System and method for automated monitoring of overhead monorail track construction

Abstract

An automated monitoring system and method for elevated tracks constructed with single-track upper and lower sections is disclosed, relating to transportation systems constructed with single-track upper and lower sections, and particularly to the technical field of track monitoring. This invention utilizes the pattern that when a track section in an elevated track experiences severe faults such as breakage or collapse, severe displacement of track components will appear in adjacent images; and when major track components experience faults such as loosening, vibration amplitude exceeding the normal range will always occur when a vehicle travels over that section. By installing an AI-powered automated monitoring device on the elevated track and monitoring the displacement of the track section in front and behind, as well as the vibration amplitude when a vehicle passes, the automated monitoring problem of elevated tracks is solved. It can be widely used for safety monitoring of elevated tracks.

Description

TECHNICAL FIELD

[0001] The present application relates to a transportation system constructed by upper and lower single tracks, and particularly relates to the technical field of track supervision. BACKGROUND

[0002] The inventor proposed a rail transit system in a kind of urban traffic system and method (invention number ZL201610071046.1). Although the track of this system is composed of upper and lower single tracks, the track is not constructed overhead, and there is no technical solution disclosed in relation to the track and track supervision.

[0003] The present application explores a transportation mode constructed by upper and lower rigid single tracks. This mode is completely different from the existing transportation mode, and brings new safety operation problems. Since the track exists in a wide area, once the track appears loose, broken or other failures, economic losses will be caused if not discovered in time, and even casualties may occur. The automatic supervision of the track is a problem that must be solved simultaneously with the system construction. SUMMARY

[0004] 1. The task of the present application is to solve the real-time fault monitoring problem of overhead tracks through product and method innovation for the new transportation mode of overhead tracks constructed by upper single tracks and lower rigid single tracks through frame-shaped track supports and track pillars.

[0005] 2. First, define three unique facilities in this application and related dependent names.

[0006] 2.1

Overhead track

overhead track

[0007] Here, a section of track between frame-shaped track supports is referred to as a section of track. The upper rigid single track and the lower rigid single track between frame-shaped track supports are collectively referred to as a section of track.

[0008] 2.2

AI automatic supervision device

traffic control center

AI automatic supervision device

[0009] 2.3

Traffic Control Center

AI automatic monitoring device

overhead rail

Traffic Control Center

[0010] 3. Invention idea.

[0011] 3.1

Overhead rail

Overhead rail

[0012] 3.2

Overhead rail

[0013] The "faults" and "safety impact factors" that can affect the normal and safe use of

overhead rail

[0014] 3.3 The principle of monitoring "

overhead rail

overhead rail

[0015] Any minor faults such as loosening or offset in the track, support, or pillar of a "section of track" will cause the track and support to show "physical offset" or "excessive vibration" under the influence of external forces (such as wind or vibration) in the image of the adjacent "in good condition" frame support. In particular, when a vehicle passes through the "loose track section", it will lead to the judgment that the "track vibration amplitude exceeds the standard".

[0016] (3) Conventional image acquisition technology mainly relies on the passive light emitted by the object surface “illuminated by other light sources”. If there are severe environmental impacts such as heavy rain or fog near the track that seriously affect visibility, it may affect image judgment.

[0017] The principle behind connector fault detection: Determining a fault in the overhead track can be done not only by observing whether the track itself has shifted, but also by checking whether the object connected to the overhead track has shifted. If this object is a device that actively emits a strong penetrating beam of light (such as an infrared laser), then determining whether the entire track is faulty becomes a matter of whether the position of the strong penetrating beam changes beyond its offset range in the acquired images, thus overcoming the influence of harsh weather conditions.

[0018] (4) Both "monitoring channel interruption failure" and "AI automatic monitoring device failure" share a common characteristic: the traffic control center will be unable to communicate normally with the "AI automatic monitoring device". As long as the traffic control center initiates an "active communication request", this type of failure can be reliably determined based on the communication results.

[0019] 4. Achievement of the invention's objective.

[0020] Based on the principles of invention, this invention achieves its objectives through the following innovative devices and steps.

[0021] 4.1 Establish the hardware conditions for monitoring elevated rail lines.

[0022] Figure 1 This is a schematic diagram illustrating an embodiment of the layout of an automatic monitoring device for elevated railway tracks. According to... Figure 1 In the embodiment, at least the following are established: (1) the most basic layer of "aerial track" is constructed from the basic components "upper rigid single track [4], lower rigid single track [5], frame track support [1] for fixing the 'upper rigid single track and lower rigid single track', and track support [6]"; n layers of track. Based on the 1-layer "track" constructed from "upper rigid single track [4]", "lower rigid single track [5] and frame track support [1]", a layered design is adopted: 2-layer, 3-layer, and n-layer "tracks". Under the n-layer "track", "track support" is added to support the "n-layer track", thus forming the various types of "aerial track".

[0023]

Overhead rail

Overhead rail

overhead rail

[0024] Because

overhead rail

overhead rail

overhead rail

overhead rail

[0025] (2) The

AI automatic monitoring device

overhead rail

AI automatic monitoring device

overhead rail

AI automatic monitoring device

AI automatic monitoring device

AI automatic monitoring device

AI automatic monitoring device

[0026] (3) Build a

traffic control center

AI automatic monitoring device

AI automatic monitoring device

AI automatic monitoring device

overhead rail

traffic control center

AI automatic monitoring device

AI automatic monitoring device

AI automatic monitoring device

[0027] 4.2 Device creation for overhead rail monitoring.

[0028] Each "frame-shaped rail support 〔1〕" in operation is equipped with at least the following technical solution unit

AI automatic monitoring device

traffic control center

[0029]

Overhead rail

[0030] AI-powered automated monitoring devices also utilize image recognition technology. Image recognition is a very mature technology; it's used in license plate recognition, complex facial recognition, and even more sophisticated robotic on-site perception technologies, and these technologies are all commercially available.

[0031] The AI-powered automated monitoring device, which monitors a single section of track, presents a significantly lower technical challenge than the aforementioned examples of license plate recognition, facial recognition, and robotic on-site perception technology. The reasons are as follows: ① Most track components are geometrically simple lines. ② The track's "normal working state" is a static, steady-state shape, the easiest to determine and feature to extract. A "fault state," on the other hand, involves changes in the track's shape, and most of these can be determined qualitatively. ③ There is no need to consider dynamic changes in the three-dimensional shape. ④ The time requirement for fault diagnosis is extremely low; even a response time in the "second range" is acceptable.

[0032] One embodiment of the AI-powered automated monitoring device comprises at least five modules: ① Image acquisition module. It acquires track images under complex lighting and low-light conditions. ② Raw image data preprocessing module. It cleans and standardizes the raw image data. ③ Feature extraction module. Its core task is to extract discriminative fingerprint information from the preprocessed image data, primarily using a convolutional neural network (CNN) to automatically learn layered features from low-level (edges, textures) to high-level (object component displacement, displacement amount). ④ Detection module. Based on the extracted features, it makes a final judgment on the "fault type." ⑤ Post-processing and output module. It optimizes the results, filters low-confidence results, and finally uploads the "fault judgment result" to the traffic control center via a two-way channel.

[0033] An embodiment of mounting an AI automatic monitoring device (Qn) on the outer side frame of a "frame-shaped track support". The installation position of the "device (Qn)" is such that the image acquired by the "image acquisition module" includes at least the outer side frame of the frame-shaped track support, which "reliably captures the jolts and amplitudes of the track" when the vehicle passes by, without being "obscured".

[0034] In one embodiment, the image acquisition module can capture that when a vehicle passes by, the "side outer frame" is not obscured, and the image acquisition module can "reliably capture the jolts and amplitudes of the track".

[0035] An automatic monitoring system for an elevated track constructed from upper and lower single-track structures includes at least a traffic control center, an elevated track equipped with an AI automatic monitoring device (Q), and a two-way communication channel between the AI ​​automatic monitoring device (Q) and the traffic control center. Its features are: a. at least a traffic control center managing the safety of the elevated track and a two-way communication channel between the AI ​​automatic monitoring device (Q) and the traffic control center; b. at least an elevated track constructed from basic components consisting of an upper rigid single track, a lower rigid single track, a frame-shaped track support, and track pillars; c. each operational frame-shaped track support is equipped with an AI automatic monitoring device (Q) containing at least the following functional units: ① an image acquisition unit capable of acquiring track images under complex lighting and low-light conditions; ② a feature database of the track section's normal state; and ③ a two-way communication channel unit with the traffic control center.

[0036] 4.3 Innovative methods for supervising elevated rail lines.

[0037] Example 1 of the steps and methods: Based on the principle of automatic supervision, construct the minimum required system hardware: [Traffic Control Center], [Aerial Rail], and a two-way communication channel between the [AI Automatic Supervision Device] and the [Traffic Control Center].

[0038] Figure 2 In the embodiment, each "frame-shaped track support [1]" is equipped with an AI automatic monitoring device [Qn]. Each AI automatic monitoring device [Qn] has a two-directional image acquisition unit, that is, it can acquire high-quality track images of the "upper and lower track and frame-shaped track support"

[65] in both the front and rear directions. Figure 2 In a long track, there are frame-shaped track supports [1] arranged in the order of (n+1), (n+2), and (n+3), where (n+1), (n+2), and (n+3) also represent the [AI automatic monitoring device] [Q] numbers installed on the frame-shaped track supports [1], and also refer to related components within the area when there is a fault.

[0039] Scenario 1: If the pillars in the sorted (n+2) suffer from the "serious faults such as breakage or collapse of the track, support, or pillar", then the "high-quality track images"

[65] on the (n+1) and (n+3) [AI automatic monitoring device] [Qn] in the "normal state" without faults will be detected in real time as "(n+2) serious fault".

[0040] Scenario 2: If the (n+2)th column experiences the aforementioned "minor faults such as loosening or offset of the track, support, or column", then when the vehicle passes the (n+2)th column position, the "high-quality track images"

[65] on the (n+1) and (n+3) [AI automatic monitoring devices] [Q] without faults will detect in real time that the vibration amplitude of the "column (n+2) component" "exceeds the threshold".

[0041] Scenario 3: If the (n+2)th pillar experiences the aforementioned "minor faults such as loosening or offset of the track, support, or pillar", then when a vehicle passes by the (n+2)th pillar, the passing vehicle will also be able to detect vibration amplitude exceeding the standard threshold.

[0042] In Example 2 of the method, an AI automatic monitoring device (Qn) capable of acquiring images of at least one section of track in both the forward and backward directions is installed on the "frame-shaped track support [1]". The installation position of the AI ​​automatic monitoring device (Qn) must meet at least the following requirements: ① The installation location must be physically connected to the support column [6] at that location. ② The image acquisition module can acquire the parts of the "one section of track" that have a key impact on the stability of the track structure in both the forward and backward directions. ③ The image acquisition module can reliably acquire the "vibration amplitude" when a vehicle passes through the "one section of track". In one embodiment, the "image acquisition module" can acquire the outer side frame of the "frame-shaped track support [1]"; when a vehicle passes through this area, the "outer side frame" will not be obscured, and the image acquisition module can "reliably capture the sway and amplitude of the track".

[0043] In Example 3 of the Step Method, after the AI ​​Automatic Monitoring Device [Qn] is put into operation, it will establish at least the following image databases according to the instructions of the Traffic Control Center: "the integrity and normality of the front and rear track sections of the frame track support during periods when no vehicles pass" and "the integrity and normality of one track section during periods when vehicles pass".

[0044] Example 4 of the method: The Traffic Control Center sends a "heartbeat request" to the AI ​​Automatic Monitoring Device (Qn), requesting the AI ​​Automatic Monitoring Device (Qn) to upload whether the channel is normal and whether the AI ​​Automatic Monitoring Device is working properly.

[0045] In Example 5 of the method, when a vehicle running on the overhead track detects that its vibration amplitude exceeds a preset threshold when it reaches the nth track segment, it will automatically report to the traffic control center through the channel between the vehicle and the traffic control center.

[0046] A method for automatically monitoring a track constructed by upper and lower single-track overhead lines, firstly establishing a two-way communication channel between a traffic control center, the overhead track, and an AI automatic monitoring device, and the traffic control center. The method is characterized by: Method a) installing an AI automatic monitoring device [Qn] on the "frame-shaped track support" capable of acquiring images of at least one section of track in both the forward and backward directions; Method b) after the AI ​​automatic monitoring device [Qn] is put into operation, it will, according to instructions from the traffic control center, establish at least two image databases: one of the "integrity and normality of the track sections in the forward and backward directions of the frame-shaped track support during periods without vehicle traffic," and another of the "integrity and normality of one section of track during periods with vehicle traffic"; Method c) the traffic control center will send "heartbeat requests" to the AI ​​automatic monitoring device [Qn]; Method d) the operating vehicles will report in real-time to the traffic control center any incidents where the vibration amplitude of the vehicle passing through a section of track exceeds a predetermined threshold.

[0047] Brief Description of the Drawings: In order to more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings, wherein: Figure 1 This is a schematic diagram of an embodiment of the layout of an automatic monitoring device for elevated railway tracks.

[0049] Figure 2 This is a schematic diagram illustrating the principle of "AI automatic monitoring device monitoring track faults" in an embodiment.

[0050] Detailed Description of Embodiments: The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] To make the advantages of the technical solution of the present invention clearer, the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0052] Appendix Figure 1 and attached Figure 2In the middle, [4] is the upper rigid monorail; [5] is the lower rigid monorail; [1] is a frame-shaped track support for fixing the upper and lower rigid monorails; [6] is a track support; [7] is a lightning rod for lightning protection of the track; [2] is a vehicle with a streamlined head that can run on the [aerial track]; [3] is a train without a head that can run on the [aerial track].

[0053] [Q] refers to the [AI Automatic Monitoring Device] installed in at least one [Aerial Rail Line] that is put into operation. [P] refers to the [AI Automatic Monitoring Device / Active Photoelectric Signal Intelligent Monitoring Unit] capable of reliable monitoring under any harsh environmental conditions. [P] is also a further extended technical solution embodiment of the [AI Automatic Monitoring Device].

[0054]

[81] is the Traffic Control Center; [Q1+P1]...[Qn+Pn] represent "each operational [aerial rail line] AI Automatic Monitoring Device [Q1] and AI Automatic Monitoring Device / Active Photoelectric Signal Intelligent Monitoring Unit [P1]"..."AI Automatic Monitoring Device [Qn] and AI Automatic Monitoring Device / Active Photoelectric Signal Intelligent Monitoring Unit [Pn]"; the bidirectional arrows between the Traffic Control Center

[81] and [Q1+P1]...[Qn+Pn] represent a multi-layered, secure bidirectional communication channel. This multi-layered, secure bidirectional communication channel includes commercial communication networks provided by multiple network companies and the transportation system's own internal communication network. This is a very mature technological field.

[0055] Each “frame track support [1]” is equipped with an AI automatic monitoring device [Qn]. Each AI automatic monitoring device [Qn] has a two-way “image acquisition unit”, that is, it can acquire “high-quality track images” of the “upper and lower track, frame track support, etc.”

[65] not only in the front direction but also in the rear direction. Figure 2 In a long track, there are frame-shaped track supports [1] arranged in the order of (n+1), (n+2), and (n+3), where (n+1), (n+2), and (n+3) also represent the [AI automatic monitoring device] [Q] numbers installed on the frame-shaped track supports [1], and also refer to related components within the area when there is a fault.

[0056] Example 1 of a system device for automatic monitoring of overhead rail lines.

[0057] Each "frame-shaped track support [1]" is equipped with an AI automatic monitoring device [Qn], which has an image acquisition unit installed in both the front and rear directions. This unit is capable of acquiring high-quality track images in complex lighting and low-light environments, and can simultaneously acquire "track images" of adjacent track sections. Complex lighting refers to light factors such as dense fog and smoke that affect image quality. Since the present invention has low requirements for image quality, the following technologies and products are sufficient to meet the needs of the present invention: "Combining a large target surface sensor (1 / 1.8"), an F1.0 ultra-large aperture, and an AI noise reduction algorithm to achieve full-color imaging in 0Lux low-light environments. Products: Hikvision PrO series, Veepai KG2-QG, etc."

[0058] The images captured by the installed AI automatic monitoring device [Qn] are of "one section of track" in the front and rear directions of the frame-shaped track support. If each frame-shaped track support is equipped with an AI automatic monitoring device [Qn], then the entire [overhead track] will be fully covered by dual (front and rear) AI automatic monitoring devices [Qn].

[0059] A further embodiment 2 of the system device for automatically monitoring the overhead rail line.

[0060] Each "frame-shaped track support [1]" is equipped with an AI automatic monitoring device [Q], which is either integrated or separately installed with: an AI automatic monitoring device / active photoelectric signal intelligent monitoring unit [Pn].

[0061] See Figure 2 The AI ​​automatic monitoring device / active photoelectric signal intelligent monitoring unit [Pn] sends active beam signals to the adjacent AI automatic monitoring device / active photoelectric signal intelligent monitoring unit [Pn-1] and AI automatic monitoring device / active photoelectric signal intelligent monitoring unit [Pn+1], and simultaneously receives beam signals from the adjacent units.

[0062] The AI ​​automatic monitoring device / active photoelectric signal intelligent monitoring unit [Pn] actively sends an infrared laser measurement signal. At the same time, the monitoring units [Pn-1], [Pn], and [Pn+1] automatically receive infrared laser measurement signals from adjacent monitoring units and determine whether the track is faulty based on the position of the received light spot and the range of light spot movement.

[0063] [AI Automatic Monitoring Device / Active Photoelectric Signal Intelligent Monitoring Unit] [Pn] By sending a "high-power, highly penetrating" "active infrared laser" beam to replace "passive reflected light from the surface of the monitored object", it can solve the monitoring problem in extreme environments, and at a lower cost, it can be installed in many road sections with lower requirements.

[0064] A further embodiment 3 of the system device for automatically monitoring the overhead rail line.

[0065] The AI-powered automated monitoring device (Q) contains a pair of "active high-intensity illumination sources." Upon receiving a "malfunction" report from the AI-powered automated monitoring device (Qn), the traffic control center can remotely activate the "active high-intensity illumination sources" to light up the monitored track section and obtain a clear image.

[0066] Further embodiment 1 of the automatic monitoring method for overhead rail lines.

[0067] Based on the preliminary disaster assessment, the Traffic Control Center directly sends "heartbeat request packets" to each of the managed AI automatic monitoring devices on a scheduled or unscheduled basis.

[0068] The Traffic Control Center can also be set up according to the hierarchical and regional planning, with Regional Traffic Control Centers set up to maintain and ensure the operation of the elevated rail lines in their respective areas. While retaining higher-priority management authority, the Regional Traffic Control Center can also proactively send "heartbeat request packets" to each of the managed AI automatic monitoring devices [Qn] within the area on a regular or irregular basis.

[0069] Upon receiving the "heartbeat request packet", the AI ​​automatic monitoring device (Qn) will send an "OK" confirmation heartbeat packet if its monitoring status is "normal". If the AI ​​automatic monitoring device (Qn) has an "abnormality" or "has had an abnormality in the past", it will provide a "summary of the abnormal event" information according to the pre-agreed agreement.

[0070] Further embodiment 2 of the automatic monitoring method for overhead rail tracks.

[0071] When a vehicle running on the overhead track reaches the nth track segment, if it is found that "the vibration amplitude of the vehicle exceeds the preset threshold", it will automatically report the "vibration amplitude exceeding the standard fault" to the traffic control center through the channel.

[0072] Further embodiment 3 of the automatic monitoring method for elevated railway tracks.

[0073] After receiving a "malfunction" report from the AI ​​Automatic Monitoring Device (Qn), the Traffic Control Center, equipped with an "active high-intensity light source," will activate the light source to "illuminate the monitored track area" and obtain a clear image when it detects an anomaly or is affected by light.

[0074] Invention Effects: This invention relates to an automatic monitoring system and method for elevated tracks constructed with single upper and lower tracks, specifically concerning the technical field of track monitoring. It fully utilizes the fact that in physically connected elevated tracks, any serious fault such as breakage or collapse in a track section will result in significant displacement of track components in adjacent images; similarly, any fault such as loosening of major track components will cause vibrations exceeding normal ranges when vehicles pass over that section. By installing an AI automatic monitoring device on the elevated track and monitoring the displacement of the track section ahead and behind, as well as the vibration amplitude when vehicles pass, the invention solves the problem of automatic monitoring of elevated tracks. Since elevated tracks utilize ultra-low-altitude road construction resources, enabling the construction of independent, closed transportation systems, this invention facilitates innovation in new transportation modes and can be widely used for safety monitoring of elevated tracks.

Claims

1. A system device for automatically monitoring a "track constructed by upper and lower single-track overhead lines", comprising at least a [traffic control center], an [aerial track] on which an [AI automatic monitoring device] [Q] is installed, and a two-way communication channel between the [AI automatic monitoring device] [Q] and the [traffic control center], characterized in that: a. There is at least a traffic control center that manages the safety of the elevated railway, and a two-way communication channel between the AI ​​automatic monitoring device [Q] and the traffic control center; b. It has at least one [elevated track] constructed from the basic components of "upper rigid monorail, lower rigid monorail, frame track support and track support". c. Each operational "frame track support [1]" is equipped with an AI automatic monitoring device [Q] containing at least the following functional units: ① an image acquisition unit that can acquire track images in complex lighting and low light environments, ② a feature database of the normal state of the track section, and ③ a two-way channel unit with the traffic control center.

2. A system device for automatically monitoring a track constructed by upper and lower single-track overhead structures according to claim 1, characterized in that: Each "frame-shaped track support [1]" is equipped with an AI automatic monitoring device [Qn], which has an image acquisition unit that can acquire high-quality track images in complex lighting and low light environments, and can simultaneously acquire "track images" of adjacent track sections.

3. A system device for automatically monitoring a track constructed by upper and lower single-track overhead structures according to claim 1, characterized in that: a. Each "frame-shaped track support [1]" has at least one "AI automatic monitoring device / active photoelectric signal intelligent monitoring unit" [Pn] installed in its "AI automatic monitoring device / active photoelectric signal intelligent monitoring unit" [Pn-1] and "AI automatic monitoring device / active photoelectric signal intelligent monitoring unit" [Pn+1] facing the adjacent "AI automatic monitoring device / active photoelectric signal intelligent monitoring unit" [Pn-1] and "AI automatic monitoring device / active photoelectric signal intelligent monitoring unit" [Pn+1]; b. [AI Automatic Monitoring Device / Active Photoelectric Signal Intelligent Monitoring Unit] [Pn] actively sends "infrared laser" measurement signals. At the same time, the "monitoring units [Pn-1], [Pn], [Pn+1]" laser image acquisition units automatically receive "infrared laser measurement signals from adjacent monitoring units" and determine whether the track is faulty based on "the position of the received light spot and the range of light spot movement".

4. A system device for automatically monitoring a track constructed by upper and lower single-track overhead structures according to claim 1, characterized in that: The AI ​​automatic monitoring device [Q] contains a pair of "active strong illumination light sources".

5. A method for automatically monitoring a track constructed by upper and lower single-track overhead lines, firstly establishing a two-way communication channel between a [traffic control center], the [aerial track], and an [AI automatic monitoring device] and the [traffic control center], characterized by the following method: Feature method a: An AI automatic monitoring device [Qn] is installed on the "frame-shaped track support" capable of acquiring images of at least one section of track in both the forward and backward directions; Feature method b. After the [AI Automatic Monitoring Device] [Qn] is put into operation, it will establish at least the following image databases according to the instructions of the [Traffic Control Center]: "Image database of the integrity and normality of the front and rear track sections of the frame track support during periods when no vehicles are passing" and "Image database of the integrity and normality of one track section during periods when vehicles are passing". Feature method c. The Traffic Control Center will send a "heartbeat request" to the AI ​​Automated Monitoring Device (Qn); Feature method d. The traffic control center will report in real time any incidents where the vibration amplitude of a vehicle exceeds a predetermined threshold on the track section it passes through.

6. A method for automatically monitoring a track constructed by upper and lower single-track overhead structures, as described in claim 5, characterized in that: Feature method a. The Traffic Control Center or its authorized "Regional Center" will periodically and irregularly send "heartbeat request packets" to each "managed AI automatic monitoring device"; Feature method b. After receiving the "heartbeat request packet", the requested [AI automatic monitoring device] will send an "OK" confirmation heartbeat packet if the monitoring status of the [AI automatic monitoring device] is "all normal"; if the [AI automatic monitoring device] has an "abnormality" or "has had an abnormality in the past", it will provide "summary information of the abnormal event" according to the pre-agreed agreement.

7. A method for automatically monitoring a track constructed by upper and lower single-track overhead structures, as described in claim 5, characterized in that: When a vehicle operating on the overhead track detects that the vibration amplitude exceeds a preset threshold when it reaches the nth track segment, it will automatically report this to the traffic control center via a communication channel.

8. A method for automatically monitoring a track constructed by upper and lower single-track overhead structures, as described in claim 5, characterized in that: The AI-powered automated monitoring device is equipped with an "active high-intensity light source." When the traffic control center detects anomalies or is affected by light, it illuminates the high-intensity light source to "illuminate the monitored track area" and obtain clear images.

9. A method for automatically monitoring a track constructed by upper and lower single-track overhead structures, as claimed in claim 5, characterized in that: After the AI ​​Automatic Monitoring Device (Qn) detects and reports a track fault, the Traffic Control Center will directly connect to the image acquisition unit of the AI ​​Automatic Monitoring Device (Qn) to observe the actual situation of the faulty section.

Images