CN108445258A - Magnetic-levitation train list iron suspension acceleration transducer diagnostic method based on integrator - Google Patents
Magnetic-levitation train list iron suspension acceleration transducer diagnostic method based on integrator Download PDFInfo
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- CN108445258A CN108445258A CN201810361867.8A CN201810361867A CN108445258A CN 108445258 A CN108445258 A CN 108445258A CN 201810361867 A CN201810361867 A CN 201810361867A CN 108445258 A CN108445258 A CN 108445258A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
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Abstract
The present invention provides a kind of magnetic-levitation train list iron suspension acceleration transducer diagnostic method based on integrator.This method includes：Obtain the gap data signal z and acceleration signal a that acceleration transducer acquires in magnetic-levitation train list iron suspension system, quadratic integral is carried out to acceleration signal a and obtains shift length s, the vertical primary clearance distance z of levitating electromagnet and lower rail level when falling within track according to shift length s and magnetic-levitation train are static0Calculate the vertical reckoning clearance distance l of levitating electromagnet and lower rail level：It calculates actual gap distance z and calculates the difference DELTA l between clearance distance l, the difference DELTA l composition sensor difference signal sequence x (t) for acquiring multiple moment carry out fault diagnosis according to x (t) and the comparison threshold value of setting to acceleration transducer.The present invention can relatively accurately identify whether magnetic-levitation train list iron suspension acceleration transducer breaks down by the way that using simple and reliable integrator as means, signal contrast threshold value is obtained by bayesian theory method.
Description
Technical field
The present invention relates to train fault diagnostic techniques field more particularly to a kind of magnetic-levitation train list iron based on integrator are outstanding
Floating acceleration transducer diagnostic method.
Background technology
Magnetic-levitation train has safe as new generation of city rail vehicle transportation system, and climbing capacity is strong, turning half
The advantage of some small equal protrusions of diameter, one of key technology is stable suspersion train.Electromagnetic suspension type magnetic-levitation train at this stage
(Electromagnetic suspension, EMS) generates suction by electromagnet and attracts track so that and train suspends, due to
Magnetic force physical characteristic magnetic-levitation train is not a self-stabilization system, and suspension system needs that feedback control, feedback information is taken to obtain
It must be fixed against suspended sensor, therefore the state of suspended sensor is suspended with larger impact to train.Between suspension system uses
Gap signal, vertical velocity signal and current signal relative to stable state deviation as feedback information.Current signal and gap letter
Number there are inductor and gap sensor to measure respectively；Speed signal is then obtained by integrator by acceleration transducer signals again.
Integrator is the element that signal is carried out to integral operation, integral is meant in the mathematical computations seek a certain function curve under area
Process, physically integral is a kind of circuit that can complete integral operation.It can be obtained by statistical data, gap sensor and electric current
Sensor reliability is high, and redundancy structure is used in engineering, therefore assert that its is in stable condition, basic fault-free；And acceleration passes
Sensor is higher compared to lower failure rate, and quickly and accurately fault diagnosis is carried out to it and can effectively ensure that magnetic-levitation train stabilization is outstanding
It is floating.
The research of the prior art suspends in the Single electromagnet of short stator low-speed maglev train and long stator high-speed maglev train
System has been achieved for certain achievement, but is concentrated mainly on the fault-tolerant control of single magnet Suspension Systems in the entirely ineffective situation of sensor
In system and redundancy setting, different types of Single electromagnet suspension failure is obtained by the failure combination of different sensors, is failed
Sensor physical fault itself is accounted for.
Wherein have and speed signal is obtained as benchmark to the gap signal differential of gap sensor to diagnose acceleration sensing
Whether device breaks down, but differential transducer structure is increasingly complex compared with integrator, is easily influenced by clutter.
Invention content
The magnetic-levitation train list iron suspension acceleration transducer diagnosis based on integrator that the embodiment provides a kind of
Method, the shortcomings that with the customer service prior art.
To achieve the goals above, this invention takes following technical solutions.
A kind of magnetic-levitation train list iron suspension acceleration transducer diagnostic method based on integrator, including：
Obtain the gap data signal z and acceleration signal that acceleration transducer acquires in magnetic-levitation train list iron suspension system
A, the gap data signal z indicate the vertical actual gap distance z of levitating electromagnet and lower rail level, the acceleration signal
A indicates the vertical acceleration of levitating electromagnet；
Quadratic integral is carried out to the acceleration signal a and obtains shift length s, according to the shift length s and the floating row of magnetic
The vertical primary clearance distance z of vehicle is static when falling within track levitating electromagnet and lower rail level0Levitating electromagnet is calculated under
The vertical reckoning clearance distance l of rail level：
The actual gap distance z and the difference DELTA l calculated between clearance distance l are calculated, multiple moment are acquired
Difference DELTA l composition sensor difference signal sequence x (t), according to the contrast threshold of sensor difference signal sequence x (t) and setting
Value carries out fault diagnosis to magnetic-levitation train list iron suspension acceleration transducer.
Further, described that quadratic integral acquisition shift length s is carried out to the acceleration signal a, according to institute's rheme
Move distance s and the vertical primary clearance distance z of magnetic-levitation train is static when falling within track levitating electromagnet and lower rail level0It calculates
The vertical reckoning clearance distance l of levitating electromagnet and lower rail level, including：
Obtain the vertical primary clearance distance z of levitating electromagnet and lower rail level when magnetic-levitation train is static to fall within track0, right
The acceleration signal a carries out quadratic integral and obtains shift length s of the levitating electromagnet with respect to rail level vertical direction：
S=∫ ∫ a (t) dt
When falling within track according to the shift length s and magnetic-levitation train are static levitating electromagnet and lower rail level it is vertical just
Beginning clearance distance z0Calculate the vertical reckoning clearance distance l of levitating electromagnet and lower rail level：
L=z0-s。
Further, the method further includes：
Single iron suspension system is with gap data signal z, vertical velocity signal v, electromagnet coil current signal i relative to steady
The difference of state is realized as feedback information and is obtained after closed-loop control, institute vertical velocity signal v are integrated by acceleration signal a.
Further, the difference DELTA calculated between the actual gap distance z and the reckoning clearance distance l
L acquires the difference DELTA l composition sensor difference signal sequence x (t) at multiple moment, according to sensor difference signal sequence x (t)
Fault diagnosis is carried out to magnetic-levitation train list iron suspension acceleration transducer with the comparison threshold value of setting, including：
Acceleration sensor is in the gap data signal z at multiple moment and acceleration under acquisition levitating electromagnet normal operating condition
Signal a is spent, by the difference DELTA l composition sensor difference signal sequences x at obtained multiple moment0(t), poor according to the sensor
Value signal sequence x0(t) the sensor difference signal average value mu for indicating suspension battery iron normal work is calculated0And normal work
Sensor difference signal variances sigma0 2；
In formula, T indicates the signal integration time；
The sensor difference signal variances sigma0 2Normal Distribution obtains x in w1Probability density in state：
In formula, and p (x | w1) in w1Indicate normal condition；
The sensor difference signal average value mu worked normally according to the suspension battery iron0, normal work sensor it is poor
Value signal variances sigma0 2With the comparison threshold value of setting, the magnetic-levitation train list iron is calculated using Bayesian decision theory algorithm and is suspended
The probability that acceleration transducer breaks down.
Further, the sensor difference signal average value mu worked normally according to the suspension battery iron0, just
The sensor difference signal variances sigma often to work0 2With the comparison threshold value of setting, calculated using Bayesian decision theory algorithm described
The probability that magnetic-levitation train list iron suspension acceleration transducer breaks down, including：
If the difference Normal Distribution of the integrated acceleration signal of acceleration transducer and actual displacement signal：
In formula, μ indicates that the mean value of difference signal to be detected, x (t) indicate acceleration in levitating electromagnet real-time running state
The difference signal sequence to be checked of sensor；
By varianceSubstitution p (x | w1) obtain the probability density that x (t) belongs to normal difference signal；
According to varianceCalculate the probability density that signal x (t) occurs in difference signal to be detected：
p(x|w2) indicate malfunction w2The probability density of signal x (t), according to Bayesian decision theory algorithm by following public affairs
Formula reasoning obtain p (x | w2)：
P(w2)=1-P (w1)
P(w1) indicate fault-free prior probability；
Trade-off decision functionIt takes：
In formulaReferred to as likelihood ratio threshold value, substitutes into：
P is fault-free prior probability in formula.
The embodiment of the present invention passes through with simple and reliable it can be seen from the technical solution that embodiments of the invention described above provide
Integrator be means, by acceleration transducer generate acceleration signal integrate after obtaining speed signal, again integral obtain
Displacement signal obtains signal contrast threshold value by bayesian theory method, judge sensor whether failure, can be relatively accurately
Identify whether magnetic-levitation train list iron suspension acceleration transducer breaks down.
The additional aspect of the present invention and advantage will be set forth in part in the description, these will become from the following description
Obviously, or practice through the invention is recognized.
Description of the drawings
In order to illustrate the technical solution of the embodiments of the present invention more clearly, required use in being described below to embodiment
Attached drawing be briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for this
For the those of ordinary skill of field, without creative efforts, others are can also be obtained according to these attached drawings
Attached drawing.
Fig. 1 is that a kind of magnetic-levitation train list iron suspension acceleration transducer based on integrator provided in an embodiment of the present invention is examined
The realization principle figure of disconnected method；
Fig. 2 is that a kind of magnetic-levitation train list iron suspension acceleration transducer based on integrator provided in an embodiment of the present invention is examined
The process chart of disconnected method.
Specific implementation mode
Embodiments of the present invention are described below in detail, the example of the embodiment is shown in the accompanying drawings, wherein from beginning
Same or similar element or element with the same or similar functions are indicated to same or similar label eventually.Below by ginseng
The embodiment for examining attached drawing description is exemplary, and is only used for explaining the present invention, and is not construed as limiting the claims.
Those skilled in the art of the present technique are appreciated that unless expressly stated, singulative " one " used herein, " one
It is a ", " described " and "the" may also comprise plural form.It is to be further understood that is used in the specification of the present invention arranges
It refers to there are the feature, integer, step, operation, element and/or component, but it is not excluded that presence or addition to take leave " comprising "
Other one or more features, integer, step, operation, element, component and/or their group.It should be understood that when we claim member
Part is " connected " or when " coupled " to another element, it can be directly connected or coupled to other elements, or there may also be
Intermediary element.In addition, " connection " used herein or " coupling " may include being wirelessly connected or coupling.Wording used herein
"and/or" includes any cell of one or more associated list items and all combines.
Those skilled in the art of the present technique are appreciated that unless otherwise defined, all terms used herein (including technology art
Language and scientific terminology) there is meaning identical with the general understanding of the those of ordinary skill in fields of the present invention.Should also
Understand, those terms such as defined in the general dictionary, which should be understood that, to be had and the meaning in the context of the prior art
The consistent meaning of justice, and unless defined as here, will not be with idealizing or the meaning of too formal be explained.
For ease of the understanding to the embodiment of the present invention, done further by taking several specific embodiments as an example below in conjunction with attached drawing
Explanation, and each embodiment does not constitute the restriction to the embodiment of the present invention.
Embodiment one
It is broadly divided into three categories in the analysis method of the fault diagnosis of magnetic-levitation train list iron suspension acceleration transducer：It is based on
The method of mathematical model, based on system input/output signal processing method and based on the method for artificial intelligence.The present invention is real
The working characteristics that example monitors sensor according to medium-and low-speed maglev train list iron suspension system first is applied, using integrator to sensor
The train acceleration signal detected is integrated twice, obtains the relevant parameters such as displacement signal and the train acceleration of train；
The displacement of acceleration sensor is integrated using Bayesian decision theory method on this basis displacement signal and gap sensor
Signal contrast difference judges, carries out fault diagnosis.
A kind of magnetic-levitation train list iron suspension acceleration transducer diagnosis side based on integrator provided in an embodiment of the present invention
The realization principle figure of method is as shown in Figure 1, specifically process flow is as shown in Fig. 2, include following processing step：
Step 11, before vehicle suspension, obtain magnetic-levitation train list iron suspension system on acceleration transducer acquisition gap
Data-signal z and acceleration signal a, between the gap data signal z expression levitating electromagnets and the vertical reality of lower rail level
Stand-off distance indicates the vertical acceleration of levitating electromagnet from z, the acceleration signal a.
Single iron suspension system is with gap data signal z, vertical velocity signal v, electromagnet coil current signal i relative to steady
The difference of state realizes closed-loop control as feedback information, targetedly to be carried out according to the state of the suspension system detected
Control.Wherein vertical velocity signal v after acceleration signal a integrals by obtaining.
Step 12, the vertical primary clearance of the levitating electromagnet that obtains that magnetic-levitation train is static when falling within track and lower rail level away from
From z0, start simultaneously to acceleration signal a carry out quadratic integral obtain levitating electromagnet with respect to rail level vertical direction displacement away from
From s：
S=∫ ∫ a (t) dt
The shift length s and primary clearance distance z obtained by integrated acceleration0Levitating electromagnet distance can be calculated
The reckoning gap l of track lower surface：
L=z0-s
Step 13 causes above-mentioned reckoning gap l and actual gap there are certain error due to signal noise and integral error,
For the gap signal z obtained using gap sensor as standard, the two obtains difference DELTA l：
Δ l=z-l
Acquire the difference DELTA l composition sensor difference signal sequence x (t) at multiple moment
Step 14, being suspended to magnetic-levitation train list iron according to sensor difference signal sequence x (t) and the comparison threshold value of setting adds
Velocity sensor carries out fault diagnosis.
Above-mentioned comparison threshold value is determined using Bayesian decision theory method.
First according to the working sensor signal under levitating electromagnet normal operating condition, normal operation of sensor is calculated
State parameter is as a reference value.The signal under all the sensors normal work is acquired, determines product under levitating electromagnet normal condition
The mean value and variance of sub-signal and actual signal difference, and rule of thumb assume difference Normal Distribution：
μ in formula0Indicate the sensor difference signal average value of suspension battery iron normal work, σ2Indicate the biography of normal work
Sensor difference signal variance, T indicate that signal integration time, x (t) indicate the sensor difference signal of levitating electromagnet normal work
Sequence.And x (t) can be obtained in w1Probability density in state：
P in formula (x | w1) in w1Indicate normal condition.
Secondly, the various statistical properties of levitating electromagnet operating status residual error are calculated using Bayesian decision theory algorithm.
Bayesian decision theory algorithm is to utilize Bayesian formula according to known class conditional probability density parameter expression and prior probability
Posterior probability is converted to, Decision Classfication is carried out according to the size of posterior probability, has that result of calculation is accurate, error rate minimum etc. is excellent
Point.
According to practical experience, it is now assumed that the integrated acceleration signal of sensor and the difference of actual displacement signal obey normal state
Distribution：
In formula, μ indicates that the mean value of difference signal to be detected, x (t) indicate the difference to be checked of levitating electromagnet real-time running state
Value signal sequence；
By varianceSubstitution p (x | w1) obtain the probability density that x (t) belongs to normal difference signal；
According to varianceCalculate the probability density that signal x (t) occurs in difference signal to be detected：
p(x|w2) indicate malfunction w2The probability density of signal x (t), can be by following according to Bayesian decision theory algorithm
Formula reasoning obtain p (x | w2)：
P(w2)=1-P (w1)
P(w1) indicate fault-free prior probability, P (w2) indicate malfunction probability.
Finally, trade-off decision functionIt takes：
In formulaReferred to as likelihood ratio threshold value, works as formulaIt sets up then x and belongs to w1, indicate the floating row of magnetic
Che Dantie suspension acceleration transducers are normal.It substitutes into：
P is fault-free prior probability in formula.
In conclusion the embodiment of the present invention is by the way that using simple and reliable integrator as means, acceleration transducer is generated
Acceleration signal integrate after obtaining speed signal, again integral obtain displacement signal, letter is obtained by bayesian theory method
Number comparison threshold value, judge sensor whether failure, can relatively accurately identify magnetic-levitation train list iron suspension acceleration sensing
Whether device breaks down.
One of ordinary skill in the art will appreciate that：Attached drawing is the schematic diagram of one embodiment, module in attached drawing or
Flow is not necessarily implemented necessary to the present invention.
Each embodiment in this specification is described in a progressive manner, identical similar portion between each embodiment
Point just to refer each other, and each embodiment focuses on the differences from other embodiments.Especially for device or
For system embodiment, since it is substantially similar to the method embodiment, so describing fairly simple, related place is referring to method
The part of embodiment illustrates.Apparatus and system embodiment described above is only schematical, wherein the conduct
The unit that separating component illustrates may or may not be physically separated, the component shown as unit can be or
Person may not be physical unit, you can be located at a place, or may be distributed over multiple network units.It can root
According to actual need that some or all of module therein is selected to achieve the purpose of the solution of this embodiment.Ordinary skill
Personnel are without creative efforts, you can to understand and implement.
The foregoing is only a preferred embodiment of the present invention, but scope of protection of the present invention is not limited thereto,
Any one skilled in the art in the technical scope disclosed by the present invention, the change or replacement that can be readily occurred in,
It should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be with scope of the claims
Subject to.
Claims (5)
1. a kind of magnetic-levitation train list iron suspension acceleration transducer diagnostic method based on integrator, which is characterized in that including：
Obtain the gap data signal z and acceleration signal a that acceleration transducer acquires in magnetic-levitation train list iron suspension system, institute
State the vertical actual gap distance z that gap data signal z indicates levitating electromagnet and lower rail level, the acceleration signal a tables
Show the vertical acceleration of levitating electromagnet；
Quadratic integral is carried out to the acceleration signal a and obtains shift length s, it is quiet according to the shift length s and magnetic-levitation train
The vertical primary clearance distance z of falling stop levitating electromagnet and lower rail level when track0Calculate levitating electromagnet and lower rail level
Vertical reckoning clearance distance l：
The actual gap distance z and the difference DELTA l calculated between clearance distance l are calculated, the difference at multiple moment is acquired
It is worth Δ l composition sensor difference signal sequence x (t), according to the comparison threshold value pair of sensor difference signal sequence x (t) and setting
Magnetic-levitation train list iron suspension acceleration transducer carries out fault diagnosis.
2. according to the method described in claim 1, it is characterized in that, described carry out quadratic integral to the acceleration signal a
Shift length s is obtained, levitating electromagnet and lower rail level hangs down when falling within track according to the shift length s and magnetic-levitation train are static
To primary clearance distance z0The vertical reckoning clearance distance l of levitating electromagnet and lower rail level is calculated, including：
Obtain the vertical primary clearance distance z of levitating electromagnet and lower rail level when magnetic-levitation train is static to fall within track0, to described
Acceleration signal a carries out quadratic integral and obtains shift length s of the levitating electromagnet with respect to rail level vertical direction：
S=∫ ∫ a (t) dt
When falling within track according to the shift length s and magnetic-levitation train are static levitating electromagnet and lower rail level it is vertical it is initial between
Stand-off distance is from z0Calculate the vertical reckoning clearance distance l of levitating electromagnet and lower rail level：
L=z0-s。
3. according to the method described in claim 1, it is characterized in that, the method further includes：
Single iron suspension system is with gap data signal z, vertical velocity signal v, electromagnet coil current signal i relative to stable state
Difference is realized as feedback information and is obtained after closed-loop control, institute vertical velocity signal v are integrated by acceleration signal a.
4. according to the method in claim 2 or 3, which is characterized in that described calculates the actual gap distance z and institute
The difference DELTA l calculated between clearance distance l is stated, the difference DELTA l composition sensor difference signal sequence x (t) at multiple moment are acquired,
Magnetic-levitation train list iron suspension acceleration transducer is carried out according to sensor difference signal sequence x (t) and the comparison threshold value of setting
Fault diagnosis, including：
Gap data signal z and acceleration of the acceleration sensor at multiple moment under levitating electromagnet normal operating condition is acquired to believe
Number a, by the difference DELTA l composition sensor difference signal sequences x at obtained multiple moment0(t), believed according to the sensor difference
Number sequence x0(t) the sensor difference signal average value mu for indicating suspension battery iron normal work is calculated0With the biography of normal work
Sensor difference signal variances sigma0 2；
In formula, T indicates the signal integration time；
The sensor difference signal variances sigma0 2Normal Distribution obtains x in w1Probability density in state：
In formula, and p (x | w1) in w1Indicate normal condition；
The sensor difference signal average value mu worked normally according to the suspension battery iron0, normal work sensor difference letter
Number variances sigma0 2With the comparison threshold value of setting, the magnetic-levitation train list iron suspension is calculated using Bayesian decision theory algorithm and is accelerated
Spend the probability of sensor failure.
5. according to the method described in claim 4, it is characterized in that, the biography worked normally according to the suspension battery iron
Sensor difference signal average value mu0, normal work sensor difference signal variances sigma0 2With the comparison threshold value of setting, using pattra leaves
This decision theory algorithm calculates the probability that the magnetic-levitation train list iron suspension acceleration transducer breaks down, including：
If the difference Normal Distribution of the integrated acceleration signal of acceleration transducer and actual displacement signal：
In formula, μ indicates that the mean value of difference signal to be detected, x (t) indicate acceleration sensing in levitating electromagnet real-time running state
The difference signal sequence to be checked of device；
By varianceSubstitution p (x | w1) obtain the probability density that x (t) belongs to normal difference signal；
According to varianceCalculate the probability density that signal x (t) occurs in difference signal to be detected：
p(x|w2) indicate malfunction w2The probability density of signal x (t) is pushed away according to Bayesian decision theory algorithm by following formula
Reason obtain p (x | w2)：
P(w2)=1-P (w1)
P(w1) indicate fault-free prior probability；
Trade-off decision functionIt takes：
In formulaReferred to as likelihood ratio threshold value, substitutes into：
P is fault-free prior probability in formula.
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| CN110196065A (en) * | 2019-06-04 | 2019-09-03 | 北京磁浮交通发展有限公司 | A kind of speed measuring and calculating of magnetic suspension train and Method for Calculate Mileage and system |
| CN111332130A (en) * | 2020-02-26 | 2020-06-26 | 同济大学 | Digital twinning technology-based debugging method for suspension system of magnetic-levitation train |
| CN113624997A (en) * | 2020-06-30 | 2021-11-09 | 株洲中车时代电气股份有限公司 | Acceleration sensor fault diagnosis method and system |
| CN113819959A (en) * | 2021-11-24 | 2021-12-21 | 中国空气动力研究与发展中心设备设计与测试技术研究所 | Suspension system anomaly detection method based on Hailinge distance and correlation coefficient |
| CN114755458A (en) * | 2022-04-19 | 2022-07-15 | 重庆嘉陵全域机动车辆有限公司 | Intelligent suspension acceleration sensor fault diagnosis method and device |
| CN115656546A (en) * | 2022-12-26 | 2023-01-31 | 北京全路通信信号研究设计院集团有限公司 | Speed measuring method, system and device for medium-low speed maglev train |
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110196065A (en) * | 2019-06-04 | 2019-09-03 | 北京磁浮交通发展有限公司 | A kind of speed measuring and calculating of magnetic suspension train and Method for Calculate Mileage and system |
| CN111332130A (en) * | 2020-02-26 | 2020-06-26 | 同济大学 | Digital twinning technology-based debugging method for suspension system of magnetic-levitation train |
| CN113624997A (en) * | 2020-06-30 | 2021-11-09 | 株洲中车时代电气股份有限公司 | Acceleration sensor fault diagnosis method and system |
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| CN113819959A (en) * | 2021-11-24 | 2021-12-21 | 中国空气动力研究与发展中心设备设计与测试技术研究所 | Suspension system anomaly detection method based on Hailinge distance and correlation coefficient |
| CN113819959B (en) * | 2021-11-24 | 2022-02-08 | 中国空气动力研究与发展中心设备设计与测试技术研究所 | Suspension system anomaly detection method based on Hailinge distance and correlation coefficient |
| CN114755458A (en) * | 2022-04-19 | 2022-07-15 | 重庆嘉陵全域机动车辆有限公司 | Intelligent suspension acceleration sensor fault diagnosis method and device |
| CN114755458B (en) * | 2022-04-19 | 2024-03-12 | 重庆嘉陵全域机动车辆有限公司 | Intelligent suspension acceleration sensor fault diagnosis method and device |
| CN115656546A (en) * | 2022-12-26 | 2023-01-31 | 北京全路通信信号研究设计院集团有限公司 | Speed measuring method, system and device for medium-low speed maglev train |
| CN115656546B (en) * | 2022-12-26 | 2023-04-04 | 北京全路通信信号研究设计院集团有限公司 | Speed measurement method, system and device for medium-low speed maglev train |
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