CN112937642B - High-speed magnetic levitation train relative mileage detection sensor and detection method - Google Patents
High-speed magnetic levitation train relative mileage detection sensor and detection method Download PDFInfo
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- CN112937642B CN112937642B CN202110380920.0A CN202110380920A CN112937642B CN 112937642 B CN112937642 B CN 112937642B CN 202110380920 A CN202110380920 A CN 202110380920A CN 112937642 B CN112937642 B CN 112937642B
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- 238000001514 detection method Methods 0.000 title claims abstract description 114
- 238000005339 levitation Methods 0.000 title claims abstract description 51
- 238000006073 displacement reaction Methods 0.000 claims abstract description 113
- 238000012545 processing Methods 0.000 claims abstract description 40
- 238000013528 artificial neural network Methods 0.000 claims abstract description 23
- 239000000725 suspension Substances 0.000 claims abstract description 22
- 230000004044 response Effects 0.000 claims abstract description 6
- 230000003750 conditioning effect Effects 0.000 claims description 33
- 238000000034 method Methods 0.000 claims description 25
- 230000000630 rising effect Effects 0.000 claims description 23
- 238000007781 pre-processing Methods 0.000 claims description 22
- 238000012549 training Methods 0.000 claims description 19
- 239000003550 marker Substances 0.000 claims description 10
- 238000001914 filtration Methods 0.000 claims description 7
- 210000003781 tooth socket Anatomy 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 claims description 3
- 230000009191 jumping Effects 0.000 claims 1
- 238000004422 calculation algorithm Methods 0.000 abstract description 7
- 230000001939 inductive effect Effects 0.000 abstract description 7
- 230000008859 change Effects 0.000 abstract description 5
- 238000010586 diagram Methods 0.000 description 5
- 238000003672 processing method Methods 0.000 description 3
- 238000012937 correction Methods 0.000 description 1
- 230000005672 electromagnetic field Effects 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000035772 mutation Effects 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L25/00—Recording or indicating positions or identities of vehicles or trains or setting of track apparatus
- B61L25/02—Indicating or recording positions or identities of vehicles or trains
- B61L25/026—Relative localisation, e.g. using odometer
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- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Measurement Of Length, Angles, Or The Like Using Electric Or Magnetic Means (AREA)
- Length Measuring Devices With Unspecified Measuring Means (AREA)
- Control Of Vehicles With Linear Motors And Vehicles That Are Magnetically Levitated (AREA)
Abstract
The application relates to a relative mileage detection sensor and a detection method of a high-speed maglev train. The laser displacement sensor comprises three laser displacement sensors with extremely high response speed, and the three laser displacement sensors are arranged in a staggered mode. By fully utilizing the tooth slot structure characteristics of the high-speed magnetic levitation train track, the relative position positioning of the high-speed magnetic levitation train is realized based on the detection combination of the laser displacement sensor and the data driving algorithm, and the requirements of a dynamic detection system of the high-speed magnetic levitation train can be met. The detection combination of the laser displacement sensor can avoid the influence of strong electromagnetic interference and large-range temperature change on the traditional inductive sensor. The influence of vehicle suspension fluctuation, stator track tooth slot size and surface inconsistency, track large rail gap and the like is solved in the signal processing unit through a data driving algorithm based on a neural network.
Description
Technical Field
The application relates to the field of high-speed magnetic levitation trains, in particular to a high-speed magnetic levitation train relative mileage detection sensor and a detection method.
Background
The magnetic suspension train has the advantages of high speed, low energy consumption, little pollution, safety, comfort and the like, and is a novel inter-city traffic tool which is spotlighted in the 21 st century. The speed measuring and positioning system is a basis for traction and operation control of the high-speed magnetic suspension train, the relative mileage detection sensor is a very important part of the operation control system of the magnetic suspension train, plays an important role in the speed measuring and positioning system, and has important significance for ensuring normal and stable operation of the train body. When the traction system is used for traction of the train to run, the speed measuring and positioning system for traction and running control of the train is used for accurately obtaining the position information of the train, namely the position information of the rotor in real time, so that the synchronization of the long stator moving magnetic field and the rotor magnetic field is ensured. Therefore, it is necessary to provide a relative mileage detection sensor for a high-speed maglev train, which meets the requirements of a high-speed maglev traction and operation control system.
At present, the suspension gap sensor and the relative position sensor of the high-speed magnetic levitation train are both inductive sensors. The basic principle is that the position signal of the vehicle is obtained by extracting the periodic change rule of the equivalent inductance of the detection coil. Inductive relative position sensors have many advantages, but at the same time have the following problems: 1) The inductive relative position sensor has obvious nonlinear characteristics, and nonlinear correction is required to be carried out in practical application to meet the requirements of a control system; 2) The sensor is obviously affected by the temperature rise of the electromagnet; 3) The magnetic field environment is complex. The environment has the interference of a suspension magnetic field, the interference of a traction traveling wave magnetic field, the mutual interference before a sensor detection coil and the like, and the electromagnetic field strength and the frequency difference are large, so that the relative position sensor detection coil can be influenced. 4) Suspension gap fluctuations can affect the relative position detection. 5) The sensor can generate distortion in the detection signal when passing through the track joint, and the distortion signal has no mutation.
Disclosure of Invention
Based on the above, it is necessary to provide a sensor and a method for detecting the relative mileage of a high-speed maglev train, which meet the requirements of a high-speed maglev traction and operation control system. .
A high speed maglev train relative mileage detecting sensor, the relative mileage detecting sensor comprising: the laser displacement sensor comprises a laser displacement sensor, a signal acquisition conditioning unit and a signal processing unit.
The laser displacement sensor includes: the three laser displacement sensors with extremely high response speed are arranged in a staggered mode, and the center-of-mass distance between the first laser displacement sensor and the third laser displacement sensor is larger than the tooth pitch and smaller than the tooth slot period; the laser displacement sensor is used for sensing a distance signal from the sensor to the surface of the long stator track.
The signal acquisition and conditioning unit is used for acquiring the distance signal and conditioning the distance signal to obtain a detection signal.
The signal processing unit is used for receiving the detection signal and preprocessing the detection signal to obtain a preprocessed signal; taking the preprocessed signals and the actual relative position information as training samples, inputting the training samples into a pre-constructed neural network for training to obtain a relative position detection model in a tooth slot period; preprocessing a current detection signal received by a signal processing unit, inputting the current detection signal into the relative position detection model, and filtering the output of the relative position detection model to obtain tooth slot relative position detection information; and obtaining the relative position information of the high-speed magnetic levitation train according to the tooth space relative position detection information and the marker plate which is arranged on the magnetic levitation train line and contains the absolute position information.
In one embodiment, the signal processing unit is further configured to acquire the clock information of the conditioning unit and the width of the teeth on the track of the high-speed maglev train according to the calculated signal, so as to obtain the speed information of the high-speed maglev train.
In one embodiment, the signal processing unit is further configured to process the detection signal, and determine a running direction of the magnetic suspension train according to an obtained processing result.
In one embodiment, the relative mileage detecting sensor further includes a power supply unit for supplying power to the laser displacement sensor combination, the signal acquisition conditioning unit, and the signal processing unit.
The relative mileage detection method of the high-speed magnetic levitation train is applied to any one of the relative mileage detection sensors of the high-speed magnetic levitation train; the relative mileage detection method comprises the following steps:
And obtaining a detection signal output by the signal acquisition conditioning unit.
And preprocessing the detection signal to obtain preprocessing information.
And acquiring actual relative position information of the high-speed magnetic suspension train measured by the guy displacement meter.
And taking the preprocessing information and the actual relative position information as training samples, and inputting the training samples into a pre-constructed neural network for training to obtain a relative position detection model of a tooth slot period.
And acquiring a current detection signal output by the signal acquisition conditioning unit.
Preprocessing the current detection signal, and inputting the obtained preprocessing result into the relative position detection model to obtain a neural network output; and filtering the output of the neural network to obtain tooth space relative position detection information.
And obtaining the relative position information of the high-speed maglev train according to the tooth slot relative position detection information and the marker plate containing the absolute position information on the maglev train line.
In one embodiment, according to the tooth space relative position detection information and the sign board containing absolute position information on the maglev train line, the method obtains the relative position information of the high-speed maglev train, and further includes:
And acquiring information of the marker plates containing absolute position information, which are arranged at fixed intervals on the magnetic levitation train line, wherein the information comprises tooth slot counting signals, track slot widths and track slot numbers.
Obtaining the relative position information of the high-speed magnetic levitation train according to the tooth slot relative position detection information, the tooth slot counting signal, the width of the track gap and the number of the track gaps; the relative position information calculation formula is as follows:
Wherein: p opposite is relative position information, L sc is a slot period width 86mm, For relative position on the kth slot, N 1 is the slot count signal, L gap (i) is the width of the ith slot, and N gap is the current slot count.
In one embodiment, the relative mileage detecting method further includes:
And acquiring clock information of the signal acquisition conditioning unit.
And obtaining the speed information of the high-speed magnetic levitation train according to the clock information of the signal acquisition conditioning unit and the width of the teeth on the high-speed magnetic levitation train track.
In one embodiment, the three laser displacement sensors are arranged in a staggered manner, and the center-of-mass distance between the second laser displacement sensor and the first laser displacement sensor is smaller than the center-of-mass distance between the second laser displacement sensor and the third laser displacement sensor; the detection signals comprise detection signals of three laser displacement sensors; the relative mileage detecting method further includes:
and taking the minimum value in the detection signals of the three laser displacement sensors as the current suspension gap.
And making differences between the detection signals of the first laser displacement sensor and the detection signals of the second laser displacement sensor and the suspension gap to obtain a first counting pulse signal and a second counting pulse signal.
Processing the first counting pulse signal by using a preset comparator to obtain a first square wave; the first square wave comprises two pulses within one slot period.
The duty ratio of the first square wave is measured, and the value of the duty ratio of the last two times is compared at the rising edge of the first square wave to obtain a comparison result; the comparison result comprises: the duty cycle is large and is the rising edge No. 1, and the duty cycle is small and is the rising edge No. 2.
And when the comparison result is the rising edge of the No. 1, the level is pulled high, and when the comparison result is the rising edge of the No. 2, the level is pulled low, and the A-path tooth space electric signal is obtained after digital signal processing.
Performing the same signal processing on the second counting pulse signal as the first counting pulse signal to obtain a B-path tooth space electric signal; the A-path tooth space electric signal and the B-path tooth space electric signal are square wave signals.
And judging the running direction of the train by reading the level of the B-path tooth socket electric signal at any jump edge of the A-path tooth socket electric signal.
In one embodiment, the method for judging the running direction of the train by reading the level of the B-path cogging electric signal at any jump edge of the a-path cogging electric signal further comprises:
At any rising edge moment of the A-path tooth space electric signal: if the B-path tooth space electric signal is at a high level, the high-speed magnetic levitation train runs in a forward direction; if the B-path tooth space electric signal is at a low level, the high-speed magnetic levitation train runs reversely; the forward running is that the high-speed maglev train runs from the first laser displacement sensor to the third laser displacement sensor in the track direction of the high-speed maglev train; the reverse running is that the high-speed maglev train runs from the third laser displacement sensor to the first laser displacement sensor in the track direction of the high-speed maglev train.
The laser displacement sensor comprises three laser displacement sensors with extremely high response speed, and the three laser displacement sensors are arranged in a staggered mode. By fully utilizing the tooth slot structure characteristics of the high-speed magnetic levitation train track, the relative position positioning of the high-speed magnetic levitation train is realized based on the detection combination of the laser displacement sensor and the data driving algorithm, and the requirements of a dynamic detection system of the high-speed magnetic levitation train can be met. The detection combination of the laser displacement sensor can avoid the influence of strong electromagnetic interference and large-range temperature change on the traditional inductive sensor. The influence of vehicle suspension fluctuation, stator track tooth slot size and surface inconsistency, track large rail gap and the like is solved in the signal processing unit through a data driving algorithm based on a neural network.
Drawings
FIG. 1 is a block diagram of a high speed maglev train relative mileage sensor in one embodiment;
FIG. 2 is a schematic diagram of a high speed maglev train track in another embodiment, wherein: FIG. 2 (a) is a top view of the high speed maglev train track and FIG. 2 (b) is a side view of the high speed maglev train track;
FIG. 3 is a schematic diagram of a laser displacement sensor arrangement in another embodiment;
FIG. 4 is a flow chart of a method for detecting relative mileage of a high-speed maglev train in one embodiment;
FIG. 5 is a block diagram of a high speed maglev train relative mileage sensor in one embodiment;
fig. 6 is a diagram illustrating a sample signal simulation in another embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
In one embodiment, as shown in fig. 1, there is provided a relative mileage detecting sensor for a high-speed maglev train, the relative mileage detecting sensor including: a laser displacement sensor 100, a signal acquisition conditioning unit 102 and a signal processing unit 104.
The laser displacement sensor assembly 100 includes: three laser displacement sensors with extremely high response speed are respectively: a first laser displacement sensor 1001, a second laser displacement sensor 1002, and a third laser displacement sensor 1003. The laser displacement sensor is used for sensing a distance signal from the sensor to the surface of the long stator track. The detection combination of the laser displacement sensor can avoid the influence of strong electromagnetic interference and large-range temperature change on the traditional inductive sensor.
The mounting mode and the mounting position of the laser sensor combination are as shown in fig. 2 and 3, the three laser displacement sensors are arranged in a staggered mode, the center-of-mass distance between the first laser displacement sensor 1001 and the third laser displacement sensor 1003 is larger than the tooth space period and smaller than the tooth space period, and the center-of-mass distance between the second laser displacement sensor 1002 and the first laser displacement sensor 1001 is smaller than the center-of-mass distance between the second laser displacement sensor 1002 and the third laser displacement sensor 1003.
The signal acquisition and conditioning unit 102 is configured to acquire a distance signal sensed by the laser displacement sensor 100, and condition the distance signal to obtain a detection signal.
The signal processing unit 104 is configured to receive the detection signal output by the signal acquisition and conditioning unit 102, and perform preprocessing on the detection signal to obtain a preprocessed signal; taking the preprocessed signals and the actual relative position information as training samples, inputting the training samples into a pre-constructed neural network for training to obtain a relative position detection model in a tooth slot period; preprocessing a current detection signal received by a signal processing unit, inputting the current detection signal into a relative position detection model, and filtering the output of the relative position detection model to obtain tooth slot relative position detection information; and obtaining the relative position information of the high-speed magnetic levitation train according to the tooth space relative position detection information and the marker plate which is arranged on the magnetic levitation train line and contains the absolute position information.
The high-speed maglev train track corresponds to a long stator in the linear synchronous motor and has a tooth slot structure, as shown in fig. 2, fig. 2 (a) is a plan view of the high-speed maglev train track, and fig. 2 (b) is a side view of the high-speed maglev train track. The width of one tooth slot period is 86mm, and the tooth width is 43mm. Since the cable is in a circular tube shape, there is a recess at the junction of the stator surface and the cable, see fig. 2 (b). The detection distance changes when the laser displacement sensor passes through the cable pit. The distance between the sensor and the tooth surface and the groove surface is measured by utilizing the difference of the tooth surface and the groove surface, the distance signal sensed by the laser displacement sensor is collected by the signal collecting and conditioning unit, the distance information is received by the signal processing unit and preprocessed, and the relative position positioning of the high-speed maglev train is realized by adopting a data processing method based on a neural network.
In the above-mentioned high-speed maglev train relative mileage detection sensor, relative mileage detection sensor laser displacement sensor combination, signal acquisition conditioning unit and signal processing unit, laser displacement sensor combination includes three laser displacement sensors that response speed is high, and three laser displacement sensors dislocation arrangement. By fully utilizing the tooth slot structure characteristics of the high-speed magnetic levitation train track, the relative position positioning of the high-speed magnetic levitation train is realized based on the detection combination of the laser displacement sensor and the data driving algorithm, and the requirements of a dynamic detection system of the high-speed magnetic levitation train can be met. The detection combination of the laser displacement sensor can avoid the influence of strong electromagnetic interference and large-range temperature change on the traditional inductive sensor. The influence of vehicle suspension fluctuation, stator track tooth slot size and surface inconsistency, track large rail gap and the like is solved in the signal processing unit through a data driving algorithm based on a neural network.
In one embodiment, the signal processing unit is further configured to acquire the clock information of the conditioning unit and the width of the teeth on the track of the high-speed maglev train according to the calculated signal, so as to obtain the speed information of the high-speed maglev train.
When the laser displacement sensor moves along the long stator track, jump occurs from the tooth to the groove, corresponding to 1/2 tooth groove period, and the time difference between 1/2 tooth groove period can be calculated through the constant information of the signal acquisition conditioning unit, so that the speed information of the high-speed magnetic levitation train is obtained.
In one embodiment, the signal processing unit is further configured to process the detection signal, and determine a running direction of the magnetic levitation train according to the obtained processing result.
The three laser displacement sensors are arranged in a staggered manner, and the distance between the two laser displacement sensors arranged on the edge is larger than half of the tooth slot period and smaller than the tooth slot period, so that the distance signal sensed by each laser displacement sensor is acquired and processed by the signal acquisition and conditioning unit and then is input into the signal processing unit to be processed to obtain the analog output waveform of the laser displacement sensor, and the running direction of the magnetic levitation train is judged according to the analog output waveform of the laser displacement sensor.
In one embodiment, the relative mileage detecting sensor further includes a power supply unit for supplying power to the laser displacement sensor, the signal acquisition conditioning unit, and the signal processing unit.
In one embodiment, as shown in fig. 4, a method for detecting the relative mileage of a high-speed magnetic levitation train is provided, and the method for detecting the relative mileage is applied to any one of the high-speed magnetic levitation train relative mileage detection sensors; the relative mileage detection method comprises the following steps:
step 400, obtaining a detection signal output by the signal acquisition conditioning unit.
Step 402, preprocessing the detection signal to obtain preprocessing information.
And step 404, acquiring actual relative position information of the high-speed magnetic suspension train measured by the guy displacement meter.
Step 406, taking the preprocessing information and the relative position information as training samples, and inputting the training samples into a pre-constructed neural network for training to obtain a relative position detection model of a tooth slot period.
Step 408, the current detection signal output by the signal acquisition conditioning unit is obtained.
Step 410, preprocessing the current detection signal, and inputting the preprocessing result into a relative position detection model to obtain a neural network output; and filtering the output of the neural network to obtain tooth space relative position detection information.
And step 412, obtaining the relative position information of the high-speed magnetic levitation train according to the tooth slot relative position detection information and the marker plate containing the absolute position information on the magnetic levitation train line.
In one embodiment, step 412 further comprises: and acquiring information of the marker plates containing absolute position information, which are arranged at fixed intervals on the magnetic levitation train line, wherein the information comprises tooth slot counting signals, track slot widths and track slot numbers.
Obtaining the relative position information of the high-speed magnetic levitation train according to the tooth slot relative position detection information, the tooth slot counting signal, the width of the track gap and the number of the track gaps; the relative position information calculation formula is:
Wherein: p opposite is relative position information, L sc is a slot period width 86mm, For relative position on the kth slot, N 1 is the slot count signal, L gap (i) is the width of the ith slot, and N gap is the current slot count.
In one embodiment, the relative mileage detecting method further includes: acquiring clock information of a signal acquisition conditioning unit; and obtaining the speed information of the high-speed magnetic levitation train according to the clock information of the signal acquisition conditioning unit and the width of the teeth on the high-speed magnetic levitation train track.
In one embodiment, the second laser displacement sensor is spaced from the first laser displacement sensor by a smaller distance than the second laser displacement sensor is spaced from the third laser displacement sensor; the detection signals comprise detection signals of three laser displacement sensors; the relative mileage detecting method further includes: taking the minimum value in the detection signals of the three laser displacement sensors as the current suspension gap; the detection signal of the first laser displacement sensor and the detection signal of the second laser displacement sensor are both differed from the suspension gap, so that a first counting pulse signal and a second counting pulse signal are obtained; processing the first counting pulse signal by using a preset comparator to obtain a first square wave; the first square wave comprises two pulses in one tooth slot period; the duty ratio of the first square wave is measured, and the value of the duty ratio of the last two times is compared at the rising edge of the first square wave to obtain a comparison result; the comparison result comprises: the duty cycle is large and is the rising edge of No. 1, the duty cycle is small and is the rising edge of No. 2; when the comparison result is the rising edge of the No. 1, the level is pulled up, and when the comparison result is the rising edge of the No. 2, the level is pulled down, and the A-path tooth socket electric signal is obtained after digital signal processing; performing the same signal processing on the second counting pulse signal as the first counting pulse signal to obtain a B-path tooth space electric signal; the A-path tooth space electric signal and the B-path tooth space electric signal are square wave signals; and judging the running direction of the train by reading the level of the B-path tooth socket electric signal at any jump edge of the A-path tooth socket electric signal.
In one embodiment, the method for judging the running direction of the train by reading the level of the B-path tooth space electric signal along any jump of the A-path tooth space electric signal further comprises: at any rising edge moment of the A-path tooth space electric signal: if the B-path tooth space electric signal is at a high level, the high-speed magnetic levitation train runs in the forward direction; if the B-path tooth space electric signal is at a low level, the high-speed magnetic levitation train runs reversely; the forward running is that the high-speed maglev train runs from the first laser displacement sensor to the third laser displacement sensor in the track direction of the high-speed maglev train; the reverse running is that the high-speed maglev train runs from the third laser displacement sensor to the first laser displacement sensor in the track direction of the high-speed maglev train.
It should be understood that, although the steps in the flowchart of fig. 4 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 4 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
In one embodiment, as shown in FIG. 5, there is provided a high-speed maglev train relative mileage detection sensor comprising: the laser displacement sensor comprises laser displacement sensors A1, A2 and A3, a signal acquisition conditioning unit, a signal processing unit and a power supply unit, wherein the laser displacement sensor comprises the laser displacement sensors A1, A2 and A3.
The arrangement of the laser displacement sensors A1, A2 and A3 is shown in FIG. 3, three laser displacement sensors A1, A2 and A3 are arranged in a staggered mode, and the centers of mass of the laser displacement sensors A1 and A3 are separated by 50mm. A2 is 21mm from A1 centroid.
The data processing method operated in the signal processing unit comprises the following steps: a neural network based data driven algorithm. The data processing method comprises the following steps:
(1) Relative mileage positioning method
And establishing a relative position detection model of a tooth slot period through a neural network by utilizing distance signals from the sensor to the surface of the long stator track, which are acquired in a fluctuation range of a suspension gap of +/-2 mm of the laser displacement sensor. The output signals of the three laser displacement sensors are as follows: and S 1(k)、S2(k)、S3 (k), wherein the input of the neural network comprises the signals obtained by preprocessing the output S 1(k)、S2(k)、S3 (k) of the three laser displacement sensors, the preprocessed signals are ：[S1(k),S2(k),S3(k),S1(k)-S2(k),S1(k)-S3(k)]T,, and the target output of the neural network is the relative position information L opposite (k) measured by the guy displacement meter. Training the neural network to obtain the output of the neural networkAnd then filtering the output of the neural network to obtain tooth space relative position detection information.
On the maglev train line, a marker plate containing absolute position information is arranged every 200 meters, and the relative position information P opposite between two marker plates, namely within the range of 200 meters is as follows:
Wherein: l sc is a slot period width 86mm, For relative position on the kth slot, N 1 is the slot count signal, L gap (i) is the width of the ith slot, and N gap is the current slot count.
(2) Speed measuring method
When the laser displacement sensor moves along the long stator track, jump occurs from the tooth to the groove, the period of the tooth groove corresponds to 1/2 of the period of 43mm, and the time difference between every 43mm can be calculated through the constant heart system of the signal acquisition conditioning unit, so that the speed information of the high-speed magnetic levitation train can be obtained.
Wherein: l s/c is the width of the teeth 43mm.
(3) Running direction judging method
Taking the minimum value of the three laser displacement sensors and the current suspension gap h 1 (k), and making the difference between the sensor A1 signal S 1 and the suspension gap, the pulse count signal S 1' can be formed.
Because grooves exist on both sides of the cable, two pulses occur within a long stator slot cycle. And (3) carrying out duty ratio measurement on the square wave after the comparator, comparing the values of the duty ratio of the last two times at the rising edge of the signal, predicting whether the current rising edge belongs to the No. 1 or the No. 2, if the current rising edge is the No. 1, pulling the level high, if the current rising edge is the No. 2, pulling the level low, and obtaining the A-path tooth space electric signal S A after digital signal processing. The same processing is performed for S2 and S1, and a B-way slot signal S B can be obtained as shown in fig. 6. The two paths of signals S A and S B have a 90-degree phase difference, so that the running direction of the train can be judged by reading the level of the square wave of the other path at any jump edge of S A. For example, at the rising edge of the square wave signal S A generated by the sensor A1, if the square wave signal S B of the sensor A2 is at a high level, the operation is forward, that is: the laser displacement sensor A1 moves towards the direction A3 in the track direction of the high-speed maglev train; if the square wave signal S B of the sensor A2 is low, the reverse operation is performed, that is: the laser displacement sensor A3 moves towards the direction A1 in the track direction of the high-speed maglev train.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (9)
1. A high-speed maglev train relative mileage detecting sensor, characterized in that the relative mileage detecting sensor comprises: the laser displacement sensor, the signal acquisition conditioning unit and the signal processing unit;
The laser displacement sensor includes: the three laser displacement sensors with extremely high response speed are arranged in a staggered mode, and the center-of-mass distance between the first laser displacement sensor and the third laser displacement sensor is larger than the tooth pitch and smaller than the tooth slot period; the laser displacement sensor is used for sensing a distance signal from the sensor to the surface of the long stator track;
the signal acquisition and conditioning unit is used for acquiring the distance signal and conditioning the distance signal to obtain a detection signal;
The signal processing unit is used for receiving the detection signal and preprocessing the detection signal to obtain a preprocessed signal; taking the preprocessed signals and the actual relative position information as training samples, and inputting the training samples into a pre-constructed neural network for training to obtain a relative position detection model in a tooth slot period; preprocessing a current detection signal received by the signal processing unit, inputting the current detection signal into the relative position detection model, and filtering the output of the relative position detection model to obtain tooth space relative position detection information; and obtaining the relative position information of the high-speed magnetic levitation train according to the tooth slot relative position detection information and a marking plate which is arranged on the magnetic levitation train line and contains absolute position information.
2. The relative mileage detecting sensor according to claim 1, wherein the signal processing unit is further configured to obtain speed information of the high-speed maglev train according to the clock information of the signal acquisition and conditioning unit and the width of the teeth on the high-speed maglev train track.
3. The relative mileage detecting sensor according to claim 1, wherein the signal processing unit is further configured to process the detection signal, and determine the traveling direction of the magnetic levitation train based on the obtained processing result.
4. The relative mileage detecting sensor of claim 1, further comprising a power supply unit for supplying power to the laser displacement sensor combination, the signal acquisition conditioning unit, and the signal processing unit.
5. A method for detecting relative mileage of a high-speed magnetic levitation train, which is characterized in that the method is applied to the sensor for detecting relative mileage of the high-speed magnetic levitation train according to any one of claims 1 to 4; the relative mileage detection method comprises the following steps:
acquiring a detection signal output by a signal acquisition conditioning unit;
preprocessing the detection signal to obtain preprocessing information;
acquiring actual relative position information of the high-speed magnetic suspension train measured by a guy displacement meter;
Taking the preprocessing information and the actual relative position information as training samples, and inputting the training samples into a pre-constructed neural network for training to obtain a relative position detection model in a tooth slot period;
Acquiring a current detection signal output by a signal acquisition conditioning unit;
Preprocessing the current detection signal, and inputting the obtained preprocessing result into the relative position detection model to obtain a neural network output; filtering the output of the neural network to obtain tooth space relative position detection information;
And obtaining the relative position information of the high-speed maglev train according to the tooth slot relative position detection information and the marker plate containing the absolute position information on the maglev train line.
6. The method for detecting relative mileage according to claim 5, wherein obtaining the relative position information of the high-speed maglev train based on the tooth space relative position detection information and the sign board including the absolute position information on the maglev train line, comprises:
Acquiring information of a marker plate containing absolute position information, which is arranged at fixed intervals on a magnetic levitation train line, wherein the information comprises tooth slot counting signals, track slot widths and track slot numbers;
Obtaining the relative position information of the high-speed magnetic levitation train according to the tooth slot relative position detection information, the tooth slot counting signal, the width of the track gap and the number of the track gaps; the relative position information calculation formula is as follows:
Wherein: p opposite is relative position information, L sc is a slot period width 86mm, For relative position on the kth slot, N 1 is the slot count signal, L gap (i) is the width of the ith slot, and N gap is the current slot count.
7. The relative mileage detecting method according to claim 5, wherein the relative mileage detecting method further includes:
Acquiring clock information of a signal acquisition conditioning unit;
And obtaining the speed information of the high-speed magnetic levitation train according to the clock information of the signal acquisition conditioning unit and the width of the teeth on the high-speed magnetic levitation train track.
8. The method of claim 5, wherein the three laser displacement sensors are arranged in a staggered manner, and wherein a center of mass distance between the second laser displacement sensor and the first laser displacement sensor is smaller than a center of mass distance between the second laser displacement sensor and the third laser displacement sensor; the detection signals comprise detection signals of three laser displacement sensors; the relative mileage detecting method further includes:
taking the minimum value in the detection signals of the three laser displacement sensors as the current suspension gap;
the detection signal of the first laser displacement sensor and the detection signal of the second laser displacement sensor are both differed from the suspension gap, so that a first counting pulse signal and a second counting pulse signal are obtained;
Processing the first counting pulse signal by using a preset comparator to obtain a first square wave; the first square wave comprises two pulses in one tooth slot period;
the duty ratio of the first square wave is measured, and the value of the duty ratio of the last two times is compared at the rising edge of the first square wave to obtain a comparison result; the comparison result comprises: the duty cycle is large and is the rising edge of No. 1, the duty cycle is small and is the rising edge of No. 2;
When the comparison result is the rising edge of the No. 1, the level is pulled high, and when the comparison result is the rising edge of the No. 2, the level is pulled low, and the A-path tooth space electric signal is obtained after digital signal processing;
performing the same signal processing on the second counting pulse signal as the first counting pulse signal to obtain a B-path tooth space electric signal; the A-path tooth space electric signal and the B-path tooth space electric signal are square wave signals;
and judging the running direction of the train by reading the level of the B-path tooth socket electric signal at any jump edge of the A-path tooth socket electric signal.
9. The relative mileage detecting method according to claim 8, wherein determining the train running direction by reading the level of the B-way alveolar electric signal at any one of the jumping edges of the a-way alveolar electric signal, includes:
At any rising edge moment of the A-path tooth space electric signal: if the B-path tooth space electric signal is at a high level, the high-speed magnetic levitation train runs in a forward direction; if the B-path tooth space electric signal is at a low level, the high-speed magnetic levitation train runs reversely; the forward running is that the high-speed maglev train runs from the first laser displacement sensor to the third laser displacement sensor in the track direction of the high-speed maglev train; the reverse running is that the high-speed maglev train runs from the third laser displacement sensor to the first laser displacement sensor in the track direction of the high-speed maglev train.
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