CN111994129A - Wheel-rail train antiskid control method and system - Google Patents
Wheel-rail train antiskid control method and system Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L15/00—Indicators provided on the vehicle or train for signalling purposes
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
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Abstract
The embodiment of the invention provides a wheel-rail train antiskid control method and a system, comprising the following steps: acquiring a track image in front of a locomotive, identifying the type of media on the track according to the track image, and acquiring a wheel-rail adhesion creep characteristic curve of the track so as to determine an adhesion power threshold value when a train runs at the current speed; determining an expected acceleration according to the current speed and the target speed of the train to obtain expected power of the train running at the current speed; and determining the target power of the train according to the expected power and the adhesion power threshold so as to output a train control command corresponding to the target power. The antiskid control method for the wheeltrack train provided by the embodiment identifies the track state by using machine vision, updates the traction braking instruction threshold value of the train according to the maximum adhesion traction force and the braking force, plans the target speed and the traction braking instruction of the ATO in the wheeltrack adhesion creeping safety working area, and effectively realizes the active antiskid control of the ATO of the train.
Description
Technical Field
The invention relates to the technical field of rail transit, in particular to a wheel-rail train antiskid control method and system.
Background
Wheel-rail adhesion is one of the important factors affecting the normal performance of traction/braking performance of high-speed trains. The adhesion between the wheel rails is limited by the road adhesion capability, and the wheel will spin or slide when traction or braking torque applied to the wheel exceeds the maximum adhesion available between the wheel rails. This phenomenon can lead to undesirable effects such as reduced passenger comfort, wheel track scuffing, reduced train traction or braking performance, and the like.
The ratio of the longitudinal tangential force between the rails and its positive pressure is defined as the adhesion coefficient and is used as an important parameter for measuring the adhesion characteristics of the rails. The adhesion coefficient is mainly related to a friction phenomenon caused on a contact surface of a wheel rail, and is affected by a material, a surface state, an attachment on the contact surface, a vehicle running condition, an environmental condition, and the like.
The test result shows that under the dry condition, the adhesion characteristic with the operation speed within 300km/h can well meet the traction and braking of the train, and the adhesion is really influenced greatly by the attachments of the surface state and the contact surface, such as water pollutants caused by rain, dew and fog, rail surface oil pollution caused by oil leakage of vehicles and engineering instruments, falling leaves in autumn, rust on the surface of the steel rail and the like, which are collectively called as 'third medium'. The wheel-rail adhesion coefficient decreases when the third medium is present on the rail. When the traction force exceeds the adhesion limit, the wheel slips on the surface of the steel rail, so that a wheel-rail contact interface is burnt; when the braking force is larger than the adhesion limit, the braking distance is prolonged, so that the braking is threatened, and the safe operation of the train is further influenced.
The available adhesion between the wheel rails can be changed under the influence of the conditions of the contact surfaces of the wheel rails, and the adhesion performance of the locomotive can be influenced if the adhesion utilization state is improved without adopting proper adhesion control, so that the maximum adhesion of the wheel rails cannot be ensured; therefore, how to achieve the purposes of improving the locomotive adhesion performance and obtaining the optimal adhesion utilization through the effective adhesion control is very important to ensure the full exertion of the traction/braking capability of the locomotive;
currently, a re-adhesion control mode is adopted for the anti-skid control of a train. The re-adhesion control is to adjust the traction force or the braking force through effective adhesion control after the wheel set idles or slides, so that the adhesion working state between the wheel rails is restored again, and the working point of the wheel rails is adjusted from the unstable area to the stable area of the adhesion characteristic curve.
Because the existing adhesion control methods all belong to a post-adjustment mode, logic threshold values are adopted to control speed difference, creep rate and speed adding (subtracting) threshold values. When wheel slip is detected, the electromagnetic torque of the traction motor is rapidly reduced, so that creep is reduced to ensure that no further slip occurs. The mode is 'after action' control during idling or sliding, cannot obtain optimal adhesion utilization, is easily influenced by road conditions, and has low control precision and poor adaptability; meanwhile, due to the fact that adjustment is carried out after wheel skidding is detected, damage to the contact surface of the wheel rail when the wheel skidding cannot be avoided.
Disclosure of Invention
The embodiment of the invention provides a wheel-rail train antiskid control method and system, which are used for improving the existing wheel-rail train antiskid control method based on a post-adjustment mode so as to timely and accurately control the running of a train through external force according to different road conditions.
In a first aspect, an embodiment of the present invention provides a wheel-rail train antiskid control method, which mainly includes: acquiring a track image in front of a train head so as to identify the type of a medium on a track according to the track image; according to the type of media on the track, obtaining a wheel track adhesion creep characteristic curve of the track to determine an adhesion power threshold value when the train runs at the current speed; determining an expected acceleration according to the current speed and the target speed of the train to obtain expected power of the train running at the current speed; and determining the target power of the train according to the expected power and the adhesion power threshold so as to output a train control command corresponding to the target power.
Optionally, the determining the target power of the train according to the expected power and the adhesion power threshold mainly includes: if the expected power is larger than the adhesion power threshold, setting the adhesion power threshold as a target power; if the desired power is not greater than the adhesion power threshold, the desired power is set as the target power.
Optionally, the above-mentioned track image that obtains the train locomotive the place ahead to according to the medium kind of track image identification on the track, mainly include: acquiring the track image in real time by using a camera arranged in front of the train head; inputting the track image into a pre-trained track medium identification network model, and acquiring the medium type corresponding to the track image according to the output result of the track medium identification network model; the track medium identification network model is obtained after training according to a track sample image with a medium type label.
Optionally, the obtaining a wheel rail adhesion creep characteristic curve of the track according to the type of the medium on the track to determine an adhesion power threshold when the train operates at the current speed mainly includes: finding out a wheel rail adhesion creep characteristic curve corresponding to the type of a medium on a track from a wheel rail adhesion creep characteristic curve list pre-stored in an automatic train driving system; determining a track adhesion coefficient when the vehicle runs at the current speed according to the wheel track adhesion creep characteristic curve; and determining an adhesion power threshold according to the rail adhesion coefficient and the load weight of the train.
Optionally, the determining an expected acceleration according to the current speed and the target speed of the train to obtain an expected power of the train running at the current speed mainly includes: acquiring an error value between the current speed and the target speed of the train; determining a desired acceleration based on the error value; and determining the target power according to the expected acceleration and the running environment and the running state of the train at the current speed.
Optionally, the determining the target power according to the expected acceleration in combination with the operation environment and the operation state of the train at the current speed mainly includes:
acquiring basic running resistance and gradient resistance of a train at the current speed;
if the running state of the train is a traction state, the target power is a target traction force, and the calculation formula of the target traction force is as follows:
Ft＝am+fs+fz；
if the running state of the train is a braking state, the target power is a target braking force, and the calculation formula of the target braking force is as follows:
Fb＝-(am+fs+fz)；
if the running state of the train is the coasting state, the target power is null, namely:
am+fs+fz＝0；
wherein a is the desired acceleration, fsFor said gradient resistance, fzM is the weight of the train load, FtFor said target tractive effort, FbThe target braking force is used.
Optionally, the media types on the track mainly include: the track is dry and clean, the track has oil stain, the track has rainwater, the track has fallen leaves or the track has snow.
In a second aspect, an embodiment of the present invention further provides a wheel-rail train antiskid control system, which mainly includes: medium type identification unit, power threshold value confirm unit, expectation power arithmetic element and control command output unit, wherein:
the medium type identification unit is mainly used for acquiring a track image in front of a train head so as to identify the type of a medium on a track according to the track image; the power threshold determination unit is mainly used for acquiring a wheel rail adhesion creep characteristic curve of the track according to the type of media on the track so as to determine the adhesion power threshold when the train operates at the current speed; the expected power operation unit is mainly used for determining expected acceleration according to the current speed and the target speed of the train so as to obtain expected power of the train running at the current speed; the control command output unit is mainly used for determining the target power of the train according to the expected power and the adhesion power threshold value so as to output a train control command corresponding to the target power.
In a third aspect, an embodiment of the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor executes the program to implement the steps of the antiskid control method for a wheel-track train as described in any one of the above.
In a fourth aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the method for anti-skid control of a train, as described in any one of the above.
According to the wheel-rail train anti-skid control method and system provided by the embodiment of the invention, the track state is identified by using machine vision, the traction braking instruction threshold value of the train is updated according to the maximum adhesion traction force and the braking force, the target speed and the traction braking instruction of an automatic train operation system (ATO) are planned in a wheel-rail adhesion creeping safety working area, and the active anti-skid control of the ATO is effectively realized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for controlling antiskid of a wheel-track train according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of another antiskid control method for a wheel-track train according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of wheel-rail adhesion-creep characteristics corresponding to different media according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a speed adhesion region and a non-adhesion region in a wheel rail adhesion creep curve chart provided by an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a wheel-rail train antiskid control system according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Because the antiskid control of the existing wheel-rail train belongs to a mode of post-adjustment, after the wheel is detected to skid, the electromagnetic torque of a traction motor is rapidly reduced, so that the creep is reduced, the control precision is low, the adaptability is poor, and the damage to the contact surface of the wheel rail when the wheel skids can not be avoided due to the adoption of the adjustment which is carried out after the wheel is detected to skid. In view of this, an embodiment of the present invention provides a method for controlling antiskid of a wheel-track train, as shown in fig. 1, which mainly includes, but is not limited to, the following steps:
step S1, acquiring a track image in front of the train head to identify the media type of the media on the track according to the track image;
step S2, acquiring a wheel rail adhesion creep characteristic curve of the track according to the media type of the media on the track to determine an adhesion power threshold value when the train operates at the current speed;
step S3, determining expected acceleration according to the current speed and the target speed of the train to obtain expected power of the train running at the current speed;
and step S4, determining the target power of the train according to the expected power and the adhesion power threshold so as to output a train control command corresponding to the target power.
Since the train runs on the rail, water pollutants caused by rain, dew and fog, oil pollution on the rail surface caused by oil leakage of vehicles and engineering instruments, fallen leaves in autumn, iron rust on the surface of the steel rail and other attachments or influences on the surface state of the rail (collectively, the third medium exists on the rail) can greatly influence the adhesion coefficient of the wheel rail. Generally, the wheel-rail adhesion coefficient decreases when the third medium is present on the rail. When the traction force exceeds the adhesion limit, the wheel slips on the surface of the steel rail, so that a wheel-rail contact interface is burnt; when the braking force is larger than the adhesion limit, the braking distance is prolonged, and the safe operation of the braking train is threatened.
In step S1 of the embodiment of the present invention, based on a machine vision method, an image of a track ahead of a train head is acquired in real time. As an alternative image capturing manner, the image capturing device may be used to capture an image continuously and capture the image according to a preset period. The preset period can be automatically adjusted according to the running speed of the train, and the faster the running speed is, the shorter the adopted preset period is set; the slower the running speed, the longer the preset period for adoption is set. Meanwhile, the preset period may be set according to the driving distance, for example, the image sampling is performed every time the train travels 1 km.
Further, the images collected in each frame can be sequentially identified, and by locating the track existing in each frame of image, whether the third medium exists on the track or not can be further identified. If a third medium is present on the track, the specific type of the medium may also be obtained.
It should be noted that, in the technical solution of the embodiment of the present invention, the media type identification of the media existing on the track is performed in real time according to the acquired track image, so that the acquired track state is also real time.
Further, in step S2, if it is determined that a third medium exists on the current track and a specific type of the third medium has been acquired, the wheeltrack adhesion creep characteristic curve corresponding to the third medium may be searched in the wheeltrack adhesion creep characteristic curve list corresponding to different track states stored in the ATO.
The wheel rail adhesion creep characteristic curve list is a list formed by wheel rail adhesion creep characteristic curves of different media, which are constructed according to different vehicle speeds by paving different media on a test track in an experimental state.
Further, in the embodiment of the invention, the current speed of the train can be detected in real time through a coded odometer, a speed sensor or a radar speed measuring device and the like. The current speed of the train is input into the current wheel rail adhesion creep characteristic curve of the train, and then the maximum adhesion traction force or the maximum brake force (collectively referred to as adhesion power threshold) corresponding to the current speed can be calculated. When the train is in a traction state, the adhesion power threshold is the maximum adhesion traction force; when the train is in a braking state, the adhesion power threshold is the maximum adhesion braking force.
Further, in step S3, first, a desired acceleration of the train in the current state is calculated from the current vehicle speed of the train and the target vehicle speed input to the ATO of the train. Then, from this acceleration, the desired power required for the train to adjust from the current speed to the target vehicle speed can be calculated. If the target vehicle speed is greater than the current speed, the expected acceleration is positive, and the applied expected power is traction; if the target vehicle speed is less than the current speed, the expected acceleration is negative, and the applied expected power is braking force; if the target vehicle speed is equal to the current speed, the application of the desired power is not required.
Finally, in step S4, the expected power required to adjust the train from the current motion state to the next motion state, which is calculated in real time in step S3, is compared with the adhesion power threshold value obtained in step S2.
Optionally, a comparison method is as follows: determining the desired tractive effort F calculated by the ATOtOr desired braking force FbWhether to adhere the adhesion area of the creep characteristic curve on the current wheel track of the track. If the train is in the adhesion zone, outputting a train control command according to the currently calculated expected traction force or braking force. If the speed exceeds the adhesion area, acquiring the current speed v of the train according to the wheel rail adhesion creep characteristic curve1Corresponding maximum adhesion coefficient umax. And according to the maximum adhesion coefficient umaxDetermining an adhesion power threshold value, and calculating the target power required by the train in the current operation according to the adhesion power threshold value, namely determining the corresponding maximum traction force FtmaxOr braking FbmaxIs the target power. And finally, converting the target power obtained by the ATO into a control command of the train according to the calculated target power.
The wheel rail train antiskid control method provided by the embodiment of the invention identifies the track state in real time by using machine vision, updates the traction braking instruction threshold value of the train according to the maximum adhesion traction force and the braking force, realizes the planning of the target speed and the traction braking instruction of the ATO in the wheel rail adhesion creeping safety working area, and effectively realizes the active antiskid control of the ATO of the train.
Based on the content of the foregoing embodiment, as an alternative embodiment, the determining the target power of the train according to the desired power and the adhesion power threshold in the foregoing step S4 mainly includes, but is not limited to: if the expected power is larger than the adhesion power threshold, setting the adhesion power threshold as a target power; setting the desired power as a target power if the desired power is not greater than the adhesion power threshold.
As shown in fig. 2, an embodiment of the present invention provides another antiskid control method for a wheel-rail train, including, but not limited to, the following steps:
firstly, based on a machine vision recognition method, recognizing the track state through a real-time track image shot by a head camera, comprising the following steps:
and judging whether a third medium exists on the front track or not, and if the third medium does not exist, not changing a train control command output in the ATO so as to keep the train continuously running according to the current state.
If the third medium exists on the front rail, the medium type of the third medium existing on the front rail can be judged according to the pre-trained rail medium recognition network model.
Further, corresponding wheel-rail adhesion creep characteristic curves stored in the ATO under different rail states are retrieved.
Furthermore, after the recognized track state specifically includes the type of a third medium existing on the track, a corresponding wheel-track adhesion creep characteristic curve is called, and an adhesion power threshold corresponding to the current vehicle speed is calculated, namely, the maximum adhesion traction force or the maximum adhesion braking force allowed when the wheel track is not idle or sliding is ensured.
Then, the current speed of the train and the target speed of the train entering the next state are calculated according to the ATO, the expected acceleration is obtained, and the target power corresponding to the expected acceleration, namely the expected traction force or the braking force is calculated according to the expected acceleration.
Further, the ATO calculated desired tractive effort or braking effort output is compared to the maximum adhesion braking effort or tractive effort. If the expected traction or braking force is smaller than the maximum adhesion traction or braking force, outputting a train control command according to the expected traction or braking force; and if the expected traction force or braking force is larger than the maximum adhesive traction force or braking force corresponding to the current speed, outputting a train control command according to the fact that the current speed is larger than the adhesive traction force or braking force.
According to the antiskid control method for the wheel rail train, provided by the embodiment of the invention, the current speed of the train in the current state is compared with the target speed of the train in the next motion state, and the proper traction force or braking force is selected according to the comparison result, so that the speed of the train is automatically controlled on the premise of ensuring that the wheel rail of the train does not idle or slide and the wheel rail exerts the maximum adhesive force, and the high-speed, stable and safe operation of the train is ensured.
Based on the content of the foregoing embodiment, as an alternative embodiment, the step S1 of acquiring the track image in front of the train head to identify the media type on the track according to the track image mainly includes, but is not limited to, the following steps:
acquiring the track image in real time by using a camera arranged in front of the train head; inputting the track image into a pre-trained track medium identification network model, and acquiring the medium type corresponding to the track image according to the output result of the track medium identification network model; the track medium identification network model is obtained after training according to a track sample image with a medium type label.
As an alternative track medium identification network model, a convolution layer, a pooling layer, a full connection layer and a logistic regression layer can be included. Firstly, inputting a track image in front of a train head into a convolution layer and a pooling layer of the neural network, extracting features of the track image by using the convolution layer and the pooling layer, and outputting a two-dimensional feature vector corresponding to the track image; inputting the two-dimensional feature vector to a full-connection layer of a preset neural network, converting the two-dimensional feature vector into a one-dimensional feature vector by using the full-connection layer, and outputting the one-dimensional feature vector; and finally, inputting the one-dimensional feature vector to a logistic regression layer of the neural network, outputting the prediction probability corresponding to the medium type, and obtaining the medium type corresponding to the track image according to the prediction probability.
As an alternative embodiment, before inputting the track image into the track medium recognition network model, a process of pre-training the network model is further included, which mainly includes the following steps:
first, a plurality of track sample images and a media type label corresponding to each track sample image are obtained, that is, the media type corresponding to each track sample image is known and labeled by the media type label. The media type label may include, among others, a dry state, a rained cover, a leafed cover, a snowed cover, and the like.
Further, a combination of each track sample image and the media type label is used as a training sample, that is, each track sample image with the media type label is used as a training sample, so that a plurality of training samples can be obtained. After obtaining a plurality of training samples, sequentially inputting the plurality of training samples to a neural network to be trained, namely simultaneously inputting the track sample image and the medium type label in each training sample to the neural network, adjusting model parameters in the preset neural network according to each output result of the neural network, and finally completing the training process of the preset neural network.
According to the antiskid control method for the wheel-rail train, provided by the embodiment of the invention, the state of the contact surface of the train track is obtained in real time through the camera device preset at the head part of the train, and the existence of the third medium and the type of the medium on the track is identified by utilizing the neural network model, so that the adhesion creep characteristic curve of the train is updated in real time. And calculating to obtain the maximum adhesion traction and braking force of the train according to the peak point of the updated adhesion creep characteristic curve, and updating the traction braking instruction threshold value of the train according to the maximum adhesion traction and braking force. Meanwhile, the target speed and the traction braking instruction of the ATO are planned in the updated wheel rail adhesion creep safe working area, so that the active anti-skid control of the ATO of the train is realized, the real-time performance and the rapidness of the neural network model identification are effectively combined with the accuracy of determining the maximum adhesion traction force and the braking force according to the adhesion creep characteristic curve, the pre-adjustment of the wheel rail train is realized, the idle running or the sliding state of the wheel rail is prevented, the running safety of the train is improved, and the abrasion condition of the wheel rail or the wheel rail caused by the idle running or the sliding of the wheel rail is prevented.
Based on the content of the foregoing embodiment, as an alternative embodiment, the step S2 of obtaining the wheel-rail adhesion creep characteristic curve of the track according to the type of the medium on the track to determine the adhesion power threshold when the train operates at the current vehicle speed includes, but is not limited to:
finding out a wheel rail adhesion creep characteristic curve corresponding to the type of a medium on a track from a wheel rail adhesion creep characteristic curve list pre-stored in an automatic train driving system; determining a track adhesion coefficient when the vehicle runs at the current speed according to the wheel track adhesion creep characteristic curve; and determining an adhesion power threshold according to the rail adhesion coefficient and the load weight of the train.
Fig. 3 is a schematic diagram of a wheel-rail adhesion creep characteristic curve corresponding to different media according to an embodiment of the present invention (the horizontal and vertical directions are creep speed of a train, and the vertical axis is a longitudinal tangential force coefficient, i.e., a wheel-rail adhesion coefficient), as shown in fig. 3, where the wheel-rail adhesion creep characteristic curve is shown in 3 states, such as oil stain on a rail, snow on a rail, and the like, when the rail is dry. Similar to the schematic diagram of fig. 3, the wheel-rail adhesion creep characteristic curves under the condition that different kinds of media exist on the rail can be obtained through an experimental mode, and all the creep characteristic curves are stored in the ATO in advance, so that the demand of calling each time when the current vehicle speed is matched with the target speed is met.
And (4) according to the type of the medium on the track, a corresponding wheel-rail adhesion creep characteristic curve is obtained in the ATO. And after the current running speed of the train is obtained, finding out a track adhesion coefficient corresponding to the current running speed in the wheel rail adhesion creep characteristic curve.
Further, the adhesion power threshold may be determined according to a rail adhesion coefficient and a load weight of the train, and specifically, the calculation formula may be:
Ftmaxu mg formula 1
Fbmax-u mg formula 2
Wherein, FtmaxFor maximum adhesive traction force, FbmaxFor maximum adhesion braking force, u is the rail adhesion coefficient, m is the load weight of the train, and g is the gravitational acceleration.
When the train is in a traction state, the maximum adhesion traction force which can be applied to the train can be calculated according to the input track adhesion coefficient and the load weight of the train by using the formula 1; when the train is in a braking state, the maximum adhesion braking force that can be applied to the train can be calculated according to the input track adhesion coefficient and the load weight of the train by using the above formula 2.
The antiskid control method of the wheel-rail train provided by the embodiment of the invention can obtain the adhesion power threshold value of the train in the current state in real time only according to the track image in front of the train head so as to provide theoretical data for preventing the wheel-rail train from idling or sliding in real time, ensure the driving safety of the train,
based on the content of the foregoing embodiment, as an alternative embodiment, the step S3 of determining the desired acceleration according to the current vehicle speed and the target speed of the train to obtain the desired power for the train to operate at the current vehicle speed includes, but is not limited to, the following steps:
obtaining an error value between the current speed and a target speed of the train; determining a desired acceleration based on the error value; and determining the target power according to the expected acceleration in combination with the running environment and the running state of the train at the current speed.
Wherein, the target power is determined according to the expected acceleration and the running environment and the running state of the train at the current speed, which may include but is not limited to the following steps:
acquiring basic running resistance and gradient resistance of a train at the current speed; if the running state of the train is a traction state, the target power is a target traction force, and the calculation formula of the target traction force is as follows:
Ft＝am+fs+fzequation 3.1
If the running state of the train is a braking state, the target power is a target braking force, and the calculation formula of the target braking force is as follows:
Fb＝-(am+fs+fz) Equation 3.2
If the running state of the train is the coasting state, the target power is null, namely:
am+fs+fz0 formula 3.3
Wherein a is the desired acceleration, fsFor said gradient resistance, fzM is the weight of the train load, FtFor said target tractive effort, FbThe target braking force is used.
Specifically, the ATO of the train can solve the expected acceleration according to the error between the current speed and the target speed, and calculate the expected traction force F corresponding to the expected acceleration according to the formula 3.1-formula 3.3tOr braking force Fb，
The calculation formula of the basic running resistance of the train can be as follows:
fz＝A+B×v+C×v2equation 4
The calculation formula for the slope resistance may be:
fsmgsin θ equation 5
Wherein A, B, C is the resistance coefficient of the running resistance, v is the current speed of the train, and theta is the slope angle.
First, various parameters required for calculating the basic running resistance and the gradient resistance of the train at the current vehicle speed, such as: A. b, C, the determination can be carried out according to the current weather state, wind power state, temperature and humidity conditions and the load state of the train; the slope angle θ can be measured according to a vehicle-mounted inclination angle measuring device.
After the basic running resistance and the gradient resistance of the train in the current state are calculated, the train is judged to be in a traction state, an automatic state or a coasting state, and the corresponding formula in the formulas 3.1 to 3.3 is selected and applied to calculate the target power.
It should be noted that, in the coasting state of the train, no external force, i.e., no tractive force or braking force, is applied. This embodiment will not be described in detail.
FIG. 4 is a schematic diagram of a speed adhesion region and a non-adhesion region in a wheel-rail adhesion creep curve according to an embodiment of the present invention, as shown in FIG. 4, determining an expected traction force F calculated by ATOtOr desired braking force FbWhether an adhesion area of a creep characteristic curve is adhered on the wheel rail or not, if so, outputting a train control command according to the currently calculated expected traction force or braking force; if the speed exceeds the adhesion area, the adhesion curve is checked to obtain the current speed v of the train1Corresponding maximum adhesion coefficient umaxThen, the corresponding maximum traction force F is calculated according to the formula 1 or the formula 2tmaxOr braking Fbmax。
According to the antiskid control method for the wheel-rail train, provided by the embodiment of the invention, the current speed and the target speed of the train are compared, so that the expected acceleration for state switching of the train is determined according to the error between the current speed and the target speed; determining the target power of the train in real time according to the expected acceleration and the current running state of the train; and finally, the determined purpose of the train is changed into a control instruction of the train so as to realize automatic control of the train, and on the basis of effectively improving the automatic regulation and control level of the train, the wheel-rail train is pre-regulated so as to prevent the wheel-rail from idling or sliding, improve the driving safety of the train and prevent the rail or the wheel-rail from being abraded due to the idling or sliding of the wheel-rail.
Based on the above description of the embodiments, as an alternative embodiment, the media types on the track include: the rail is dry and clean, oil stain exists in the rail, rainwater exists in the rail, fallen leaves exist in the rail or snow exists in the rail.
It should be noted that the media types indicated in the above embodiments are only relatively common states where the tracks are covered by the third medium, and are not intended to specifically limit the scope of the embodiments of the present invention. For example, it may further include: the rail is provided with gravels, branches are arranged on the rail, and leaves are covered and wait.
Fig. 5 is a wheel-rail train antiskid control system provided in an embodiment of the present invention, as shown in fig. 5, including but not limited to: a medium type identification unit 1, a power threshold determination unit 2, a desired power arithmetic unit 3, and a control instruction output unit 4, wherein:
the medium type identification unit 1 is used for acquiring a track image in front of a train head so as to identify the type of a medium on a track according to the track image; the power threshold determining unit 2 is used for acquiring a wheel rail adhesion creep characteristic curve of the track according to the type of media on the track so as to determine an adhesion power threshold when the train operates at the current speed; the expected power operation unit 3 is used for determining expected acceleration according to the current speed and the target speed of the train so as to obtain expected power of the train running at the current speed; the control command output unit 4 is configured to determine a target power of the train according to the expected power and the adhesion power threshold, so as to output a train control command corresponding to the target power.
Specifically, in the medium type identification unit 1, the track state is identified by a real-time track image captured by a vehicle head camera based on a machine vision identification method, and the method includes:
judging whether a third medium exists on the front track or not, and if the third medium does not exist, not changing a train control instruction output in the ATO so as to keep the train continuously running according to the current state;
if the third medium exists on the front rail, the medium type of the third medium existing on the front rail can be judged according to the pre-trained rail medium recognition network model.
Further, the dynamic threshold value determination unit 2 is used for retrieving corresponding wheel-rail adhesion creep characteristic curves stored in the ATO under different rail states. After the recognized track state specifically includes the type of the third medium existing on the track, the corresponding wheel-track adhesion creep characteristic curve is called, and the adhesion power threshold corresponding to the current vehicle speed is calculated, that is, the maximum adhesion traction force or the maximum adhesion braking force allowed when the wheel track is not idle or slides is ensured.
Then, the expected power arithmetic unit 3 calculates a target speed when the train enters the next state from the current speed of the train according to the ATO, obtains an expected acceleration, and calculates a target power corresponding thereto, that is, an expected traction or braking force, according to the expected acceleration.
Further, the control command output unit 4 compares the desired traction or braking force output calculated by the ATO with the maximum adhesion or traction force. If the expected traction or braking force is smaller than the maximum adhesion traction or braking force, outputting a train control command according to the expected traction or braking force; and if the expected traction force or braking force is larger than the maximum adhesive traction force or braking force corresponding to the current speed, outputting a train control command according to the fact that the current speed is larger than the adhesive traction force or braking force.
According to the antiskid control system for the wheel rail train, provided by the embodiment of the invention, the current speed of the train in the current state is compared with the target speed of the train in the next motion state, and the proper traction force or braking force is selected according to the comparison result, so that the speed of the train is automatically controlled on the premise of ensuring that the wheel rail of the train does not idle or slide and ensuring that the wheel rail exerts the maximum adhesive force, and the high speed of the train is ensured. Stable and safe operation.
It should be noted that, when specifically executed, the antiskid control system for a wheel-rail train provided in the embodiment of the present invention may be implemented based on the antiskid control method for a wheel-rail train described in any of the above embodiments, and details of this embodiment are not described herein.
Fig. 6 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 6: a processor (processor)610, a communication interface (communication interface)620, a memory (memory)630 and a communication bus (bus)640, wherein the processor 610, the communication interface 620 and the memory 630 complete communication with each other through the communication bus 640. The processor 610 may invoke logic instructions in the memory 630 to perform a method of antiskid control of a train, the method comprising: acquiring a track image in front of a train head so as to identify the type of a medium on a track according to the track image; according to the type of media on the track, obtaining a wheel track adhesion creep characteristic curve of the track to determine an adhesion power threshold value when the train runs at the current speed; determining an expected acceleration according to the current speed and the target speed of the train to obtain expected power of the train running at the current speed; and determining the target power of the train according to the expected power and the adhesion power threshold so as to output a train control command corresponding to the target power.
In addition, the logic instructions in the memory 630 may be implemented in software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and the like.
In addition, the logic instructions in the memory 630 may be implemented in software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, an embodiment of the present invention further provides a computer program product, where the computer program product includes a computer program stored on a non-transitory computer-readable storage medium, where the computer program includes program instructions, and when the program instructions are executed by a computer, the computer is capable of executing the method for controlling antiskid of a wheel-track train provided by the above-mentioned method embodiments, where the method includes: acquiring a track image in front of a train head so as to identify the type of a medium on a track according to the track image; according to the type of media on the track, obtaining a wheel track adhesion creep characteristic curve of the track to determine an adhesion power threshold value when the train runs at the current speed; determining an expected acceleration according to the current speed and the target speed of the train to obtain expected power of the train running at the current speed; and determining the target power of the train according to the expected power and the adhesion power threshold so as to output a train control command corresponding to the target power.
In still another aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented by a processor to execute the method for controlling antiskid of a wheel-rail train provided in the foregoing embodiments, and the method includes: acquiring a track image in front of a train head so as to identify the type of a medium on a track according to the track image; according to the type of media on the track, obtaining a wheel track adhesion creep characteristic curve of the track to determine an adhesion power threshold value when the train runs at the current speed; determining an expected acceleration according to the current speed and the target speed of the train to obtain expected power of the train running at the current speed; and determining the target power of the train according to the expected power and the adhesion power threshold so as to output a train control command corresponding to the target power.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A wheel-rail train antiskid control method is characterized by comprising the following steps:
acquiring a track image in front of a train head so as to identify the type of a medium on a track according to the track image;
according to the type of the medium on the track, obtaining a wheel track adhesion creep characteristic curve of the track to determine an adhesion power threshold value when the train operates at the current speed;
determining an expected acceleration according to the current speed and the target speed of the train to obtain expected power of the train running at the current speed;
and determining the target power of the train according to the expected power and the adhesion power threshold so as to output a train control command corresponding to the target power.
2. The antiskid control method for a wheel-track train according to claim 1, wherein the determining a target power of the train according to the desired power and the adhesion power threshold value comprises:
if the expected power is greater than the adhesion power threshold, setting the adhesion power threshold as the target power;
setting the desired power as the target power if the desired power is not greater than the adhesion power threshold.
3. The antiskid control method for the wheel-track train according to claim 1, wherein the acquiring of the track image in front of the train head to identify the type of the medium on the track according to the track image includes:
acquiring the track image in real time by using a camera arranged in front of the train head;
inputting the track image into a pre-trained track medium identification network model, and acquiring the medium type of a medium corresponding to the track image according to the result output by the track medium identification network model;
the track medium identification network model is obtained after training according to a track sample image with a medium type label.
4. The antiskid control method of the wheel-track train according to claim 1, wherein the step of obtaining a wheel-track adhesion creep characteristic curve of the track according to the type of media on the track to determine an adhesion power threshold when the train operates at the current speed comprises:
finding out a wheel rail adhesion creep characteristic curve corresponding to the type of the medium on the track from a wheel rail adhesion creep characteristic curve list pre-stored in an automatic train driving system;
determining a track adhesion coefficient when the vehicle runs at the current speed according to the wheel track adhesion creep characteristic curve;
and determining the adhesion power threshold according to the rail adhesion coefficient and the load weight of the train.
5. The antiskid control method of a wheel-track train according to claim 1, wherein the determining a desired acceleration according to the current speed and the target speed of the train to obtain the desired power for the train to run at the current speed comprises:
obtaining an error value between the current speed and a target speed of the train;
determining the desired acceleration based on the error value;
and determining the target power according to the expected acceleration in combination with the running environment and the running state of the train at the current speed.
6. The antiskid control method for a wheel-track train according to claim 5, wherein the determining the target power according to the desired acceleration in combination with the running environment and the running state of the train at the current speed comprises:
acquiring basic running resistance and gradient resistance of a train at the current speed;
if the running state of the train is a traction state, the target power is a target traction force, and the calculation formula of the target traction force is as follows:
Ft＝am+fs+fz；
if the running state of the train is a braking state, the target power is a target braking force, and a calculation formula of the target braking force is as follows:
Fb＝-(am+fs+fz)；
if the running state of the train is the coasting state, the target power is null, namely:
am+fs+fz＝0；
wherein a is the desired acceleration, fsFor said gradient resistance, fzM is the weight of the train load, FtFor said target tractive effort, FbThe target braking force is used.
7. The antiskid control method for a wheel-track train according to claim 1, wherein the media types of the media on the track include: the track is dry and clean, the track has oil stain, the track has rainwater, the track has fallen leaves or the track has snow.
8. A wheel-rail train antiskid control system, characterized by comprising:
the device comprises a medium type identification unit, a power threshold value determination unit, an expected power operation unit and a control instruction output unit;
the medium type identification unit is used for acquiring a track image in front of a train head so as to identify the type of a medium on a track according to the track image;
the power threshold determining unit is used for acquiring a wheel rail adhesion creep characteristic curve of the track according to the type of media on the track so as to determine an adhesion power threshold when the train operates at the current speed;
the expected power operation unit is used for determining expected acceleration according to the current speed and the target speed of the train so as to obtain expected power of the train running at the current speed;
the control instruction output unit is used for determining the target power of the train according to the expected power and the adhesion power threshold value so as to output a train control instruction corresponding to the target power.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and operable on the processor, wherein the processor when executing the program implements the steps of the method for antiskid control of a train as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, the computer program, when being executed by a processor, implementing the steps of the method for controlling antiskid of a wheel-rail train according to any one of claims 1 to 7.
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