CN211869371U

CN211869371U - Intelligent obstacle detection vehicle based on modular control

Info

Publication number: CN211869371U
Application number: CN201921494540.4U
Authority: CN
Inventors: 刘家�; 王博
Original assignee: Xian Electrification Engineering Co Ltd of China Railway Electrification Engineering Group Co Ltd
Current assignee: Xian Electrification Engineering Co Ltd of China Railway Electrification Engineering Group Co Ltd
Priority date: 2019-09-09
Filing date: 2019-09-09
Publication date: 2020-11-06
Anticipated expiration: 2029-09-09

Abstract

The utility model belongs to the technical field of the obstacle detection, concretely relates to intelligent obstacle detection car based on modular control. It includes: a vehicle body; the bottom of the vehicle body is provided with track wheels, and the vehicle body can move along the tracks through the track wheels; the track wheel is electrically connected with a driving motor, and the driving motor drives the track wheel to move; a driving position is arranged in the vehicle body and is used for a user to ride; it is characterized in that it also comprises: the system comprises a control module, an image identification module, an obstacle detection judgment module, a speed detection module, a power supply control module and a data storage module; the control module is respectively in signal connection with the image recognition module, the obstacle detection judging module, the speed detection module, the power supply control module and the data storage module. The method has the advantages of high intelligent degree, wide applicability, accurate obstacle detection and high safety.

Description

Intelligent obstacle detection vehicle based on modular control

Technical Field

The utility model belongs to the technical field of the obstacle detection, concretely relates to intelligent obstacle detection car based on modular control.

Background

As artificial intelligence has permeated into every industry, its functions have become more and more obvious, and in the field of high-speed railways, intelligent devices are used more and more. For example, in railway engineering, the limit detection or inspection needs to be carried out on a track and two sides, and the obstacle and foreign matter on the overhead line of the contact network needs to be further deeply identified, so that the obstacle is manually removed.

The clearance is an extremely important parameter of a railway system, and a clearance detection method in a high-speed railway system is mature and uses a clearance detection vehicle. Due to the particularity of the urban rail transit line, no unified limit detection method and equipment exist at present, more traditional physical mechanical models are adopted, the detection of the method is not accurate, manpower and financial resources are needed to be spent for manufacturing, and meanwhile, the existing physical mechanical models and large-scale equipment are inconvenient to get in and out of the field.

SUMMERY OF THE UTILITY MODEL

In view of this, the utility model discloses a main aim at provides intelligent obstacle detection car based on modular control has intelligent degree height, extensive applicability, obstacle detection accuracy and the high advantage of security.

In order to achieve the above purpose, the technical scheme of the utility model is realized like this:

intelligent obstacle detection car based on modularization control, it includes: a vehicle body; the bottom of the vehicle body is provided with track wheels, and the vehicle body can move along the tracks through the track wheels; the track wheel is electrically connected with a driving motor, and the driving motor drives the track wheel to move; a driving position is arranged in the vehicle body and is used for a user to ride; it still includes: the system comprises a control module, an image identification module, an obstacle detection judgment module, a speed detection module, a power supply control module and a data storage module; the control module is respectively in signal connection with the image identification module, the obstacle detection judging module, the speed detection module, the power supply control module and the data storage module; the image recognition module is used for acquiring a real-time image of the vehicle traveling direction and sending the real-time image to the data storage module for storage; the obstacle detection and judgment module is used for sensing an obstacle in the vehicle traveling direction, calculating the distance between the obstacle and the vehicle, and sending the calculated data to the data storage module for storage; the speed detection module monitors the motion speed of the vehicle in real time and sends the monitored data to the data storage module for storage; and the power supply control module is used for providing power supply voltage for each module.

Further, the image recognition module comprises: the device comprises an acquisition module and an identification module; the acquisition module is a night vision high-definition camera, is arranged in front of the vehicle body, acquires image information when the vehicle travels, and sends the acquired image information to the identification module; and the recognition module receives the collected image information, recognizes the image information, classifies the recognition result, and simultaneously sends the recognition result and the classification result to the control module.

Further, the obstacle detection determination module includes: a sensor module and a laser module; the sensor module includes: the sensor array and the microprocessor are composed of a plurality of distributed sensors; after the sensor array senses a front obstacle, the sensor array sends sensed data to the first microprocessor, and the first microprocessor calculates the distance between the obstacles; the laser module includes: the laser light path and the second microprocessor; the laser light path measures distance through laser and sends detected data to the second microprocessor; the second microprocessor calculates the distance between the obstacles; the first microprocessor and the second microprocessor both send the calculated barrier distance to the control module; and the control module calculates the final obstacle distance according to the obstacle distance measured by the two modules.

Further, the probe vehicle further comprises: a communication module; the communication module is in communication connection with the WEB background and is in real-time communication with the WEB background.

Further, the speed detection module comprises: the photoelectric encoder, the GPS satellite positioning module and the third microprocessor; the photoelectric encoder measures the advancing speed of the vehicle, determines the displacement distance of the vehicle and sends the detected data to the third microprocessor; the GPS satellite positioning module acquires the GPS position information of the vehicle in real time and sends the acquired GPS position information to the third microprocessor; and after receiving the data, the third microprocessor corrects the data information acquired by the photoelectric encoder in real time according to the GPS position information to obtain the final speed information.

Furthermore, a multistage high-power supply conversion control chip is further arranged in the vehicle, and the conversion efficiency of multistage voltage conversion and lower power supply ripples are ensured by arranging a multi-filter circuit, so that stable and appropriate power supply voltage is provided for different control circuits of the whole set of system.

The utility model discloses an intelligence obstacle detection car and detection method based on modular control has following beneficial effect: the utility model discloses do not receive the restriction of region and site operation condition, make things convenient for field assembly and use. The manpower and financial resources are saved, partial parameters of a detection limit and a contact network are detected, the inconvenience brought to the site by using a large detection vehicle is replaced, and the trolley can be used in many occasions. The vehicle is designed into a modularized quick assembly and disassembly mode, a trolley functional structure can be quickly added, a rail clearance detection function, a contact network detection module, a rail construction quality detection module and other multifunctional detection modules are realized, and the functional design of the trolley is further expanded so as to adapt to more application scene requirements and meet different functional requirements of different users; the other is that the trolley has two driving modes, can be driven by no person and can also carry people.

And simultaneously, the utility model discloses when carrying out image recognition, adopt the classification algorithm of innovation, simplified the image recognition flow, simultaneously, also need not artificially to filter, promoted efficiency. When the obstacle distance detection is carried out, the accuracy of the obstacle distance detection is improved through comprehensive judgment of various measurements of the obstacles.

The innovative classification algorithm does not need to carry out complete identification on each picture in the calculation process, only needs to calculate the probability of the sample point of each picture, simplifies the identification process, and meanwhile, corrects the result by using the loss function, thereby improving the accuracy. The efficiency is ensured, and the accuracy is also ensured.

In the process of calculating the distance, the distance is calculated for each dimension in the space, so that inaccuracy caused by space blockage or single-dimension measurement is avoided.

Drawings

Fig. 1 is a schematic structural diagram of an intelligent obstacle detection vehicle based on modular control according to an embodiment of the present invention;

fig. 2 is a schematic flow chart of a method of an intelligent obstacle detection method based on modular control according to an embodiment of the present invention;

fig. 3 is a schematic diagram illustrating an experimental effect of an image recognition module in the intelligent obstacle detection method based on the modular control according to an embodiment of the present invention compared with the prior art;

fig. 4 is a schematic diagram of an experimental effect of obstacle distance accuracy of the embodiment of the present invention, compared with the prior art, of an obstacle detection determination module in an intelligent obstacle detection method based on modular control.

Wherein, 1-the experimental curve of the utility model; 2-experimental curves of the prior art.

Detailed Description

The method of the present invention will be described in further detail with reference to the accompanying drawings and embodiments of the present invention.

Example 1

Specifically, the control module is a core control system, and an embedded control system is adopted as the core control system of the trolley. A Cortex-M3 series single-chip microcomputer is used as a core control platform, so that the stability, the accuracy and the rapidity of vehicle control are guaranteed. Meanwhile, the Cortex-M3 series single-chip microcomputer has the advantages of low price, good power consumption control, high processing speed, multiple application interfaces and the like, meets the control requirements of the system, and can better realize the functional design of the system. The Cortex-M3 series single chip microcomputer is supposed to adopt an STM32F03 series single chip microcomputer as a main control chip of an embedded control system. The STM32 singlechip adopts outside high accuracy 8M crystal oscillator, can reach 72M operating frequency after the frequency multiplication of inside PLL phase-locked loop, is enough to satisfy most control system's processing demand. Meanwhile, the STM32 single chip microcomputer has the advantages of register processing and data processing compared with an 8-bit single chip microcomputer as a 32-bit single chip microcomputer. STM32 has integrateed including a plurality of interior modules of establishing such as ADC, DAC, CRC, PWR, watchdog to divide into the version of different storage size and pin quantity according to the needs of difference, the different development demands of satisfying that can be better.

Example 2

On the basis of the above embodiment, the image recognition module includes: the device comprises an acquisition module and an identification module; the acquisition module is a night vision high-definition camera, is arranged in front of the vehicle body, acquires image information when the vehicle travels, and sends the acquired image information to the identification module; and the recognition module receives the collected image information, recognizes the image information, classifies the recognition result, and simultaneously sends the recognition result and the classification result to the control module.

Specifically, when the trolley system detects that a front obstacle enters a vehicle limit, an obstacle image is collected in time and stored so that a rail limit detector can judge whether the front obstacle is an obstacle needing to be processed in time, and false touch alarm caused by animals or other factors is avoided. Meanwhile, the use and detection in a tunnel and other non-lighting environments need to be considered, so that an infrared array light source needs to be added beside a high-definition camera module to serve as a light source of a night camera. An LED array searchlight may be used as an auxiliary lighting system to help background workers better identify obstacles if necessary. The high-definition camera adopts a main module of TL-VPort-A series camera called image acquisition, supports high frame rate image processing, supports 500 ten thousand pixels and 8/10-bit RGB RAW, can be controlled by a program, has resolution as high as 2595x1944(15fps), and completely meets the requirements of the image acquisition system.

Example 3

On the basis of the above embodiment, the obstacle detection determination module includes: a sensor module and a laser module; the sensor module includes: the sensor array and the microprocessor are composed of a plurality of distributed sensors; after the sensor array senses a front obstacle, the sensor array sends sensed data to the first microprocessor, and the first microprocessor calculates the distance between the obstacles; the laser module includes: the laser light path and the second microprocessor; the laser light path measures distance through laser and sends detected data to the second microprocessor; the second microprocessor calculates the distance between the obstacles; the first microprocessor and the second microprocessor both send the calculated barrier distance to the control module; and the control module calculates the final obstacle distance according to the obstacle distance measured by the two modules.

Specifically, the obstacle detection determination module adopts an industrial-grade high-precision visible laser distance sensor as a main sensor for boundary detection. And a laser light path is built through the reasonable design of a mechanical structure, and the sensor array acquisition is reasonably distributed through a core control system. Obstacles entering the vehicle boundary are detected by a plurality of acquisition modes. The visible laser array is used as a monitoring and sensing system of the obstacle, so that the obstacle detection accuracy and detection speed can be guaranteed to the maximum extent. Meanwhile, the visible laser is subjected to harmless treatment, the safety of the visible laser is guaranteed while the laser power is guaranteed to meet the detection requirement, and the damage of the visible laser to human eyes or track facilities is prevented. An SK-Z-20 series laser measuring module is used as a limit distance measuring module of the system in a vehicle limit detection system. The module adopts advanced TOF principle to carry out laser distance detection, can be quick detect the distance value of target under test, and response speed can reach 200Hz, and the precision error is within 2 CM. The output interface of the whole module adopts a TTL level mode for output, is convenient to carry out butt-joint communication with the single chip microcomputer, and is embedded into the whole trolley system. In addition, for the safety problem in the use process, the module laser light source adopts 780nm I-type safe invisible red laser as the laser light source of the laser ranging module, so that the use environment can be protected from being damaged by the laser, and the condition that users cannot be burnt by the laser can be ensured.

Specifically, in the design of the speed detection module, a high-precision photoelectric encoder is adopted to measure the advancing speed of the trolley, the displacement distance of the trolley is determined, meanwhile, error accumulation is avoided for reducing errors, a high-precision GPS satellite positioning module is used in an auxiliary mode, position parameters are refreshed in real time, and meanwhile, various optimization algorithms are adopted to reduce errors, so that the relative position of the foreign matter is accurately judged. Through the mutual cooperation of the photoelectric encoder and the A-GPS, the relative position of the trolley in movement is accurately calculated, and meanwhile, the problem of relative position positioning in various special application environments such as tunnels and the like can be solved. The accurate relative position parameters of the obstacles and the kilometers of the rail line can be given through the speed detection system, and background workers can be helped to quickly find the positions of the obstacles. And obstacles are removed in time, so that the maintenance work after the rail limit monitoring is greatly facilitated. The A-GPS module is supposed to adopt an ADGM322D module as a positioning module of the GPS. The module supports GPS satellite communication and Beidou satellite communication, an IPX interface antenna is provided, the design of a middle-science-micro fourth-generation low-power-consumption GNSS SOC single-chip AT6558 chip is provided, the cold start capturing sensitivity reaches-148 dBm, the tracking sensitivity reaches-162 dBm, the first positioning time of the positioning precision position is 2.5 m (CEP50) for 30 seconds, and the continuous operation power consumption is less than 25ma (3.3V). And meanwhile, a UART protocol is adopted, so that the system is simple in communication and convenient to develop, and can be well embedded into a trolley system. Meanwhile, a relative positioning system of the trolley adopts a 500-line photoelectric encoder of ohm dragon company as a main sensor for the displacement and the speed of the trolley. The photoelectric encoder of ohm dragon company has the advantages of stable pulse, high testing precision and the like, and can be matched with a GPS system to accurately position the position of the trolley.

Example 4

On the basis of the above embodiment, the probe vehicle further includes: a communication module; the communication module is in communication connection with the WEB background and is in real-time communication with the WEB background.

Example 5

On the basis of the above embodiment, the speed detection module includes: the photoelectric encoder, the GPS satellite positioning module and the third microprocessor; the photoelectric encoder measures the advancing speed of the vehicle, determines the displacement distance of the vehicle and sends the detected data to the third microprocessor; the GPS satellite positioning module acquires the GPS position information of the vehicle in real time and sends the acquired GPS position information to the third microprocessor; and after receiving the data, the third microprocessor corrects the data information acquired by the photoelectric encoder in real time according to the GPS position information to obtain the final speed information.

Specifically, in the data storage system, in order to ensure that the obstacles detected during the running of the trolley can be completely recorded so as to be inquired by maintainers to avoid the influence of missed obstacles on the driving safety, the data storage system is specially arranged to timely store the running data of the trolley and the image information and the position information of the obstacles detected during the running of the trolley, so that the maintainers in a background can conveniently inquire and timely process the obstacles, and the driving safety is ensured. Meanwhile, the data storage system can provide data samples for later data analysis, the positions and the types of the obstacles which are easy to appear can be obtained by analyzing the data in the data storage system, reference can be provided for overall railway maintenance, attention key points are provided for later new railway trunk line construction, the frequency of the appearance of the obstacles is reduced, the workload of obstacle processing is reduced, and the railway construction efficiency is improved. In the work of actual data storage, in order to reduce the workload of later-stage personnel data analysis, the data recording system only records the image information and the position information of the obstacles, so that background workers can conveniently check the authenticity of the obstacles and dispatch the workers to process the obstacles in time. The storage size of each image data is about 6MB, the storage space occupied by text information such as position information is about 1KB, and the number of obstacles appearing on the line is different. The memory space to be used in the present system is about 16 GB.

On the basis of the previous embodiment, a multistage high-power supply conversion control chip is further arranged in the vehicle, and the conversion efficiency of multistage voltage conversion and lower power supply ripples are guaranteed by arranging a multi-filter circuit, so that stable and appropriate power supply voltage is provided for different control circuits of the whole set of system.

Example 6

The above is only an embodiment of the present invention, but the scope of the present invention can not be limited thereby, and structural changes made by the present invention can be considered as falling within the protection scope of the present invention as long as the gist of the present invention is not lost.

It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process and related description of the system described above may refer to the corresponding process in the foregoing method embodiments, and will not be described herein again.

It should be noted that, the system provided in the foregoing embodiment is only illustrated by the division of the functional modules, and in practical applications, the above functions may be allocated to different functional modules according to needs, that is, the modules or steps in the embodiment of the present invention are further decomposed or combined, for example, the modules in the foregoing embodiment may be combined into one module, or may be further split into multiple sub-modules, so as to complete all or part of the functions described above. The names of the modules and steps related to the embodiments of the present invention are only for distinguishing the modules or steps, and are not to be construed as limitations of the present invention.

It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes and related descriptions of the storage device and the processing device described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

Those of skill in the art would appreciate that the various illustrative modules, method steps, and modules described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that programs corresponding to the software modules, method steps may be located in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. To clearly illustrate this interchangeability of electronic hardware and software, various illustrative components and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as electronic hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

The terms "first," "second," and the like are used for distinguishing between similar elements and not necessarily for describing or implying a particular order or sequence.

The terms "comprises," "comprising," or any other similar term are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.

So far, the technical solution of the present invention has been described with reference to the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, a person skilled in the art can make equivalent changes or substitutions to the related technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention.

Claims

1. Intelligent obstacle detection car based on modularization control, it includes: a vehicle body; the bottom of the vehicle body is provided with track wheels, and the vehicle body can move along the tracks through the track wheels; the track wheel is electrically connected with a driving motor, and the driving motor drives the track wheel to move; a driving position is arranged in the vehicle body and is used for a user to ride; it is characterized in that it also comprises: the system comprises a control module, an image identification module, an obstacle detection judgment module, a speed detection module, a power supply control module and a data storage module; the control module is respectively in signal connection with the image identification module, the obstacle detection judging module, the speed detection module, the power supply control module and the data storage module; the image recognition module is used for acquiring a real-time image of the vehicle traveling direction and sending the real-time image to the data storage module for storage; the obstacle detection and judgment module is used for sensing an obstacle in the vehicle traveling direction, calculating the distance between the obstacle and the vehicle, and sending the calculated data to the data storage module for storage; the speed detection module monitors the motion speed of the vehicle in real time and sends the monitored data to the data storage module for storage; and the power supply control module is used for providing power supply voltage for each module.

2. The intelligent obstacle-detecting vehicle based on modular control of claim 1, wherein the image recognition module comprises: the device comprises an acquisition module and an identification module; the acquisition module is a night vision high-definition camera, is arranged in front of the vehicle body, acquires image information when the vehicle travels, and sends the acquired image information to the identification module; and the recognition module receives the collected image information, recognizes the image information, classifies the recognition result, and simultaneously sends the recognition result and the classification result to the control module.

3. The intelligent obstacle-detecting vehicle based on modular control of claim 1, wherein the obstacle detection determination module comprises: a sensor module and a laser module; the sensor module includes: the sensor array and the microprocessor are composed of a plurality of distributed sensors; after the sensor array senses a front obstacle, the sensor array sends sensed data to the first microprocessor, and the first microprocessor calculates the distance between the obstacles; the laser module includes: the laser light path and the second microprocessor; the laser light path measures distance through laser and sends detected data to the second microprocessor; the second microprocessor calculates the distance between the obstacles; the first microprocessor and the second microprocessor both send the calculated barrier distance to the control module; and the control module calculates the final obstacle distance according to the obstacle distance measured by the two modules.

4. The modular control based intelligent obstacle-detecting vehicle of claim 1, wherein the detecting vehicle further comprises: a communication module; the communication module is in communication connection with the WEB background and is in real-time communication with the WEB background.

5. The intelligent obstacle-detecting vehicle based on modular control of claim 1, wherein the speed detection module comprises: the photoelectric encoder, the GPS satellite positioning module and the third microprocessor; the photoelectric encoder measures the advancing speed of the vehicle, determines the displacement distance of the vehicle and sends the detected data to the third microprocessor; the GPS satellite positioning module acquires the GPS position information of the vehicle in real time and sends the acquired GPS position information to the third microprocessor; and after receiving the data, the third microprocessor corrects the data information acquired by the photoelectric encoder in real time according to the GPS position information to obtain the final speed information.

6. An intelligent obstacle detection vehicle based on modular control as claimed in any one of claims 1 to 5, wherein a multi-stage high-power conversion control chip is further arranged inside the vehicle, and a multi-filter circuit is arranged to ensure the conversion efficiency of multi-stage voltage conversion and lower power ripple, so as to provide stable and appropriate power supply voltage for each different control circuit of the whole set of system.