CN110501421A - A kind of track profiling method of detection based on mechanical arm - Google Patents
A kind of track profiling method of detection based on mechanical arm Download PDFInfo
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- CN110501421A CN110501421A CN201910670771.4A CN201910670771A CN110501421A CN 110501421 A CN110501421 A CN 110501421A CN 201910670771 A CN201910670771 A CN 201910670771A CN 110501421 A CN110501421 A CN 110501421A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/22—Details, e.g. general constructional or apparatus details
- G01N29/26—Arrangements for orientation or scanning by relative movement of the head and the sensor
- G01N29/265—Arrangements for orientation or scanning by relative movement of the head and the sensor by moving the sensor relative to a stationary material
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- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B25/00—Models for purposes not provided for in G09B23/00, e.g. full-sized devices for demonstration purposes
- G09B25/02—Models for purposes not provided for in G09B23/00, e.g. full-sized devices for demonstration purposes of industrial processes; of machinery
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- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B9/00—Simulators for teaching or training purposes
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2291/00—Indexing codes associated with group G01N29/00
- G01N2291/02—Indexing codes associated with the analysed material
- G01N2291/023—Solids
- G01N2291/0234—Metals, e.g. steel
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2291/00—Indexing codes associated with group G01N29/00
- G01N2291/26—Scanned objects
- G01N2291/262—Linear objects
- G01N2291/2623—Rails; Railroads
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Abstract
The track profiling method of detection based on mechanical arm that the present invention relates to a kind of, it include: step S1, artificial teaching cooperates with the profiling flaw detection operation completed to continuous welded rail track connector by people with mechanical arm, mechanical arm terminal position and speed data, teaching m times when being fulfiled assignment with certain frequency f record；Step S2, track generate, by m time repeat teaching generate data set using Gaussian process return establish mapping model, obtain the time to position Function Mapping relationship；Step S3, autonomous to detect a flaw, the track that mechanical arm is generated according to step S2 drives failure detector to detect a flaw continuous welded rail track connector, while using location-based impedance control strategy, guarantees the constant-force contact of failure detector and joint surface in detection process.To the adaptability of continuous welded rail track joints when present invention study is manually detected a flaw, the contact force of control failure detector docking head surface is constant, realizes mechanical arm and detects a flaw to the autonomous profiling of rail joint, improves detection quality.
Description
Technical field
The present invention relates to track inspection fields, more particularly, to a kind of track profiling method of detection based on learning from instruction.
Background technique
With continuing to increase for train speed raising, heavy duty and rate of traffic flow, sub-rail foundation equipment is proposed more acute
Test is itself compared to rail, bigger to the damage capability of gapless rail joint.Gapless rail joint can generate weld seam and split
It the defects of line, pit, will affect the stationarity and safety of train operation, while rail can be accelerated to fail, bring biggish warp
Ji loss just can guarantee the quality of track, reduce the generation of accident so needing to carry out periodic detection to gapless rail joint.
For the research of track flaw detection, China has developed some achievements in recent years.Patent of invention (CN109212038) is announced
A kind of rail detector car and its probe layout system, including be set on car body, for raceway surface emit ultrasonic wave into
Several monocrystalline ultrasonic probes of row carrying out flaw detection, twin crystal ultrasonic probe and with adjustable ultrasonic incident angle function
Phased-array ultrasonic probe, and each probe can rotate horizontally, to adapt to different types of track.Patent of invention
(CN105109518A) disclose a kind of novel track inspection car, including a flat evacuation bottom plate, width be less than two rails it
Between width, height be less than rail height, further include multiple transmission shafts, two transmission shafts of the outermost at two tracks
Outer end be respectively provided with a rail wheel, track failure detector, the axle sleeve between the transmission shaft are installed on the rail wheel
Lower section is fixed with vertically flexible dipper crowding gear.
Existing rail detector car, failure detector fastening are set on car body, i.e. the relative position of failure detector and track
Fixed, the contact force of failure detector and raceway surface is uncontrollable, and can only detect a flaw along track to rail itself, cannot be right
Gapless rail joint carries out complete profiling flaw detection.And the flaw detection to gapless rail joint, main there are two main points, one is to visit
The profiling for hurting device along joint surface is moved, the other is the constant force control that failure detector is contacted with joint surface.
Summary of the invention
The track profiling method of detection based on learning from instruction that the object of the present invention is to provide a kind of, is able to solve background technique
The problems in, it overcomes the deficiencies of existing technologies, improves detection quality.
In order to solve the above technical problems, the present invention provides a kind of track profiling method of detection based on learning from instruction, including
Following steps:
Step S1, artificial teaching cooperate with the profiling flaw detection operation completed to continuous welded rail track connector by people with mechanical arm.People
Driving machinery arm completes flaw detection operation, the terminal position and speed of itself when mechanical arm is fulfiled assignment with certain frequency f record
Data, teaching m times；
The purpose of teaching is to complete flaw detection work, intermediate as long as the process of teaching can achieve the purpose that complete flaw detection work
The motion profile process of mechanical arm will not uniquely not influence the result of flaw detection work.
Step S2, track generate, and repeat the data set that teaching generates for m times and establish mapping mould using Gaussian process recurrence
Type, obtain the time to position Function Mapping relationship；
Step S3, autonomous to detect a flaw, the track that mechanical arm is generated according to step S2 drives failure detector to continuous welded rail track connector
It detects a flaw, while impedance is utilized that is, while controlling mechanical arm tail end position using location-based impedance control strategy
The control of power is converted correction position control by model, guarantees the constant-force contact of failure detector and joint surface in detection process.
Preferably, in step S1, the interaction of people and mechanical arm are realized using admittance controller, so that mechanical arm can be
Flaw detection operation is completed under the guidance of manpower, while remaining that failure detector is adjacent to continuous welded rail track joint surface.With certain frequency
The position data in each joint of mechanical arm, teaching m times when rate f record fulfils assignment.
Preferably, in step sl, by teaching process, n data point is collected on every trackIts
Middle t=[t1,t2,…,tn]TFor time point, x=[x1,x2,…,xn]TFor flaw detection point, the Descartes under robot coordinate system is sat
Mark；The likelihood function of time point and coordinate is obtained according to prior distribution:
Linear regression function f (t) based on bayesian theory=tTω, wherein t ∈ Rd, ω=[ω1,ω2,…,ωn]T,
F (t) representative function value.
Assuming that ω: (0, Σp), the probability distribution of ω is found out by the definition of bayesian theory and Gaussian Profile:
The Posterior probability distribution of ω is found out by maximum posteriori probability:
Wherein, p (x | t) is edge similar density, unrelated with weight ω, then another representation of formula (3):
p(ω|t,x)∝p(x|t,ω)p(ω) (4)
Wherein, ∝ expression is proportional to.Formula (1) and formula (2) is brought into formula (4), obtains the posterior probability point of weight vector ω
Cloth form:
Wherein,It enablesThe posterior probability of weight vector ω meets Gauss point
Cloth:
When there is data t*When input, corresponding predicted value x*Probability distribution are as follows:
It can be seen that predicted value x*Distribution or Gaussian Profile, manner is the Posterior probability distribution of weight vector ω
Mean value and data t*Product, variance is data t*With the quadratic form of the variance of the Posterior probability distribution of weight vector ω.
Preferably, in step s3, when executing flaw detection task, location-based impedance control strategy is by actually connecing
The deviation of touch and expected force obtains position deviation amount through impedance controller, and then adjusts the position of mechanical arm tail end failure detector
It sets, realizes the constant-force contact of failure detector and continuous welded rail track joint surface.
The beneficial effects of the present invention are: 1. are applied to learning from instruction in track flaw detection, to seamless when learning manually to detect a flaw
The adaptability of rail joint shape, it is only necessary to artificial teaching can carry out autonomous profiling flaw detection operation to gapless rail joint,
Improve flaw detection efficiency；2. realizing failure detector and nothing in detection process by using location-based impedance control strategy
The constant-force contact for stitching rail joint surface, improves detection quality.
Detailed description of the invention
Fig. 1 is the method for the present invention flow chart.
Fig. 2 is the impedance control block diagram the present invention is based on position.
Specific embodiment
Below with reference to the embodiments and with reference to the accompanying drawing the technical solutions of the present invention will be further described.
Embodiment:
In the embodiment of the present invention, artificial teaching is carried out first.The interaction that people and mechanical arm are realized using admittance controller, from
And mechanical arm can complete flaw detection operation under the guidance of manpower, cooperate with completion to continuous welded rail track connector with mechanical arm by people
Profiling flaw detection operation, mechanical arm terminal position and speed data, teaching m times when being fulfiled assignment with certain frequency f record.
Then track generation is carried out.The data set that teaching generates is repeated by m times, and foundation mapping mould is returned using Gaussian process
Type, obtain the time to position Function Mapping relationship.By teaching process, n data point is collected on every trackWherein t=[t1,t2,…,tn]TFor time point, x=[x1,x2,…,xn]TIt is flaw detection point under robot coordinate system
Cartesian coordinate；The likelihood function of time point and coordinate is obtained according to prior distribution:
Linear regression function f (t) based on bayesian theory=tTω, wherein t ∈ Rd, ω=[ω1,ω2,…,ωn]T,
F (t) representative function value.
Assuming that ω: (0, Σp), the probability distribution of ω is found out by the definition of bayesian theory and Gaussian Profile:
The Posterior probability distribution of ω is found out by maximum posteriori probability:
Wherein, p (x | t) is edge similar density, unrelated with weight ω, then another representation of formula (3):
p(ω|t,x)∝p(x|t,ω)p(ω) (4)
Wherein, ∝ expression is proportional to.Formula (1) and formula (2) is brought into formula (4), obtains the posterior probability point of weight vector ω
Cloth form:
Wherein,It enablesThe posterior probability of weight vector ω meets Gauss point
Cloth:
When there is data t*When input, corresponding predicted value x*Probability distribution are as follows:
It can be seen that predicted value x*Distribution or Gaussian Profile, manner is the Posterior probability distribution of weight vector ω
Mean value and data t*Product, variance is data t*With the quadratic form of the variance of the Posterior probability distribution of weight vector ω.
It is finally independently detected a flaw, the track that tool arm is generated according to step S2 drives failure detector to continuous welded rail track connector
It detects a flaw, while impedance is utilized that is, while controlling mechanical arm tail end position using location-based impedance control strategy
The control of power is converted correction position control by model, guarantees the constant-force contact of failure detector and joint surface in detection process.
Although having shown and having described the embodiment of the present invention above, it is to be understood that above-described embodiment is example
Property, it is not considered as limiting the invention, those skilled in the art is in the feelings for not departing from the principle of the present invention and objective
It can make changes, modifications, alterations, and variations to the above described embodiments, should belong to of the invention within the scope of the invention under condition
Protection scope.
Claims (2)
1. a kind of track profiling method of detection based on mechanical arm, which comprises the following steps:
Step S1, artificial teaching cooperate with the profiling flaw detection operation completed to continuous welded rail track connector, people's dragging by people with mechanical arm
Mechanical arm completes flaw detection operation, the terminal position and speed data of itself when mechanical arm is fulfiled assignment with certain frequency f record,
Teaching m times；
Step S2, track generate, and repeat the data set that teaching generates for m times and establish mapping model using Gaussian process recurrence, obtain
The Function Mapping relationship set in place to the time, specifically:
By teaching process, n data point is collected on every trackWherein t=[t1,t2,…,tn]TFor the time
Point, x=[x1,x2,…,xn]TFor cartesian coordinate of the flaw detection point under robot coordinate system；The time is obtained according to prior distribution
The likelihood function of point and coordinate:
Linear regression function f (t) based on bayesian theory=tTω, wherein t ∈ Rd, ω=[ω1,ω2,…,ωn]T, f (t)
Representative function value；
Assuming that ω: (0, Σp), the probability distribution of ω is found out by the definition of bayesian theory and Gaussian Profile:
The Posterior probability distribution of ω is found out by maximum posteriori probability:
Wherein, p (x | t) is edge similar density, unrelated with weight ω, then another representation of formula (3):
p(ω|t,x)∝p(x|t,ω)p(ω)(4)
Wherein, ∝ expression is proportional to；Formula (1) and formula (2) is brought into formula (4), obtains the Posterior probability distribution shape of weight vector ω
Formula:
Wherein,It enablesThe posterior probability of weight vector ω meets Gaussian Profile:
When there is data t*When input, corresponding predicted value x*Probability distribution are as follows:
It can be seen that predicted value x*Distribution or Gaussian Profile, manner is the mean value of the Posterior probability distribution of weight vector ω
With data t*Product, variance is data t*With the quadratic form of the variance of the Posterior probability distribution of weight vector ω；
Step S3, autonomous to detect a flaw, the track that mechanical arm is generated according to step S2 drives failure detector to carry out continuous welded rail track connector
Flaw detection, while by using location-based impedance control strategy shown in Fig. 2, guarantee failure detector and connector table in detection process
The constant-force contact in face；Specifically: the contact force for first acquiring failure detector and continuous welded rail track joint surface, by input impedance controller
Output displacement correction amount afterwards obtains the mechanical arm target to be adjusted then in conjunction with mechanical arm tail end failure detector home position
Position, target position are converted into the angle in each joint through mechanical arm inverse kinematics, are input in position control ring, then through machine
Tool arm forward kinematics solution exports the position actually adjusted, and failure detector and rail joint surface can generate new contact force at this time,
To realize closed-loop control.
2. the track profiling method of detection according to claim 1 based on mechanical arm, which is characterized in that in step s3,
It is the deviation by practical contact force and expected force using location-based impedance control strategy, through hindering when executing flaw detection task
Anti- controller obtains position deviation amount, and then adjusts the position of mechanical arm tail end failure detector, realizes failure detector and seamless rail
The constant-force contact of road joint surface.
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