CN111332130A - Digital twinning technology-based debugging method for suspension system of magnetic-levitation train - Google Patents
Digital twinning technology-based debugging method for suspension system of magnetic-levitation train Download PDFInfo
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- CN111332130A CN111332130A CN202010119806.8A CN202010119806A CN111332130A CN 111332130 A CN111332130 A CN 111332130A CN 202010119806 A CN202010119806 A CN 202010119806A CN 111332130 A CN111332130 A CN 111332130A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L13/00—Electric propulsion for monorail vehicles, suspension vehicles or rack railways; Magnetic suspension or levitation for vehicles
- B60L13/04—Magnetic suspension or levitation for vehicles
- B60L13/06—Means to sense or control vehicle position or attitude with respect to railway
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/16—Information or communication technologies improving the operation of electric vehicles
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Abstract
The invention relates to a digital twinning technology-based debugging method for a maglev train suspension system, which comprises the following steps of: a digital twinning construction step: constructing a digital twin body of a suspension system of a magnetic-levitation train, wherein the digital twin body is in communication connection with the suspension system of the magnetic-levitation train; suspension data acquisition and sensing: the magnetic-levitation train suspension system collects and senses suspension data through a sensor and transmits the suspension data to the digital twin body in real time; a suspension system debugging step: and observing and debugging the suspension state of the digital twin body in real time through a visualization means, so as to react on the suspension system of the magnetic-levitation train. Compared with the prior art, the method effectively verifies the effectiveness of parameter debugging when the train operation condition has obvious change, further improves the debugging accuracy based on the digital twin virtual model, improves the working environment of debugging personnel, and reduces the labor time cost and the economic cost.
Description
Technical Field
The invention relates to the field of rail transit, in particular to a debugging method of a maglev train suspension system based on a digital twinning technology.
Background
At present, the running speed of a high-speed wheel-rail train reaches 350km/h, and the wheel-rail abrasion is aggravated by accelerating again, so that the running cost is multiplied. And the magnetic suspension train ensures the non-contact operation between the train rails during the operation, and can realize higher speed at lower cost, thereby realizing short-time commuting between long-distance cities. In addition, the contact between the wheel and the rail is avoided, so that the mechanical noise in the running process is effectively reduced, which is another reason that the existing wheel-rail train cannot compare.
The stable suspension of the magnetic-levitation train is one of the most important preconditions for ensuring the normal operation of the magnetic-levitation train, and the debugging of the suspension system controller is more important. At the initial stage of debugging, the suspension performance is poor due to the self adaptability of the equipment and the matching of software such as an algorithm, parameters and the like, and preliminary parameter determination and operation debugging are required. In the running test and business operation process on the actual line, the system also needs to be continuously optimized to achieve and maintain the expected suspension stability effect in consideration of the conditions of rail irregularity, rail deflection deformation, foundation settlement, climate change and the like. The debugging of current suspension system needs to carry out the on-the-spot test of following the car, and the actual data carries out two-dimensional curve through the CAN signal and observes, but this kind of debugging method needs to spend great manpower, time and economic cost. In addition, the suspension train has a plurality of carriage marshalling, and each carriage has a plurality of suspension points, and the manual repeated observation of the two-dimensional curve of a plurality of suspension single points can not be visualized, possibly resulting in poor debugging effect, thereby prolonging the debugging time.
Disclosure of Invention
The invention aims to provide a debugging method of a maglev train suspension system based on a digital twinning technology, aiming at overcoming the defects that the prior art needs to spend larger manpower, time and economic cost.
The purpose of the invention can be realized by the following technical scheme:
a digital twin technology-based debugging method for a maglev train suspension system comprises the following steps:
a digital twinning construction step: constructing a digital twin body of a suspension system of a magnetic-levitation train, wherein the digital twin body is in communication connection with the suspension system of the magnetic-levitation train;
suspension data acquisition and sensing: the magnetic-levitation train suspension system collects and senses suspension data through a sensor and transmits the suspension data to the digital twin body in real time;
a suspension system debugging step: and observing and debugging the suspension state of the digital twin body in real time through a visualization means, so as to react on the suspension system of the magnetic-levitation train.
Further, the digital twin is in the form of a multi-body kinetic model or a multi-physical field model.
Further, the levitation data includes an acceleration value, a levitation gap value, and a control current value.
Further, the suspension gap value is obtained by integrating the acceleration value.
Furthermore, the step of debugging the levitation system further comprises the step of independently debugging each levitation point of each carriage in the levitation system of the magnetic-levitation train.
Furthermore, parallel data transmission is carried out between the digital twin body and the suspension system of the magnetic-levitation train by adopting 4G/5G or field wireless hotspot/field bus.
Further, the data transmission is carried out by adopting the Ethernet/Modbus technology.
Further, the magnetic-levitation train suspension system comprises a suspension execution component, the digital twin body is correspondingly provided with a suspension execution virtual component, and the parameters of the suspension execution virtual component are consistent with those of the suspension execution component through identification.
Further, the data transmitted by the digital twin body received by the maglev train levitation system is stored in an on-site storage device or a cloud server.
Further, the communication connection between the digital twin body and the magnetic-levitation train suspension system is carried out through virtual reality, augmented reality and mixed reality technologies.
Further, in the step of debugging the floating system, the visualization means includes, but is not limited to, report, curve, Augmented Reality (AR) and rendered video.
Furthermore, the digital twin body is also used for analyzing the acquired data after the debugging is finished, and further optimizing the performance of the suspension system of the magnetic-levitation train through a data mining technology.
Compared with the prior art, the invention has the following advantages:
(1) the invention greatly improves the working environment of the debugging personnel of the suspension system of the magnetic-levitation train by utilizing the digital twinning technology, can finish corresponding debugging work in a remote distance in a central control room under the condition of avoiding car following, greatly reduces the economic cost and the labor time cost, and promotes the intelligent process of the system.
(2) The working condition of the existing suspension system can only be observed by a two-dimensional curve graph, whether the rail is hit or not can only be judged by the curve graph and the feeling of a debugging person following the vehicle, and certain errors and contingency exist; the invention combines the digital twinning technology, can demonstrate the visual model of the suspension system in real time according to the digital twinning body, can accurately master the suspension state of the whole vehicle through operations such as local amplification or reduction, and is beneficial to the efficient development of suspension debugging.
(3) The debugging method of the suspension system of the magnetic-levitation train provided by the invention is generally applicable to high, medium and low speed magnetic-levitation trains.
Drawings
FIG. 1 is a schematic diagram of information interaction according to the present invention;
FIG. 2 is a schematic diagram of a digital twinning system in accordance with the present invention;
FIG. 3 is a schematic diagram of a basic flow of levitation debugging according to the present invention;
in the figure, 1, a carriage, 2, a secondary suspension, 3, an electromagnet, 4, a suspension bracket, 5 and a track.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
Example 1
As shown in fig. 1, the present embodiment provides a method for debugging a maglev train levitation system based on a digital twinning technology, which includes the following steps:
a digital twinning construction step: constructing a digital twin body of a suspension system of a magnetic-levitation train, wherein the digital twin body is in communication connection with the suspension system of the magnetic-levitation train;
suspension data acquisition and sensing: the magnetic-levitation train suspension system collects and senses suspension data through a sensor and transmits the suspension data to the digital twin body in real time;
a suspension system debugging step: observing and debugging the suspension state of the digital twin body, thereby reacting to the suspension system of the magnetic-levitation train.
The method is described in detail below:
1. digital twin
The digital twin body is in the form of a multi-body dynamic model or a multi-physical field model, can be constructed by adopting commercial modeling software, and can also be developed secondarily on the basis.
The digital twin body is a digital model of the whole suspension train and is not designed for suspension debugging alone, and any single component/module is allowed to be modeled in detail in a model framework.
2. Floating data
The real-time suspension data measured by the sensor comprises an acceleration value, a suspension clearance value, a control current value and the like. Further, the velocity value of the levitation gap may be obtained by integrating the acceleration value. The data and the external environment variable are sensed in real time, and the digital twin body in the virtual space is convenient to debug.
3. Suspension system debugging step
Observing and debugging the suspension state of the digital twin body, thereby reacting to the suspension system of the magnetic-levitation train. Specifically, the output quantity of the suspension system is calculated in real time and the running condition of the train is observed. And (4) performing deviation compensation according to the state of the suspension system, judging whether the suspension state is normal or not, and performing repeated debugging if the suspension state is abnormal.
In the embodiment of the invention, the suspension system and the boundary conditions thereof are subjected to necessary high-precision modeling, and the real situation of the suspension system and the debugging site is simulated. In the digital twin-based debugging process, the debugging result of the suspension system is visually displayed by further performing graphic rendering on the model.
Specifically, the running state of the actual maglev train suspension system is visually displayed in the digital twin body of the maglev train and comprehensively compared with a two-dimensional curve graph, and digital twin body control parameters of the maglev train are debugged and error-compensated according to the field suspension state. The digital twin can accurately express the dynamic behavior of the actual suspension system on site, and parameter debugging is carried out on the basis of the dynamic behavior.
Means of visual presentation include, but are not limited to, reports, curves, Augmented Reality (AR), rendered video, and the like.
The step of debugging the suspension system also comprises the step of independently debugging a plurality of suspension points of different carriages of the same train, and finally the aim of stably suspending the whole maglev train is achieved. In order to guarantee the transmission speed, parallel data transmission is carried out by adopting 4G/5G or field wireless hotspot/field bus technology including but not limited to Ethernet/Modbus technology and the like. In a typical engineering application example, five suspension frames are required for supporting suspension of a carriage together, each suspension frame has 4 suspension points, and therefore 20 suspension points need to be debugged respectively.
4. Communication connection between digital twin body and suspension system of magnetic-levitation train
The communication module of the digital twin body receives field data, and the operation of the digital twin body is utilized to realize the online interruption and debugging of the suspension system. The suspension execution component in the real working environment is replaced by a virtual component in a virtual space, and the parameters of the suspension execution component are kept consistent with those of the real part through identification and other means.
During interactive debugging of the actual physical levitation system and the virtual space digital twin body, the on-site levitation system receives input from the virtual space and records the input in on-site storage equipment or cloud servers, wherein the on-site storage equipment or cloud servers comprise a private cloud and/or a public cloud platform service space which are built on site. And information and data between the physical world and the digital world are mutually transmitted in real time through deep immersion technologies such as Virtual Reality (VR), Augmented Reality (AR) and Mixed Reality (MR).
5. Further optimization method
After the debugging is finished, the actual measurement data collected in the subsequent debugging and operation can still be analyzed in the virtual model, the actual measurement data is displayed to engineering personnel in a visual mode, the performance optimization of the suspension system is continuously carried out through a data mining technology, and parameters in the controller are updated on site or remotely.
And analyzing the collected actual measurement data, including but not limited to single-point running clearance analysis, whole vehicle dynamics analysis and the like, comprehensively evaluating the rationality and the optimization degree of the preceding parameters, and performing new remote or field debugging if necessary.
6. Concrete equipment
Hardware and software equipment used by the method comprise real magnetic-levitation train levitation control system sensing equipment, data transmission interaction equipment for realizing digital twin and a real levitation system, a virtual space controller application program, a virtual model calling program, and real magnetic-levitation train levitation control system sensing equipment acquisition signals related to virtual space digital twin; during operation of the controller application in virtual space, the digital twin enables data and parameter interaction with the real-world levitation system.
The debugging method of the magnetic-levitation train suspension system based on the digital twinning technology can be configured into different working modules: the first module is used for receiving and sensing data collected by the sensing equipment of the actual suspension control system on site; the second module is used for virtual component constraint and working environment rendering, the activity site environment is kept consistent, and the working state of the suspension system is visualized; the third module is used for calculating and determining debugging parameters by utilizing the data received and sensed by the first module and sending the debugging parameters to the field maglev train suspension system and the corresponding digital twins in real time. The dynamic matching of the field magnetic-levitation train suspension system and the corresponding digital twin body is firstly debugged through an application program.
7. Principle of principle
The debugging method of the magnetic-levitation train suspension system based on the digital twinning technology mainly comprises the following parts: 1. acquiring data of real environment sensing equipment; 2. data mapping perception of the corresponding virtual space; 3. bidirectional communication; 4. modeling and updating a virtual space digital twin model; 4. analyzing and storing historical data; 5. feedback, interaction and visualization of parameter debugging. Sensing equipment, such as a suspension gap sensor, a current sensor, an acceleration sensor and the like, which can effectively acquire actual sports car data, can be used in the debugging method; 6. the corresponding data are mapped to the virtual space for sensing and storing, a large amount of data are analyzed through the data analysis and storage module, each parameter of the model is identified on line, and the digital twin body is optimized continuously, so that the suspension state of the magnetic suspension train in the real environment can be accurately expressed, and the matching performance of the digital twin body and the suspension system of the magnetic suspension train in the real environment is improved. The storage medium can be located on site or uploaded to a cloud platform in the form of a private cloud, a public cloud, or the like. On the basis, real-time simulation of the digital twin model is carried out, real-time and effective monitoring of the suspension state based on the digital twin is guaranteed, the monitoring behavior of the conventional two-dimensional curve graph is kept, and the monitoring reliability and the debugging precision are further improved by combining the digital twin model and the monitoring behavior.
8. Potential for application
The magnetic suspension train runs in a non-contact mode, the suspension clearance is small, the suspension stability is easily reduced due to the fact that the track is not smooth and the track is deformed, particularly, the corner of the joint of the tracks at the two ends is the largest when the track is deformed, and the influence on the suspension stability is also the largest. Therefore, the continuous debugging is needed in combination with the actual situation. Digital twin bodies of the maglev train suspension system provide a convenient mode for debugging work in the embodiment, can effectively improve the working environment of debugging personnel and improve the suspension precision.
The maglev train is divided into a high-speed maglev train and a medium-low speed maglev train, and for the medium-low speed maglev train, the characteristics of low noise, small turning radius, low cost and the like can inevitably make the medium-low speed maglev train become an important component of urban rail transit, so that the medium-low speed maglev train can face high-strength and long-time dynamic passenger flow volume day after day, the working condition of the medium-low speed maglev train is changeable, and the complete description of the medium-low speed. However, the debugging personnel can only simulate the working conditions of no-load, light load, heavy load and overload by increasing or decreasing sandbags in the prior debugging process, and can not effectively debug the load change. In the example, the digital twin body can effectively simulate and simulate more real and complex load working conditions to effectively debug, the control parameters are transmitted to the suspension system of the magnetic suspension train in the real environment in real time, and the suspension effect can be verified from three aspects of a digital twin body model, a two-dimensional suspension curve diagram and a field real vehicle test.
9. Detailed description of the invention
As shown in fig. 2, the real space maglev train levitation system transmits measurement and report data to the virtual space maglev train levitation system, and the virtual space maglev train levitation system transmits control parameters and reports to the real space maglev train levitation system.
Historical data and measurement data can effectively act on a control algorithm on the digital twin model, and the digital twin model can also perform real-time data feedback. At the moment, in the actual train test process under the real environment, only a safety worker needs to be reserved on the train to take charge of emergency braking; the debugging personnel can detect the suspension state through the digital twin model in the master control room, if the instability/rail break phenomenon occurs, the digital twin model is subjected to parameter debugging, meanwhile, the control parameters can be transmitted to the suspension system of the magnetic suspension train in the real environment in real time, and the two modes are synchronously debugged. The specific debugging process is shown in fig. 3, and includes the following steps:
1) establishing a digital twin body of a suspension system of the magnetic-levitation train;
2) performing digital twin state updating and real system state updating through a bidirectional data channel;
3) the updating of the digital twin body state is monitored in real time;
4) respectively detecting and calculating suspension errors in multiple dimensions;
5) debugging parameters according to the suspension error;
6) judging whether the expected suspension gap is reached, if so, performing a step 7), and otherwise, performing a step 4);
7) stable suspension is achieved.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (10)
1. A digital twin technology-based debugging method for a maglev train suspension system is characterized by comprising the following steps:
a digital twinning construction step: constructing a digital twin body of a suspension system of a magnetic-levitation train, wherein the digital twin body is in communication connection with the suspension system of the magnetic-levitation train;
suspension data acquisition and sensing: the magnetic-levitation train suspension system collects and senses suspension data through a sensor and transmits the suspension data to the digital twin body in real time;
a suspension system debugging step: and observing and debugging the suspension state of the digital twin body in real time through a visualization means, so as to react on the suspension system of the magnetic-levitation train.
2. The debugging method of the digital twinning technology-based maglev train suspension system according to claim 1, wherein the digital twinning body is in the form of a multi-body dynamic model or a multi-physical field model.
3. The debugging method of the digital twinning technology-based maglev train suspension system, as claimed in claim 1, wherein the suspension data comprises acceleration values, suspension gap values and control current values.
4. The debugging method of the digital twinning technology-based maglev train suspension system according to claim 3, wherein the suspension gap value is obtained by integrating the acceleration value.
5. The digital twinning technology-based debugging method for the levitation system of the magnetic-levitation train as claimed in claim 1, wherein the step of debugging the levitation system further comprises the step of individually debugging each levitation point of each car in the levitation system of the magnetic-levitation train.
6. The debugging method of the digital twin technology-based maglev train suspension system according to claim 1, wherein a 4G/5G or field wireless hotspot/field bus is adopted between the digital twin and the maglev train suspension system for parallel data transmission.
7. The debugging method of the digital twin technology-based maglev train suspension system according to claim 1, wherein the maglev train suspension system comprises a suspension execution component, the digital twin is correspondingly provided with a suspension execution virtual component, and the parameters of the suspension execution virtual component are consistent with those of the suspension execution component through identification.
8. The digital twin technology-based debugging method for a maglev train levitation system according to claim 1, wherein the data transmitted by the digital twin received by the maglev train levitation system is stored in an on-site storage device or a cloud server.
9. The debugging method of the maglev train levitation system based on the digital twinning technology as claimed in claim 1, wherein the communication connection between the digital twinning body and the maglev train levitation system is performed through virtual reality, augmented reality and mixed reality technologies.
10. The debugging method of the maglev train suspension system based on the digital twin technology as claimed in claim 1, wherein the digital twin is further used for analyzing the acquired data after the debugging is completed, and further optimizing the performance of the maglev train suspension system through a data mining technology.
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| CN114416566A (en) * | 2022-01-20 | 2022-04-29 | 中车青岛四方机车车辆股份有限公司 | Debugging method, system, equipment and storage medium of magnetic-levitation train |
| CN114524007A (en) * | 2022-02-07 | 2022-05-24 | 北京交通大学 | Magnetic levitation running control digital twin system |
| WO2024087288A1 (en) * | 2022-10-28 | 2024-05-02 | 中车长春轨道客车股份有限公司 | Simulation method for vehicle-bridge system of magnetic levitation vehicle, and related product |
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