CN112785891B - Steel rail flaw detection simulation learning training system platform and training method - Google Patents
Steel rail flaw detection simulation learning training system platform and training method Download PDFInfo
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Abstract
The invention discloses a steel rail flaw detection simulation learning practical training instrument, a training system platform and a practical training method, which are based on computer integration reproduction technology of existing steel rail flaw waveform map information and the like and behavior simulation research of steel rail flaw detection operation operators, and achieve the purposes of guiding flaw detection operators to stand a post, autonomously and efficiently improving service skills, and performing double cultivation of skills and responsibility, enhancing the steel rail flaw detection practical operation experience of the operators and rapidly improving the flaw detection analysis and judgment capability of the flaw detection operators; the training device is a training technical device integrating fragmentization, recreation and invasion type learning concepts. On one hand, a large amount of standard practical training materials are provided for practical training organizers, and training courses are creatively customized to achieve training intents; on the other hand, an autonomous learning environment is provided for the training personnel, the skill training is efficiently completed, and meanwhile, the execution of strict operation standards is realized, so that the aim of comprehensively improving the occupation literacy of trainees is fulfilled, and the method has popularization value in the aspect of realizing the rapid culture of flaw detection skill talents.
Description
Technical Field
The invention relates to the technical field of technical learning and training of rail flaw detection in the technology of railway rail application equipment, in particular to a rail flaw detection simulation learning training system platform and a training method.
Background
The steel rail flaw detector is a main force for preventing the steel rail from being broken and belongs to single-person operation, the level of self skill level directly determines the misjudgment rate and the missed detection rate of flaw detection work, and the misjudgment and the missed detection event slightly cause the waste of maintenance cost, and seriously directly threaten the railway transportation safety.
At present, a training base is built in the field of steel rail flaw detection training, a physical damaged rail is placed in the training base to serve as a training means, and the training is carried out in a mouth-to-mouth manner with a bare-training mode, so that on one hand, the investment is repeated, the investment is dispersed, the training damaged rail is not shared, and the scale effect is difficult to form; on the other hand, the steel rail flaw detector has long culture period, high culture cost, great training difficulty and outstanding engineering contradiction. On the other hand, the current rail flaw detection training is lack of training conditions, on one hand, rail damage is not concentrated, the distance between each damage is long, the time required for training practice is long, energy is consumed, the cost is high in all aspects, and therefore the current training and learning are completed in a training base, but the training base is few, and the requirements for increasingly training, multi-point training and fragmenting training cannot be met. In addition, the physical damaged rail is an in-service rail on a line, a rail with specific damage is naturally formed in the rolling process of a high-load train, and each natural damaged rail is unique and cannot be artificially copied. Because the formation of the injury type has deep regional characteristics, the injury type needs a lot of manpower, material resources and fields from the next procedure, collection and transportation to storage, and the injury type always needs a section or a local training scarce resource. Taking the applicant as an example: at the beginning of the 2016 construction period, 15 flaw detectors are extracted from 4 brother units, a flaw detection work area is established, for four years, 25 flaw detectors are cultured only marginally under the strong support of a work department and the vigorous culture of the flaw detectors by the self, most of the flaw detectors are still grade 1 at present, and in addition, the maintenance of the flaw detectors is conducted by the Shankun high-speed railway and the Nankun passenger which are opened at the end of 2016, the steel rails are good in condition, the practical training experience cannot be accumulated, and the overall flaw detection skill is weak, so that the flaw detectors are very unfavorable for the maintenance of the high-speed railway.
Today, with rapid development of science and technology, the traditional training mode cannot meet the requirements of vigorous energy and vigorous learning and desire of young people, a qualified flaw detector with independent flaw detection capability needs a culture period of 3-5 years, and cannot keep pace with the step of increasing equipment of group companies in recent years. How to rapidly and efficiently cultivate the flaw detectors with high quality and qualified ability of training places is a difficult problem in the current industry.
Disclosure of Invention
In order to solve the defects and defects of the prior art, in order to accelerate the culture of flaw detection personnel and reverse the situation that the reserves of on-site steel rail flaw detection skills are insufficient, an inventor research and development team constructs a steel rail flaw detection simulation implementation platform, effectively integrates a damaged rail data resource, establishes a damaged waveform database, develops a set of simulation means and an immersion type training mode at present, and realizes a system, equipment and a method for rapidly improving the technical skills of flaw detection industry. Specifically, the invention is realized by the following steps:
a rail flaw detection simulation learning training system platform comprises:
steel rail damage data resource library: the real rail damage waveform acquisition system is used for acquiring real rail damage generated in actual use and converting the real rail damage to a digital rail damage to form damage waveform data for storage; qualitative, positioning and quantitative analysis are carried out on each injury, and the injury is used as an injury judgment standard answer to form a database;
a walking chassis: the walking crawler comprises a walking crawler belt, a host module and a walking module, wherein the walking crawler belt is used for enabling a student to walk on site on the walking crawler belt, collecting walking speed information and moving direction information and sending the speed information and the moving direction information to the host module in a wired or wireless mode;
steel rail flaw detector: the system is installed on a simulated steel rail model and is fixed or walks in situ, is connected to a steel rail damage data resource library and a host module in a wired or wireless mode, and is used for receiving steel rail damage waveform data from the steel rail damage data resource library and displaying the received steel rail damage waveform data in the form of an image of a steel rail damage wave through an oscilloscope;
a host module: the system is used for loading or storing a steel rail damage data resource library, is connected with the traveling chassis and the steel rail flaw detector in a wired or wireless mode, can perform extraction, arrangement, classification, analysis and updating on data resources in the steel rail damage data resource library, and can send the data resources to the steel rail flaw detector for display and output.
In another aspect of the invention, a rail flaw detection simulation learning training method is provided, which comprises the following steps:
s1, acquiring real-object damage waveforms of real rail damage generated in actual use, and converting the real-object damage waveforms into digital damage waveforms to be stored; qualitative, positioning and quantitative analysis are carried out on each injury, and the injury is used as an injury judgment standard answer to form a database;
s2, loading or reading a rail damage data resource library, and transmitting damage waveform data to a rail flaw detector in a waveform image form;
s3, transmitting speed information and direction information of the trainee walking on the walking track to a steel rail flaw detector, and displaying the received damage waveform image on an oscilloscope of the steel rail flaw detector at corresponding speed and direction according to the received speed information and direction information;
s4, the trainees make corresponding injury judgment results based on the seen injury waveform images;
and S5, comparing the injury judgment result made by the student with the injury judgment standard answer information corresponding to the injury waveform image, judging whether the injury judgment result made by the student is correct or not, and recording or feeding back the standard answer in real time.
The working principle of the invention is introduced: the method integrates the physical damaged rail resources of the current global flaw detection training base, uses the same GT-20 steel rail flaw detector by a first technician of the section steel rail flaw detection, uses two interference sensitivities and one damage judging sensitivity to acquire the damage waveform, and accurately performs qualitative, positioning and quantitative analysis on each damage to be used as a standard damage judging answer. Carrying out unit splitting on the damage waveform by a waveform analysis team, establishing a damage database, completing the conversion from a physical damage rail to a digital damage rail, eliminating the exchange barrier of the physical damage rail among units, achieving the global shared scale effect and solving the high dependence of practical training on the physical damage rail; the method comprises the following steps of utilizing a steel rail flaw detection training instrument comprising a steel rail flaw detector, a walker and a learning all-in-one machine, controlling flaw detection speed by the walker, displaying flaw detection waveforms by the steel rail flaw detector, learning and answering by the learning all-in-one machine, highly simulating and restoring a steel rail flaw detection situation, simulating the field flaw detection advancing direction and speed by a student walking on the walker, and bringing the repeated flaw detection and flaw detection speed requirements in flaw detection operation standards into an evaluation system; reproducing the A/B ultrasonic waveform of the rail flaw detection by an oscilloscope, and simulating the detection of an on-site flaw detection instrument and the wave identification and damage judgment process of flaw detection personnel; the injury waveform collected by two interference sensitivities and one injury judging sensitivity is elaborately coiled by a trained organizer to simulate the adjustment of field flaw detection sensitivity. The objective evaluation is carried out according to the standard of the rail flaw detection technical match in the modes of answering on the product of the invention by the student or automatically collecting by the system, so as to achieve the intelligent management of the student's integral, and realize the continuous excitation of improving the interest of the training student's skill by the integral upgrading mechanism.
The invention has the beneficial effects that:
(1) The real rail damage is digitalized, the waveform image is extracted, and then the waveform image and the standard answer of the damage information are integrated to form image information which can be repeatedly played back for study of students, so that the functions of flaw detection study and training can be realized on the system platform, the visual, repeatable, mass-production and online flaw detection practice is realized, and the problem that the rail damage data is not dispersed and concentrated is solved;
(2) The system is scientifically and reasonably established, the existing mainstream steel rail flaw detection equipment is utilized, a notebook is additionally arranged to form a field waveform acquisition device, waveform acquisition, unit splitting and damage warehousing maintenance for subsequent damage discovery are completed, and damage dilatation can be conveniently realized; the method is convenient for an organization expert team to solidify the rail flaw detection standard in an assessment evaluation system, makes the damaged rail object anatomical data into a unique assessment standard answer in the future, and solves the problem of skill and responsibility double culture while carrying out good flaw detection habit culture in the immigration.
(3) The combined mode of the walker and the steel rail flaw detector is utilized, flaw detection speed is controlled by the walker, the steel rail flaw detector is synchronously displayed for displaying flaw detection waveforms, waveform display is consistent with walking speed of students, a display screen is used for displaying simulated rail track environment, even VR technology can be used for simulating the rail environment, damage waveform images are combined, steel rail flaw detection situations are highly simulated and reduced, a real work flow link of simulating flaw detection on rails is realized, an immersive learning and teaching mode is established, the problem that training can only be carried out in a centralized training base originally is solved, the problems that damage on real training rails is not centralized and the rails are frequently replaced for training are solved, efficiency is greatly improved, training cost is reduced, popularization and learning, training and testing operation can be quickly established at low cost;
(4) By utilizing an implementation training system, taking injury waveform composition paper with different difficulty levels and automatic marking after student answers as a core, establishing a personal skill assessment and evaluation system taking point management and game upgrading as carriers, leading workers to learn in an interesting way, and solving the problem of aversion to learning emotion; the multifunctional training machine has the advantages of being multifunctional, multi-mode, full-range targeted learning and training functions, effectively shortening the training period, reducing the training cost, improving the training efficiency, improving the learning efficiency and the practice efficiency, achieving excellent training effect and quality on the whole, and reducing the engineering contradiction.
Drawings
FIG. 1 is a side view of a rail flaw detection simulation learning training instrument;
FIG. 2 is a perspective view of a rail flaw detection simulation learning training instrument;
FIG. 3 is a schematic view of a coding wheel structure of a traveling chassis of a rail flaw detection simulation learning training instrument;
FIG. 4 is a schematic view of a rotating shaft mounting structure of a walking chassis of a steel rail flaw detection simulation learning practical training instrument;
FIG. 5 is a schematic structural diagram of a simulated rail model of a rail flaw detection simulation learning training instrument on a mounting rack;
FIG. 6 is a schematic structural diagram of a rail flaw detection simulation learning training system platform;
FIG. 7 is a schematic flow chart of a rail flaw detection simulation learning training method;
FIG. 8 is a diagram of a content module in the training learning module;
FIG. 9 is a supplementary view of the amount of data in the damage database;
FIG. 10 is a schematic diagram showing the variation of time that trainees can practice weekly after using the product of the present invention;
fig. 11 and 12 are waveform diagrams illustrating rail flaws.
Wherein: the device comprises a traveling chassis 1, a traveling chassis 2, a mounting rack, a damping disc 3, an operation display screen 4, an imitation steel rail model 5, a steel rail flaw detector 6, an oscilloscope 7, a walking crawler 8, a pushing handle 9, a rotating shaft 10, a bearing seat 11, a cross arm 13, a coding wheel 12, a fixing rack hanger 14, a wheel box 15, a mounting seat 16, a screw 17 and a traveling wheel 18.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings in conjunction with the following detailed description. It should be understood that the description is intended to be exemplary only, and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.
Example 1: a rail flaw detection simulation learning training instrument comprises: walking chassis 1, install in the mounting bracket 2 of walking chassis 1 front end, install host computer and operation display screen 4 on the mounting bracket 2, install imitative rail model 5 in walking chassis 1 front end one side, install a rail flaw detector 6 on imitative rail model 5, host computer and operation display screen 4 realize data interconnection with rail flaw detector 6 with wired or wireless mode, oscilloscope 7 of installing on the rail flaw detector 6 is used for showing the data waveform image of detecting a flaw that comes from the host computer and sends. A student stands on a walking crawler 8 of a walking chassis 1, starts a host, operates a display screen 4, performs preparation work before flaw detection work according to system language prompts, selects a corresponding mode, prepares flaw detection data waveform image data, holds a steel rail flaw detector 6 by the student to start walking, and directly or indirectly drives a coding wheel 12 to be installed on a rotating shaft 10 in front of the walking crawler 8 inside the walking crawler 8, wherein the coding wheel 12 is used for recording the rotating speed and direction information of the walking crawler 8, namely the rotation of the walking crawler 8 can transmit motion information to the coding wheel 12 to drive the coding wheel 12 to move forwards or backwards, so that the motion information of the walking crawler 8 is obtained and transmitted to the steel rail flaw detector 6; a data receiving element and an image playing element are installed in an oscilloscope 7 of the steel rail flaw detector 6, the data receiving element is used for receiving damage waveform image information prepared by a host computer, the image playing element is used for playing the received damage waveform image information through the oscilloscope 7, the speed of playing the damage waveform image information by the image playing element is acquired by connecting the image playing element to a coding wheel 12, when a forward rotation signal and a speed signal sent by the coding wheel 12 are received, the image playing element plays the damage waveform image signal forward at the same or matched speed, and when a reverse rotation signal and a speed signal sent by the coding wheel 12 are received, the image playing element plays the damage waveform image backward at the same or matched speed, so that the image playing of the oscilloscope 7 is synchronous with the walking crawler 8; the student knows the injury information according to the observed injury waveform image, at the moment, the host sends the injury information corresponding to the currently displayed injury waveform image to the operation display screen 4, the student acquires the information corresponding to the injury waveform image through the operation display screen 4 to learn, or the student judges the injury type and the information corresponding to the injury waveform image through the operation display screen 4 or answers the judgment information by answering questions, so that the purposes of learning and training are achieved. In the whole process, a student walks by holding the handrail of the steel rail flaw detector 6 on the walking crawler 8, a behavior mode in the actual flaw detection process is simulated, an image of a flaw waveform is also displayed in a simulation mode, and the whole process and the walking speed direction of the student are synchronous, so that strong immersive learning experience is generated, and the process of performing rail flaw detection on a real rail is simulated.
Preferably, the walking chassis 1 can bear 160kg, the length and width of the sports chassis are 2000mm multiplied by 900mm, the design of the arc chassis is most suitable for ergonomics, although the design advantage is outstanding in endurance running, the damage to the knees and ankles of a human body caused by long-time sports is avoided, the requirements of daily training, teaching or detection are greatly met, the walking chassis can be perfectly replaced into a high-end treadmill in leisure time, the walking crawler 8 adopts an anti-skidding design, the friction force on the crawler is large, and the walking chassis is prevented from skidding in the sports process. Because the device adopts a unpowered motion mode, the device is more environment-friendly and energy-saving. Preferably, if there is a demand, can also install driving motor additional, drive walking track 8 and rotate with variable, controllable speed, or, can install microgenerator additional, form from electricity generation running chassis, provide the electric energy for other equipment.
Preferably, the mounting frame 2 of the simulated steel rail model 5 is arranged on the inner side close to the front end of the walking crawler 8, the length of the mounting frame is not less than that of the steel rail flaw detector 6, the size and the model of the mounting frame are the same as those of a steel rail track in practical application, the steel rail flaw detector 6 is mounted on the simulated steel rail model 5, the running direction of the steel rail flaw detector is the same as the front direction of the walking chassis 1, the oscilloscope 7 faces the direction of the walking crawler 8, and a push handle 9 of the steel rail flaw detector 6 is arranged below the oscilloscope 7. In the whole process, the student walks by holding the handle of the steel rail flaw detector 6 on the walking crawler 8, the behavior mode in the actual flaw detection process is simulated, the image of the flaw waveform is also displayed in a simulation mode, and the walking speed directions of the whole process and the student are synchronous, so that strong immersive learning experience is generated, and the process of performing rail flaw detection on a real rail is simulated.
The walking crawler 8 is arranged between the front end and the rear end of the walking chassis 1 through a front rotating shaft 10 and a rear rotating shaft 11 and a bearing seat 11, the middle part of the walking crawler 8 is opposite to the arc-shaped chassis with two concave end parts, and the rotating shaft 10 is provided with a damping disc 3 with an adjustable damping value. The walking chassis 1 can bear 160kg, the length and width of the sports chassis is 2000mm multiplied by 900mm, the design of the arc-shaped chassis is the most suitable for human engineering, although the design advantage is outstanding in endurance running, the damage to the knees and ankles of a human body caused by long-time sports is avoided, the requirements of daily training, teaching or detection are far met, the walking chassis can be perfectly replaced into a high-end treadmill when in leisure, the walking crawler 8 adopts an anti-skidding design, the friction force on the crawler is large, and the walking chassis is prevented from skidding in the movement. Because the device adopts a unpowered motion mode, the device is more environment-friendly and energy-saving.
Preferably, the simulated steel rail model 5 is detachably mounted on the mounting frame 2, and can be respectively mounted and fixed on the left side surface or the right side surface of the walking chassis 1. The method is used for simulating flaw detection operation on the left steel rail and the right steel rail in training.
Preferably, the industrial control integrated machine which is designed by integrating the host and the operation display screen 4 is installed at the top of the installation frame 2 and faces the middle of the walking chassis 1, and the industrial control integrated machine is connected to a server of the steel rail flaw detection simulation practical training system platform or is independently installed and operated with the steel rail flaw detection simulation practical training system platform in a wireless or wired communication mode. The industrial control all-in-one machine is used for loading or storing a steel rail damage data resource library, is connected with the walking chassis 1 and the steel rail flaw detector in a wired or wireless mode, can send data resources to the steel rail flaw detector to display and output, can use a cloud end and a remote system to replace hardware, forms a cloud end server through the internet technology, and realizes online operation of a system platform.
After the system platform is started, the main program and the functional devices of the system are operated by the host module, the corresponding teaching module or training module is operated by the host module, and the subprogram of learning or training is started, so that the corresponding data in the rail damage data resource library is called, the data is controlled to be output to the rail flaw detector, and the learning or training is started.
And the speed information and the moving direction information acquired by the walking chassis 1 are transmitted to the steel rail flaw detector, so that the moving direction and speed of the image of the steel rail damage wave displayed by the oscilloscope 7 on the steel rail flaw detector are matched or consistent with the speed and direction acquired by the walking chassis 1. The purpose is that let the student walk at 8 handrails of walking rail flaw detector 6, has simulated the behavioral pattern of actual flaw detection in-process, also the emulation image that shows the impairment waveform, and whole process and student's walking speed direction all are synchronous, so produced very strong immersive study and experienced, has simulated the process of carrying out the track on real track and detected a flaw, promotes teaching and training quality.
Preferably, a cross arm 13 is further installed between the mounting frames 2, a fixing frame hanger 14 is hung on the cross arm 13, and the fixing frame hanger 14 extends downwards to be fastened and connected with the steel rail flaw detector 6 in a detachable structure so as to fix the steel rail flaw detector 6. When the device is used, the flaw detector can be fixed by the fixing frame hanger 14, and the travelling wheel 18 of the flaw detector is locked by adopting a mechanical locking mode, so that an operator can simulate a real scene to the maximum extent when walking on the moving chassis, and great help is provided for the service level of the operator;
preferably, a pair of wheel boxes 15 is respectively installed on two side surfaces of the simulated steel rail model 5, and the arrangement positions, the size intervals and the heights of the four wheel boxes 15 correspond to four traveling wheels 18 of the steel rail flaw detector 6, so that the steel rail flaw detector 6 is placed on the four wheel boxes 15 through the four traveling wheels 18 so as to be placed on the simulated steel rail model 5. The bottom of the simulated steel rail model 5 is arranged on the mounting seat 16 in a mounting mode of adjusting the height in a lifting mode, and the mounting seat 16 is detachably arranged on the mounting seat 16 through screws. The mounting seat 16 is provided with at least one mounting hole, the bottom of the simulated steel rail model 5 is provided with at least one screw rod 17 penetrating through the mounting hole for mounting at a corresponding part, and the simulated steel rail model 5 can realize the height relative to the mounting seat 16 through adjusting the screw rod 17.
The whole machine adopts a centralized power supply structure, mainly carries out comprehensive power supply for the industrial control integrated machine and the flaw detector, the walking chassis 1 is in a structural design without power drive and does not need power supply, and the walking chassis rotates by the force of a student walking on the walking chassis to realize in-situ walking;
the comprehensive power supply is connected with a total branch power supply of 4 paths from a 220V household power supply: the comprehensive power supply is uniformly controlled by a single-pole double-throw switch, and the unified opening and closing of 4 power supplies can be realized.
Real standard appearance of rail flaw detection emulation study is at least one deck insulating layer of complete machine shell spraying, and it has the transformer to change 220V alternating current into direct current and supply rail flaw detector 6 to use, and mounting bracket 2 is whole to be the cold-rolled steel sheet manufacturing, and embedded installation operation display screen 4 of operation panel or the industry control all-in-one at 2 tops of mounting bracket.
Example 2: a rail flaw detection simulation learning training system platform comprises:
steel rail damage data resource library: the real rail damage waveform acquisition system is used for acquiring real rail damage generated in actual use and converting the real rail damage to a digital rail damage to form damage waveform data for storage; qualitative, positioning and quantitative analysis are carried out on each injury, and the injury is used as an injury judgment standard answer to form a database; the acquisition of a damage waveform and the extraction and conversion of digitalized damage data and waveform image data are conventional means, the technical details are not described in detail in the embodiment, and the steel rail damage data resource library is a damaged rail information database which is built based on real rail damage data in daily rail flaw detection work and comprises a damaged waveform image, damaged basic information and the like;
a walking chassis: the walking crawler comprises a walking crawler belt, a host module and a walking module, wherein the walking crawler belt is used for enabling a student to walk on site on the walking crawler belt, collecting walking speed information and moving direction information and sending the speed information and the moving direction information to the host module in a wired or wireless mode;
steel rail flaw detector: the system is installed on a simulated steel rail model and is fixed or walks in situ, is connected to a steel rail damage data resource library and a host module in a wired or wireless mode, and is used for receiving steel rail damage waveform data from the steel rail damage data resource library and displaying the received steel rail damage waveform data in the form of an image of a steel rail damage wave through an oscilloscope; a rail flaw detector, i.e., the rail flaw detector in example 1;
a host module: the system is used for loading or storing a steel rail damage data resource library, is connected with the traveling chassis and the steel rail flaw detector in a wired or wireless mode, can perform extraction, arrangement, classification, analysis and updating on data resources in the steel rail damage data resource library, and can send the data resources to the steel rail flaw detector for display and output. The host module can be regarded as an industrial control all-in-one machine, can be a computer host independent from the equipment, is connected to other functional components of the invention in a wired or wireless mode, and can also be built in the product of the invention. The method is mainly used for processing and analyzing the damage data and the like; such as the expansion and supplement of the database, the modification and editing, the teaching mode and the setting of the teaching content. Correspondingly, the host module can use the cloud end and the remote system to replace hardware, a cloud end server is formed through the internet technology, and online operation of a system platform is achieved.
After the system platform is started, the main program and the functional devices of the system are operated by the host module, the corresponding teaching module or training module is operated by the host module, and the subprogram of learning or training is started, so that the corresponding data in the rail damage data resource library is called, the data is controlled to be output to the rail flaw detector, and the learning or training is started.
Preferably, the system platform of the embodiment further comprises a training learning module, which is connected with or installed in the host module, and comprises an interactive display screen, which can receive and display data resources sent by the host module and receive operation instruction feedback of the trainee to perform multifunctional interaction with the trainee; the rail damage training information formed based on the data resources can be stored, edited and output, the rail damage training information can be output to the trainees in a test, practice or teaching mode, and whether the corresponding operation or answer made by the trainees is correct or not can be judged. The interactive display screen is used for displaying necessary interfaces, information, interactive buttons and the like for system operation, is designed for the touch screen, can control the host module to perform mode selection, system login and other operations through the interactive display screen, can call data in the steel rail damage data resource library, arranges, classifies and arranges the data according to a set program, and outputs the data according to the program, for example, the interactive display screen has a plurality of teaching modes, comprises basic knowledge, middle-level knowledge, high-level knowledge and the like, and plays, demonstrates and trains the teaching modes according to the teaching program content; and testing, wrong question collection, testing and the like can be performed according to the teaching requirements, so that the purposes of learning and training are achieved.
Preferably, the data resource is sent to the steel rail flaw detector for display and output, and the method comprises the following steps: and transmitting the speed information and the moving direction information acquired by the walking chassis to the steel rail flaw detector, so that the moving direction and speed of the image of the steel rail damage wave displayed by an oscilloscope on the steel rail flaw detector are matched or consistent with the speed and direction acquired by the walking chassis. The purpose is that let the student walk at the handrail of walking rail flaw detector on the track of walking, has simulated the behavioral pattern of actual flaw detection in-process, the image that has also simulated the demonstration impairment waveform, and whole process and student's walking speed direction all are synchronous, so produced very strong immersive study and experienced, has simulated the process of carrying out the track on real track and detecting a flaw, promotes teaching and training quality.
Preferably, the physical damage waveform acquisition comprises: collecting injury waveforms by using two interference sensitivities and one injury judging sensitivity; the steel rail flaw detector can also be used for adjusting the interference sensitivity or the gear of the flaw detection sensitivity by a student in the process of simulating the flaw detection and the judgment, so that the oscilloscope displays the A-type, B-type or A + B ultrasonic waveform corresponding to the steel rail flaw detection when displaying the flaw waveform image. Based on different damage characteristics in the flaw detection process, different frequencies are required to be used for detection, so that a flaw detector needs to form experience on the detection characteristics of the damage, namely, flaw detection frequency is switched, the damage is found, and the content of training and repeated practice is required, so that when the damage is collected, different band frequencies are used for collecting for multiple times to realize full-band data collection, a section of data information is separately formed and corresponds to the same damage, a student can manually switch the current frequency band in the actual training process, correspondingly, image data information corresponding to the corresponding band is displayed on an oscilloscope, and the operation details of simulating frequency band switching in the flaw detection process are realized; according to the steel rail flaw detection simulation learning training system platform, the thought of the internet is used for constructing a damage database, the existing digital waveform and anatomical picture of a real object damage rail are collected according to specific requirements, and the digital waveform and anatomical picture are divided into independent damage units to be stored after being in one-to-one correspondence. In a learning module of the system, the learning module provides the trainees with classification and learning one by one from the aspects of wave outlet channels, waveform display, A/B ultrasonic contrast analysis, injury judgment and the like, helps the trainees to search for the law of the injury wave outlet and meets the requirements of short-time high frequency and character symbol-ahead image of the trainees in the identification stage. In addition, shooting a flaw detection operation standard execution video, loading the video into a learning module, and carrying out detailed and minute teaching on students from the aspects of instrument testing, debugging of flaw detection sensitivity, adjustment of probe positions in various scenes, daily maintenance of instruments and the like. In addition, the learning module collects and arranges damage wave pattern data, typical damage analysis reports and accident teaching accumulated by brothers over the years, so that the visual field of the student is widened, and the perceptual knowledge of the student on the seriousness of the flaw detection work is deepened. The requirement that the learner can understand the sound image before the character symbol in the recognition stage is met.
Preferably, according to practical training requirements, the training learning module is used for carrying out injury identification and judgment on one piece of flaw detection data with a specific training intention formed by combining unit injuries, anatomical data is used as standard answers for injury qualification, positioning and quantification, the whole training process from injury identification to judgment of a steel rail flaw detector is perfectly explained, and uncertainty of injury quantification is avoided. Secondly, during course setting, training organizers can set training scenes and damage types and difficulty levels independently, instrument testing, preparation before the previous course, flaw detection under various scenes to instrument maintenance after operation, an immersive training environment is constructed, a background simultaneously provides three flaw detection waveforms consisting of two interference sensitivities and one damage judging sensitivity for students to switch, sensitivity adjustment in the pushing process of the flaw detector is strengthened, one-day operation standards of steel rail flaw detection are solidified in a course setting and assessment system, the rigidness of flaw detection work is reflected in repeated training of filling flaw detection logs, damage notification books and match answer sheets, good flaw detection habits are cultured for the students in the stealth training process, and the problem of double culture of skills and responsibility centers is solved.
Specifically, the resource data form of the rail damage training information includes one or more of the following:
classifying and sorting according to the damage type of the steel rail damage, and performing training output in a single-class or mixed-class mode according to the damage type;
sorting according to the damage depth distance of the damaged steel rail, and performing training output according to the ordered or disordered arrangement mode of the damage depth distance;
classifying and sorting according to the length of the damaged crack of the damaged steel rail, and performing training output according to the orderly or unordered arrangement mode of the length of the damaged crack;
sorting according to the damage grade of the steel rail damage, and performing training output according to the orderly or disordered arrangement mode of the damage grade;
sorting according to the difficulty degree of the damage of the steel rail, and carrying out training output in a mode of mixing the difficulty degrees of the damage with the same degree or different degrees;
and (4) training and outputting damage data acquired according to an actual real track in a real generation sequence or random sequence mode.
Meanwhile, the training learning module can establish personal file information of the students, record, store, output and analyze learning data of each time or all the students, and can count and record the accuracy, error information and flaw detection rate of the students in the learning process; the student scoring mode is established and a ranking list is formed, and learning stage tasks, learning periods, learning modes, wrong-question review, stage testing or/and student evaluation functions can be formulated.
For example, an implementation training system is developed, a damage waveform group chart with different difficulty levels and a system automatic marking after the answer of a student are taken as a core, four modules of learning, practical training, attacking and practicing are divided, the requirements of personal skill improvement and practical training organization practicing of flaw detection workers at different levels are met from flaw detection entry learning, four practical training levels promotion, the ranking list of the attacking and the attacking at the same level to practice training of practicing, and seamless butt joint of a conversion stage and an output stage is achieved. Meanwhile, a personal skill assessment and evaluation system with point management and game upgrading as carriers is established, so that the system leads workers to interesting learning and solves the problem of aversion to learning.
The system platform is developed and tried in my section since 4 months in 2020, and a personal learning system mainly comprising a learning module and a practical training module, a personal incentive system mainly comprising an attacking module and a skill PK system mainly comprising a practicing module are formed. 180 real object damaged rail resources of 5 flaw detection training bases of a group company are integrated successively, a first technician of section rail flaw detection adopts the same GT-20 rail flaw detector, two interference sensitivities and one judging sensitivity are used for acquiring a damaged waveform, 200 damaged units are put in storage, and quarter technical match is organized for 2 times, so that the practical training problem that natural damaged rail resources do not exist in the section is solved, and the current flaw detection practical training situation that instrument testing is mainly used in the section, workshop and work area is changed.
The platform integrates fitness and practical training, and utilizes fragment time to realize interesting learning, so that the engineering contradiction is solved, the learning experience of people is enriched, the platform is popular with workers since trial, and the daily practical training time of the workers in the flaw detection work area in Kunming is increased from 0.17 hour per month to 8 hours per month.
A steel rail flaw detection simulation training platform is a training technical device integrating fragmentization, recreation and sink-invasion learning concepts. On one hand, a large amount of standard practical training materials are provided for practical training organizers, and training courses are creatively customized to achieve training intents; on the other hand, an autonomous learning environment is provided for training personnel, and the execution of strict operation standards is realized while the skill training is efficiently completed, so that the aim of comprehensively improving the occupation literacy of trainees is fulfilled. The platform creates an immersive practical training environment, follows the principle of natural acquisition of human brain, and based on the application of damage waveform big data, the platform can highlight core practical training of students on detection waveform identification, analysis and judgment, standard execution and the like, can attract and stimulate students to autonomously and efficiently promote business skills by means of point management and game upgrading, and has popularization value in the aspect of realizing rapid culture of fault detection skills.
Example 3: a steel rail flaw detection simulation learning practical training method comprises the following steps:
s1, acquiring real-object damage waveforms of real rail damage generated in actual use, and converting the real-object damage waveforms into digital damage waveforms to be stored; qualitative, positioning and quantitative analysis are carried out on each injury, and the injury is used as an injury judgment standard answer to form a database;
s2, loading or reading a rail damage data resource library, and transmitting damage waveform data to a rail flaw detector in a waveform image form;
s3, transmitting speed information and direction information of the trainee walking on the walking track to a steel rail flaw detector, and displaying the received damage waveform image on an oscilloscope of the steel rail flaw detector at corresponding speed and direction according to the received speed information and direction information; 1. can be manually controlled according to the advancing speed of the human body (the walking speed supports the self-control within the range of 1-10 km/h); 2. the functions of retreating and stopping in situ are added, the requirements of human engineering and safe operation are met, and the requirements of simulating field simulation flaw detection are met; a common unpowered walking machine is purchased for modification, the walking machine can transmit the walking direction and speed parameters to a steel rail flaw detector and is used as a control signal to determine flaw detection waveform data A, B super display; 3. transforming a coding wheel and an oscilloscope of the GT-20 flaw detector, connecting the walker with the flaw detector, and adjusting a damping disc of the walker, 4. Displaying content operation prompts, a question display lamp and a 21.5-inch screen by utilizing an industrial control all-in-one machine; the power consumption is less than 90W; CPU4 core, 1.8GHz dominant frequency; 4.4G memory; 5.64G built-in memory; transmitting the damage waveform image to an oscilloscope;
s4, the trainees make corresponding injury judgment results based on the seen injury waveform images; the damage waveform image is shown in the legend of fig. 11 and 12;
and S5, comparing the injury judging result made by the student with injury judging standard answer information corresponding to the injury waveform image, judging whether the injury judging result made by the student is correct or not, and recording or feeding back the standard answer in real time.
The real object damage waveform acquisition comprises the following steps: collecting injury waveforms by using two interference sensitivities and one injury judging sensitivity; in step S4, the method further includes: the trainee can adjust the gear of the interference sensitivity or the damage judging sensitivity in the process of simulating wave identification and damage judgment, so that the oscilloscope displays the A-type, B-type or A + B ultrasonic wave shape corresponding to the rail flaw detection when displaying the damage waveform image.
Preferably, the loading or reading of the rail damage data repository further comprises:
classifying and sorting according to the damage type of the steel rail damage, and performing training output in a single-class or mixed-class mode according to the damage type; the training system is used for carrying out classification management on various common types of injuries, and can be convenient for students to carry out special exercises aiming at weak link types, so that the pertinence of learning and training is improved; correspondingly, classification and sorting can be carried out according to the damage depth distance of the damaged steel rail, and training output can be carried out according to the ordered or disordered arrangement mode of the damage depth distance; classifying and sorting according to the length of the damaged crack of the damaged steel rail, and performing training output according to the orderly or unordered arrangement mode of the length of the damaged crack; sorting according to the damage grade of the steel rail damage, and performing training output according to the ordered or disordered arrangement mode of the damage grade; the classification and the arrangement are carried out according to the difficulty degree of the damage of the steel rail, and the training output can be carried out in a mode of mixing the difficulty degrees of the damage with the same degree or different degrees, so that a gradual and gradual learning process from easy to difficult can be conveniently formed, and the learning quality is improved; the real damage data collected by the track can be actually output in a training mode in a real generation sequence or a random sequence, simulation is carried out, and training experience is improved. The specific learning and training contents can be drawn up according to the actual situation, as shown in fig. 8.
In the embodiment, the damaged data is acquired by sharing natural damaged rails of each work section, and the physical damaged rail ultrasonic flaw detection waveform information resource is used for replacing the physical damaged rail, as shown in fig. 9, so that the damaged rail database is expanded to meet the requirements of flaw detection training conditions. The workers in the flaw detection work area can be trained by using 30 minutes of fragment time every day, and the working time of 22 days every month, so that the training duration of not less than 8 school hours can be realized every month, as shown in fig. 10.
The present example analyzes and concludes: the quality of the group members is high, on the basis of successful development of the practical training instrument, the specific management measures are adopted for the flaw detection practical training, and the target is feasible.
The steel rail flaw detector is a main force for preventing the steel rail from being broken, belongs to single-person operation, and is particularly important for improving the skills of the flaw detector in daily flaw detection practice training. The development of the flaw detection training instrument provides a brand-new solution for daily flaw detection training.
The invention is based on computer integration reproduction technology of existing steel rail flaw waveform, map information and the like and behavior simulation research of steel rail flaw detection operation operators, and trial-produces corresponding steel rail flaw detection operation practical training equipment so as to enhance the experience of steel rail flaw detection practical operation of the operators and achieve the purpose of rapidly improving analysis and judgment capabilities of flaw detectors compared with the existing training mode.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modification, equivalent replacement, improvement and the like made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. Further, it is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.
Claims (9)
1. The utility model provides a rail flaw detection simulation learning training system platform which characterized in that including:
steel rail damage data resource library: the real rail damage waveform acquisition system is used for acquiring real rail damage generated in actual use and converting the real rail damage to a digital rail damage to form damage waveform data for storage; qualitative, positioning and quantitative analysis are carried out on each injury, and the injury is used as an injury judgment standard answer to form a database;
a walking chassis: the walking crawler comprises a walking crawler belt, a host module and a walking module, wherein the walking crawler belt is used for enabling a student to walk on site on the walking crawler belt, collecting walking speed information and moving direction information and sending the speed information and the moving direction information to the host module in a wired or wireless mode;
steel rail flaw detector: the system is installed on a simulated steel rail model and is fixed or walks in situ, is connected to a steel rail damage data resource library and a host module in a wired or wireless mode, and is used for receiving steel rail damage waveform data from the steel rail damage data resource library and displaying the received steel rail damage waveform data in the form of an image of a steel rail damage wave through an oscilloscope;
a host module: the system is used for loading or storing a steel rail damage data resource library, is connected with the traveling chassis and the steel rail flaw detector in a wired or wireless mode, can perform extraction, arrangement, classification, analysis and updating on data resources in the steel rail damage data resource library, and can send the data resources to the steel rail flaw detector for display and output.
2. The steel rail flaw detection simulation learning training system platform according to claim 1, further comprising a training learning module connected with or installed in the host module, and comprising an interactive display screen capable of receiving and displaying data resources sent by the host module and receiving operation instruction feedback of a trainee to perform multifunctional interaction with the trainee; the rail damage training information formed based on the data resources can be stored, edited and output, the rail damage training information can be output to the trainees in a testing, practicing or teaching mode, and whether the corresponding operation or answer made by the trainees is correct or not can be judged.
3. The steel rail flaw detection simulation learning training system platform according to claim 1, wherein the sending of the data resource to the steel rail flaw detector for display output comprises: and transmitting the speed information and the moving direction information acquired by the walking chassis to the steel rail flaw detector, so that the moving direction and speed of the image of the steel rail damage wave displayed by an oscilloscope on the steel rail flaw detector are matched or consistent with the speed and direction acquired by the walking chassis.
4. The steel rail flaw detection simulation learning training system platform according to claim 1, wherein the physical flaw waveform acquisition comprises: collecting injury waveforms by using two interference sensitivities and one injury judging sensitivity; the steel rail flaw detector can also be used for adjusting the interference sensitivity or the gear of the flaw detection sensitivity by a student in the process of simulating the flaw detection and the judgment, so that the oscilloscope displays the A-type, B-type or A + B ultrasonic waveform corresponding to the steel rail flaw detection when displaying the flaw waveform image.
5. The rail flaw detection simulation learning training system platform of claim 2, wherein the resource dataform of the rail flaw detection training information includes one or more of:
classifying and sorting according to the damage type of the steel rail damage, and performing training output in a single-class or mixed-class mode according to the damage type;
sorting according to the damage depth distance of the damaged steel rail, and performing training output according to the ordered or disordered arrangement mode of the damage depth distance;
classifying and sorting according to the length of the damaged crack of the damaged steel rail, and performing training output according to the orderly or unordered arrangement mode of the length of the damaged crack;
sorting according to the damage grade of the steel rail damage, and performing training output according to the orderly or disordered arrangement mode of the damage grade;
classifying and sorting according to the difficulty level of judging damage of the steel rail, and carrying out training output according to the mode of mixing the difficulty levels of judging damage to the same degree or different degrees;
and training and outputting damage data acquired according to actual real tracks in a real generation sequence or random sequence mode.
6. The rail inspection simulation learning training system platform of claim 2, wherein the training learning module is further operable to one or more of:
the personal file information of the students is established, each time or all learning data of each student can be recorded, stored, output and analyzed, and the accuracy, error information and flaw detection rate of the students in the learning process can be counted and recorded;
the student scoring mode is established and a ranking list is formed, and learning stage tasks, learning periods, learning modes, wrong-question review, stage testing or/and student evaluation functions can be formulated.
7. A steel rail flaw detection simulation learning practical training method is characterized by comprising the following steps:
s1, acquiring real-object damage waveforms of real rail damage generated in actual use, and converting the real-object damage waveforms into digital damage waveforms to be stored; qualitative, positioning and quantitative analysis are carried out on each injury, and the injury is used as an injury judgment standard answer to form a database;
s2, loading or reading a rail damage data resource library, and transmitting damage waveform data to a rail flaw detector in a waveform image form;
s3, transmitting speed information and direction information of the trainee walking on the walking track to a steel rail flaw detector, and displaying the received damage waveform image on an oscilloscope of the steel rail flaw detector at corresponding speed and direction according to the received speed information and direction information;
s4, the trainees make corresponding injury judgment results based on the seen injury waveform images;
and S5, comparing the injury judging result made by the student with injury judging standard answer information corresponding to the injury waveform image, judging whether the injury judging result made by the student is correct or not, and recording or feeding back the standard answer in real time.
8. The steel rail flaw detection simulation learning practical training method according to claim 7, wherein in the step S1, the acquiring of the physical flaw waveform comprises: collecting injury waveforms by using two interference sensitivities and one injury judging sensitivity; in step S4, the method further includes: the trainee can adjust the gear of the interference sensitivity or the damage judging sensitivity in the process of simulating wave identification and damage judgment, so that the oscilloscope displays the A-type, B-type or A + B ultrasonic wave shape corresponding to the rail flaw detection when displaying the damage waveform image.
9. The steel rail flaw detection simulation learning practical training method according to claim 7, wherein in the step S2, loading or reading the steel rail damage data resource library further comprises: one or more of the following:
classifying and sorting according to the damage types of the damaged steel rails, and performing training output in a single-class or mixed-class mode according to the damage types;
sorting according to the damage depth distance of the damaged steel rail, and performing training output according to the ordered or disordered arrangement mode of the damage depth distance;
classifying and sorting according to the length of the damaged crack of the damaged steel rail, and performing training output according to the orderly or unordered arrangement mode of the length of the damaged crack;
sorting according to the damage grade of the steel rail damage, and performing training output according to the ordered or disordered arrangement mode of the damage grade;
classifying and sorting according to the difficulty level of judging damage of the steel rail, and carrying out training output according to the mode of mixing the difficulty levels of judging damage to the same degree or different degrees;
and training and outputting damage data acquired according to actual real tracks in a real generation sequence or random sequence mode.
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| CN101699273A (en) * | 2009-10-29 | 2010-04-28 | 北京交通大学 | Auxiliary detection device and method of image processing for on-line flaw detection of rails |
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| SU1018142A1 (en) * | 1981-10-30 | 1983-05-15 | Московско-Курское Отделение Московской Железной Дороги | Simulator |
| CN202661445U (en) * | 2012-07-18 | 2013-01-09 | 长安大学 | Rail flaw detector |
| CN203148700U (en) * | 2013-03-06 | 2013-08-21 | 广州市特种机电设备检测研究院 | Wheel type track structure for explosion-proof test |
| CN103226132B (en) * | 2013-04-25 | 2014-12-10 | 哈尔滨工业大学 | High speed railway steel rail flaw detection experiment platform and detection method |
| CN203386407U (en) * | 2013-06-09 | 2014-01-08 | 柳州铁道职业技术学院 | Simulation teaching platform of railway seamed curve track |
| CN207225355U (en) * | 2017-07-26 | 2018-04-13 | 广东汕头超声电子股份有限公司 | A kind of electronic double track inspection car |
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| US11254336B2 (en) * | 2018-12-19 | 2022-02-22 | Nordco Inc. | Rail flaw detector |
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