CN114526910A - Transmission system fault positioning method based on digital twin drive - Google Patents
Transmission system fault positioning method based on digital twin drive Download PDFInfo
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- CN114526910A CN114526910A CN202210419903.8A CN202210419903A CN114526910A CN 114526910 A CN114526910 A CN 114526910A CN 202210419903 A CN202210419903 A CN 202210419903A CN 114526910 A CN114526910 A CN 114526910A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
- G01M13/02—Gearings; Transmission mechanisms
- G01M13/025—Test-benches with rotational drive means and loading means; Load or drive simulation
Abstract
The invention discloses a transmission system fault positioning method based on digital twin drive, which comprises the steps of establishing a digital twin model of a transmission system, searching an optimal digital twin model with the similarity between fault transmission system information and model information in a model database exceeding a first threshold value through a server to obtain a predictable fault sample, and carrying out training simulation according to the predictable fault sample to obtain a scheme that the fault type and the fault reason are displayed in a user interface.
Description
Technical Field
The invention belongs to the field of fault location, and particularly relates to a transmission system fault location method based on digital twin driving.
Background
Digital twin (Digital twin) refers to describing and modeling the characteristics, behaviors, forming processes, performances and the like of physical entity objects by utilizing data such as physical entity data, sensor data, operation history and the like and combining multiple physical quantities, multiple disciplines, multiple scales and multiple probabilities, so that the full life cycle of the corresponding physical entity is reflected. The method and the process for describing and modeling the behaviors, characteristics, performances, forming processes and the like of physical entity objects by utilizing a digital technology have the characteristics of real-time synchronization, high fidelity, faithful mapping and the like, and can realize the interaction and fusion of a physical world and an information world. The digital twin body is a virtual model which is established by using a digital twin technology and completely corresponds and accords with a physical entity in the real world, and can simulate the behavior and performance of the physical entity in the real environment in real time, and the digital twin body is also called as a digital twin model. The digital twin technology is considered as a bridge erected between a real physical world and a virtual digital world, and the digital twin technology is a key technology for realizing an information physical system. At present, the digital twinning technology is applied to various fields of airplane structure service life prediction, workshop production scheduling optimization, product design and the like.
At present, the problems of scarce fault samples and complex fault mechanism exist in the intelligent operation and maintenance of various small-batch products. For example: the model and the working condition of the existing fault sample are inconsistent with the model and the working condition of the equipment to be diagnosed, so that the mobility of the learning model is not high, the existing mode identification model is directly used, and the fault diagnosis identification rate is too low. How to position the fault of the equipment with few samples by using the digital twin technology becomes a technical problem to be solved urgently.
Disclosure of Invention
Aiming at the problems that the mobility of a learning model is not high due to the fact that the model and the working condition of the existing fault sample are inconsistent with the model and the working condition of equipment to be diagnosed, the existing mode identification model is directly used, the fault diagnosis identification rate is too low and the like at present, the invention provides a method for establishing a digital twin model of a transmission system, a sensing module is used for periodically collecting a plurality of measured data of the transmission system, key parameters of an optimization mechanism model are fed back through the measured data, the digital twin model is continuously dynamically optimized and updated, and a model database containing a multi-state digital twin model is established; when a client receives a fault diagnosis request, an optimal digital twin model with the similarity between fault transmission system information and model information in a model database exceeding a first threshold value is searched through a server, the actually measured information of the fault transmission system is injected into the optimal digital twin model to obtain a predictable fault sample, and a scheme that the fault type and the fault reason are displayed in a user interface is obtained by training and simulating according to the predictable fault sample.
The technical scheme adopted by the invention for solving the technical problems is as follows:
the transmission system fault locating method based on the digital twin drive comprises the following steps:
s1, establishing a digital twin model of the transmission system, wherein the digital twin model comprises a mechanism model and a dynamic model;
s2, periodically collecting a plurality of measured data of the transmission system by using a sensing module, feeding back key parameters of the optimization mechanism model through the measured data, continuously and dynamically optimizing and updating the digital twin model, and establishing a model database containing the multi-state digital twin model;
s3, when the client receives the fault diagnosis request, searching the optimal digital twin model with the similarity of the fault transmission system information and the model information in the model database exceeding a first threshold value through the server,
s4, injecting the measured information of the fault transmission system into the optimal digital twin model to obtain a predictable fault sample,
and S5, performing training simulation according to the predictable fault sample to obtain the fault type and the fault reason, and displaying the fault type and the fault reason in a user interface.
Further, the fault transmission system information includes an operation state, a driving type, a maximum rotation speed, a base speed, a rated torque, a rated power, a peak operation torque, and an artificial mark fault type.
Further, the establishing of the model database containing the digital twin model with multiple states comprises a break-in state, a steady state and a loss state.
Further, the transmission system mechanism model includes a final drive model.
Further, the main reducer model is:
whereinreq_TIs the requested torque at the output of the final drive,req_nis the requested rotational speed at the output of the final drive,av _Tbeing the torque available at the output of the final drive,av _nis the available rotational speed at the output of the final drive,T loss is a loss of torque of the final drive,Iis the moment of inertia of the main reducer,av _T tran the transmission can be made to obtain an output torque,av _ n tran in order for the transmission to achieve an output speed,ωin order to be the angular velocity of the object,T wheel to output the torque to the wheels of the vehicle,req_n wheel the rotational speed is output for the wheels of the vehicle,i 0is the transmission coefficient.
Further, the user interface displays the fault type and the fault reason and provides decision options, and the decision options provide information query, labeling and modification functions.
Further, the similarity calculation includes:
whereinC i In order to measure the index value,C i0is a predetermined value of the index,ware weights.
Further, the step S5 of performing training simulation according to the predictable failure sample to obtain a failure type and a failure cause, wherein the displaying in the user interface includes:
s501: transmitting the simulation information of the predictable fault sample to interaction equipment to realize the visualization of the real-time running state of the transmission system; s502: the diagnosis result and the residual life prediction result of the transmission system of the analysis module are transmitted to the interactive equipment through the data transfer module, and the running state of the transmission system is displayed by combining the simulation information of the transmission system; s503: and calling a corresponding maintenance strategy from a maintenance and maintenance database based on the diagnosis result and the residual life prediction result information of the transmission system so as to guide personnel to carry out maintenance and guarantee operation on the transmission system in a physical space.
The invention has the following beneficial effects:
the method can effectively improve the mobility of the model, reduce the requirements on the number of the models, effectively reduce the operation time of simulation by the multi-state model, improve the accuracy of fault judgment of the model, reduce the main management and blindness of artificial judgment, and show the details of the model in more detail by adopting the three-dimensional display of the interactive interface, indicate the position of the fault and improve the operability of maintenance personnel.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical means of the present invention more clearly understood, the present invention may be implemented in accordance with the content of the description, and in order to make the above description and other objects, features, and advantages of the present invention more clearly understandable, preferred embodiments are specifically described below.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a flow chart of a transmission system fault location method based on digital twin drive.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
In the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be connected or detachably connected or integrated; can be mechanically or electrically connected; they may be directly connected or indirectly connected through intervening media, or may be connected through the use of two elements or the interaction of two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Example 1
The transmission system fault locating method based on the digital twin drive comprises the following steps:
s1, establishing a digital twin model of the transmission system, wherein the digital twin model comprises a mechanism model and a dynamic model;
s2, periodically collecting a plurality of measured data of the transmission system by using a sensing module, feeding back key parameters of the optimization mechanism model through the measured data, continuously and dynamically optimizing and updating the digital twin model, and establishing a model database containing the multi-state digital twin model;
s3, when the client receives the fault diagnosis request, searching the optimal digital twin model with the similarity of the fault transmission system information and the model information in the model database exceeding a first threshold value through the server,
s4, injecting the measured information of the fault transmission system into the optimal digital twin model to obtain a predictable fault sample,
and S5, performing training simulation according to the predictable fault sample to obtain the fault type and the fault reason, and displaying the fault type and the fault reason in a user interface.
Further, the fault driveline information includes operating condition, drive type, top speed, base speed, rated torque, rated power, peak operating torque, and optionally a signature fault type.
Further, the establishing of the model database containing the digital twin model with multiple states comprises a break-in state, a steady state and a loss state.
Further, the transmission system mechanism model includes a final drive model.
Further, the main reducer model is:
whereinreq_TIs the requested torque at the output of the final drive,req_nis the requested rotational speed at the output of the final drive,av _Tbeing the torque available at the output of the final drive,av _nthe available speed of rotation at the output of the final drive,T loss is a loss of torque of the final drive,Iis the moment of inertia of the main reducer,av _T tran the transmission can be made to obtain an output torque,av _ n tran in order for the transmission to obtain an output speed,ωin order to be the angular velocity of the object,T wheel to output the torque to the wheels of the vehicle,req_n wheel the rotational speed is output for the wheels of the vehicle,i 0is the transmission coefficient.
Further, the user interface displays the fault type and the fault reason and provides decision options, and the decision options provide information query, labeling and modification functions.
Further, the similarity calculation includes:
whereinC i In order to measure the index value,C i0is a predetermined value of the index,ware weights.
Further, the step S5 of performing training simulation according to the predictable failure sample to obtain a failure type and a failure cause, wherein the displaying in the user interface includes:
s501: transmitting the simulation information of the predictable fault sample to interaction equipment to realize the visualization of the real-time running state of the transmission system; s502: the diagnosis result and the residual life prediction result of the transmission system of the analysis module are transmitted to the interactive equipment through the data transfer module, and the running state of the transmission system is displayed by combining the simulation information of the transmission system; s503: and calling a corresponding maintenance strategy from a maintenance and maintenance database based on the diagnosis result and the residual life prediction result information of the transmission system so as to guide personnel to carry out maintenance and guarantee operation on the transmission system in a physical space.
The invention has the following beneficial effects:
the method can effectively improve the mobility of the model, reduce the requirements on the number of the models, effectively reduce the operation time of simulation by the multi-state model, improve the accuracy of fault judgment of the model, reduce the main management and blindness of artificial judgment, and show the details of the model in more detail by adopting the three-dimensional display of the interactive interface, indicate the position of the fault and improve the operability of maintenance personnel.
Example 2
The transmission system fault locating method based on the digital twin drive comprises the following steps:
s1, establishing a digital twin model of the transmission system;
s2, periodically collecting a plurality of measured data of the transmission system by using a sensing module, and continuously and dynamically optimizing and updating the digital twin model;
s3, when the client receives the fault diagnosis request, searching the optimal digital twin model through the server,
s4, injecting the measured information of the fault transmission system into the optimal digital twin model to obtain a predictable fault sample,
and S5, performing training simulation according to the predictable fault sample to obtain the fault type and the fault reason, and displaying the fault type and the fault reason in a user interface.
The invention has the advantages that:
the method can effectively improve the mobility of the model, reduce the requirements on the number of the models, effectively reduce the operation time of simulation by the multi-state model, improve the accuracy of fault judgment of the model, reduce the main management and blindness of artificial judgment, and show the details of the model in more detail by adopting the three-dimensional display of the interactive interface, indicate the position of the fault and improve the operability of maintenance personnel.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. A transmission system fault locating method based on digital twin driving is characterized by comprising the following steps:
s1, establishing a digital twin model of the transmission system, wherein the digital twin model comprises a mechanism model and a dynamic model;
s2, periodically collecting a plurality of measured data of the transmission system by using a sensing module, feeding back key parameters of the optimization mechanism model through the measured data, continuously and dynamically optimizing and updating the digital twin model, and establishing a model database containing the multi-state digital twin model;
s3, when the client receives the fault diagnosis request, searching the optimal digital twin model with the similarity of the fault transmission system information and the model information in the model database exceeding a first threshold value through the server,
s4, injecting the measured information of the fault transmission system into the optimal digital twin model to obtain a predictable fault sample,
and S5, performing training simulation according to the predictable fault sample to obtain the fault type and the fault reason, and displaying the fault type and the fault reason in a user interface.
2. The transmission system fault location method based on the digital twin drive as claimed in claim 1, wherein: the fault transmission system information comprises an operation state, a driving type, a highest rotating speed, a basic speed, a rated torque, a rated power, an operation peak torque and an artificial mark fault type.
3. The transmission system fault location method based on the digital twin drive as claimed in claim 1, wherein: and establishing a model database containing the digital twin model in multiple states, wherein the multiple states comprise a running-in state, a steady state and a loss state.
4. The transmission system fault location method based on the digital twin drive as claimed in claim 1, wherein: the transmission system mechanism model comprises a main reducer model.
5. The transmission system fault location method based on the digital twin drive as claimed in claim 4, wherein: the main reducer model is as follows:
whereinreq_TIs the requested torque at the output of the final drive,req_nis the requested rotational speed at the output of the final drive, av _ Tbeing the torque available at the output of the final drive,av _nthe available speed of rotation at the output of the final drive,T loss is a loss of torque in the final drive,Iis the moment of inertia of the main reducer,av _T tran the transmission can be made to obtain an output torque,av _n tran in order for the transmission to obtain an output speed,ωin order to be the angular velocity of the object,T wheel to output the torque to the wheels of the vehicle,req_n wheel the rotational speed is output for the wheels of the vehicle,i 0is the transmission coefficient.
6. The transmission system fault location method based on the digital twin drive as claimed in claim 1, wherein: the user interface displays the fault type and the fault reason and provides decision options, and the decision options provide information query, labeling and modification functions.
7. The method for locating faults of a transmission system based on the digital twin drive as claimed in claim 1, wherein the method comprises the following steps: the similarity calculation includes:
whereinC i In order to measure the index value,C i0is a predetermined value of the index,ware weights.
8. The transmission system fault location method based on the digital twin drive as claimed in claim 1, wherein: the step S5 of performing training simulation according to the predictable fault sample to obtain a fault type and a fault cause, and displaying the fault type and the fault cause in a user interface includes:
s501: the simulation information of the predictable fault sample is transmitted to interaction equipment to realize the visualization of the real-time running state of the transmission system; s502: the diagnosis result and the residual life prediction result of the transmission system of the analysis module are transmitted to the interactive equipment through the data transfer module, and the running state of the transmission system is displayed by combining the simulation information of the transmission system; s503: and calling a corresponding maintenance strategy from a maintenance and maintenance database based on the diagnosis result and the residual life prediction result information of the transmission system so as to guide personnel to carry out maintenance and guarantee operation on the transmission system in a physical space.
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