHZ, more than common 5000 HZ is called high-frequency noise.
The auxiliary acoustic emission testing pipe leakage experimental setup of waveguide rod and method that the present invention builds, compare with the treatment technology of classical signal, its advantage is: (1) measured leakage signal is not transmitted by air-borne sound coupled modes, but transmit by solid coupled modes.So not only structure is simpler, and installation is also more convenient, and mounting point is more flexible, does not also need corresponding soot blower; (2) what on pipeline, install is not Air Coupling waveguide rod and air-borne sound sensor, but solid coupled wave guide rod and ultrasonic wave sensor.Because solid coupling ratio Air Coupling has better signal propagation characteristics, less decay, the acoustic noise of hyperacoustic signal frequency during also higher than boiler operatiopn, therefore ultrasonic method has higher sensitivity, larger signal cover, more trustworthy leakage monitoring reliability; (3) can only analysing low frequency signal with respect to traditional Fourier's analysis method, HHT can decompose signal one by one from high frequency to low frequency, and each component is done to Hilbert conversion, determines its instantaneous frequency and instantaneous amplitude.The method can accurately effectively be extracted characteristic parameter, for follow-up classification, processes and lays the first stone.(4) with respect to traditional classifier, need to provide in advance Heuristics and the discriminant function of relevant pattern, neuron network can form needed decision region automatically by the study mechanism of self, make full use of status information and train one by one and obtain certain mapping relations and carry out adaptive adjustment, there is the features such as parallel computation, distributed information storage, self adaption and learning ability are strong.
Accompanying drawing explanation
Fig. 1 is apparatus of the present invention structural representations;
Fig. 2 is the inventive method flow chart;
Fig. 3 is BP neuron network simulation schematic diagram of the present invention.
Embodiment
Below in conjunction with embodiment, the invention will be further described.
Mode of execution one: as shown in Figures 1 to 3, the simulator of the pipe leakage acoustic emission signal of present embodiment is: the inflator that one end sealing of pipeline, the other end connect pressurization, there is the Leak hole of adjustable air leakage on the surface of pipeline, with leak holes different distance, the waveguide rod with sensor is installed, one end of waveguide rod is connected with Acoustic radiating instrument.Inflating device is the gas tank of being controlled by air compressor.Pipeline is provided with pressure gauge detected pressures.Leak hole is provided with the screw with leakage hole, and screw is controlled the size of air leakage by needle type valve adjustment aperture.
5 waveguide rod are welded on the bearing pipe of experiment use, have set up acoustic emission detection system.At Leak hole place, according to experimentation, open successively φ 1, φ 2, and φ 3, and φ 4, the Leak hole of φ 5mm, apart from Leak hole 1000,3000,4500,5500, the waveguide rod of position welding φ 12 * 1000mm equal-specification of 6500mm, and the wide-band sound-emission sensor that is respectively coupled on waveguide rod top, respectively install a wide-band sound-emission sensor in the bottom of Leak hole place and each waveguide rod.At each, leak under the condition of aperture and change internal pipe pressure, from 0.15MPa, change to 0.4MPa, increase 0.05MPa pressure at every turn, pressure of every change, gathers one group and leaks acoustic emission data.By bearing pipe being revealed to the acoustic emission on-line monitoring of process, we can be by the size of control valve and Leak hole radius, obtain at different pressures, different leak aperture and apart from Leak hole different distance in the situation that, the original filtering of the received signal of calibrate AE sensor in waveguide rod.By changing the size of d, control the size of leak holes, the Leak hole of simulating different sizes obtains the information of signal.
Concrete grammar is: (1) finds out all Local Extremum of signal, comprises local maximum and local minimum.All maximum points are become to a curve by Cubic Spline Functions Fitting, just form
coenvelope line; Equally, all minimum points are become to a curve by Cubic Spline Functions Fitting,
lower envelope line.Upper and lower envelope should comprise all data-signals.The mean value of obtaining upper and lower envelope, is denoted as
, and obtain a new data sequence
, that is:
if,
meet two conditions of IMF, claim
for
first IMF component.(2) in general,
not necessarily can meet the requirement of IMF, now just need to do further screening.?
as initial data, repeating step (1), obtains the mean value of upper and lower envelope
, and a new data sequence
, then judge
whether meet the condition of IMF.If do not met, continue circulation k time, until average envelope trends towards zero, obtain
, make
meet the condition of IMF.Note
,
it is exactly signal
meet first component of IMF.(3) will
from
in separate, obtain a new data sequence of removing radio-frequency component
,
, will
as initial data, repeat (1), (2) step, and then obtain
second component that meets IMF condition
.N above-mentioned mode decomposition process of repetitive cycling, obtains signal again
n meet the component of IMF condition
:
, when
or
be less than predictive error, or
become a monotonic function, in the time of can not therefrom extracting the component that meets IMF condition again, just stop mode decomposition process.So far just obtain sequence can be decomposed into IMF component and remainder and:
, wherein
be called remaining function, the average tendency of representation signal.
For BP neuron network, any continuous function in closed interval can approach with single hidden layer BP network, so we adopt the BP neuron network of 3-tier architecture.Get front 4 EMD decomposed components, be IMF (Intrinsic Mode Function, Intrinsic mode function) characteristic vector of component is as input quantity, therefore input layer has 4 input units, six kinds of corresponding disturbance types are as output vector, output layer is 6 unit, for choosing of hidden layer neuron number, if neuron very little, network can not well be learnt, need training often, training precision is not high, if neuron number is too much, the amount of calculation that will carry out in cyclic process each time also can increase thereupon, training time not necessarily reduces thereupon, therefore, we select 10 of the neuron numerical digits of hidden layer.Hidden layer and output layer transfer function are selected respectively S type tan (tansig) and S type logarithmic function (logsig), and learning function is selected trainlm.After determining the initial weight and threshold value of BP network optimum, BP network training is energy Fast Convergent just, can meet the training requirement to target, obtains the pipe leakage acoustic emission signal of simulation.
Below by reference to the accompanying drawings the specific embodiment of the present invention is explained in detail, but the present invention is not limited to above-mentioned mode of execution, in the ken possessing those of ordinary skills, can also under the prerequisite that does not depart from aim of the present invention, make various variations.
Claims (8)
1. the simulator of a pipe leakage acoustic emission signal, it is characterized in that structure is: the inflator that one end sealing of pipeline, the other end connect pressurization, there is the Leak hole of adjustable air leakage on the surface of pipeline, on pipeline, with leak holes certain distance, the waveguide rod with sensor is installed, one end of waveguide rod is connected with Acoustic radiating instrument.
2. the simulator of pipe leakage acoustic emission signal according to claim 1, is characterized in that: described inflating device is the gas tank of being controlled by air compressor.
3. the simulator of pipe leakage acoustic emission signal according to claim 1, is characterized in that: described pipeline is provided with pressure gauge detected pressures.
4. the simulator of pipe leakage acoustic emission signal according to claim 1, is characterized in that: described Leak hole is provided with the screw with leakage hole, and screw is controlled the size of air leakage by needle type valve adjustment aperture.
5. the simulator of pipe leakage acoustic emission signal according to claim 1, is characterized in that: the distance that described waveguide rod and leak holes are installed is 1000～6500mm.
6. an analogy method for pipe leakage acoustic emission signal, is characterized in that concrete steps comprise:
(1), to the air that is filled with pressurization in pipeline, by Leak hole adjutage internal pressure, the Acoustic radiating instrument filtering then connecting by each waveguide rod exceeds reveals the high-frequency noise that signal frequency domain occurs, and obtains revealing acoustic emission signal;
(2) by reveal acoustic emission signal with HHT by its decomposition and extract the signal characteristic that in decomposition layer, each frequency layer is divided
, then and obtain the total energy of each node signal:
, construct characteristic vector
;
(3) characteristic vector is inputted to BP network training, obtained classification results, realize the simulation of pipe leakage acoustic emission signal.
7. the analogy method of pipe leakage acoustic emission signal according to claim 6, is characterized in that: the pressure range of described inner air tube is 0.1～3MPa.
8. the analogy method of pipe leakage acoustic emission signal according to claim 6, is characterized in that: described in exceed and reveal the high-frequency noise that signal frequency domain occurs and refer to the sound of flowing through undesired signal outside the high-frequency signal of removing regulation sensor sending.
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Cited By (11)
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|---|---|---|---|---|
| CN104035434A (en) * | 2014-06-13 | 2014-09-10 | 武汉理工大学 | Air leakage monitoring system for diesel engine air valve |
| CN104776941A (en) * | 2015-01-09 | 2015-07-15 | 济南智轩智能科技有限公司 | Adaptive amplification system for echo signal of ultrasonic heat meter |
| CN105042341A (en) * | 2015-07-31 | 2015-11-11 | 中国石油大学(华东) | Multilayer buried pipeline leakage source locating device and method based on acoustic emission inspection |
| CN105864643A (en) * | 2016-03-24 | 2016-08-17 | 华北电力大学 | Gas pipeline leakage positioning experimental device and method based on RBF neural network |
| CN104500981B (en) * | 2014-10-20 | 2017-02-15 | 成都创源油气技术开发有限公司 | Natural gas pipe detecting tool |
| CN106764451A (en) * | 2016-12-08 | 2017-05-31 | 重庆科技学院 | The modeling method of gas pipeline tiny leakage is detected based on sound wave signals |
| CN106855494A (en) * | 2015-12-08 | 2017-06-16 | 中国石油化工股份有限公司 | A kind of storage tank bottom plate acoustic emission detection system |
| CN111076097A (en) * | 2019-10-09 | 2020-04-28 | 中国核电工程有限公司 | Method and device for extracting effective signal from pipeline leakage acoustic emission signal |
| CN113960176A (en) * | 2021-10-20 | 2022-01-21 | 应急管理部上海消防研究所 | Non-contact acoustic emission detection method for fire scene building structure safety state |
| CN115655887A (en) * | 2022-11-01 | 2023-01-31 | 广东建设职业技术学院 | Concrete strength prediction method |
| CN115949891A (en) * | 2023-03-09 | 2023-04-11 | 天津佰焰科技股份有限公司 | Intelligent control system and control method for LNG (liquefied Natural gas) filling station |
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Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104035434A (en) * | 2014-06-13 | 2014-09-10 | 武汉理工大学 | Air leakage monitoring system for diesel engine air valve |
| CN104500981B (en) * | 2014-10-20 | 2017-02-15 | 成都创源油气技术开发有限公司 | Natural gas pipe detecting tool |
| CN104776941A (en) * | 2015-01-09 | 2015-07-15 | 济南智轩智能科技有限公司 | Adaptive amplification system for echo signal of ultrasonic heat meter |
| CN105042341A (en) * | 2015-07-31 | 2015-11-11 | 中国石油大学(华东) | Multilayer buried pipeline leakage source locating device and method based on acoustic emission inspection |
| CN106855494A (en) * | 2015-12-08 | 2017-06-16 | 中国石油化工股份有限公司 | A kind of storage tank bottom plate acoustic emission detection system |
| CN106855494B (en) * | 2015-12-08 | 2020-03-17 | 中国石油化工股份有限公司 | Acoustic emission detection device for storage tank bottom plate |
| CN105864643A (en) * | 2016-03-24 | 2016-08-17 | 华北电力大学 | Gas pipeline leakage positioning experimental device and method based on RBF neural network |
| CN106764451B (en) * | 2016-12-08 | 2018-10-12 | 重庆科技学院 | The modeling method of gas pipeline tiny leakage is detected based on sound wave signals |
| CN106764451A (en) * | 2016-12-08 | 2017-05-31 | 重庆科技学院 | The modeling method of gas pipeline tiny leakage is detected based on sound wave signals |
| CN111076097A (en) * | 2019-10-09 | 2020-04-28 | 中国核电工程有限公司 | Method and device for extracting effective signal from pipeline leakage acoustic emission signal |
| CN111076097B (en) * | 2019-10-09 | 2022-10-21 | 中国核电工程有限公司 | Method and device for extracting effective signal from pipeline leakage acoustic emission signal |
| CN113960176A (en) * | 2021-10-20 | 2022-01-21 | 应急管理部上海消防研究所 | Non-contact acoustic emission detection method for fire scene building structure safety state |
| CN115655887A (en) * | 2022-11-01 | 2023-01-31 | 广东建设职业技术学院 | Concrete strength prediction method |
| CN115655887B (en) * | 2022-11-01 | 2023-04-21 | 广东建设职业技术学院 | Concrete strength prediction method |
| CN115949891A (en) * | 2023-03-09 | 2023-04-11 | 天津佰焰科技股份有限公司 | Intelligent control system and control method for LNG (liquefied Natural gas) filling station |
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