CN113792360A - Industrial pipeline twin health monitoring method and system based on simulation technology - Google Patents
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Abstract
A method and a system for monitoring the twin health of an industrial pipeline based on a simulation technology are disclosed, wherein the monitoring method comprises the following steps: acquiring actual load data of a pipeline in a working state at a key position of the pipeline through a sensor; classifying and storing data acquired by the sensor according to the sensor interface; loading data acquired by a sensor to a CAE simulation model, carrying out loading calculation on the CAE simulation model through real test data to obtain a finite element simulation result, and obtaining multi-physical field information of any position of a pipe network by using the finite element simulation result; storing the multi-physical field information of any position of the pipe network and displaying the data in a visual form; and analyzing according to the finite element simulation result to obtain the health state of the pipeline, and intelligently alarming according to the health state of the pipeline. The invention can realize the inspection of the whole pipe network, save the labor cost, ensure the authenticity of the monitoring effect and realize the accurate prediction of the damaged part.
Description
Technical Field
The invention belongs to the technical field of industrial pipeline health detection, and particularly relates to a method and a system for monitoring twin health of an industrial pipeline based on a simulation technology.
Background
Industrial pipelines play an important role in miners, especially chemical energy enterprises, but due to the particularity of the industrial pipelines, the pipelines are easily affected by the external environment, the operating quality of the pressure pipelines is affected by damage, even accidents are seriously caused, and irreparable loss is caused.
At present, processes such as flange connection, groove pipeline connection and welding are mostly adopted for assembly in the aspect of safe operation of industrial pipelines at home and abroad, the pipelines are mostly made of steel, ceramics, PVC, various engineering plastics and the like, sealing materials are mostly sealed by rubber and various synthetic rubbers, and in the practical application of the pipelines, due to pressure, pulse, vibration, negative pressure, vacuum, rapid deformation and numerous reasons of unqualified materials, leakage, damage and abrasion are caused, various phenomena such as pressure cannot be kept, and huge loss is caused to industrial production.
As an emerging research field, the development time of the industrial pipeline health detection technology is short, a plurality of application technologies are not mature at present, a plurality of detection methods have different degrees of limitations, and a plurality of problems are to be solved. Present solution selects for use the manual work mostly to patrol and examine, modes such as supersound and flaw detector carry out selective examination and local inspection, solves through the mode of periodic replacement, and there are a large amount of wrong reports in current mode, the emergence of lou examining the phenomenon, however in case the pipeline breaks down, will bring huge hidden danger such as personnel's security threat, industrial cost increase.
Disclosure of Invention
The invention aims to solve the problems in the prior art, and provides an industrial pipeline twin health monitoring method and system based on a simulation technology, which can realize the inspection of a whole pipe network, wherein the inspection data are pipeline full-operation period data and predictive data, can save labor cost, ensure the authenticity of an effect, and realize accurate prediction of a damaged part.
In order to achieve the purpose, the invention has the following technical scheme:
in a first aspect, an embodiment of the present invention provides a simulation technology-based industrial pipeline twin health monitoring method, including the following steps:
acquiring actual load data of a pipeline in a working state at a key position of the pipeline through a sensor;
classifying and storing data acquired by the sensor according to the sensor interface;
loading data acquired by a sensor to a CAE simulation model, carrying out loading calculation on the CAE simulation model through real test data to obtain a finite element simulation result, and obtaining multi-physical field information of any position of a pipe network by using the finite element simulation result;
storing the multi-physical field information of any position of the pipe network and displaying the data in a visual form;
and analyzing according to the finite element simulation result to obtain the health state of the pipeline, and intelligently alarming according to the health state of the pipeline.
As a preferable scheme of the monitoring method, the pipeline key positions comprise pipeline joints, the middle part of a long straight pipeline and pipeline elbow positions.
In a preferred embodiment of the monitoring method of the present invention, the sensors include an acceleration sensor and a strain sensor, the velocity sensor is used for measuring dynamic acceleration caused by fluid movement or impact inside the pipe, and the strain sensor is used for measuring the strain magnitude of the pipe.
As a preferred scheme of the monitoring method, the acceleration sensor selects an ultra-low power consumption 3-axis accelerometer with the model number of ADXL345, the resolution of 13 bits is realized, the measurement range is +/-16 g, the output data is in a 16-bit binary complement format, and the accelerometer is accessed through a 3-line or 4-line SPI or an I2C digital interface;
the model of the strain sensor is Columbia DT 3625.
As a preferred scheme of the monitoring method of the present invention, data acquired by the sensor is classified and stored according to the sensor interface by the ADAS3022 data acquisition system.
As a preferred scheme of the monitoring method, the CAE simulation model discretizes a geometric model of the pipeline, boundary layer grids are adopted on the pipe wall, and the grids in the long straight section of the pipeline are uniform in size.
As a preferred embodiment of the monitoring method of the present invention, the displaying the data in a visual form includes displaying the data through a virtual meter, a virtual curve and a key value.
As a preferred scheme of the monitoring method of the present invention, the specific value of the health state of the pipeline is obtained by analyzing according to the finite element simulation result: and (3) carrying out big data analysis on the data collected by the sensor and the finite element simulation result, evaluating whether the pipeline is abnormal in pressure, vibration, pulse, negative pressure, air bubble and blockage, and giving an alarm if the pipeline is abnormal in pressure, vibration, pulse, negative pressure and blockage.
In a second aspect, an embodiment of the present invention provides an industrial pipeline twin health monitoring system based on a simulation technology, including:
the pipeline load data acquisition module is used for acquiring load data actually received by the pipeline in a working state at a key position of the pipeline through a sensor;
the data classification storage module is used for classifying and storing the data acquired by the sensor according to the sensor interface;
the CAE simulation model analysis module is used for loading the data acquired by the sensor to the CAE simulation model, carrying out loading calculation on the CAE simulation model through real test data to obtain a finite element simulation result, and obtaining multi-physical field information of any position of the pipe network by using the finite element simulation result;
the data visualization module is used for storing the multi-physical field information of any position of the pipe network and displaying the data in a visualization form;
and the pipeline health state analysis and alarm module is used for obtaining the health state of the pipeline according to the finite element simulation result and intelligently alarming according to the health state of the pipeline.
Compared with the prior art, the invention has the following beneficial effects:
the method comprises the steps of loading data acquired by a sensor on a CAE simulation model, carrying out loading calculation on the CAE simulation model through real test data to obtain a finite element simulation result, and obtaining multi-physical field information of any position of a pipe network by using the finite element simulation result.
Secondly, the detection data of the position is detected to realize digital data, the real world operation data is completely digitalized and truly reflected, a physical field is established, and a computer mirror image is formed. The invention uses the detected vibration and strain data as the input of finite element simulation model to obtain real time finite element simulation result and form the virtual model on the computer.
And thirdly, the invention monitors along with the operation of the whole pipeline system, analyzes the fatigue life of the pipeline by a finite element simulation algorithm and predicts whether the structure is damaged or not. The invention checks the data into full operation period data and predictive data, thereby forming the life period management of the product.
Fourthly, the invention can completely reduce the labor cost and ensure the authenticity of the monitoring effect, and particularly can truly feed back the data acquired by the sensor under the condition that the transportation medium on the inner wall of the pipeline is very complex.
Fifth, according to the invention, the early warning of the damage position of any high-pressure conveying pipeline in normal operation and under the conditions of sudden leakage, negative pressure, vibration, pulse and the like and the change condition of other positions of the pipeline caused by accidents can be obtained through simulation calculation on the outer wall of the pipeline.
And sixthly, manual calculation is not needed, one-time cost investment is achieved, the alarm is given immediately after the monitoring data of the sensor exceeds a normal numerical range, the predictive safety problem is found, and unplanned shutdown and production halt are not caused. The safety stock is ensured, and planned overall operation is formed.
And seventhly, the fatigue life of the model can be calculated based on a finite element analysis method, and the platform alarms to provide replacement or maintenance suggestions when the equipment is about to reach the service life. Therefore, the method and the device can accurately predict the damaged part to carry out the purposeful preparation of the stock in advance, and achieve accurate maintenance.
Drawings
FIG. 1 is a flow chart of an industrial pipeline twin health monitoring method based on a simulation technology according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an internal circuit structure of an ADAS3022 data acquisition system according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an external connection circuit of an ADAS3022 data collection system according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a simulation process of a CAE simulation model on a certain pipeline in the embodiment of the present invention:
(a) a pipeline geometric model schematic diagram; (b) a schematic diagram of a discretized CAE simulation model;
FIG. 5 is a schematic diagram of a multi-physical field at a location in a pipe network according to an embodiment of the present invention;
FIG. 6 is a schematic view of a virtual instrument interface for visually presenting data in accordance with an embodiment of the present invention;
FIG. 7 is a schematic view of a virtual curve interface for visually presenting data according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of a comprehensive interface for visually presenting data according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
In recent years, with the continuous development of sensor technology and signal detection technology, more and more intelligent pipeline health monitoring technology is applied. The current prior art has mainly two technical directions:
firstly, a portable high-precision detection device is utilized to intelligently analyze a detection signal and directly feed back the detection result and a use suggestion to a technician. The technical scheme mainly focuses on continuously optimizing software and hardware of the detection equipment and reducing dependence of enterprises on technical experience of personnel. However, the method still needs the enterprise to be equipped with special inspection personnel, and effective control is not carried out on personnel cost.
Secondly, sensors are arranged at key positions of the pipeline, and typical signal characteristics of pipeline faults are obtained by analyzing and summarizing a large amount of data detected in the operation process of the pipeline. And in the production process, the sensor operates and detects in real time, and when the same fault characteristic signal is detected again, the pipeline is considered to be in fault, and prompt or alarm is generated. The method effectively reduces the personnel cost, but only can acquire the position information measured by the sensors, the fault diagnosis precision depends on the number of the arranged sensors, and the misdiagnosis rate is higher when fewer sensors are arranged. Placing more sensors increases system cost.
The invention aims at solving the problems that the existing detection means of the industrial pipeline is basically performed by modes of manual inspection, ultrasonic inspection, flaw detector and the like for spot inspection and local inspection and periodic replacement, and the defects of the existing mode mainly comprise:
(1) the inspection position can only be inspected locally, and the inspection of the whole pipeline cannot be realized.
(2) The detection data are analog data, digital data cannot be realized, the accuracy is not enough, and the judgment basis is lacked.
(3) The inspection data is current data, periodic data of operation cannot be predicted, and predictive data.
(4) The labor cost is extremely high and the authenticity cannot be guaranteed, especially under the condition that the transportation medium on the inner wall of the pipeline is very complicated.
(5) The inner wall of the pipeline cannot detect the change of other positions except the damage position of the high-pressure transportation pipeline under the conditions of sudden leakage, negative pressure, vibration, pulse and the like.
(6) The method has the advantages of complex calculation in a manual mode, high cost, slow response and solution period, immediate problem occurrence when problems are found, great possibility of loss and huge loss caused by unplanned shutdown and production halt.
(7) The cost of overall replacement and maintenance is high, the damage part cannot be accurately predicted, the purpose of advance inventory preparation is achieved, and accurate maintenance cannot be achieved.
As shown in FIG. 1, the industrial pipeline twin health monitoring method based on the simulation technology comprises the following steps:
acquiring actual load data of a pipeline in a working state at a key position of the pipeline through a sensor;
classifying and storing data acquired by the sensor according to the sensor interface;
loading data acquired by a sensor to a CAE simulation model, carrying out loading calculation on the CAE simulation model through real test data to obtain a finite element simulation result, and obtaining multi-physical field information of any position of a pipe network by using the finite element simulation result;
storing the multi-physical field information of any position of the pipe network and displaying the data in a visual form;
and analyzing according to the finite element simulation result to obtain the health state of the pipeline, and intelligently alarming according to the health state of the pipeline.
In this embodiment, the purpose of installing the sensor is to monitor the actual load on the pipeline in the operating state, and provide data support for the calculation of the simulation model. The distribution positions of the sensors are distributed according to actual conditions by selecting key positions such as pipeline joints, elbows and the like, and the common installation positions are the outer wall of the pipeline flange joint, the outer wall of the long straight pipeline and the outer wall of the elbow respectively.
The sensors comprise an acceleration sensor and a strain sensor, in the embodiment, the acceleration sensor is an ADXL345 ultra-low power consumption 3-axis accelerometer, the resolution is high (13 bits), and the measurement range reaches +/-16 g. The digital output data is in 16-bit two's complement format and is accessible through SPI (3-or 4-wire) or I2C digital interfaces. Dynamic acceleration due to motion or shock can be measured. Its high resolution (3.9mg/LSB) can measure the inclination angle change of less than 1.0 deg.. The strain sensor is selected from Columbia DT3625, and the sensor meets the measurement accuracy of industrial pipe network strain, is firm and is easy to install.
In the embodiment, an ADAS3022 data acquisition system is used to store the acquired data according to the sensor classification, and the ADAS3022 data acquisition system integrates an 8-channel, low-leakage multiplexer; high impedance PGIA; a high-precision low-drift 4.096V reference voltage source and a buffer; 16-bit successive approximation ADC. The internal circuit diagram is shown in fig. 2.
The sensor data acquisition solution occupies a small circuit board space, which is conducive to reducing the size of an industrial data acquisition system. Buffering, level conversion, amplification, attenuation or other conditioning of input signals are not needed, the influence on common mode rejection, noise and establishment time is eliminated, and a plurality of problems related to designing a high-precision 16-bit data acquisition system are solved. The rated temperature range of the device is-40 ℃ to +85 ℃ industrial temperature range, and the device meets the application condition of an industrial pipe network.
The adopted 8-channel data acquisition scheme is shown in fig. 3, and the external connection circuit of the ADAS3022 data acquisition system facilitates calling in the subsequent use process by classifying and storing the acquired data according to the sensor interface.
Referring to (a) and (b) in fig. 4, a CAE simulation model needs to be established according to a pipeline real object. Comparing the pipeline geometric model with the discretized CAE simulation model, boundary layer grids are applied to the pipe wall, and the grids in the long straight section of the pipeline are uniform in size.
And carrying out loading calculation on the simulation model according to the real test data to obtain a simulation result. The obtained result is not limited by the arrangement position of the sensor, and the finite element simulation result can obtain multi-physical field information of any position, as shown in fig. 5.
In this embodiment, the displaying the data in the visualization form includes displaying the data through a virtual meter, a virtual curve and a key value. The virtual instrument interface, the virtual curve interface and the comprehensive interface of the embodiment are respectively shown in fig. 6, fig. 7 and fig. 8.
The comprehensive interface comprises sensor test data display and CAE simulation calculation data display, and the running state of the pipeline and the calculation result of the pipeline multi-physical field can be visually displayed through the display of a virtual instrument, a virtual curve and a key numerical value.
According to the embodiment, the data acquired by the sensor and the mass data obtained by simulation calculation are finally relied on to perform big data analysis, whether the pipeline has faults such as abnormal pressure, abnormal vibration, abnormal pulse, abnormal negative pressure, abnormal bubble, abnormal blockage and the like is evaluated, if dangerous damage occurs, the platform can give an alarm in time, and the safe production of the pipeline and workers is ensured.
Another embodiment of the present invention further provides a simulation technology-based industrial pipeline twin health monitoring system, including:
the pipeline load data acquisition module is used for acquiring load data actually received by the pipeline in a working state at a key position of the pipeline through a sensor;
the data classification storage module is used for classifying and storing the data acquired by the sensor according to the sensor interface;
the CAE simulation model analysis module is used for loading the data acquired by the sensor to the CAE simulation model, carrying out loading calculation on the CAE simulation model through real test data to obtain a finite element simulation result, and obtaining multi-physical field information of any position of the pipe network by using the finite element simulation result;
the data visualization module is used for storing the multi-physical field information of any position of the pipe network and displaying the data in a visualization form;
and the pipeline health state analysis and alarm module is used for obtaining the health state of the pipeline according to the finite element simulation result and intelligently alarming according to the health state of the pipeline.
The industrial pipeline twin health monitoring method and system based on the simulation technology have the following advantages that:
(1) the multichannel data high-speed acquisition of pipeline data is realized through an ADAS3022 data acquisition system;
(2) after the monitoring data are extracted, directly loading and calculating in a CAE model divided with grids, and realizing the mapping connection of the data from the pipeline physical world to the pipeline virtual world;
(3) the intelligent platform realizes the visual display of the monitoring data and the twin data;
(4) the monitoring data and the simulation data jointly form a pipeline full-life-cycle database, so that the health assessment and the digital monitoring operation of a pipeline system are realized, an intelligent alarm is given at any time if a problem exists, and the operation and maintenance cost of personnel is reduced.
(5) The system integrally realizes platform monitoring, and is convenient for a supervision department to detect and predict safety data of the production process.
The above-mentioned embodiments are only preferred embodiments of the present invention, and are not intended to limit the technical solution of the present invention, and it should be understood by those skilled in the art that the technical solution can be modified and replaced by a plurality of simple modifications and replacements without departing from the spirit and principle of the present invention, and the modifications and replacements also fall into the protection scope covered by the claims.
Claims (9)
1. A twin health monitoring method for an industrial pipeline based on a simulation technology is characterized by comprising the following steps:
acquiring actual load data of a pipeline in a working state at a key position of the pipeline through a sensor;
classifying and storing data acquired by the sensor according to the sensor interface;
loading data acquired by a sensor to a CAE simulation model, carrying out loading calculation on the CAE simulation model through real test data to obtain a finite element simulation result, and obtaining multi-physical field information of any position of a pipe network by using the finite element simulation result;
storing the multi-physical field information of any position of the pipe network and displaying the data in a visual form;
and analyzing according to the finite element simulation result to obtain the health state of the pipeline, and intelligently alarming according to the health state of the pipeline.
2. The industrial pipeline twin health monitoring method based on the simulation technology as claimed in claim 1, wherein: the key positions of the pipeline comprise a pipeline connecting part, the middle part of the long straight pipeline and a pipeline elbow position.
3. The industrial pipeline twin health monitoring method based on the simulation technology as claimed in claim 1, wherein: the sensors comprise an acceleration sensor and a strain sensor, the speed sensor is used for measuring dynamic acceleration caused by fluid movement or impact in the pipeline, and the strain sensor is used for measuring the strain of the pipeline.
4. The industrial pipeline twin health monitoring method based on the simulation technology as claimed in claim 3, wherein: the acceleration sensor selects an ultra-low power consumption 3-axis accelerometer with the model of ADXL345, the resolution of 13 bits is realized, the measurement range is +/-16 g, the output data is in a 16-bit binary complement format, and the data is accessed through a 3-line or 4-line SPI or an I2C digital interface;
the model of the strain sensor is Columbia DT 3625.
5. The industrial pipeline twin health monitoring method based on the simulation technology as claimed in claim 1, wherein: and classifying and storing the data acquired by the sensor according to the sensor interface through the ADAS3022 data acquisition system.
6. The industrial pipeline twin health monitoring method based on the simulation technology as claimed in claim 1, wherein: the CAE simulation model discretizes a geometric model of the pipeline, boundary layer grids are adopted on the pipeline wall, and the grids in the long straight section of the pipeline are uniform in size.
7. The industrial pipeline twin health monitoring method based on the simulation technology as claimed in claim 1, wherein: the displaying the data in the visual form comprises displaying through a virtual instrument, a virtual curve and a key numerical value.
8. The industrial pipeline twinning health monitoring method based on the simulation technology as claimed in claim 1, wherein the specific health state value of the pipeline is obtained by analyzing according to the finite element simulation result: and (3) carrying out big data analysis on the data collected by the sensor and the finite element simulation result, evaluating whether the pipeline is abnormal in pressure, vibration, pulse, negative pressure, air bubble and blockage, and giving an alarm if the pipeline is abnormal in pressure, vibration, pulse, negative pressure and blockage.
9. An industrial pipeline twin health monitoring system based on simulation technology is characterized by comprising:
the pipeline load data acquisition module is used for acquiring load data actually received by the pipeline in a working state at a key position of the pipeline through a sensor;
the data classification storage module is used for classifying and storing the data acquired by the sensor according to the sensor interface;
the CAE simulation model analysis module is used for loading the data acquired by the sensor to the CAE simulation model, carrying out loading calculation on the CAE simulation model through real test data to obtain a finite element simulation result, and obtaining multi-physical field information of any position of the pipe network by using the finite element simulation result;
the data visualization module is used for storing the multi-physical field information of any position of the pipe network and displaying the data in a visualization form;
and the pipeline health state analysis and alarm module is used for obtaining the health state of the pipeline according to the finite element simulation result and intelligently alarming according to the health state of the pipeline.
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| CN110025318A (en) * | 2018-01-11 | 2019-07-19 | 南京理工大学 | A kind of tumble real-time detecting system and method based on acceleration transducer |
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Application publication date: 20211214 |