CN117444935A - Hanging rail AI artificial intelligent inspection system and use method thereof - Google Patents
Hanging rail AI artificial intelligent inspection system and use method thereof Download PDFInfo
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- CN117444935A CN117444935A CN202311520851.4A CN202311520851A CN117444935A CN 117444935 A CN117444935 A CN 117444935A CN 202311520851 A CN202311520851 A CN 202311520851A CN 117444935 A CN117444935 A CN 117444935A
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- 238000007689 inspection Methods 0.000 title claims abstract description 81
- 238000000034 method Methods 0.000 title claims abstract description 29
- 238000013473 artificial intelligence Methods 0.000 claims abstract description 14
- 238000003745 diagnosis Methods 0.000 claims description 30
- 230000033001 locomotion Effects 0.000 claims description 14
- 238000007726 management method Methods 0.000 claims description 10
- 230000005540 biological transmission Effects 0.000 claims description 9
- 238000012544 monitoring process Methods 0.000 claims description 7
- 238000007781 pre-processing Methods 0.000 claims description 7
- 238000005516 engineering process Methods 0.000 claims description 6
- 238000012706 support-vector machine Methods 0.000 claims description 6
- 238000004891 communication Methods 0.000 claims description 5
- 238000012545 processing Methods 0.000 claims description 5
- 238000012549 training Methods 0.000 claims description 5
- 230000008859 change Effects 0.000 claims description 4
- 238000013135 deep learning Methods 0.000 claims description 4
- 238000001514 detection method Methods 0.000 claims description 4
- 230000000694 effects Effects 0.000 claims description 4
- 238000003709 image segmentation Methods 0.000 claims description 4
- 230000005856 abnormality Effects 0.000 claims description 3
- 238000013528 artificial neural network Methods 0.000 claims description 3
- 238000003066 decision tree Methods 0.000 claims description 3
- 238000010801 machine learning Methods 0.000 claims description 3
- 238000012423 maintenance Methods 0.000 claims description 3
- 238000010223 real-time analysis Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 239000000523 sample Substances 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
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- 238000012986 modification Methods 0.000 description 1
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- 238000006467 substitution reaction Methods 0.000 description 1
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- 239000013598 vector Substances 0.000 description 1
Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J5/00—Manipulators mounted on wheels or on carriages
- B25J5/02—Manipulators mounted on wheels or on carriages travelling along a guideway
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J19/00—Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
- B25J19/02—Sensing devices
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J19/00—Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
- B25J19/02—Sensing devices
- B25J19/021—Optical sensing devices
- B25J19/023—Optical sensing devices including video camera means
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- Engineering & Computer Science (AREA)
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- Mechanical Engineering (AREA)
- Multimedia (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
Abstract
The invention relates to the technical field of intelligent inspection of hanging rail AI (artificial intelligence), and discloses an intelligent inspection system of hanging rail AI and a use method thereof. According to the hanging rail AI artificial intelligent inspection system and the application method thereof, the temperature and humidity sensor and the vibration sensor are connected through the additional fixing tube and the extension tube on the inspection robot for multi-type data acquisition, and comprehensive judgment is carried out through matching with image information which is difficult to extract, so that multi-scale object recognition is facilitated, and recognition problems under a complex environment are solved.
Description
Technical Field
The invention relates to the technical field of hanging rail AI artificial intelligence inspection, in particular to a hanging rail AI artificial intelligence inspection system and a use method thereof.
Background
The artificial intelligent inspection of the suspended rail AI refers to a method for inspecting and monitoring suspended rail equipment by utilizing an artificial intelligent technology, and the suspended rail equipment is automatically inspected and subjected to fault diagnosis by using an AI algorithm and an image recognition technology so as to improve inspection efficiency and accuracy.
The common rail-mounted AI intelligent inspection robot automatically runs in a space, carries a high-definition camera, a high-sensitivity infrared thermal imager and an environment monitoring sensor, has the functions of hearing, vision, smell and the like of people, performs inspection one by one according to the operation sequence set by a system and inspection content, pre-judges collected data, uploads the pre-judged data to a comprehensive management platform at a high speed through a redundant optical fiber network, stores detailed inspection information and analysis diagnosis in a database by a data analysis and report management module of the management platform, and can be downloaded and checked by an operator to generate a task report, a diagnosis report and the like, wherein the system can monitor problem data change in the whole space according to long-time operation data analysis and provide data support for structural transition of a pipe gallery.
In the process, the data quality relied by the existing inspection robot inspection system is important for accurate identification and fault diagnosis, however, in reality, the rail hanging equipment is usually in a complex industrial environment, shielding, reflection, dirt and the like can exist, the fault of the rail hanging equipment can have diversity and complexity, and the fault cause can not be accurately diagnosed only by means of image identification, so that the rail hanging AI artificial intelligent inspection system and the use method thereof are provided for solving the problems.
Disclosure of Invention
(one) solving the technical problems
Aiming at the defects of the prior art, the invention provides a lifting rail AI artificial intelligent inspection system and a use method thereof, which have the advantages of introducing more sensor data, such as a vibration sensor, a temperature sensor and the like, comprehensively analyzing by combining an image recognition result, improving the accuracy of fault diagnosis and the like.
(II) technical scheme
In order to realize the aim of introducing more sensor data, such as a vibration sensor, a temperature sensor and the like, comprehensively analyzing by combining an image recognition result and improving the accuracy of fault diagnosis, the invention provides the following technical scheme: the intelligent inspection system comprises an inspection robot for the movement of a hanging rail, wherein an MCU (micro control unit) main board, a power module, an image acquisition module, a movement module and a data acquisition module are arranged in the inspection robot, and the data acquisition module comprises a vibration sensor and a temperature and humidity sensor for additionally acquiring data;
the inspection robot comprises a shell, wherein a fixing pipe is arranged on the lower surface of the shell of the inspection robot in an extending mode, an extending pipe is arranged in the fixing pipe in a sliding mode, a connecting box is fixedly arranged on the lower end face of the extending pipe, and a vibration sensor and a temperature and humidity sensor are both arranged on the connecting box.
Preferably, a radiator is further installed on one side surface of the inspection robot, and the radiator and the motion module are electrically connected with each other.
Preferably, the image acquisition module comprises a camera for acquiring image information and a photoelectric sensor for judging the distance of the inspection robot.
Preferably, a servo motor for driving the extension tube to extend is installed in the connecting box, and a transmission member for connecting the fixed tube is installed on the output end of the servo motor.
Preferably, the transmission member includes a rotation rod fixedly connected to an output end of the servo motor, the rotation rod penetrates through the extension tube, and a diameter of the rotation rod is smaller than that of the extension tube.
Preferably, the transmission member further includes a screw post connected to an end of the rotation rod, and the screw post is screw-coupled to the fixing tube.
Preferably, a guide groove for guiding is recessed in the inner wall of the fixed tube, a guide strip for matching with the guide groove is fixedly arranged outside the extension tube, and the guide strip is slidably connected with the guide groove.
A use method of an intelligent inspection system of a hanging rail AI comprises the following steps:
s1, mounting equipment: firstly, equipment required by a patrol system is required to be installed, wherein the equipment comprises a camera, a temperature and humidity sensor, a vibration sensor and a photoelectric sensor, and the camera is required to be installed at a proper position so as to comprehensively monitor the state and the running condition of the lifting rail equipment;
s2, data acquisition and training: the inspection system is required to train and learn by collecting images and data of the hanger rail equipment, wherein the data can comprise images in a normal running state, images in a fault state, and data of a temperature and humidity sensor, a vibration sensor and a photoelectric sensor;
s3, system configuration and parameter setting: before the inspection system is used, system configuration and parameter setting are required, which comprises setting the working mode, fault diagnosis algorithm and alarm threshold of the inspection system;
s4, real-time monitoring and inspection: the configuration of the inspection system is completed, the inspection system can start to monitor and inspect the hanging rail equipment in real time, the system can continuously acquire images and data of the hanging rail equipment, and perform real-time analysis and identification, if the system detects abnormality or failure, the system can send out an alarm or inform related personnel, when the auxiliary image acquires additional acquired vibration data, a rotating rod fixedly connected with an output end can be driven by a servo motor to rotate, the rotating rod drives a threaded column fixedly connected with the rotating rod to be in threaded fit with a fixed pipe, and then the extending pipe which is in sliding connection with the fixed pipe is extended, so that a vibration sensor and a temperature and humidity sensor can acquire data of different detection points in a factory building;
s5, integrating data information and diagnosing faults: the data are transmitted to an MCU main board for preprocessing after being acquired, an image processing module is used for preprocessing the acquired image or video, including image enhancement, denoising, image segmentation and the like, so that the subsequent image recognition effect is improved, an object recognition module is used for recognizing and classifying each component in the hanger rail equipment by utilizing a deep learning algorithm and an image recognition technology, such as recognizing the track, the hanging hook and the sensor of the hanger rail, and finally the data are transmitted to a hanger rail artificial intelligent system management platform by a 4/5G communication module;
s6, fault diagnosis and report generation: the method comprises the steps of extracting useful characteristics from preprocessed data, wherein the characteristics can be vibration frequency, temperature change and texture characteristics in images of the hanger rail equipment, constructing a fault diagnosis model by using the preprocessed and characteristic extracted data, and performing fault diagnosis on new data by using a trained fault diagnosis model based on a machine learning algorithm such as a Support Vector Machine (SVM), a decision tree, a neural network and the like, inputting the new data into the model, judging whether the hanger rail equipment has faults according to learned knowledge and rules, giving out corresponding fault types and possible reasons, and giving out an alarm or notifying related personnel by a system if the fault diagnosis model judges that the hanger rail equipment has faults, and analyzing and sorting information to generate a patrol report for subsequent maintenance and management.
(III) beneficial effects
Compared with the prior art, the invention provides the hanging rail AI artificial intelligent inspection system and the use method thereof, which have the following beneficial effects:
according to the hanging rail AI artificial intelligent inspection system and the application method thereof, the temperature and humidity sensor and the vibration sensor are connected through the additional fixing tube and the extension tube on the inspection robot for multi-type data acquisition, and comprehensive judgment is carried out through matching with image information which is difficult to extract, so that multi-scale object recognition is facilitated, and recognition problems under a complex environment are solved.
Drawings
Fig. 1 is a schematic structural diagram of an artificial intelligent inspection system for a hanging rail AI and a use method thereof;
FIG. 2 is a system diagram of an artificial intelligent inspection system for a suspended rail AI and a method of using the same;
FIG. 3 is a schematic diagram of an artificial intelligent inspection system for a suspended rail AI and an elongated tube structure of a method for using the same according to the present invention;
fig. 4 is a bottom view of a fixed pipe of the hanging rail AI artificial intelligence inspection system and the method of using the same according to the present invention.
In the figure: 1. inspection robot; 2. an MCU main board; 3. a power module; 4. an image acquisition module; 5. a motion module; 6. a fixed tube; 7. an extension tube; 8. a connection box; 9. a vibration sensor; 10. a temperature and humidity sensor; 11. a heat sink; 12. a servo motor; 13. a rotating lever; 14. a threaded column; 15. a guide bar; 16. a guide groove.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-2, an intelligent inspection system for a hanging rail AI comprises an inspection robot 1 for hanging rail movement, wherein an MCU main board 2, a power module 3, an image acquisition module 4, a movement module 5 and a data acquisition module are arranged in the inspection robot 1.
The MCU motherboard 2 in this embodiment is a motherboard integrated with a micro controller unit MCU, and the MCU motherboard 2 is built in the inspection robot 1 for controlling and managing various functions and operations of the module.
The MCU main board 2 also comprises a plurality of interfaces, wherein the power interface is used for connecting the power module 3, the communication interface such as 4/5G communication is used for connecting the hanging rail artificial intelligent system management platform to complete the analysis of data, and the digital input/output interface is used for connecting the image acquisition module 4 and the data acquisition module.
The further movement module 5 comprises a storage battery and a power switch, wherein the storage battery and the power switch are used for supplying power to the inspection robot 1, the power switch is arranged outside a shell of the inspection robot and used for controlling the on-off of a circuit, and the storage battery of the movement module 5 is further electrically connected with the image acquisition module 4, the data acquisition module and the movement module to be used as a power supply.
A radiator 11 is further installed on one side surface of the inspection robot 1, and the radiator 11 and the motion module 5 are electrically connected with each other to radiate heat of the inspection robot 1.
Referring to fig. 1, the motion module 5 in this embodiment includes a steering engine for driving the inspection robot 1 to move on the hanger rail and a steering engine control switch for driving the inspection robot to move on the hanger rail.
The image acquisition module 4 in this embodiment includes a camera for acquiring image information and a photoelectric sensor for determining a distance between the inspection robots, and can cooperate with the MCU motherboard 2 to complete position information interaction.
The data acquisition module comprises a vibration sensor 9 and a temperature and humidity sensor 10 for additionally acquiring data, and as the rail hanging equipment is usually in a complex industrial environment, faults of the rail hanging equipment can have diversity and complexity and the fault cause can not be accurately diagnosed only by means of image recognition, more sensor data are introduced to be comprehensively analyzed by combining image recognition results, and the accuracy of fault diagnosis is improved.
Referring to fig. 2, the MCU motherboard 2 in the present embodiment has an image processing module integrated thereon: preprocessing the image or video acquired by the image acquisition module 4, including image enhancement, denoising, image segmentation and the like, so as to improve the subsequent image recognition effect;
an object recognition module: and (3) identifying and classifying each component in the hanger rail equipment in the picture processed by the image processing module by using a deep learning algorithm and an image identification technology, such as identifying the track, the hanging hook and the sensor of the hanger rail.
Because vibration sensor 9 and temperature and humidity sensor 10 are different to the different equipment probe points in the industrial environment, extend on the shell lower surface of inspection robot 1 has fixed pipe 6, and sliding mounting has extension pipe 7 in the fixed pipe 6, fixedly mounted with joint box 8 on the lower terminal surface of extension pipe 7, vibration sensor 9 and temperature and humidity sensor 10 all install on joint box 8, can accomplish the probe point data acquisition to the industrial environment under the extension of extension pipe 7, reduce the manual work burden.
Referring to fig. 3-4, a servo motor 12 for driving the extension tube 7 to extend is installed in the connection box 8 in this embodiment, and a transmission member for connecting the fixed tube 6 is installed at an output end of the servo motor 12, so that the extension length of the extension tube 7 can be conveniently controlled by the arrangement of the transmission member.
The transmission member in this embodiment includes a rotation rod 13 fixedly connected to the output end of the servo motor 12, the rotation rod 13 passes through the extension tube 7, and the diameter of the rotation rod 13 is smaller than that of the extension tube 7, so that the rotation of the rotation rod 13 does not interfere with the extension tube 7, and further includes a threaded post 14 connected to the end of the rotation rod 13, the threaded post 14 is screwed to the fixed tube 6, and the rotation screw is engaged with the threaded post for the servo motor 12 to adjust the extension position relative to the fixed tube 6.
The inner wall of the fixed tube 6 is recessed with a guide groove 16 for guiding, the outside of the elongated tube 7 is fixedly provided with a guide bar 15 for matching with the guide groove 16, the guide bar 15 is slidably connected with the guide groove 16, and the connection box 8 can be limited to rotate relative to the fixed tube 6 by sliding fit between the guide bar 15 and the guide groove 16.
A use method of an intelligent inspection system of a hanging rail AI comprises the following steps:
s1, mounting equipment: firstly, equipment required by the inspection system is required to be installed, wherein the equipment comprises a camera, a temperature and humidity sensor 10, a vibration sensor 9 and a photoelectric sensor, and the camera is required to be installed at a proper position so as to be capable of comprehensively monitoring the state and the running condition of the hanger rail equipment.
S2, data acquisition and training: the inspection system needs to train and learn by collecting images and data of the hanger rail equipment, wherein the data can comprise images in normal operation state, images in fault state, and data of the temperature and humidity sensor 10, the vibration sensor 9 and the photoelectric sensor, and the inspection system can learn and identify various states and faults through the data.
S3, system configuration and parameter setting: before the inspection system is used, system configuration and parameter setting are required, which include setting the working mode, fault diagnosis algorithm, alarm threshold and the like of the inspection system, and the system can be configured in a personalized way according to actual conditions and requirements.
S4, real-time monitoring and inspection: the configuration of the inspection system is completed, the inspection system can start to monitor and inspect the hanging rail equipment in real time, the system can continuously acquire images and data of the hanging rail equipment, and perform real-time analysis and identification, if the system detects abnormality or failure, the system can send out an alarm or inform related personnel, when the auxiliary image acquisition is used for acquiring additional vibration data, the rotating rod 13 fixedly connected to the output end can be driven by the servo motor 12 to rotate, the rotating rod 13 drives the threaded column 14 fixedly connected to be in threaded fit relative to the fixed pipe 6 under rotation, and then the extending pipe 7 which is in sliding connection with the fixed pipe 6 can extend, so that the vibration sensor 9 and the temperature and humidity sensor 10 can perform data acquisition on different detection points in a factory building.
S5, integrating data information and diagnosing faults: the data are transmitted to the MCU main board 2 for preprocessing through an interface after being acquired, the image processing module is used for preprocessing the acquired image or video, including image enhancement, denoising, image segmentation and the like, so that the subsequent image recognition effect is improved, the object recognition module is used for recognizing and classifying all components in the hanger rail equipment by utilizing a deep learning algorithm and an image recognition technology, such as recognizing the track, the hanging hook and the sensor of the hanger rail, and finally the data are transmitted to the hanger rail artificial intelligent system management platform through the 4/5G communication module.
S6, fault diagnosis and report generation: the method comprises the steps of extracting useful characteristics from preprocessed data, wherein the characteristics can be vibration frequency, temperature change, texture characteristics in images and the like of hanger rail equipment, the purpose of extracting the characteristics is to convert original data into characteristic vectors which can be used for fault diagnosis, the preprocessed and characteristic-extracted data are used for constructing a fault diagnosis model, the purpose of model training can be to identify and classify various faults by learning characteristics and modes of known fault samples based on models of machine learning algorithms such as Support Vector Machines (SVM), decision trees, neural networks and the like, the purpose of model training is to conduct fault diagnosis on new data by using the trained fault diagnosis model, the model can judge whether the hanger rail equipment has faults according to learned knowledge and rules and give corresponding fault types and possible reasons, if the fault diagnosis model judges that the hanger rail equipment has faults, the system can send out alarms or inform related personnel by means of sound, short messages, mails and the like, meanwhile, information is analyzed and sorted, and a patrol report is generated, and the subsequent maintenance and management are convenient.
In summary, the lifting rail AI artificial intelligent inspection system and the use method thereof, through the rotation of the rotating rod 13 fixedly connected to the output end driven by the servo motor 12, the rotating rod 13 drives the fixedly connected threaded column 14 to be in threaded fit relative to the fixed pipe 6 under rotation, and then the extending pipe 7 slidingly connected to the fixed pipe 6 is extended, so that the vibration sensor 9 and the temperature and humidity sensor 10 can perform data acquisition on different detection points in a factory building, useful characteristics are extracted from the preprocessed data, the preprocessed and characteristic extracted data are used for constructing a fault diagnosis model, the trained fault diagnosis model is used for performing fault diagnosis on new data, the new data are input into the model, the model can judge whether the lifting rail equipment has faults according to learned knowledge and rules, and give out corresponding fault types and possible reasons, and if the fault diagnosis model judges that the lifting rail equipment has faults, the system can send out alarms or notify related personnel.
It should be noted that the terms "comprises," "comprising," or any other variation thereof, 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. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. The utility model provides a system is patrolled and examined to hanging rail AI artificial intelligence, is including being used for hanging rail motion's inspection robot (1), inspection robot (1) embeds has MCU mainboard (2), power module (3), image acquisition module (4), motion module (5) and data acquisition module, its characterized in that: the data acquisition module comprises a vibration sensor (9) and a temperature and humidity sensor (10) for additionally acquiring data;
the inspection robot is characterized in that a fixed pipe (6) extends from the lower surface of the shell of the inspection robot (1), an extension pipe (7) is slidably installed in the fixed pipe (6), a connecting box (8) is fixedly installed on the lower end face of the extension pipe (7), and a vibration sensor (9) and a temperature and humidity sensor (10) are installed on the connecting box (8).
2. The hanger rail AI artificial intelligence inspection system of claim 1, wherein: a radiator (11) is further arranged on one side face of the inspection robot (1), and the radiator (11) and the movement module (5) are electrically connected with each other.
3. The hanger rail AI artificial intelligence inspection system of claim 1, wherein: the image acquisition module (4) comprises a camera for acquiring image information and a photoelectric sensor for judging the distance of the inspection robot.
4. The hanger rail AI artificial intelligence inspection system of claim 1, wherein: the inside of the connecting box (8) is provided with a servo motor (12) for driving the extension tube (7) to extend, and the output end of the servo motor (12) is provided with a transmission component for connecting the fixed tube (6).
5. The hanging rail AI artificial intelligence inspection system of claim 4, wherein: the transmission member comprises a rotating rod (13) fixedly connected to the output end of the servo motor (12), the rotating rod (13) penetrates through the extension tube (7), and the diameter of the rotating rod (13) is smaller than that of the extension tube (7).
6. The hanger rail AI artificial intelligence inspection system of claim 5, wherein: the transmission member further comprises a threaded column (14) connected to the end of the rotating rod (13), and the threaded column (14) is in threaded connection with the fixed pipe (6).
7. The hanger rail AI artificial intelligence inspection system of claim 6, wherein: the inner wall of the fixed pipe (6) is sunken to be provided with a guide groove (16) for guiding, a guide strip (15) for matching with the guide groove (16) is fixedly arranged outside the extension pipe (7), and the guide strip (15) is in sliding connection with the guide groove (16).
8. The application method of the hanging rail AI artificial intelligent inspection system is characterized by comprising the following steps of: the method comprises the following steps:
s1, mounting equipment: firstly, equipment required by a patrol system is required to be installed, wherein the equipment comprises a camera, a temperature and humidity sensor (10), a vibration sensor (9) and a photoelectric sensor, and the camera is required to be installed at a proper position so as to be capable of comprehensively monitoring the state and the running condition of the lifting rail equipment;
s2, data acquisition and training: the inspection system is required to train and learn by collecting images and data of the hanger rail equipment, wherein the data can comprise images in a normal running state, images in a fault state, temperature and humidity sensors (10), vibration sensors (9) and photoelectric sensor data;
s3, system configuration and parameter setting: before the inspection system is used, system configuration and parameter setting are required, which comprises setting the working mode, fault diagnosis algorithm and alarm threshold of the inspection system;
s4, real-time monitoring and inspection: the configuration of the inspection system is completed, the inspection system can start to monitor and inspect the hanging rail equipment in real time, the system can continuously acquire images and data of the hanging rail equipment, and perform real-time analysis and identification, if the system detects abnormality or failure, the system can send out an alarm or inform related personnel, when the auxiliary image acquires additional acquired vibration data, a rotating rod (13) fixedly connected with an output end can be driven by a servo motor (12) to rotate, the rotating rod (13) drives a threaded column (14) fixedly connected with the rotating rod to perform threaded fit relative to a fixed pipe (6), and then an extension pipe (7) which is connected with the fixed pipe (6) in a sliding manner extends, so that a vibration sensor (9) and a temperature and humidity sensor (10) can perform data acquisition on different detection points in a factory building;
s5, integrating data information and diagnosing faults: the data are transmitted to an MCU main board (2) for preprocessing after being acquired, an image processing module is used for preprocessing the acquired image or video, the image enhancement, the denoising, the image segmentation and the like are included, the subsequent image recognition effect is improved, an object recognition module is used for recognizing and classifying all components in the hanger rail equipment by utilizing a deep learning algorithm and an image recognition technology, such as the rail, the hanging hook and the sensor of the hanger rail are recognized, and finally the data are transmitted to a hanger rail artificial intelligent system management platform through a 4/5G communication module;
s6, fault diagnosis and report generation: the method comprises the steps of extracting useful characteristics from preprocessed data, wherein the characteristics can be vibration frequency, temperature change and texture characteristics in images of the hanger rail equipment, constructing a fault diagnosis model by using the preprocessed and characteristic extracted data, and performing fault diagnosis on new data by using a trained fault diagnosis model based on a machine learning algorithm such as a Support Vector Machine (SVM), a decision tree, a neural network and the like, inputting the new data into the model, judging whether the hanger rail equipment has faults according to learned knowledge and rules, giving out corresponding fault types and possible reasons, and giving out an alarm or notifying related personnel by a system if the fault diagnosis model judges that the hanger rail equipment has faults, and analyzing and sorting information to generate a patrol report for subsequent maintenance and management.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311520851.4A CN117444935A (en) | 2023-11-15 | 2023-11-15 | Hanging rail AI artificial intelligent inspection system and use method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311520851.4A CN117444935A (en) | 2023-11-15 | 2023-11-15 | Hanging rail AI artificial intelligent inspection system and use method thereof |
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| Publication Number | Publication Date |
|---|---|
| CN117444935A true CN117444935A (en) | 2024-01-26 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311520851.4A Pending CN117444935A (en) | 2023-11-15 | 2023-11-15 | Hanging rail AI artificial intelligent inspection system and use method thereof |
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| CN (1) | CN117444935A (en) |
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- 2023-11-15 CN CN202311520851.4A patent/CN117444935A/en active Pending
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