A method for detecting faults of maglev train

Abstract

This invention discloses a fault detection method for maglev trains, relating to the field of maglev train technology. The invention includes: step 1. acquiring operational data; step 2. fault detection; step 3. guide rail fault analysis; and step 4. guide rail fault handling. This invention detects faults in the guide rails of the maglev train after each run, classifies the faults, and handles them accordingly. On the one hand, when the guide rails are subjected to minor external environmental damage, timely repairs can be performed, reducing the incidence of replacing entire sections of the guide rail and thus reducing the consumption of guide rail resources. On the other hand, it allows for the timely replacement of electromagnets with relatively weak electromagnetic force generation capabilities, thereby increasing the safety of the maglev train.

Description

Technical Field

[0001] The invention relates to the technical field of maglev trains, and in particular to a method for detecting faults of maglev trains. Background Art

[0002] The electromagnetic levitation train in the maglev train, in addition to the electromagnetic levitation train body, the guide rail is also an important part of it. Compared with the electromagnetic levitation train body, the protection of the guide rail is relatively less important. However, since the guide rail is completely exposed to the external environment, it is often subject to more natural damage. Once the guide rail is seriously damaged, the safety of the electromagnetic levitation train will be greatly reduced, or even unable to operate. Therefore, it is very necessary to perform fault detection on the guide rail of the electromagnetic levitation train to ensure the safety of passengers.

[0003] Prior art, such as the invention patent application with announcement number: CN111460392B, discloses a method and system for detecting faults in a maglev train and its suspension system, the method comprising: for each working condition, obtaining M healthy samples under the working condition as training samples to obtain a feature matrix; obtaining a distance data set by calculating the Euclidean distance between a principal component matrix and a mean of the principal component matrix; establishing a fault alarm threshold under the working condition based on the mean and standard deviation of the distance data set that obeys a normal distribution; for any sample to be tested, when the Euclidean distance between the principal component matrix of the sample to be tested and the mean of the principal component matrix is ​​greater than the fault alarm threshold under the pre-established target working condition, determining that the suspension system fails.

[0004] Prior art, such as the invention patent application with announcement number: CN114035553B, discloses a control system fault detection method and device based on system identification and fit, which includes: identifying the closed-loop transfer function of the current magnetic levitation control system when it is in the degradation stage; performing difference comparison to calculate the fit of the closed-loop control system; comparing the calculated fit of the closed-loop control system with a preset fit warning value to determine the fault state of the current magnetic levitation control system. The present invention can detect whether the system has a fault in real time, conveniently and quickly, and has high detection accuracy, thereby improving the safety performance of the magnetic levitation train.

[0005] It can be seen from the above scheme that the current electromagnetic levitation train fault detection method is usually only for the electromagnetic levitation train body, but lacks fault detection for the guide rail. The guide rail is equipped with an electromagnet, and the electromagnetic levitation train is suspended and moves forward by generating electromagnetic force by passing current into the guide rail. On the one hand, with the increase of application time and external environmental erosion, the guide rail is prone to appearance damage and the electromagnetic force generated by the electromagnet is weakened. On the other hand, unreasonable operation when installing the guide rail and the increase of application time can easily cause the electromagnet to fail to function normally, thereby reducing the safety of the electromagnetic levitation train. Summary of the invention

[0006] The purpose of the present invention is to provide a magnetic levitation train fault detection method, which solves the problems existing in the background technology.

[0007] In order to solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a method for detecting faults of a maglev train, comprising: Step 1. Acquisition of operation data: The guide rails of the electromagnetic levitation train are segmented to obtain each section of the guide rails, and after the electromagnetic levitation train has completed its operation, the electromagnetic force value, speed value, guide rail current, external ambient temperature and wind speed values ​​in each direction of the electromagnetic levitation train at each monitoring time point on each section of the guide rails during the operation are obtained.

[0008] Step 2. Fault detection: Analyze the electromagnetic force fault coefficient of the electromagnetic levitation train on each section of the guide rail to determine whether each section of the guide rail has a fault. If a fault occurs, select each section of the abnormal guide rail and obtain the current value of the experimental guide rail.

[0009] Step 3. Guide rail fault analysis: dispatch drones to each section of abnormal guide rail, obtain 3D modeling of each section of abnormal guide rail, screen each section of cracked guide rail and each section of normal-looking guide rail, pass each section of normal-looking guide rail into the experimental guide rail current value, obtain the external environmental temperature and the electromagnetic force value generated by each section of normal-looking guide rail at each experimental monitoring time point, and screen each section of electromagnetic force abnormal guide rail and each section of normal electromagnetic force guide rail.

[0010] Step 4. Guide rail fault processing: Calculate the historical threat coefficient of each section of normal electromagnetic force guide rail, so as to screen each section of inspection rail and each section of abnormal installation rail, send the number of each section of cracked rail, the number of each section of abnormal electromagnetic force rail, the number of each section of inspection rail and the number of each section of abnormal installation rail to the safety person in charge of the electromagnetic levitation train, and notify him to carry out corresponding safety processing.

[0011] Preferably, the electromagnetic force failure coefficient of the electromagnetic levitation train on each section of the guide rail is analyzed by a specific analysis method: obtaining from a local database the electromagnetic force increase value used by the electromagnetic levitation train to resist each external environmental hazard coefficient interval and the propulsion electromagnetic force value used to achieve each speed value.

[0012] Calculate the external environmental hazard coefficient of the electromagnetic suspension train at each monitoring time point on each section of the guide rail, and map the electromagnetic force increase value c of the electromagnetic suspension train at each monitoring time point on each section of the guide rail nx , where n represents the number of each section of the guide rail, n=1,2,...,m, m is a positive integer greater than 2, and x represents the number of each monitoring time point, x=1,2,...,y, y is a positive integer greater than 2.

[0013] Calculate the electromagnetic force value ε generated by the guideway electromagnet of the electromagnetic levitation train at each monitoring time point on each section of the guideway nx .

[0014] According to the speed value of the electromagnetic suspension train at each monitoring time point on each section of the guide rail, the propulsion electromagnetic force value l of the electromagnetic suspension train at each monitoring time point on each section of the guide rail is mapped. nx .

[0015] According to the electromagnetic force value L of the electromagnetic suspension train at each monitoring time point on each section of the guide rail nx , analyze the electromagnetic force failure coefficient of electromagnetic suspension train on each section of the guide rail

[0016] Preferably, the external environment hazard coefficient of the electromagnetic suspension train at each monitoring time point is calculated by: calculating the wind speed hazard coefficient δ of the electromagnetic suspension train at each monitoring time point on each section of the guide rail nx .

[0017] The suitable temperature range of the guide rail electromagnet is obtained from the local database, and the maximum value A and the minimum value B of the suitable temperature range of the guide rail electromagnet are extracted.

[0018] According to the external ambient temperature a of the electromagnetic suspension train at each monitoring time point on each section of the guide rail nx , calculate the external environmental hazard coefficient of the electromagnetic levitation train at each monitoring time point on each section of the guide rail Where e is a natural constant.

[0019] Preferably, the wind speed hazard coefficient of the electromagnetic suspension train at each monitoring time point on each section of the guide rail is calculated by: obtaining the wind speed adjustment parameter value D in each direction from the local database i , where i represents the number of each direction, i = 1, 2, ..., j, j is a positive integer greater than 2, and is based on the wind speed value b in each direction at each monitoring time point of the electromagnetic suspension train on each section of the guide rail. nxi , calculate the wind speed hazard coefficient of the electromagnetic suspension train at each monitoring time point on each section of the guide rail

[0020] Preferably, the electromagnetic force value generated by the guide rail electromagnet of the electromagnetic suspension train at each monitoring time point on each guide rail is calculated by: obtaining the number of coil turns d of the electromagnet of each guide rail from the local database n , effective magnetic circuit length f n , magnetic pole area g n and magnetic permeability h n .

[0021] According to the rail current k of the electromagnetic suspension train at each monitoring time point on each section of the railnx , calculate the electromagnetic force value generated by the guide rail electromagnet of the electromagnetic suspension train at each monitoring time point on each section of the guide rail

[0022] Preferably, the specific method of screening each section of cracked guide rail and each section of normal-looking guide rail is: based on 3D modeling of each section of abnormal guide rail, and through appearance detection technology, each section of cracked guide rail and each section of normal-looking guide rail are screened.

[0023] Preferably, the specific screening method for screening each section of guide rail with abnormal electromagnetic force and each section of guide rail with normal electromagnetic force is: calculating the electromagnetic force abnormality coefficient of each section of guide rail with normal appearance.

[0024] The electromagnetic force anomaly coefficient threshold is obtained from the local database, and the electromagnetic force anomaly coefficient of each section of apparently normal guide rail is compared with the electromagnetic force anomaly coefficient threshold. If the electromagnetic force anomaly coefficient of a section of apparently normal guide rail is greater than the electromagnetic force anomaly coefficient threshold, the section of apparently normal guide rail is marked as an electromagnetic force anomaly guide rail; otherwise, the section of apparently normal guide rail is marked as an electromagnetic force normal guide rail, thereby screening out sections of electromagnetic force anomaly guide rail and sections of electromagnetic force normal guide rail.

[0025] Preferably, the electromagnetic force abnormal coefficient of each section of the normal-looking guide rail is calculated by: obtaining the original electromagnetic force value generated by each section of the guide rail at each external environmental temperature after the experimental guide rail current value is passed through the local database, and mapping the original electromagnetic force value generated by each section of the normal-looking guide rail at the current external environmental temperature after the experimental guide rail current value is passed through the guide rail according to the external environmental temperature of each section of the normal-looking guide rail at each experimental monitoring time point. r , where r represents the number of each section of normal-looking guide rail, r=1,2,...,s, and s is a positive integer greater than 2.

[0026] According to the electromagnetic force value u generated by each section of normal-looking guide rail at each experimental monitoring time point rp , where p represents the number of each experimental monitoring time point, p = 1, 2, ..., q, q is a positive integer greater than 2, and the electromagnetic force anomaly coefficient of each section of the normal-looking guide rail is calculated Where q is the number of experimental monitoring time points.

[0027] Preferably, the historical threat coefficient of each section of electromagnetic force normal guide rail is calculated by: obtaining the electromagnetic application time K of each section of the guide rail from the local database n and the electromagnetic force failure coefficient E at each historical monitoring time point nv , where v represents the number of each historical monitoring time point, v = 1, 2, ..., w, w is a positive integer greater than 2, and the electromagnet application time F of each section of the electromagnetic force normal guide rail is extracted Nand the electromagnetic force fault coefficient G at each historical monitoring time point NP , where N represents the number of each section of the electromagnetic force normal guide rail, N = 1, 2, ..., M, M is a positive integer greater than 2, and P represents the number of each historical monitoring time point, P = 1, 2, ..., Q, Q is a positive integer greater than 2.

[0028] Calculate the historical threat coefficient of each section of electromagnetic normal guide rail Where m represents the number of guide rail segments, Q represents the number of historical monitoring time points, and w represents the number of electromagnetic force normal guide rail segments.

[0029] Preferably, the corresponding safety treatment is carried out, and the specific treatment method is: dispatching guide rail maintenance personnel to repair the cracks on each section of the cracked guide rail.

[0030] Guide rail maintenance personnel are dispatched to replace the electromagnets in each section of guide rail with abnormal electromagnetic force.

[0031] According to the historical threat coefficient of each section of electromagnetic normal guide rail, the historical threat coefficient of each section of inspection guide rail is extracted, and the number of inspections and inspection intervals corresponding to each historical threat coefficient interval are obtained from the local database. Based on this, drones are dispatched to inspect each section of inspection guide rail, and electromagnetic force experiments and appearance inspections are carried out during the inspection process.

[0032] Guide rail maintenance personnel are dispatched to conduct internal installation inspections between the electromagnet and the guide rail for each section of abnormally installed guide rail.

[0033] The beneficial effects of the present invention are as follows: (1) Step 1 of the present invention is to obtain operating data, which is to obtain the operating data of the electromagnetic levitation train, thereby facilitating subsequent analysis.

[0034] (2) Step 2 of the present invention is to detect faults. By analyzing various data during the operation of the electromagnetic levitation train, it is possible to preliminarily determine whether there is an abnormal electromagnetic force supply in each section of the guide rail during the operation of the electromagnetic levitation train, and to select each section of the abnormal guide rail to facilitate further analysis.

[0035] (3) Step 3 of the present invention is to analyze the guide rail fault, using drones to accurately monitor each section of the abnormal guide rail, analyze whether each section of the abnormal guide rail has cracks, and analyze whether each section of the abnormal guide rail has problems with abnormal electromagnetic force generated by the electromagnet, so as to facilitate subsequent processing.

[0036] (4) Step 4 of the present invention, guide rail fault handling, performs corresponding handling on various fault problems. On the one hand, it can not only promptly repair guide rails with cracks on the exterior, but also promptly replace abnormal electromagnets, thereby ensuring that environmental damage problems can be dealt with in a timely manner and protecting the functional integrity of the guide rails. On the other hand, it can promptly handle improperly installed guide rails, and dispatch drones to inspect guide rails that cannot be detected as faulty temporarily, thereby ensuring the safety of the electromagnetic levitation train. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0038] Figure 1 It is a schematic diagram of the method flow of the present invention. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] Reference Figure 1 As shown, the present invention provides a method for detecting faults of a maglev train, comprising: step 1. acquiring operation data: dividing the guide rails of the electromagnetic levitation train into sections, thereby acquiring each section of the guide rails, and after the electromagnetic levitation train has finished running, acquiring the electromagnetic force value, speed value, guide rail current, external environment temperature and wind speed values ​​in each direction at each monitoring time point of the electromagnetic levitation train on each section of the guide rail during the running process.

[0041] In a specific embodiment, the guide rail of the electromagnetic suspension train is divided into sections, and the specific method is: the guide rail is divided into sections according to the sections of electromagnets installed on the guide rail.

[0042] In a specific embodiment, the electromagnetic force value, speed value, guide rail current, external ambient temperature and wind speed values ​​in each direction of the electromagnetic levitation train at each monitoring time point on each guide rail during the operation are obtained, and the specific acquisition method is: the electromagnetic force value, speed value and guide rail current of the electromagnetic levitation train at each monitoring time point on each guide rail are obtained through the control terminal of the electromagnetic levitation train, the external ambient temperature of the electromagnetic levitation train at each monitoring time point on each guide rail is obtained through the temperature sensor carried by the electromagnetic levitation train, and the wind speed value of each direction at each monitoring time point on each guide rail of the electromagnetic levitation train is obtained through the wind speed detector carried by the electromagnetic levitation train.

[0043] The step 1 of the present invention is to obtain the operation data of the electromagnetic levitation train, so as to facilitate the subsequent analysis.

[0044] Step 2. Fault detection: Analyze the electromagnetic force fault coefficient of the electromagnetic levitation train on each section of the guide rail to determine whether each section of the guide rail has a fault. If a fault occurs, select each section of the abnormal guide rail and obtain the current value of the experimental guide rail.

[0045] In a specific embodiment of the present invention, the electromagnetic force failure coefficient of the electromagnetic levitation train on each section of the guide rail is analyzed by a specific analysis method: obtaining from a local database the electromagnetic force increase value used by the electromagnetic levitation train to resist each external environmental hazard coefficient interval and the propulsion electromagnetic force value used to achieve each speed value.

[0046] Calculate the external environmental hazard coefficient of the electromagnetic suspension train at each monitoring time point on each section of the guide rail, and map the electromagnetic force increase value c of the electromagnetic suspension train at each monitoring time point on each section of the guide rail nx , where n represents the number of each section of the guide rail, n=1,2,...,m, m is a positive integer greater than 2, and x represents the number of each monitoring time point, x=1,2,...,y, y is a positive integer greater than 2.

[0047] Calculate the electromagnetic force value ε generated by the guideway electromagnet of the electromagnetic levitation train at each monitoring time point on each section of the guideway nx .

[0048] According to the speed value of the electromagnetic suspension train at each monitoring time point on each section of the guide rail, the propulsion electromagnetic force value l of the electromagnetic suspension train at each monitoring time point on each section of the guide rail is mapped. nx .

[0049] According to the electromagnetic force value L of the electromagnetic suspension train at each monitoring time point on each section of the guide rail nx , analyze the electromagnetic force failure coefficient of electromagnetic suspension train on each section of the guide rail

[0050] It should be noted that the local database is used to store the electromagnetic force increase value used by the electromagnetic levitation train to resist each external environmental hazard coefficient interval, the propulsion electromagnetic force value used to achieve each speed value, the suitable temperature range of the guide rail electromagnet, the wind speed adjustment parameter values ​​in each direction, the number of coil turns of the electromagnet of each section of the guide rail, the effective magnetic circuit length, the pole area and the magnetic permeability, the electromagnetic force failure coefficient threshold, the experimental guide rail current value, the electromagnetic force abnormality coefficient threshold, the original electromagnetic force value generated by each section of the guide rail after the experimental guide rail current value is passed through the guide rail at each external environmental temperature, the number of each section of the cracked guide rail, the number of each section of the electromagnetic force abnormal guide rail, the number of each section of the inspection guide rail and the number of each section of the installation abnormal guide rail, the application time of the electromagnet of each section of the guide rail and the electromagnetic force failure coefficient at each historical monitoring time point, the historical threat coefficient threshold, the number of inspections and the inspection interval corresponding to each historical threat coefficient interval.

[0051] In a specific embodiment of the present invention, the external environment hazard coefficient of the electromagnetic suspension train at each monitoring time point is calculated by: calculating the wind speed hazard coefficient δ of the electromagnetic suspension train at each monitoring time point on each section of the guide rail nx .

[0052] The suitable temperature range of the guide rail electromagnet is obtained from the local database, and the maximum value A and the minimum value B of the suitable temperature range of the guide rail electromagnet are extracted.

[0053] According to the external ambient temperature a of the electromagnetic suspension train at each monitoring time point on each section of the guide rail nx , calculate the external environmental hazard coefficient of the electromagnetic levitation train at each monitoring time point on each section of the guide rail Where e is a natural constant.

[0054] In a specific embodiment of the present invention, the wind speed hazard coefficient of the electromagnetic suspension train at each monitoring time point on each section of the guide rail is calculated by: obtaining the wind speed adjustment parameter value D in each direction from the local database i , where i represents the number of each direction, i = 1, 2, ..., j, j is a positive integer greater than 2, and is based on the wind speed value b in each direction at each monitoring time point of the electromagnetic suspension train on each section of the guide rail. nxi , calculate the wind speed hazard coefficient of the electromagnetic suspension train at each monitoring time point on each section of the guide rail

[0055] In a specific embodiment of the present invention, the electromagnetic force value generated by the guide rail electromagnet of the electromagnetic suspension train at each monitoring time point on each guide rail is calculated by: obtaining the number of coil turns d of the electromagnet of each guide rail from the local database n , effective magnetic circuit length f n , magnetic pole area g n and magnetic permeability h n.

[0056] According to the rail current k of the electromagnetic suspension train at each monitoring time point on each section of the rail nx , calculate the electromagnetic force value generated by the guide rail electromagnet of the electromagnetic suspension train at each monitoring time point on each section of the guide rail

[0057] In a specific embodiment, the specific screening method for screening each section of abnormal guide rail is: obtaining an electromagnetic force failure coefficient threshold from a local database, comparing the electromagnetic force failure coefficient of the electromagnetic levitation train on each section of guide rail with the electromagnetic force failure coefficient threshold; if the electromagnetic force failure coefficient of the electromagnetic levitation train on a certain section of guide rail is greater than the electromagnetic force failure coefficient threshold, then it is determined that the section of guide rail has a failure, and the section of guide rail is marked as an abnormal guide rail, thereby screening each section of abnormal guide rail.

[0058] In a specific embodiment, the method for obtaining the current value of the experimental guide rail is as follows: obtaining the current value of the experimental guide rail from a local database.

[0059] Step 2 of the present invention is to detect faults. By analyzing various data during the operation of the electromagnetic levitation train, it is preliminarily determined whether there is an abnormal electromagnetic force supply in each section of the guide rail when the electromagnetic levitation train is running, and each section of the abnormal guide rail is screened to facilitate further analysis.

[0060] Step 3. Guide rail fault analysis: dispatch drones to each section of abnormal guide rail, obtain 3D modeling of each section of abnormal guide rail, screen each section of cracked guide rail and each section of normal-looking guide rail, pass each section of normal-looking guide rail into the experimental guide rail current value, obtain the external environmental temperature and the electromagnetic force value generated by each section of normal-looking guide rail at each experimental monitoring time point, and screen each section of electromagnetic force abnormal guide rail and each section of normal electromagnetic force guide rail.

[0061] In a specific embodiment of the present invention, the specific method for screening each section of cracked guide rail and each section of normal-looking guide rail is: based on 3D modeling of each section of abnormal guide rail, and through appearance detection technology, each section of cracked guide rail and each section of normal-looking guide rail are screened.

[0062] It should be noted that the existing technology for appearance inspection through 3D modeling is relatively mature. By using the existing technology for appearance inspection through 3D modeling, it is possible to screen out each section of cracked rails and each section of normal-looking rails.

[0063] In a specific embodiment, the external environmental temperature and the electromagnetic force value generated by each section of the normal-looking guide rail at each experimental monitoring time point are obtained by using an electromagnetic detector carried on the drone to obtain the electromagnetic force value generated by each section of the normal-looking guide rail at each experimental monitoring time point, and the external environmental temperature of each section of the normal-looking guide rail at each experimental monitoring time point is obtained by using a temperature detector carried on the drone.

[0064] In a specific embodiment of the present invention, the screening of each section of guide rail with abnormal electromagnetic force and each section of guide rail with normal electromagnetic force, the specific screening method is: calculating the electromagnetic force abnormality coefficient of each section of guide rail with normal appearance.

[0065] The electromagnetic force anomaly coefficient threshold is obtained from the local database, and the electromagnetic force anomaly coefficient of each section of apparently normal guide rail is compared with the electromagnetic force anomaly coefficient threshold. If the electromagnetic force anomaly coefficient of a section of apparently normal guide rail is greater than the electromagnetic force anomaly coefficient threshold, the section of apparently normal guide rail is marked as an electromagnetic force anomaly guide rail; otherwise, the section of apparently normal guide rail is marked as an electromagnetic force normal guide rail, thereby screening out sections of electromagnetic force anomaly guide rail and sections of electromagnetic force normal guide rail.

[0066] In a specific embodiment of the present invention, the electromagnetic force abnormal coefficient of each section of the normal-looking guide rail is calculated by: obtaining the original electromagnetic force value generated by each section of the guide rail at each external environmental temperature after the experimental guide rail current value is passed through the local database, and mapping the original electromagnetic force value generated by each section of the normal-looking guide rail at the current external environmental temperature after the experimental guide rail current value is passed through the guide rail according to the external environmental temperature of each section of the normal-looking guide rail at each experimental monitoring time point. r , where r represents the number of each section of normal-looking guide rail, r=1,2,...,s, and s is a positive integer greater than 2.

[0067] It should be noted that the original electromagnetic force values ​​are the electromagnetic force values ​​obtained when each section of the guide rail is experimentally tested before installation.

[0068] According to the electromagnetic force value u generated by each section of normal-looking guide rail at each experimental monitoring time point rp , where p represents the number of each experimental monitoring time point, p = 1, 2, ..., q, q is a positive integer greater than 2, and the electromagnetic force anomaly coefficient of each section of the normal-looking guide rail is calculated Where q is the number of experimental monitoring time points.

[0069] Step 3 of the present invention is to analyze the guide rail fault, which uses drones to accurately monitor each section of the abnormal guide rail, analyze whether each section of the abnormal guide rail has cracks, and analyze whether each section of the abnormal guide rail has abnormal electromagnetic force generated by the electromagnet, so as to facilitate subsequent processing.

[0070] Step 4. Guide rail fault processing: Calculate the historical threat coefficient of each section of normal electromagnetic force guide rail, so as to screen each section of inspection rail and each section of abnormal installation rail, send the number of each section of cracked rail, the number of each section of abnormal electromagnetic force rail, the number of each section of inspection rail and the number of each section of abnormal installation rail to the safety person in charge of the electromagnetic levitation train, and notify him to carry out corresponding safety processing.

[0071] It should be noted that the number of each section of cracked guide rail, the number of each section of electromagnetic force abnormal guide rail, the number of each section of inspection guide rail and the number of each section of installation abnormal guide rail are obtained from the local database.

[0072] In a specific embodiment of the present invention, the historical threat coefficient of each section of electromagnetic force normal guide rail is calculated by: obtaining the electromagnet application time K of each section of the guide rail from the local database n and the electromagnetic force failure coefficient E at each historical monitoring time point nv , where v represents the number of each historical monitoring time point, v = 1, 2, ..., w, w is a positive integer greater than 2, and the electromagnet application time F of each section of the electromagnetic force normal guide rail is extracted N and the electromagnetic force fault coefficient G at each historical monitoring time point NP , where N represents the number of each section of the electromagnetic force normal guide rail, N = 1, 2, ..., M, M is a positive integer greater than 2, and P represents the number of each historical monitoring time point, P = 1, 2, ..., Q, Q is a positive integer greater than 2.

[0073] Calculate the historical threat coefficient of each section of electromagnetic normal guide rail Where m represents the number of guide rail segments, Q represents the number of historical monitoring time points, and w represents the number of electromagnetic force normal guide rail segments.

[0074] In a specific embodiment, the screening of each section of inspection guide rail and each section of guide rail with abnormal installation, the specific screening method is: obtain the historical threat coefficient threshold from the local database, compare the historical threat coefficient of each section of normal electromagnetic force guide rail with the historical threat coefficient threshold, if the historical threat coefficient of a section of normal electromagnetic force guide rail is greater than the historical threat coefficient threshold, then mark the section of normal electromagnetic force guide rail as an abnormally installed guide rail, otherwise, mark the section of normal electromagnetic force guide rail as an inspection guide rail, thereby screening each section of inspection guide rail and each section of abnormally installed guide rail.

[0075] In a specific embodiment of the present invention, the corresponding safety processing is specifically carried out in the following manner: dispatching guide rail maintenance personnel to repair the cracks on each section of the cracked guide rail.

[0076] Guide rail maintenance personnel are dispatched to replace the electromagnets in each section of guide rail with abnormal electromagnetic force.

[0077] According to the historical threat coefficient of each section of electromagnetic normal guide rail, the historical threat coefficient of each section of inspection guide rail is extracted, and the number of inspections and inspection intervals corresponding to each historical threat coefficient interval are obtained from the local database. Based on this, drones are dispatched to inspect each section of inspection guide rail, and electromagnetic force experiments and appearance inspections are carried out during the inspection process.

[0078] Guide rail maintenance personnel are dispatched to conduct internal installation inspections between the electromagnet and the guide rail for each section of abnormally installed guide rail.

[0079] Step 4 of the present invention is to handle guide rail faults. Various fault problems are handled accordingly. On the one hand, not only can guide rails with cracks on the surface be repaired in time, but also abnormal electromagnets can be replaced in time, thereby ensuring that environmental damage problems can be dealt with in time and the functional integrity of the guide rails can be guaranteed. On the other hand, improperly installed guide rails can be handled in time, and guide rails that cannot be detected as faulty temporarily can be inspected by dispatching drones, thereby ensuring the safety of the electromagnetic levitation train.

[0080] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A method for detecting faults of a maglev train, characterized in that: include: Step 1. Operation data acquisition: the guide rails of the electromagnetic suspension train are divided into sections, so as to obtain each section of the guide rails. After the electromagnetic suspension train is completed, the electromagnetic force value, speed value, guide rail current, external environment temperature and wind speed values ​​in each direction at each monitoring time point of the electromagnetic suspension train on each section of the guide rails during the operation are obtained; Step 2. Fault detection: Analyze the electromagnetic force fault coefficient of the electromagnetic suspension train on each section of the guide rail to determine whether each section of the guide rail has a fault. If a fault occurs, select each section of the abnormal guide rail and obtain the current value of the experimental guide rail; Step 3. Guide rail fault analysis: dispatch drones to each section of abnormal guide rail, obtain 3D modeling of each section of abnormal guide rail, select each section of cracked guide rail and each section of normal-looking guide rail, pass each section of normal-looking guide rail into the experimental guide rail current value, obtain the external environment temperature and electromagnetic force value generated by each section of normal-looking guide rail at each experimental monitoring time point, and select each section of electromagnetic force abnormal guide rail and each section of electromagnetic force normal guide rail; Step 4. Handling of guide rail faults: Calculate the historical threat coefficient of each section of normal electromagnetic force guide rail, thereby screening each section of inspection guide rail and each section of abnormal installation guide rail, send the number of each section of cracked guide rail, the number of each section of abnormal electromagnetic force guide rail, the number of each section of inspection guide rail and the number of each section of abnormal installation guide rail to the safety person in charge of the electromagnetic suspension train, and notify him to carry out corresponding safety handling; The specific calculation method of calculating the historical threat coefficient of each section of electromagnetic force normal guide rail is as follows: Get the electromagnet application time K of each section of the guide rail from the local database n and the electromagnetic force failure coefficient E at each historical monitoring time point nv , where n represents the number of each section of the guide rail, n = 1, 2, ..., m, m is a positive integer greater than 2, v represents the number of each historical monitoring time point, v = 1, 2, ..., w, w is a positive integer greater than 2, and the electromagnet application time F of each section of the electromagnetic force normal guide rail is extracted N and the electromagnetic force fault coefficient G at each historical monitoring time point NP , where N represents the number of each section of electromagnetic force normal guide rail, N = 1, 2, ..., M, M is a positive integer greater than 2, P represents the number of each historical monitoring time point, P = 1, 2, ..., Q, Q is a positive integer greater than 2; Calculate the historical threat coefficient of each section of electromagnetic normal guide rail Where m represents the number of guide rail segments, Q represents the number of historical monitoring time points, and w represents the number of electromagnetic force normal guide rail segments.

2. A magnetic levitation train fault detection method according to claim 1, characterized in that: The specific analysis method for analyzing the electromagnetic force failure coefficient of the electromagnetic suspension train on each section of the guide rail is as follows: Obtaining from the local database the electromagnetic force increase value used by the electromagnetic suspension train to resist each external environmental hazard coefficient interval and the propulsion electromagnetic force value used to reach each speed value; Calculate the external environmental hazard coefficient of the electromagnetic suspension train at each monitoring time point on each section of the guide rail, and map the electromagnetic force increase value c of the electromagnetic suspension train at each monitoring time point on each section of the guide rail nx , where x represents the number of each monitoring time point, x=1,2,...,y, and y is a positive integer greater than 2; Calculate the electromagnetic force value ε generated by the guideway electromagnet of the electromagnetic levitation train at each monitoring time point on each section of the guideway nx ; According to the speed value of the electromagnetic suspension train at each monitoring time point on each section of the guide rail, the propulsion electromagnetic force value l of the electromagnetic suspension train at each monitoring time point on each section of the guide rail is mapped. nx ; According to the electromagnetic force value L of the electromagnetic suspension train at each monitoring time point on each section of the guide rail nx , analyze the electromagnetic force failure coefficient of electromagnetic suspension train on each section of the guide rail 3. A magnetic levitation train fault detection method according to claim 2, characterized in that: The specific calculation method for calculating the external environmental hazard coefficient of the electromagnetic suspension train at each monitoring time point is as follows: Calculate the wind speed hazard coefficient δ of the electromagnetic suspension train at each monitoring time point on each section of the guide rail nx ; Obtaining the suitable temperature range of the guide rail electromagnet from the local database, and extracting the maximum value A and the minimum value B of the suitable temperature range of the guide rail electromagnet; According to the external ambient temperature a of the electromagnetic suspension train at each monitoring time point on each section of the guide rail nx , calculate the external environmental hazard coefficient of the electromagnetic levitation train at each monitoring time point on each section of the guide rail Where e is a natural constant.

4. A magnetic levitation train fault detection method according to claim 3, characterized in that: The specific calculation method for calculating the wind speed hazard coefficient of the electromagnetic suspension train at each monitoring time point on each section of the guide rail is: Get the wind speed adjustment parameter value D in each direction from the local database i , where i represents the number of each direction, i = 1, 2, ..., j, j is a positive integer greater than 2, and is based on the wind speed value b in each direction at each monitoring time point of the electromagnetic suspension train on each section of the guide rail. nxi , calculate the wind speed hazard coefficient of the electromagnetic suspension train at each monitoring time point on each section of the guide rail 5. A magnetic levitation train fault detection method according to claim 2, characterized in that: The specific calculation method for calculating the electromagnetic force value generated by the guide rail electromagnet of the electromagnetic suspension train at each monitoring time point on each section of the guide rail is: Get the number of turns d of the electromagnet coils of each section of the guide rail from the local database n , effective magnetic circuit length f n , magnetic pole area g n and magnetic permeability h n ; According to the rail current k of the electromagnetic suspension train at each monitoring time point on each section of the rail nx , calculate the electromagnetic force value generated by the guide rail electromagnet of the electromagnetic suspension train at each monitoring time point on each section of the guide rail 6. A magnetic levitation train fault detection method according to claim 1, characterized in that: The specific method of screening each section of the cracked guide rail and each section of the guide rail with normal appearance is as follows: Based on the 3D modeling of each section of abnormal guide rail and the use of appearance inspection technology, the sections of cracked guide rails and the sections of normal-looking guide rails are screened out.

7. A magnetic levitation train fault detection method according to claim 1, characterized in that: The specific screening method of screening each section of the guide rail with abnormal electromagnetic force and each section of the guide rail with normal electromagnetic force is as follows: Calculate the electromagnetic force anomaly coefficient of each section of the apparently normal guide rail; The electromagnetic force anomaly coefficient threshold is obtained from the local database, and the electromagnetic force anomaly coefficient of each section of apparently normal guide rail is compared with the electromagnetic force anomaly coefficient threshold. If the electromagnetic force anomaly coefficient of a section of apparently normal guide rail is greater than the electromagnetic force anomaly coefficient threshold, the section of apparently normal guide rail is marked as an electromagnetic force anomaly guide rail; otherwise, the section of apparently normal guide rail is marked as an electromagnetic force normal guide rail, thereby screening out sections of electromagnetic force anomaly guide rail and sections of electromagnetic force normal guide rail.

8. A method for detecting faults in a maglev train according to claim 7, characterized in that: The specific calculation method for calculating the electromagnetic force abnormal coefficient of each section of the normal-looking guide rail is as follows: The original electromagnetic force value generated by each section of the rail at each external ambient temperature after the experimental rail current value is passed through is obtained from the local database, and the original electromagnetic force value t generated by each section of the normal-looking rail at the current external ambient temperature after the experimental rail current value is passed through is mapped according to the external ambient temperature of each section of the normal-looking rail at each experimental monitoring time point. r , where r represents the number of each section of normal-looking guide rail, r = 1, 2, ..., s, s is a positive integer greater than 2; According to the electromagnetic force value u generated by each section of normal-looking guide rail at each experimental monitoring time point rp , where p represents the number of each experimental monitoring time point, p = 1, 2, ..., q, q is a positive integer greater than 2, and the electromagnetic force anomaly coefficient of each section of the normal-looking guide rail is calculated Where q is the number of experimental monitoring time points.

9. A method for detecting faults in a maglev train according to claim 1, characterized in that: The corresponding security processing is carried out, and the specific processing method is as follows: Send rail maintenance personnel to repair cracks on each section of cracked rails; Dispatch rail maintenance personnel to replace the electromagnets of each section of rail with abnormal electromagnetic force; According to the historical threat coefficient of each section of electromagnetic force normal rail, the historical threat coefficient of each section of inspection rail is extracted, and the inspection times and inspection intervals corresponding to each historical threat coefficient interval are obtained from the local database. Based on this, drones are dispatched to inspect each section of inspection rail, and electromagnetic force experiments and appearance inspections are carried out during the inspection process. Guide rail maintenance personnel are dispatched to conduct internal installation inspections between the electromagnet and the guide rail for each section of abnormally installed guide rail.

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