CN107433962B

CN107433962B - Method and system for track traffic fault monitoring and intelligent early warning

Info

Publication number: CN107433962B
Application number: CN201610440765.6A
Authority: CN
Inventors: 刘春梅
Original assignee: Tibet Qiancheng Information Technology Co ltd
Current assignee: Tibet Qiancheng Information Technology Co ltd
Priority date: 2016-06-18
Filing date: 2016-06-18
Publication date: 2023-05-05
Anticipated expiration: 2036-06-18
Also published as: CN107433962A

Abstract

The invention discloses a method and a system for monitoring and intelligent early warning of rail transit faults, wherein the system comprises the following steps: the system comprises a data acquisition module, a data comparison module, a data transmission module, a region processor module, a central processing unit module, a database module and a display module. The data acquisition module is arranged on the data acquisition equipment to collect real-time state data, the data comparison module is used for comparing the real-time state data with corresponding data of the database module to generate fault information or early warning information, classification information, position information and rating information of the fault or early warning information are fed back to a user through the display module, and meanwhile, the central processing unit module can intelligently update the database module by summarizing the fault information and the early warning information transmitted by the processor modules of all areas. The system for monitoring and intelligent early warning of rail transit faults can quickly and accurately determine fault types and fault addresses, and early warning can be carried out on foreseeable faults in advance.

Description

Method and system for track traffic fault monitoring and intelligent early warning

Technical Field

The invention relates to the field of rail traffic safety, in particular to a method for monitoring and intelligent early warning of rail traffic faults and a system for realizing the method.

Background

Along with the increasing population of large cities, on-road traffic is unable to meet the increasing traffic usage amount of people, and the development of urban rail traffic plays an important role in relieving urban traffic jams. Since the first subway was built in london in 1863, the subway has been widely used as an important urban rail vehicle in developed countries such as europe and america and developed areas such as Beijing, shanghai, guangzhou, shenzhen and the like in China.

Urban rail transit is taken as a special service industry, and in addition to personnel safety of workers, the urban rail transit also comprises personnel safety of passengers and operation safety of various equipment and facilities, and meanwhile, a plurality of unpredictable potential safety hazards exist, and the safety characteristics of the urban rail transit comprise: (1) utility characteristics; (2) high flow and high density; (3) a closure; (4) affected by directional air flow; (5) difficulty in prevention.

The faults of the rail transit are various and can be classified into faults of rail equipment, platform equipment, auxiliary equipment and power supply circuits according to the positions of the faults; powering off, equipment abrasion, fracture and crack according to the fault expression form; the physical types of the cause of the fault may be classified into an electrical fault, a signal fault, a mechanical fault, and an electronic fault.

The existing rail transit fault diagnosis method mainly comprises the following four types: (1) empirical method: the operation inspector diagnoses the faults through experience, visual inspection and logic judgment; (2) component replacement method: replacing the replaceable component with a new component, and verifying through operation; (3) device detection method: locating a fault point by testing by using a professional instrument and equipment; (4) running a record searching method: and searching for fault problems by comparing and referring to the operation records. The existing diagnosis method requires that an operation inspector is familiar with the working principle of each component part of rail transit and various fault information, has large working intensity and low efficiency, and the accuracy of fault diagnosis is easily interfered by personnel factors.

Disclosure of Invention

The invention aims to solve the problems that in the prior art, the working intensity is high, the efficiency is low, and the accuracy of fault diagnosis is easily interfered by personnel factors in the fault diagnosis process of the rail transit, and provides a method for monitoring and intelligent early warning of the rail transit and a system for realizing the method, which can rapidly and accurately determine fault types and fault addresses and early warn foreseeable faults in advance.

The invention provides a method for monitoring and intelligent early warning of rail transit faults, which is suitable for real-time and dynamic monitoring of a rail transit fault monitoring and intelligent early warning system, and sets the corresponding relation between real-time state data and corresponding data in a database module, and comprises the following steps:

S1, a data acquisition device acquires real-time state data;

s2, the data comparison device compares and judges the real-time state data with corresponding data in the database module to generate fault information or early warning information;

s3, fault information or early warning information is transmitted to the regional processor module through the data transmission module;

s4, the regional processor module classifies the fault information or the early warning information according to the classification information in the database module, feeds the fault information or the early warning information back to the user through the display module and transmits the fault information or the early warning information to the central processor module;

and S5, the central processing unit module gathers fault information or early warning information transmitted by each regional processing unit module, and stores and updates the fault information or early warning information to the database module.

The invention relates to a method for monitoring and intelligent early warning of rail transit faults, which is characterized in that the step S2 further comprises the following steps:

s21, comparing the real-time state data with corresponding data of a database module, and displaying differences between the real-time state data and the corresponding data;

s22, judging whether the difference exceeds a set threshold according to the threshold setting of the database module, if not, directly ending, and if so, executing the step S23;

S23, positioning and grading fault information or early warning information.

The invention relates to a method for monitoring and intelligent early warning of rail transit faults, which is characterized in that the method comprises the following steps as a preferable mode:

s24, classifying the early warning information or the fault information received by the regional processor module through the database module to obtain an early warning or fault category i;

s25, counting the occurrence times F of the early warning or the fault class i in the current month _ix ；

S26, acquiring the occurrence frequency F of one month on the early warning or fault class i through a database module _iy And a month average F of the number of occurrences in approximately 12 months _iz ；

S27, calculating a threshold value of the early warning or fault class i

S28, grading according to the threshold F calculated in the step S27, wherein the method comprises the following steps:

(1) if F is less than or equal to 1, the grade is green early warning or fault, the early warning or fault number is stable, no measures are needed, and the safety state is realized;

(2) if F is more than 1 and less than or equal to 3, the grade is yellow early warning or failure, which means that the early warning or failure number is not high and attention is needed to observe;

(3) if F is more than 3 and less than or equal to 5, the grade is orange early warning or fault, which means that the early warning or fault number is higher, and the attention and the key inspection are needed at the moment;

(4) if F is more than 5, the grade is red early warning or fault, which means that the early warning or fault number is very high, and the emergency guarantee measures need to be developed immediately.

The invention provides a system for realizing a method for monitoring and intelligent early warning of rail transit faults, which comprises the following steps:

and a data acquisition module: the real-time state data of each detection point are collected; according to different manifestations of detection points, the detection points can be divided into generalized detection points and narrow detection points, wherein the generalized detection points refer to all positions on a rail transit system, and the narrow detection points comprise sensors installed on rail equipment, platform equipment, tunnel equipment, train equipment and auxiliary equipment, marks installed on the rail transit system and the like; according to the difference of the positions of the detection points, the detection points can be divided into a track equipment detection point, a platform equipment detection point, a tunnel equipment detection point, a train equipment detection point, an auxiliary equipment detection point and the like; according to different expression forms of the detection points, the detection points can be divided into external detection points and internal detection points, wherein the external detection points comprise the appearance (such as tunnel surfaces, train surfaces, platform surfaces and the like) of rail transit system equipment, sound and the like, and the internal detection points comprise the running conditions (such as engine temperature, shielding door opening and closing states, train door opening and closing states and the like) of the rail transit system equipment;

And a data comparison module: the real-time state data collected by the data acquisition module is compared and judged with corresponding data in the database module, fault information or early warning information is generated, and the fault information or the early warning information is transmitted to the data transmission module;

a data transmission module: the system comprises a regional processor module, a fault information module and a warning information module, wherein the regional processor module is used for transmitting fault information or early warning information to the regional processor module;

region processor module: the data transmission module is used for transmitting the comparison result to the central processing unit module, and transmitting the comparison result to the user;

and a central processing unit module: the system comprises a region processor module, a database module, a processing module and a processing module, wherein the region processor module is used for receiving classification information and processing results transmitted by the region processor module, and updating the classification information and the processing results to the database module after summarizing;

a database module: the system comprises a central processing unit module, a fault information storage module, a warning information storage module and a control module, wherein the fault information storage module is used for storing fault information, warning information and update information summarized by the central processing unit module;

and a display module: and the processing result sent by the regional processor module is fed back to the user.

The invention relates to a system for monitoring and intelligent early warning of rail transit faults, which is characterized in that a data acquisition module comprises

And a data recording module: the real-time state data acquisition device is used for recording real-time state data acquired by the data acquisition device in the motion process;

And a data collection module: the system is used for collecting real-time state data sent by sensors on equipment such as trains, tracks, platforms and the like.

The data acquisition module is arranged on the data acquisition device, the whole rail transit operation system is divided into a plurality of detection areas, one or more data acquisition devices are arranged in each area, each data acquisition device reciprocates according to a set rail, and real-time state data are collected in the operation process.

The invention relates to a system for monitoring and intelligent early warning of rail transit faults, which is characterized in that a data acquisition device comprises one or a combination of the following devices as a preferable mode: the device comprises a radio frequency scanning device, a laser scanning device, a compound eye high definition camera, a sound collector, an odor collector and a temperature collector. The radio frequency scanning device can scan the electronic tag on the equipment and is used for determining the basic data information and the position information of each equipment; the laser scanning device can detect internal foreign matters in the rail transit system and corresponding emergencies and can form 3D images; the compound eye high definition camera can comprehensively detect potential safety hazards in a rail transit system, and display the running state of a train, the environmental factor condition in the rail transit system and the state of each device in an omnibearing manner through image data; the sound collector can identify abnormal sounds (such as abnormal engine sounds and abnormal train sounds) in the running process of the rail transit system; the odor collector can identify peculiar smell in the rail transit system and classify the peculiar smell (such as explosives, drugs and the like); the temperature collector can record the temperature state in the running process of the rail transit system and can identify abnormal temperature changes (such as cable temperature rise, temperature rise caused by fire, temperature rise caused by power short circuit and the like) in the rail transit system.

The invention relates to a system for monitoring and intelligent early warning of rail transit faults, which is characterized in that a data comparison module comprises

And a data comparison module: the real-time state data collected by the data collection module is compared with corresponding data in the database module, and a comparison result is transmitted to the data judgment module;

and a data judging module: and the comparison result is used for judging according to a threshold value set in the database module, generating fault information or early warning information, and transmitting the fault information or the early warning information to the data transmission module.

The data comparison module is arranged on the data acquisition device, and the data acquisition device is also provided with a data memory for storing the comparison data transmitted by the database module, so that the real-time state data can be judged whether to have fault information or early warning information according to the comparison data at the first time after acquisition.

The invention relates to a system for monitoring and intelligent early warning of rail transit faults, which is characterized in that, as an optimal mode, a regional processor module comprises

And a fault diagnosis module: the system comprises a display module, a fault classification module, a fault ranking module, a fault locating module, a fault classification module, a fault ranking module and a fault locating module, wherein the display module is used for displaying fault classification information, fault ranking information and fault locating information;

And the fault early warning module is used for: the early warning information processing system is used for classifying and grading the early warning information, positioning the early warning information and feeding back the early warning classification information, the early warning grading information and the early warning positioning information to a user through the display module.

The regional processor module firstly divides the data transmitted by the data transmission module into normal data, fault data and early warning data, wherein the normal data is directly stored and transmitted to the central processor module, the fault data is transmitted to the fault diagnosis module for classification, positioning and rating, and the early warning information is transmitted to the fault early warning module for classification, positioning and rating.

The invention relates to a system for monitoring and intelligent early warning of rail transit faults, which is characterized in that a database module comprises:

and a fault information module: the system is used for storing rail transit fault information, fault classification information, fault positioning information, fault rating information and fault thresholds;

and the early warning information module: the system is used for storing rail transit early warning information, early warning classification information, early warning positioning information, early warning rating information and early warning thresholds;

knowledge base module: the method is used for storing service life and abrasion data information of each part and component of rail transit;

An reasoner module: and the system is used for classifying and updating the fault information or the warning information summarizing result transmitted by the central processing unit module to the fault information module, the warning information module and the knowledge base module.

The database module can realize automatic updating according to the fault information and the early warning information summarized by the central processing unit, and takes the updated result as the basis for judging or rating the next fault information or the early warning information, thereby realizing the intelligent growth of the whole rail transit fault monitoring and intelligent early warning system.

The invention relates to a system for monitoring and intelligent early warning of rail transit faults, which is characterized in that a display module comprises one or a combination display, a loudspeaker and a signal lamp of the following devices. The display can restore the fault or early warning site in an image mode, provides a basis for further understanding the fault or early warning information, and can also illustrate the fault or early warning classification information, position information, rating information and the like through the display of characters; the horn can enable a user to know the occurrence of faults or early warning in the whole platform range at the first time, and the classification and rating information of the faults or the early warning can be reflected by setting different sounds; the signal lamp enables a user to know the occurrence of faults or early warning in the first time through visual effect, and the classification and rating information of the faults or the early warning can be reflected through the color and the flashing state of the signal lamp.

The system for monitoring and intelligent early warning of rail transit faults, disclosed by the invention, is characterized in that the fault information comprises a power circuit fault, a rail equipment fault, a tunnel equipment fault, a platform equipment fault, a train fault and an auxiliary equipment fault in a preferable mode. The fault mainly refers to equipment damage affecting the safe operation of rail transit and various emergencies such as power failure, foreign matter entering and the like, and when the fault occurs, fault information is sent out.

The invention relates to a system for monitoring and intelligent early warning of rail transit faults, which is characterized in that the power circuit faults comprise power short circuits, power supply stop and battery faults as an optimal mode; the faults of the track equipment comprise roadbed deformation, sleeper crack, abrasion, rail abrasion, crack, corrosion, connector fracture, crack, defect, deformation, corrosion, damage to the track reinforcing equipment and track foreign matters; the tunnel equipment faults comprise tunnel cracks and foreign matters; the platform equipment faults comprise shielding door equipment faults, platform board faults and foreign matters; the train faults comprise train running state faults, train surface cracks and foreign matters; the auxiliary equipment fault marks the defect.

The system for monitoring and intelligent early warning of rail transit faults, disclosed by the invention, is used for realizing the optimal way that early warning information comprises power supply circuit early warning, rail equipment early warning, tunnel equipment early warning, platform equipment early warning, train early warning and auxiliary equipment early warning. Because the components and parts on each equipment have fixed service life according to different requirements, and the damage such as abrasion, cracks and the like of each equipment also have different grades, the early warning information is sent out when the set threshold value is reached.

The system for monitoring the rail transit faults and intelligently pre-warning is characterized in that the power circuit pre-warning comprises battery pre-warning, cable pre-warning and component service life pre-warning as a preferable mode; the rail equipment early warning comprises roadbed deformation, sleeper crack, abrasion, rail abrasion, crack, corrosion, connector crack, defect, deformation, corrosion, rail reinforcing equipment, rail foreign matters and component service life early warning; the tunnel equipment early warning comprises tunnel crack early warning; the platform equipment early warning comprises early warning of the service life of components of the shielding door equipment and early warning of the service life of a platform board; the train early warning comprises train running state early warning, train surface crack early warning and train component early warning; fault indication defect early warning of auxiliary equipment.

The power supply circuit comprises a track power supply, a train power supply, a platform screen door power supply, a data acquisition device power supply and the like, when the power supply has the conditions of short circuit, power failure and the like, the corresponding sensor sends a fault signal, the data acquisition device collects the fault signal and performs positioning and rating, and the result is transmitted to the regional processor module for alarming so as to remove the fault in time; when the equipment such as battery, cable reach predetermined life, corresponding sensor sends the early warning signal, and data acquisition device gathers early warning signal and fixes a position and rate, and the result is transmitted to regional processor module and is carried out the early warning to in time change elimination hidden danger.

The track equipment comprises roadbeds, track beds, sleepers, steel rails, connecting parts, track reinforcing equipment and the like.

The roadbed is a strip-shaped structure which is built according to the route position and certain technical requirements and is used as a road foundation, is a foundation of a railway and a highway, and is a linear structure built by using soil or stone; and when the deformation of the roadbed reaches the fault threshold, sending a fault signal.

The ballast bed is an important component of a track and is a foundation of a track frame, and is generally referred to as a ballast (ballast) cushion layer paved on a roadbed below a railway sleeper, and is mainly used for supporting the sleeper, uniformly transmitting huge pressure on the upper part of the sleeper to the roadbed, fixing the position of the sleeper, preventing the sleeper from moving longitudinally or transversely, greatly reducing the deformation of the roadbed, and relieving the impact of locomotive wheels on a steel rail so as to facilitate drainage; and when the deformation of the ballast bed reaches the fault threshold, sending a fault signal.

The sleeper is also called sleeper, is one of railway accessories, is used for supporting the steel rail, keeping the position of the steel rail, and transmitting huge pressure transmitted by the steel rail to the track bed, so that the sleeper has certain flexibility and elasticity, can be properly deformed to buffer the pressure when a train passes, and needs to be restored as far as possible after the train passes; the fault or early warning of the sleeper comprises crack, abrasion and displacement deformation, namely, when the sleeper crack reaches an early warning threshold value, an early warning signal is sent, and when the sleeper crack reaches the fault threshold value, a fault signal is sent; when the sleeper abrasion reaches the early warning threshold value, an early warning signal is sent, and when the sleeper abrasion reaches the fault threshold value, a fault signal is sent; when the displacement (namely the sleeper spacing) generated by the sleeper reaches an early warning threshold value, an early warning signal is sent, and when the displacement (namely the sleeper spacing) generated by the sleeper reaches a fault threshold value, a fault signal is sent; the sleeper also has a set threshold value of service life, and when the service life of the sleeper reaches the set threshold value, an early warning signal is sent out.

Rails are the main component of a railway track for guiding the wheels of a rolling stock to advance, bear the great pressure of the wheels, and transmit the pressure to the sleeper, and must provide the wheels with a continuous, smooth rolling surface with minimal resistance; the fault or early warning of the steel rail comprises cracks, abrasion, rust, offset and the like, namely, when the crack of the steel rail reaches an early warning threshold value, an early warning signal is sent, and when the crack of the steel rail reaches a fault threshold value, a fault signal is sent; when the abrasion of the steel rail reaches an early warning threshold value, an early warning signal is sent, and when the abrasion of the steel rail reaches a fault threshold value, a fault signal is sent; when the steel rail corrosion reaches the early warning threshold value, an early warning signal is sent, and when the steel rail corrosion reaches the fault threshold value, a fault signal is sent; when the steel rail offset reaches the early warning threshold value, an early warning signal is sent, and when the steel rail offset reaches the fault threshold value, a fault signal is sent; the steel rail also has a set threshold value of service life, and when the service life of the steel rail reaches the set threshold value, an early warning signal is sent.

The connecting part comprises a joint clamping plate, a joint bolt, a backing plate and the like, and the fault or early warning information comprises cracks, defects, deformation, corrosion and the like, namely, when the cracks, defects, deformation, corrosion and the like of the connecting part reach an early warning threshold value, an early warning signal is sent, and when the cracks, defects, deformation, corrosion and the like of the connecting part reach a fault threshold value, a fault signal is sent; each connecting part is also provided with a respective service life set threshold value, and when the service life of the connecting part reaches the set threshold value, an early warning signal is sent out.

The track reinforcing equipment comprises track gauge pull rods, track supports, anti-climbing devices and the like, and fault or early warning information comprises cracks, wear, deformation, corrosion and the like, namely, when the cracks, the wear, the deformation, the corrosion and the like of the track reinforcing equipment reach an early warning threshold value, an early warning signal is sent, and when the cracks, the wear, the deformation, the corrosion and the like of the track reinforcing equipment reach a fault threshold value, a fault signal is sent; each track reinforcing device is also provided with a respective service life set threshold value, and when the service life of the track reinforcing device reaches the set threshold value, an early warning signal is sent out.

The platform equipment comprises shielding doors, platform boards and the like, fault and early warning information comprises appearance (including cracks, abrasion, deformation and the like) and components (including engines, sensors, conveying devices and the like); when the cracks, the abrasion and the deformation of the shielding door and the platform plate reach the early warning threshold value, an early warning signal is sent, and when the cracks, the abrasion and the deformation of the shielding door and the platform plate reach the fault threshold value, a fault signal is sent; when the service condition of the component reaches the early warning threshold value, an early warning signal is sent, and when the service condition of the component reaches the fault threshold value, a fault signal is sent; and meanwhile, each part and component of the shielding door and the platform plate also have respective service life set threshold values, and when the service lives of the parts and components of the shielding door and the platform plate reach the set threshold values, an early warning signal is sent out.

According to the invention, the data acquisition module is arranged on the data acquisition equipment to reciprocate in the monitoring area, so that faults and early warning of rail transit in the movement process can be found in real time, and fault information and early warning information can be rapidly transmitted to the area processor module for classification, positioning and grading, and the fault category and fault address can be rapidly and accurately determined.

The invention further establishes a knowledge base module of service life and abrasion data information of each device component of the rail transit, can early warn foreseeable faults in advance, reduces the probability of occurrence of the faults, and simultaneously has the intelligent updating function of the related fault information module, the early warning information module and the knowledge base module.

Drawings

FIG. 1 is a flow chart of a method of using a system for rail transit fault monitoring and intelligent pre-warning;

FIG. 2 is a flowchart of a method step S2 of using a system for monitoring and intelligent pre-warning of rail transit faults;

FIG. 3 is a flow chart of a method of rating a system for rail transit fault monitoring and intelligent pre-warning;

FIG. 4 is a diagram of a system for rail transit fault monitoring and intelligent pre-warning;

FIG. 5 is a diagram of the data acquisition module of a system for monitoring rail transit faults and intelligent pre-warning;

FIG. 6 is a diagram of a data comparison module for a rail transit fault monitoring and intelligent pre-warning system;

FIG. 7 is a block diagram of a regional processor module of a system for rail transit fault monitoring and intelligent pre-warning;

FIG. 8 is a diagram of a database module configuration of a system for rail transit fault monitoring and intelligent pre-warning;

FIG. 9 is a flowchart of an embodiment 1 of a method of using a system for rail transit fault monitoring and intelligent pre-warning;

FIG. 10 is a flowchart of an embodiment 2 of a method of using a system for rail transit fault monitoring and intelligent pre-warning;

FIG. 11 is a flowchart of an embodiment 3 of a method for using a system for rail transit fault monitoring and intelligent pre-warning;

FIG. 12 is a flowchart of an embodiment 4 of a method for using a system for rail transit fault monitoring and intelligent pre-warning;

FIG. 13 is a flowchart of an embodiment 5 of a method of using a system for rail transit fault monitoring and intelligent pre-warning;

FIG. 14 is a flowchart of an embodiment 6 of a method of using a system for rail transit fault monitoring and intelligent pre-warning;

FIG. 15 is a flowchart of an embodiment 7 of a method of using a system for rail transit fault monitoring and intelligent pre-warning;

FIG. 16 is a flowchart of an embodiment 8 of a method of using a system for rail transit fault monitoring and intelligent pre-warning;

fig. 17 is a flowchart of an embodiment 9 of a method for using a system for monitoring and intelligent pre-warning of rail transit faults.

Detailed Description

Specific embodiments of the present invention will be described below with reference to the drawings.

The invention provides a method for a rail transit fault monitoring and intelligent early warning system, which is suitable for real-time and dynamic monitoring of the rail transit fault monitoring and intelligent early warning system, and sets the corresponding relation between real-time state data and corresponding data in a database module, as shown in figures 1-3, and comprises the following steps:

s1, a data acquisition device acquires real-time state data;

s2, the data comparison device compares and judges the real-time state data with corresponding data in the database module to generate fault information or early warning information; comprising

S23, positioning and grading fault information or early warning information; the rating comprises the steps of:

S27, calculating a threshold value of the early warning or fault class i

(4) if F is more than 5, the grade is red early warning or fault, which means that the early warning or fault number is very high, and emergency guarantee measures need to be immediately carried out;

The invention provides a system for realizing a rail traffic fault monitoring and intelligent early warning method, as shown in figures 4-8, the system comprises:

the data acquisition module 100: the real-time state data of each detection point are collected; comprising

The data recording module 110: the real-time state data used for recording the data acquisition device in the motion process is acquired, and the data acquisition device comprises one or a combination of the following devices: the device comprises a radio frequency scanning device, a laser scanning device, a compound eye high definition camera, a sound collector, an odor collector and a temperature collector;

the data collection module 120: the system is used for collecting real-time state data sent by sensors on equipment such as trains, tracks, platforms and the like;

data comparison module 200: the real-time state data collected by the data acquisition module is compared and judged with corresponding data in the database module, fault information or early warning information is generated, and the fault information or the early warning information is transmitted to the data transmission module; comprising

The data comparison module 210: the real-time state data collected by the data collection module is compared with corresponding data in the database module, and a comparison result is transmitted to the data judgment module;

the data judging module 220: the data transmission module is used for judging the comparison result according to the threshold value set in the database module, generating fault information or early warning information and transmitting the fault information or the early warning information to the data transmission module;

data transfer module 300: the system is used for compressing fault information or early warning information and then transmitting the compressed fault information or early warning information to the regional processor module;

the zone processor module 400: the data transmission module is used for transmitting the comparison result to the central processing unit module, and transmitting the comparison result to the user; comprising

The fault diagnosis module 410: the system comprises a display module, a fault classification module, a fault ranking module, a fault locating module, a fault classification module, a fault ranking module and a fault locating module, wherein the display module is used for displaying fault classification information, fault ranking information and fault locating information;

fault early warning module 420: the early warning information processing system is used for classifying and grading the early warning information, positioning the early warning information and feeding back the early warning classification information, the early warning grading information and the early warning positioning information to a user through the display module.

Central processing module 500: the system comprises a region processor module, a database module, a processing module and a processing module, wherein the region processor module is used for receiving classification information and processing results transmitted by the region processor module, and updating the classification information and the processing results to the database module after summarizing;

database module 600: the system comprises a central processing unit module, a fault information storage module, a warning information storage module and a control module, wherein the fault information storage module is used for storing fault information, warning information and update information summarized by the central processing unit module; comprising the following steps:

fault information module 610: the system is used for storing rail transit fault information, fault classification information, fault positioning information, fault rating information and fault thresholds;

the early warning information module 620: the system is used for storing rail transit early warning information, early warning classification information, early warning positioning information, early warning rating information and early warning thresholds;

knowledge base module 630: the method is used for storing service life and abrasion data information of each part and component of rail transit;

reasoner module 640: the system comprises a fault information module, an early warning information module and a knowledge base module, wherein the fault information module is used for receiving fault information or early warning information summarized results transmitted by the central processing unit module;

display module 700: the display module is used for feeding back the processing result sent by the regional processor module to the user, and comprises one of the following devices or a combined display, a loudspeaker and a signal lamp.

Example 1

As shown in fig. 9, the method comprises the following steps:

S11, acquiring real-time state data of tunnel cracks by a compound eye high-definition camera;

s12, the data comparison module 200 compares corresponding data in the database module to judge whether the tunnel crack exceeds a set threshold value, if not, the step S18 is entered, and if so, the step S13 is entered;

s13, generating fault information or early warning information, and positioning and grading the fault information or the early warning information;

s14, the data transmission module 300 transmits real-time state data, fault information or early warning information to the area processing module 400;

s15, the area processing module 400 classifies the real-time state data, the fault information or the early warning information, transmits the classification information, the positioning information and the rating information of the fault or the early warning to the display module 700, and transmits all data to the central processing module 500;

s16, the CPU module 500 updates the real-time status data and fault information or early warning information to the database module 600;

s17, the display module 700 feeds back fault information or early warning information to a user through a display, and when F is more than 5, an alarm signal is sent to a train to enable the train to slow down or stop running, meanwhile, the regional processor 400 sends a signal to a maintenance center to arrange fault treatment, and the treatment result is transmitted to the central processor module 500;

S18, the data transmission module 300 transmits the real-time status data to the area processing module 400;

s19, the area processing module 400 transmits the real-time status data to the central processing module 500;

s110, the central processing unit module 500 updates the real-time status data to the database module 600.

In the embodiment, the cracks of the tunnel are detected through compound eye camera shooting, the form and the size of the cracks are displayed in an image mode, the early warning rating or the fault rating of the cracks are judged through the data comparison module 200, and the crack image data, the position information and the rating information are fed back to a user through the display module.

Example 2

As shown in fig. 10, the method comprises the following steps:

s21, acquiring real-time state data of steel rail deformation by a compound eye high-definition camera;

s22, the data comparison module 200 compares corresponding data in the database module to judge whether the rail deformation exceeds a set threshold value, if not, the step S28 is entered, and if so, the step S23 is entered;

s23, generating fault information or early warning information, and positioning and grading the fault information or the early warning information;

s24, the data transmission module 300 transmits real-time state data, fault information or early warning information to the area processing module 400;

S25, the area processing module 400 classifies the real-time state data, the fault information or the early warning information, transmits the classification information, the positioning information and the rating information of the fault or the early warning to the display module 700, and transmits all data to the central processing module 500;

s26, the CPU module 500 updates the real-time status data and fault information or early warning information to the database module 600;

s27, the display module 700 feeds back fault information or early warning information to a user through a display, wherein the deformation position, the deformation and the grading result of the steel rail are fed back to the user, when F is more than 5, an alarm signal is sent to the train to stop the train, meanwhile, the regional processor 400 sends a signal to a maintenance center to arrange fault treatment, and the treatment result is transmitted to the central processor module 500;

s28, the data transmission module 300 transmits the real-time status data to the area processing module 400;

s29, the area processing module 400 transmits the real-time status data to the central processing module 500;

s210, the central processing unit module 500 updates the real-time status data to the database module 600.

In this embodiment, the deformed state of the track is detected by the compound eye camera, the deformed state and the deformed size are determined by the data comparison module 200, and early warning rating or failure rating of the deformation is determined, so that the track deformed field image data, position information and rating information are fed back to the user by the display module.

Example 3

As shown in fig. 11, the method comprises the following steps:

s31, acquiring real-time state data of abnormal sound in the running process of the train by a sound collector;

s32, the data comparison module 200 compares the corresponding data in the database module to judge whether the class of the abnormal sound is a fault or a suspected abnormal sound of early warning, if not, the step S39 is entered, and if yes, the step S33 is entered;

s33, judging suspicious abnormal sound according to a preset threshold, if the suspicious abnormal sound does not exceed the preset threshold, entering a step S39, and if the suspicious abnormal sound exceeds the preset threshold, entering a step S34;

s34, generating fault information or early warning information, and positioning and grading the fault information or the early warning information;

s35, the data transmission module 300 transmits real-time state data, fault information or early warning information to the area processing module 400;

s36, the area processing module 400 classifies the real-time state data, the fault information or the early warning information, transmits the classification information, the positioning information and the rating information of the fault or the early warning to the display module 700, and transmits all the data to the central processing module 500;

s37, the CPU module 500 updates the real-time state data and fault information or early warning information to the database module 600;

S38, the display module 700 feeds back the position information and the rating information of abnormal sound to the user through the display, and feeds back the fault information or the early warning information to the user through the loudspeaker, and when F is more than 5, the regional processor 400 sends a signal to the maintenance center to arrange for processing the fault and transmits the processing result to the central processor module 500; the method comprises the steps of carrying out a first treatment on the surface of the

S39, the data transmission module 300 transmits the real-time status data to the area processing module 400;

s310, the area processing module 400 transmits the real-time status data to the central processing module 500;

s311, the cpu module 500 updates the real-time status data to the database module 600.

The abnormal sound in the running process of the train is found through the sound collector, the early warning rating or the fault rating of the abnormal sound is judged through the data comparison module 200, and the position information and the rating information of the abnormal sound are fed back to the user through the display module. For the generation of abnormal sound, the sensor on the train can also send a signal to the data collection module 120 to judge and grade, and the abnormal sound can be judged secondarily.

Example 4

As shown in fig. 12, the method comprises the following steps:

s41, collecting real-time state data of platform foreign bodies by a laser scanning device;

S42, the data comparison module 200 compares corresponding data in the database module to judge whether the size of the foreign matter exceeds a set threshold, if not, the step S48 is entered, and if so, the step S43 is entered;

s43, generating fault information or early warning information, and positioning and grading the fault information or the early warning information;

s44, the data transmission module 300 transmits the real-time status data, the fault information or the early warning information to the area processing module 400;

s45, the area processing module 400 classifies the real-time state data, the fault information or the early warning information, transmits the classification information, the positioning information and the rating information of the fault or the early warning to the display module 700, and transmits all data to the central processing module 500;

s46, the CPU module 500 updates the real-time status data and the fault information or the early warning information to the database module 600;

s47, the display module 700 feeds back the position, the size, the 3D image and the grading result of the foreign matters to the user through the display, and feeds back the position, the size, the 3D image and the grading result to the user through the signal lamp flickering, when F is more than 5, an alarm signal is sent to the train to stop the train, meanwhile, the area processor 400 sends a signal to the maintenance center to arrange the foreign matters to be processed, and the processing result is transmitted to the central processor module 500; the method comprises the steps of carrying out a first treatment on the surface of the

S48, the data transmission module 300 transmits the real-time status data to the area processing module 400;

s49, the area processing module 400 transmits the real-time status data to the central processing module 500;

s410, the central processing unit module 500 updates the real-time status data to the database module 600.

In this embodiment, the laser scanning device discovers the foreign matter on the platform, the morphological characteristics of the foreign matter are displayed through 3D imaging, the early warning rating or the fault rating of the foreign matter is judged through the data comparison module 200, and the position information and the rating information of the foreign matter are fed back to the user through the display module. For appearance of foreign matters, the compound eye high-definition camera can also collect influence data of the foreign matters to judge and grade, and can judge the foreign matters secondarily.

Example 5

As shown in fig. 13, the method comprises the following steps:

s51, a radio frequency scanning device collects real-time state data of a platform screen door sensor;

s52, the data comparison module 200 compares corresponding data in the database module, judges whether the number of times of opening and closing the shielding door exceeds a set threshold, and if the number of times of opening and closing the shielding door does not exceed the set threshold, the step S58 is entered, and if the number of times of opening and closing the shielding door exceeds the set threshold, the step S53 is entered;

s53, generating early warning information, and positioning and grading the early warning information;

S54, the data transmission module 300 transmits the real-time state data and the early warning information to the area processing module 400;

s55, the area processing module 400 classifies the real-time state data and the early warning information, transmits the classification information, the positioning information and the rating information of the early warning information to the display module 700, and transmits all data to the central processing module 500;

s56, the CPU module 500 updates the real-time status data and the early warning information to the database module 600;

s57, the display module 700 feeds back the failure information or early warning information to the user through the display, and feeds back the shielding door switching times and early warning rating results to the user through signal lamp flickering;

s58, the data transmission module 300 transmits the real-time status data to the area processing module 400;

s59, the area processing module 400 transmits the real-time status data to the central processing module 500;

s510, the cpu module 500 updates the real-time status data to the database module 600.

In this embodiment, the real-time status data of the platform screen door sensor is collected by the radio frequency scanning device, the early warning rating or the fault rating of the running status of the platform screen door is judged by the data comparison module 200, and the position information and the rating information are fed back to the user by the display module.

Example 6

As shown in fig. 14, the method comprises the following steps:

s61, acquiring real-time state data of a track traffic sign by a compound eye high-definition camera;

s62, the data comparison module 200 compares corresponding data in the database module, judges whether the marked defect exceeds a set threshold, and if the marked defect does not exceed the set threshold, the step S68 is entered, and if the marked defect exceeds the set threshold, the step S63 is entered;

s63, generating early warning information, and positioning and grading the early warning information;

s64, the data transmission module 300 transmits the real-time state data and the early warning information to the area processing module 400;

s65, the area processing module 400 classifies the real-time state data and the early warning information, transmits the classification information, the positioning information and the rating information of the early warning information to the display module 700, and transmits all data to the central processing module 500;

s66, the central processing unit module 500 updates the real-time state data and the early warning information to the database module 600;

s67, the display module 700 feeds back the fault information or the early warning information to the user through the display to indicate the defect state and the rating result;

s68, the data transmission module 300 transmits the real-time status data to the area processing module 400;

S69, the area processing module 400 transmits the real-time status data to the central processing module 500;

s610, the cpu module 500 updates the real-time status data to the database module 600.

In this embodiment, the missing marks are found by the compound eye high definition camera, the morphological characteristics of the missing marks are displayed by the image data, the early warning rating or the fault rating of the missing marks are judged by the data comparison module 200, and the position information and the rating information of the missing marks are fed back to the user through the display module.

Example 7

As shown in fig. 15, the method comprises the following steps:

s71, collecting real-time state data of station odor by an odor collector;

s72, the data comparison module 200 compares according to the corresponding data in the database module, judges whether the type of the peculiar smell is a fault or a suspicious peculiar smell of early warning, if not, the step S79 is entered, and if so, the step S73 is entered;

s73, the data comparison module 200 compares corresponding data in the database module to judge whether the concentration of the peculiar smell exceeds a set threshold value, if the concentration of the peculiar smell does not exceed the set threshold value, the step S79 is carried out, and if the concentration of the peculiar smell exceeds the set threshold value, the step S74 is carried out;

s74, generating fault information or early warning information, and positioning and grading the fault information or the early warning information;

S75, the data transmission module 300 transmits real-time state data, fault information or early warning information to the area processing module 400;

s76, the area processing module 400 classifies the real-time status data, the fault information or the early warning information, transmits the classification information, the positioning information and the rating information of the fault or the early warning to the display module 700, and transmits all the data to the central processing module 500;

s77, the CPU module 500 updates the real-time status data and the fault information or the early warning information to the database module 600;

s78, the display module 700 feeds back the fault information or the early warning information to the user through the display, and feeds back the peculiar smell type, concentration and grading result to the user through the signal lamp flashing, when F is more than 5, an alarm signal is sent to the train to stop the train, meanwhile, the area processor 400 sends a signal to the maintenance center to process suspicious peculiar smell, and the processing result is transmitted to the central processor module 500; the method comprises the steps of carrying out a first treatment on the surface of the

S79, the data transmission module 300 transmits the real-time status data to the area processing module 400;

s710, the area processing module 400 transmits the real-time status data to the central processing module 500;

s711, the cpu module 500 updates the real-time status data to the database module 600.

The odor collector finds the odor on the platform, the data comparison module 200 judges the classification information, the early warning rating or the fault rating of the air temperature, and the type, the position information and the rating information of the odor are fed back to the user through the display module. For the generation of certain peculiar smell, such as fire disaster, the temperature collector can also judge and grade through collecting temperature change data, and can carry out compound judgment on the peculiar smell.

Example 8

As shown in fig. 16, the method comprises the following steps:

s81, a temperature collector collects real-time state data of the temperature of the cable;

s82, the data comparison module 200 compares corresponding data in the database module to judge whether the temperature change exceeds a set threshold, if not, the step S88 is entered, and if so, the step S83 is entered;

s83, generating fault information or early warning information, and positioning and grading the fault information or the early warning information;

s84, the data transmission module 300 transmits real-time status data, fault information or early warning information to the area processing module 400;

s85, the area processing module 400 classifies the real-time state data, the fault information or the early warning information, transmits the classification information, the positioning information and the rating information of the fault or the early warning to the display module 700, and transmits all data to the central processing module 500;

S86, the CPU module 500 updates the real-time status data and the fault information or the early warning information to the database module 600;

s87, the display module 700 feeds back the temperature change condition and the grading result to the user through the display, when F is more than 5, an alarm signal is sent to the train to stop the train, and meanwhile, the area processor 400 sends a signal to the maintenance center to arrange for processing the suspicious temperature change and transmits the processing result to the central processor module 500;

s88, the data transmission module 300 transmits the real-time status data to the area processing module 400;

s89, the area processing module 400 transmits the real-time status data to the central processing module 500;

s810, the central processing unit module 500 updates the real-time status data to the database module 600.

In the embodiment, real-time state data of the cable temperature is collected through the temperature collector, early warning rating or fault rating of the cable temperature change is judged through the data comparison module 200, and position information and rating information of the cable are fed back to a user through the display module. For the cable temperature change to a certain extent, if combustion is caused, the odor collector can also judge and grade through collecting the odor data, and can carry out compound judgment on the cable temperature change.

Example 9

As shown in fig. 17, the method comprises the following steps:

s91, acquiring real-time state data of a vehicle door in the running process of a train by using a compound eye high-definition camera and a laser scanning device;

s92, the data comparison module 200 compares corresponding data in the database module to judge whether the deformation of the train door exceeds a set threshold, if not, the step S98 is carried out, and if so, the step S93 is carried out;

s93, generating fault information or early warning information, and positioning and grading the fault information or the early warning information;

s94, the data transmission module 300 transmits real-time status data, fault information or early warning information to the area processing module 400;

s95, the area processing module 400 classifies the real-time status data, the fault information or the early warning information, transmits the classification information, the positioning information and the rating information of the fault or the early warning to the display module 700, and transmits all the data to the central processing module 500;

s96, the CPU module 500 updates the real-time status data and the fault information or the early warning information to the database module 600;

s97, the display module 700 feeds back the door status and the rating result of the train in the running process of the train to a user through a display, when F is more than 5, (if the door is abnormally opened), the laser scanning device displays a 3D image, the compound eye high definition camera generates real-time status influence data, an alarm signal is sent to the train to stop the running of the train, meanwhile, the regional processor 400 sends a signal to a maintenance center to arrange for processing faults, and the processing result is transmitted to the central processor module 500; the method comprises the steps of carrying out a first treatment on the surface of the

S98, the data transmission module 300 transmits the real-time status data to the area processing module 400;

s99, the area processing module 400 transmits the real-time status data to the central processing module 500;

s910, the cpu module 500 updates the real-time status data to the database module 600.

In the embodiment, real-time state data of a vehicle door in the running process of a train is collected through the compound eye high definition camera and the laser scanning device, early warning rating or fault rating of the abnormal vehicle door is judged through the data comparison module 200, and the position information and the rating information of the vehicle door which generate faults are fed back to a user through the display module. The laser scanning device can generate a 3D image, and the compound eye high-definition camera can generate image data for compound judgment.

The foregoing description is intended to be illustrative only and not limiting, and it will be understood by those skilled in the art that any modifications, changes or equivalents may be made without departing from the spirit and scope of the invention as defined in the following claims.

Claims

1. The method for monitoring the rail transit fault and intelligent early warning is suitable for real-time and dynamic monitoring of a rail transit fault monitoring and intelligent early warning system and is characterized in that: setting the corresponding relation between the real-time state data and the corresponding data in the database module, comprising the following steps:

S1, acquiring real-time state data through a data acquisition module;

s2, the data comparison module compares and judges the real-time state data with corresponding data in the database module to generate fault information or early warning information;

s3, the fault information or the early warning information is transmitted to a regional processor module through a data transmission module;

s4, the regional processor module classifies the fault information or the early warning information according to the classification information in the database module, feeds the fault information or the early warning information back to a user through a display module and transmits the fault information or the early warning information to the central processor module;

s5, the central processing unit module gathers the fault information or the early warning information transmitted by each regional processing unit module, and stores and updates the fault information or the early warning information to the database module;

wherein, the step S2 further comprises the following steps:

s21, comparing the real-time state data with corresponding data of the database module, and displaying differences between the real-time state data and the corresponding data;

s22, judging whether the difference exceeds the set threshold according to the set threshold of the database module, if not, directly ending, and if so, executing step S23;

S23, positioning and grading the fault information or the early warning information;

wherein the evaluation comprises the steps of:

s24, classifying the early warning information or the fault information received by the area processor module through the database module to obtain an early warning or fault category i;

S26, acquiring the occurrence frequency F of one month on the early warning or fault class i through the database module _iy And a month average F of the number of occurrences in approximately 12 months _iz ；

S27, calculating a threshold value of the early warning or fault class i

(2) if F is more than 1 and less than or equal to 3, the grade is yellow early warning or failure, which means that the number of early warning or failure is not high, and the observation needs to be paid attention to;

2. A system for implementing a method for monitoring and intelligent pre-warning rail transit faults, characterized in that: the system comprises:

and a data acquisition module: the real-time state data of each detection point are collected;

and a data comparison module: the real-time state data collected by the data collection module is compared and judged with corresponding data in the database module, fault information or early warning information is generated, and the fault information or the early warning information is transmitted to the data transmission module;

a data transmission module: the fault information or early warning information is transmitted to the regional processor module;

region processor module: the data transmission module is used for transmitting the information transmitted by the data transmission module to the central processing unit module, and transmitting the information to the central processing unit module;

and a central processing unit module: the database module is used for receiving the classification information and the processing result transmitted by the regional processor module, and updating the classification information and the processing result to the database module after summarizing;

and a display module: the processing result sent by the regional processor module is fed back to the user;

The data comparison module specifically executes the following steps:

the evaluation comprises the following steps:

S27, calculating a threshold value of the early warning or fault class i

3. A system for implementing a method for rail transit fault monitoring and intelligent pre-warning as claimed in claim 2, wherein: the data acquisition module comprises

and a data collection module: the system is used for collecting real-time state data sent by sensors on the train, the track and the platform equipment.

4. A system for implementing a method for rail transit fault monitoring and intelligent pre-warning as claimed in claim 3, wherein: the data acquisition device comprises one or a combination of the following devices

The device comprises a radio frequency scanning device, a laser scanning device, a compound eye high definition camera, a sound collector, an odor collector and a temperature collector.

5. A system for implementing a method for rail transit fault monitoring and intelligent pre-warning as claimed in claim 2, wherein: the data comparison module comprises

And a data comparison module: the data acquisition module is used for acquiring real-time state data of the data acquisition module, and transmitting the real-time state data to the database module;

6. The system for implementing the method for monitoring and intelligent pre-warning of rail transit faults as claimed in claim 5, wherein: the zone processor module includes

And a fault diagnosis module: the fault information processing module is used for classifying and grading the fault information, positioning the fault information and feeding back the fault classification information, the fault grading information and the fault positioning information to a user through the display module;

and the fault early warning module is used for: the early warning information processing module is used for classifying and grading the early warning information, positioning the early warning information, and feeding back the early warning classification information, the early warning grading information and the early warning positioning information to a user through the display module.

7. A system for implementing a method for rail transit fault monitoring and intelligent pre-warning as claimed in claim 2, wherein: the database module comprises:

8. A system for implementing a method for rail transit fault monitoring and intelligent pre-warning as claimed in claim 2, wherein: the display module comprises one or a combination of the following devices: display, loudspeaker, signal lamp.

9. The system for implementing the method for monitoring and intelligent pre-warning of rail transit faults as claimed in claim 7, wherein: the fault information includes power circuit faults, rail equipment faults, tunnel equipment faults, platform equipment faults, train faults and auxiliary equipment faults.

10. The system for implementing the method for monitoring and intelligent pre-warning of rail transit faults according to claim 9, wherein: the power circuit faults comprise power short circuit, power supply stop and battery faults; the rail equipment faults comprise roadbed deformation, sleeper crack, abrasion, rail abrasion, crack and corrosion, connector fracture, crack, defect, deformation and corrosion, rail reinforcing equipment damage and rail foreign matters; the tunnel equipment faults comprise tunnel cracks and foreign matters; the platform equipment faults comprise shielding door equipment faults, platform board faults and foreign matters; the train faults comprise train running state faults, train surface cracks and foreign matters; the auxiliary device failure includes a tamper evident defect.

11. The system for implementing the method for monitoring and intelligent pre-warning of rail transit faults as claimed in claim 7, wherein: the early warning information comprises a power supply circuit early warning, a track device early warning, a tunnel device early warning, a platform device early warning, a train early warning and an auxiliary device early warning.

12. The system for implementing the method for monitoring and intelligent pre-warning of rail transit faults as claimed in claim 11, wherein: the power supply circuit early warning comprises battery early warning, cable early warning and component service life early warning; the rail equipment early warning comprises roadbed deformation early warning, sleeper crack, abrasion early warning, rail abrasion, crack and corrosion early warning, connector crack, defect, deformation and corrosion early warning, rail reinforcing equipment early warning, rail foreign matter early warning and component service life early warning; the tunnel equipment early warning comprises tunnel crack early warning; the platform equipment early warning comprises early warning of the service life of components of the shielding door equipment and early warning of the service life of the platform plate; the train early warning comprises train running state early warning, train surface crack early warning and train component early warning; the auxiliary equipment early warning comprises indication defect early warning.