Intelligent fault diagnosis method of multi-video transmission link and intelligent video transmission system

Abstract

The application relates to an intelligent fault diagnosis method of a multi-video transmission link and an intelligent video transmission system, and belongs to the technical field of video signal management. An integrated diagnosis module integrated in a video adapter line executes a method, which comprises the following steps: monitoring working currents of branch channels of the video adapter line in real time; based on the working currents, state indication devices corresponding to the branch channels execute actions matched with the working currents. The application can monitor the states of the multi-video link in real time and accurately.

Description

Technical Field

[0001] This application relates to the technical field of video signal management, and in particular to an intelligent fault diagnosis method and intelligent video transmission system for multiple video transmission links. Background Technology

[0002] With the widespread adoption of vehicle-mounted video surveillance systems in agricultural machinery, freight vehicles, and other fields, they have become crucial equipment for ensuring operational safety and assisting driving. These systems utilize multiple cameras and aggregate the signals to a display terminal via bundled video transmission cables.

[0003] Currently, most video cables use aviation connectors. As consumables, video cables suffer hidden damage to their internal core wires after prolonged exposure to severe vibration, soil corrosion, and accidental pulling. When one or more video signals malfunction, on-site personnel or after-sales technicians cannot quickly pinpoint the fault location. Traditional troubleshooting methods require the use of multimeters and other tools to measure each section of the potentially several-meter-long, concealed wiring harness, making the process cumbersome and inefficient.

[0004] Therefore, there is an urgent need for a technical solution that can perform real-time, intelligent status monitoring and fault diagnosis of multi-channel video transmission links. Summary of the Invention

[0005] To enable real-time monitoring of the status of multiple video links, this application provides an intelligent fault diagnosis method and an intelligent video transmission system for multiple video transmission links.

[0006] Firstly, this application provides an intelligent fault diagnosis method for multiple video transmission links, executed by an integrated diagnostic module within the video adapter cable, employing the following technical solution: Real-time monitoring of the operating current of each branch channel of the video adapter cable; Based on the operating current, the status indicator device corresponding to the branch channel performs an action that matches the operating current.

[0007] By adopting the above technical solution, the integrated diagnostic module monitors the operating current of each branch channel in real time, and the status indicator device accurately reflects the operating condition. It can quickly identify faults such as open circuit and short circuit without the need for external equipment. It has a high degree of integration, rapid response, greatly simplifies the fault diagnosis process, reduces operation and maintenance costs, and ensures the stable and reliable operation of multiple video transmission links.

[0008] Furthermore, based on the operating current, the status indication device corresponding to the branch channel performs an action matching the operating current, including: When the operating current is in the first normal range, the branch channel is in normal condition, and the green light of the status indicator device illuminates. When the operating current is lower than the first threshold, the branch channel is in an open circuit state, and the status indicator device is turned off. When the operating current exceeds the second threshold and triggers the protection mechanism, the branch channel is in a short-circuit state, and both the red and green lights of the status indicator device illuminate. Wherein, the first threshold is less than the lower limit of the first normal range, and the second threshold is greater than the upper limit of the first normal range.

[0009] By adopting the above technical solution and clearly mapping the current range to the status indication, the green light on, the light off, and the red and green lights on simultaneously provide intuitive feedback on the normal, open circuit, and short circuit status, respectively. The fault type is clear at a glance. No complex testing equipment is required. Maintenance personnel can quickly locate the problem channel, greatly shorten the troubleshooting time, improve the efficiency of fault handling, and at the same time, the protection mechanism is linked to prevent the fault from escalating and ensure the stability of the transmission link.

[0010] Furthermore, it also includes an onboard main control chip, which is connected to the integrated diagnostic module. The method is executed by the onboard video main control chip. When at least two branch channels are simultaneously determined to be faulty, the method further includes: Obtain the fault type and fault occurrence time for each fault channel; Based on the pre-stored physical topology of each branch channel, determine whether the faulty channels are physically adjacent or share a link. A correlation analysis is performed based on the fault type, the fault occurrence time, and the physical topology to infer common fault sources; wherein the correlation analysis includes at least one of the following rules: If two physically adjacent channels are simultaneously determined to be open circuits, it is inferred that the common link of those adjacent channels is open circuit. If one channel is determined to be short-circuited, and one or more other channels are determined to be abnormal voltage or power failure within a preset time, it is inferred that the power supply system is subjected to short-circuit disturbance. If all channels are simultaneously determined to have the same current anomaly, it is inferred that there is a fault in the main power input or the main grounding circuit. Based on the inference results, a prompt message containing the location of the common fault source is generated and reported.

[0011] By adopting the above technical solutions and leveraging the integrated diagnostic module linked to the vehicle main control chip, the system can conduct correlation analysis based on fault type, occurrence time, and physical topology to accurately deduce common fault sources such as shared links and power systems, quickly locate the root cause, avoid inefficient troubleshooting, significantly improve the efficiency of handling multi-channel concurrent faults, and reduce the operation and maintenance costs of the vehicle video transmission system.

[0012] Furthermore, the method also includes: During the preset learning period after the camera is first powered on or installed, monitor and record the current timing data of each branch channel in typical working mode as learning data. Based on the learning data, a dynamic reference curve characterizing the normal current variation of the branch channel is generated through modeling processing. In subsequent operation, the real-time operating current will be compared with the dynamic reference curve. If the real-time operating current deviates from the dynamic reference curve by more than the adaptive tolerance range, but has not yet reached the open circuit state or the open circuit state, it is determined as a latent fault warning.

[0013] By adopting the above technical solution, data is collected and modeled to generate a dynamic reference curve through a preset learning period. The current is compared with the reference curve in real time, and hidden faults that have not reached the open circuit / short circuit threshold are accurately captured and warned. It is adapted to complex vehicle operating conditions, avoids the risk of fault deterioration in advance, does not rely on fixed thresholds, improves diagnostic adaptability and foresight, ensures the long-term stability of the vehicle video transmission link, and reduces the cost of later maintenance.

[0014] Furthermore, the exceeding of the adaptive tolerance range includes sudden abnormal deviation and gradual abnormal deviation. If the real-time operating current deviates from the dynamic reference curve beyond the adaptive tolerance range, but has not yet reached the open circuit state, it is determined as a latent fault warning, including: For each sampling time, perform the following steps: Obtain the expected value of the reference current and the standard deviation of the reference current corresponding to the current sampling time from the dynamic reference curve; Calculate the standard instantaneous deviation between the sampled current and the expected value of the reference current, where the standard instantaneous deviation = |sampled current - expected value of reference current| / standard deviation of reference current; Within a preset analysis window, calculate the moving average and / or cumulative excess area of ​​the standard instantaneous deviation, wherein the cumulative excess area is the integral of the portion of the standard instantaneous deviation that exceeds a preset static threshold. If the standard instantaneous deviation continues to exceed the first dynamic threshold and reaches the first time period, it is determined to be a sudden abnormal deviation; If the moving average value continuously exceeds the second dynamic threshold and reaches the second time period, or if the cumulative area exceeding the standard exceeds the area threshold within the third time period, it is determined to be a gradual abnormal deviation.

[0015] By adopting the above technical solutions, the instantaneous deviation, moving average, and cumulative excess area of ​​the standard are quantified to accurately distinguish between two types of latent deviations: sudden and gradual. This adapts to the dynamic working conditions of vehicles, breaks through the limitations of fixed thresholds, improves the accuracy of latent fault identification, avoids missed or misjudged cases, and captures potential problems such as instantaneous interference and slow aging in advance. It provides targeted guidance for operation and maintenance and further ensures the stability and reliability of the vehicle video transmission link.

[0016] Furthermore, the generation of a dynamic reference curve characterizing the normal current variation features of the branch channel based on the learned data through modeling processing includes: The learning data is divided according to different working conditions; For the learning data under each of the identified typical operating conditions, an independent dynamic benchmark sub-curve is established; wherein each dynamic benchmark sub-curve contains a benchmark current expected value sequence and a benchmark current standard deviation sequence corresponding to the time series of the operating condition. The comparison of the real-time operating current with the dynamic reference curve includes: Establish a mapping table from system operating conditions to the corresponding dynamic reference sub-curves; Based on the current system operating conditions, query the mapping relationship table and select the corresponding dynamic baseline sub-curve for comparison.

[0017] By adopting the above technical solution, learning data is divided according to operating conditions and independent dynamic benchmark sub-curves are established. Operating condition mapping is used to accurately match and compare benchmarks. This adapts to complex operating condition differences such as vehicle startup and idling, avoiding misjudgments across operating conditions, significantly improving the accuracy and reliability of hidden fault identification, making diagnosis more closely aligned with actual operating conditions, further ensuring the stability of the vehicle video transmission link, and reducing the difficulty of maintenance and troubleshooting.

[0018] Furthermore, if the problem is determined to be a latent fault warning, the method further includes: Based on the magnitude of the instantaneous deviation of the standard, the duration of the gradual abnormal deviation, or the growth rate of the cumulative area exceeding the standard, the hidden fault warning is divided into multiple warning levels. Based on the warning level, perform at least one of the following differentiated response actions: The status indicator device is controlled to indicate in a mode corresponding to the warning level; When the warning level is Level 1, log the information locally. When the warning level is the second level, a log is recorded locally, and the warning information is actively sent to the upper-level system through the wireless communication unit; When the warning level reaches the third level, a log is recorded locally, and the warning information and suggested maintenance window period are actively sent to the superior system through the wireless communication unit.

[0019] The warning levels of the first, second, and third levels gradually increase.

[0020] By adopting the above technical solution, multiple early warning levels are defined based on quantitative indicators, and differentiated responses are matched with log recording, wireless reporting, and maintenance window period suggestions. This ensures clear levels and precise responses, avoiding excessive resource consumption by minor warnings while ensuring timely handling of serious hidden dangers. It provides tiered guidance for vehicle-mounted maintenance, proactively preventing fault escalation, maximizing video transmission stability, and reducing maintenance costs and driving risks.

[0021] Secondly, this application provides an intelligent video transmission system, which adopts the following technical solution: This includes video adapter cables, integrated diagnostic modules, and onboard main control chips; The video adapter cable includes a main cable and at least one branch channel for connecting the video source and the display device; The integrated diagnostic module is encapsulated in the connector or middle of the video adapter cable, and includes a current detection circuit, a multi-state indicator, and a self-resetting fuse, and performs the method described in the first and second items of the first aspect; The vehicle-mounted video main control chip is electrically connected to the integrated diagnostic module and configured to perform the method described in items three through seven of the first aspect.

[0022] Thirdly, this application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium storing a computer program that can be loaded by a processor and execute the methods described in any of the first aspects.

[0023] For a detailed description of the second and third aspects of the present invention and their various implementations, please refer to the detailed description in the first aspect and its various implementations; and for a detailed description of the beneficial effects of the second and third aspects and their various implementations, please refer to the beneficial effect analysis in the first aspect and its various implementations, which will not be repeated here.

[0024] In summary, this application includes at least one of the following beneficial technical effects: 1. The integrated diagnostic module monitors the operating current of each branch channel in real time, and the status indicator device accurately reflects the operating condition. It can quickly identify faults such as open circuit and short circuit. No external equipment is required. It has a high degree of integration and rapid response, which greatly simplifies the fault diagnosis process, reduces operation and maintenance costs, and ensures the stable and reliable operation of multiple video transmission links. 2. By leveraging the integrated diagnostic module linked to the vehicle's main control chip, and combining the fault type, occurrence time, and physical topology to conduct correlation analysis, common fault sources such as shared links and power systems can be accurately inferred, and the root cause can be quickly located, avoiding the inefficient problem of troubleshooting one by one. Attached Figure Description

[0025] Figure 1 This is a flowchart illustrating the intelligent fault diagnosis method for multiple video transmission links executed by the integrated diagnostic module in this embodiment of the application.

[0026] Figure 2 This is a schematic diagram of the integrated diagnostic module in an embodiment of this application.

[0027] Figure 3 This is a flowchart illustrating the intelligent fault diagnosis method for multiple video transmission links executed by the vehicle-mounted main control chip in this embodiment of the application. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0029] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0030] This application discloses an intelligent fault diagnosis method for multiple video transmission links, which is applied to an intelligent video transmission system.

[0031] The intelligent video transmission system includes a video adapter cable, an integrated diagnostic module, and an onboard main control chip. The video adapter cable includes a main cable and at least one branch channel for connecting the video source to a display device. The integrated diagnostic module is encapsulated in the connector or middle of the video adapter cable and includes a current detection circuit, a multi-state indicator, and a resettable fuse. The onboard video main control chip is electrically connected to the integrated diagnostic module.

[0032] The integrated diagnostic module can quickly determine the status of the video path through logic circuits. (Refer to...) Figure 1 The steps performed by the integrated diagnostic module include steps S101 to S102:

[0033] Step S101: Monitor the operating current of each branch channel of the video adapter cable in real time.

[0034] Step S102: Based on the operating current, the status indicator device corresponding to the branch channel performs an action that matches the operating current.

[0035] Specifically, the video adapter cable uses a single aviation video connector to generate multiple video cables, enabling the vehicle-mounted video system to display multiple video streams by connecting a single connector. Each branch channel corresponds to an independent integrated diagnostic module.

[0036] Reference Figure 2 Taking one of the paths as an example, the integrated diagnostic module includes: the camera power input Vin is connected to the anode of diode D1, the cathode of diode D1 is connected to resistor R1, the other end of resistor R1 is connected to resettable fuse F1, and the other end of resettable fuse F1 is connected to camera output Vin1.

[0037] The other end of resistor R1 is connected to the emitter of PNP transistor Q1. The base of transistor Q1 is connected to resistor R21, and the other end of resistor R21 is connected to the camera output Vin1. The collector of transistor Q1 is connected to resistor R3, and the other end of resistor R3 is connected to the positive terminal of the green light of the red-green dual-color indicator LED1, with the negative terminal of the green light grounded. The red-green dual-color indicator LED1 serves as the status indicator.

[0038] The other end of resistor R1 is connected to resistor R2, and the other end of resistor R2 is connected to the base of PNP transistor Q2. The emitter of transistor Q2 is connected to the camera power input Vin. The collector of transistor Q2 is connected to resistor R4, and the other end of resistor R4 is connected to the positive terminal of the red LED1 (a dual-color indicator light). The negative terminal of the red LED is grounded. The other end of resistor R4 is also connected to resistor R5, and the other end of resistor R5 is grounded.

[0039] When the branch channel is working normally, the operating current is in the first normal range. The current flows from the camera power input Vin through diode D1, resistor R1 and resettable fuse F1 to the camera output Vin1. When the emitter voltage of transistor Q2 is higher than the base voltage, transistor Q2 conducts and the green light of the red-green dual-color indicator LED1 lights up. When the emitter and base voltages of transistor Q1 are the same, transistor Q1 does not conduct and the red light of the red-green dual-color indicator LED1 does not light up.

[0040] When the camera corresponding to the branch channel is not connected or the line is broken, the operating current is lower than the first threshold, and neither transistor Q1 nor transistor Q2 can reach the conduction condition, so the green and red lights of the red and green dual-color indicator LED1 will be turned off.

[0041] When a branch channel is short-circuited, the operating current exceeds the second threshold and triggers the protection mechanism. The self-resetting fuse F1 enters a high-impedance state to limit and protect the circuit. The emitter voltage of transistor Q1 is higher than its base voltage, so transistor Q1 conducts, and the red light of the red-green indicator LED1 illuminates. Simultaneously, the emitter voltage of transistor Q2 is higher than its base voltage, so transistor Q2 conducts, and the green light of the red-green indicator LED1 illuminates. Therefore, the red and green lights remain constantly on, indicating that there is both an abnormal current and a short-circuit abnormality.

[0042] Wherein, the first threshold is less than the lower limit of the first normal range, and the second threshold is greater than the upper limit of the first normal range. For example, the first threshold is 0.01A, the first normal range is 0.1A-0.5A, and the second threshold is 1.5A.

[0043] Specifically, the operating current of the branch channels of the video adapter cable differs under normal, open-circuit, and short-circuit conditions. Under normal conditions, the current remains stable within a reasonable range; under open-circuit conditions, the current approaches zero; and under short-circuit conditions, the current spikes dramatically. By monitoring the current signal in real time and receiving feedback from the status device, fault visualization is achieved.

[0044] Furthermore, when multiple branch channels fail simultaneously, the faults are often not isolated but related to the channel physical topology. By associating the fault type, occurrence time, and physical topology relationship, common fault sources can be traced, avoiding the inefficient problem of troubleshooting individual channels one by one. The video adapter cable also integrates an in-vehicle video main control chip, which performs the following steps (steps S11 to S14):

[0045] Step S11: Obtain the fault type and fault occurrence time for each fault channel.

[0046] Specifically, when the vehicle-mounted video main control chip detects a fault in at least two branch channels, it automatically records the fault type and the time of occurrence of each faulty channel.

[0047] Step S12: Based on the pre-stored physical topology of each branch channel, determine whether the faulty channels are physically adjacent or share a link.

[0048] Specifically, the vehicle-mounted video main control chip pre-stores the physical topology of each branch channel of the video adapter cable, including information such as channel number, physical location, and shared link.

[0049] Step S13: Perform correlation analysis based on the fault type, the fault occurrence time, and the physical topology to infer common fault sources; wherein the correlation analysis includes at least one of the following rules:

[0050] (1) If two physically adjacent channels are simultaneously determined to be open circuits, it is inferred that the common link of the adjacent channels is open circuit.

[0051] (2) If one channel is determined to be short-circuited, and one or more other channels are determined to be abnormal voltage or power failure within a preset time, it is inferred that the power supply system is subjected to short-circuit disturbance.

[0052] (3) If all channels are simultaneously determined to have the same current abnormality, it is inferred that the main power input or main grounding circuit is faulty.

[0053] Step S14: Based on the inference results, generate and report a prompt message containing the location of the common fault source.

[0054] For example, in a vehicle-mounted 360-degree panoramic imaging system, the video adapter cable contains four branch channels (front, rear, left, and right cameras). The topology table shows that the left and right channels share a main grounding circuit, and the front and rear channels share a main power supply branch. When the vehicle-mounted video main control chip detects that the left and right channels are simultaneously open-circuited, it infers through correlation analysis that the common fault source is an open circuit in the main grounding circuit, generates a prompt message "Main grounding circuit open, related to left and right camera channels," and reports it to the vehicle-mounted host.

[0055] Therefore, it enables the root cause location of multi-channel faults, significantly improves fault handling efficiency, and clarifies the location of common fault sources, providing precise maintenance guidance for operation and maintenance personnel, reducing troubleshooting time and costs, and reporting fault information to the upper-level system for easy remote monitoring and centralized management, which is especially suitable for large equipment or distributed video transmission scenarios.

[0056] Furthermore, the normal operating current of the branch channels in the vehicle-mounted video system varies under different operating conditions, such as vehicle system startup, driving, and idling. By collecting current timing data under typical operating conditions during the learning period, a dynamic reference curve is established. During subsequent operation, this curve is compared with the real-time current to identify hidden faults that have deviated from the normal state but have not reached the short-circuit or open-circuit thresholds. Therefore, the method also includes (steps S21 to S24):

[0057] Step S21: During the preset learning period after the camera is first powered on or installed, monitor and record the current timing data of each branch channel in typical working mode as learning data.

[0058] Specifically, after the camera is powered on for the first time, a 72-hour learning mode is set. During this period, the current timing data of each branch channel under typical operating modes is monitored and recorded to form a learning dataset. Typical operating modes include vehicle system startup, idling, high-speed driving, and reversing; and daytime or nighttime modes for industrial monitoring. Obvious abnormal data is further removed, and valid timing data under normal operating conditions is retained as learning data.

[0059] Step S22: Based on the learning data, a dynamic reference curve characterizing the normal current variation of the branch channel is generated through modeling processing.

[0060] Specifically, time series statistical modeling methods, such as sliding window statistics and Gaussian mixture models, are used to analyze the learning data. First, the learning data is split along the time dimension, and the current characteristics at each sampling time are calculated, including the mean, standard deviation, fluctuation range, and trend, thus establishing the time-current characteristic mapping relationship. Then, a dynamic baseline curve is fitted and generated with time on the horizontal axis and current on the vertical axis, encompassing the expected range of normal current.

[0061] Furthermore, when establishing the dynamic reference curve, the vehicle-mounted video main control chip divides the learning data according to different operating conditions; for the learning data under each typical operating condition, an independent dynamic reference sub-curve is established; wherein, each of the dynamic reference sub-curves includes a reference current expected value sequence and a reference current standard deviation sequence corresponding to the operating condition time series.

[0062] Specifically, the vehicle-mounted video control chip receives operating condition signals from the CAN bus to determine the current operating mode. Alternatively, the chip can automatically identify the operating mode based on the step change characteristics of the operating current. For example, if the current suddenly increases from 0 to 0.4A when the vehicle system starts, it can be identified as a startup condition. The effective current timing data during the learning period is then categorized according to the identified operating condition labels. Furthermore, a dynamic baseline sub-curve is established for the learning data under each typical operating condition.

[0063] Step S23: In subsequent operation, compare the real-time operating current with the dynamic reference curve.

[0064] Establish a mapping table from system operating conditions to the corresponding dynamic reference sub-curves; query the mapping table according to the current system operating conditions, and select the corresponding dynamic reference sub-curves for comparison.

[0065] Step S24: If the real-time operating current deviates from the dynamic reference curve by more than the adaptive tolerance range, but has not yet reached the open circuit state or the open circuit state, it is determined as a latent fault warning.

[0066] For example, during the learning period, current timing data for three operating conditions were recorded: 0.4A-0.5A during startup, 0.28A-0.32A during idle, and 0.3A-0.35A during high speed. A dynamic baseline curve was generated: at t=100ms, the normal range for the startup phase is 0.42A-0.48A; at t=1000ms, the normal range for the idle phase is 0.29A-0.31A. During operation, the real-time current at t=1000ms during the idle phase was 0.34A, exceeding the adaptive tolerance range of the baseline curve (0.29A-0.31A), but not reaching the open circuit or short circuit threshold, triggering a latent fault warning.

[0067] Latent faults include both sudden and gradual types. Therefore, exceeding the adaptive tolerance range includes both sudden abnormal deviations and gradual abnormal deviations. To accurately distinguish between these two types of deviations, step S24 includes:

[0068] For each sampling time, perform the following steps (steps S241 to S245):

[0069] Step S241: Obtain the expected value of the reference current and the standard deviation of the reference current corresponding to the current sampling time from the dynamic reference curve.

[0070] Step S242: Calculate the standard instantaneous deviation between the sampled current and the expected value of the reference current, wherein the standard instantaneous deviation = |sampled current - expected value of reference current| / standard deviation of reference current.

[0071] Specifically, the standard instantaneous deviation can eliminate the influence of the absolute value of the reference current at different times.

[0072] Step S243: Within a preset analysis window, calculate the moving average and / or cumulative excess area of ​​the standard instantaneous deviation, wherein the cumulative excess area is the integral of the portion of the standard instantaneous deviation that exceeds a preset static threshold.

[0073] Specifically, the analysis window extends backward from the current sampling time to cover a continuous number of sampling points over a given time period. The moving average is the arithmetic mean of multiple sampling points within the analysis window, reflecting the persistence of the deviation. For the portion within the analysis window exceeding the static threshold, an integral is approximated using discrete sampling points, reflecting the cumulative effect of the deviation.

[0074] Step S244: If the standard instantaneous deviation continues to exceed the first dynamic threshold and reaches the first time period, it is determined to be a sudden abnormal deviation.

[0075] For example, if the first dynamic threshold is 2 and the first time period is 50ms, then the standard instantaneous deviations between t=50ms and t=90ms are 2.1, 2.3, 2.2, 2.4, and 2.3, respectively, which are then identified as sudden anomalies.

[0076] Step S245: If the moving average value continues to exceed the second dynamic threshold and reaches the second time period, or the cumulative area exceeding the standard exceeds the area threshold in the third time period, it is determined to be a gradual abnormal deviation.

[0077] For example, if the second dynamic threshold is 1.2 and the second time period is 200ms, then the moving average of the sampling points over 200ms is 1.3, which is then determined to be a gradual abnormal deviation.

[0078] If either of the above two deviation types is met, and the sampling current does not reach the open circuit or short circuit threshold, a latent fault warning will be triggered immediately.

[0079] Specifically, the system presets an adaptive tolerance range, such as ±20% of the average of the dynamic reference curve. For example, during the learning period, the current during vehicle system startup is collected and stabilized at 0.4A ± 0.05A, generating a dynamic reference curve. If, during actual operation, the current limit of a certain channel is consistently found to be 0.48A, deviating from the adaptive tolerance range of the dynamic reference curve, but not due to a short circuit or open circuit, then this is identified as a latent fault warning. Therefore, early fault warnings can be achieved, providing sufficient time for maintenance and preventing the fault from escalating into a visible fault.

[0080] Furthermore, if the problem is determined to be a latent fault warning, the method further includes (steps S31 to S32):

[0081] Step S31: Based on the magnitude of the instantaneous deviation of the standard, the duration of the gradual abnormal deviation, or the growth rate of the cumulative area exceeding the standard, the hidden fault warning is divided into multiple warning levels.

[0082] Specifically, the vehicle-mounted video main control chip is divided into multiple warning levels, each corresponding to different standard instantaneous deviation, the timing of progressive abnormal deviation, and the growth rate of the cumulative exceeding area. For example, in the first, second, and third warning levels, which are progressively higher, the larger the standard instantaneous deviation, the longer the duration of progressive abnormal deviation, and the larger the cumulative exceeding area, the higher the warning level.

[0083] Step S32: Based on the warning level, perform at least one of the following differentiated response operations:

[0084] (1) Control the status indicator device to indicate in a mode corresponding to the warning level.

[0085] Specifically, the vehicle-mounted video main control chip presets corresponding indication modes for each warning level. For example, the indication mode for the third level is slow flashing red light, the indication mode for the second level is fast flashing red light, and the indication mode for the third level is frequent flashing red light.

[0086] (2) When the warning level is the first level, logs are recorded locally.

[0087] (3) When the warning level is the second level, logs are recorded locally and warning information is actively sent to the upper-level system through the wireless communication unit.

[0088] (4) When the warning level reaches the third level, logs are recorded locally and warning information and suggested maintenance window period are sent to the upper system through the wireless communication unit.

[0089] Therefore, different response strategies are corresponding to different levels to avoid minor faults consuming too many operation and maintenance resources, ensure timely response to severe faults, and record complete fault information in local logs to facilitate subsequent tracing of the cause of the fault. Severe fault warnings are accompanied by maintenance windows to provide a reference for operation and maintenance planning.

[0090] This application also provides a computer-readable storage medium storing a computer program. When the program is executed by a processor, it implements the intelligent fault diagnosis method for multiple video transmission links provided in the above embodiments. By combining the fault type, occurrence time and physical topology to conduct correlation analysis, it accurately infers common fault sources such as shared links and power systems, quickly locates the root cause, avoids inefficient troubleshooting, significantly improves the efficiency of multi-channel concurrent fault handling, and reduces the operation and maintenance cost of vehicle video transmission systems.

[0091] In this embodiment, the computer-readable storage medium can be a tangible device that holds and stores instructions used by an instruction execution device. The computer-readable storage medium can be, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof. Specifically, the computer-readable storage medium can be a portable computer disk, a hard disk, a USB flash drive, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory stick, floppy disk, optical disk, magnetic disk, mechanical encoding device, or any combination thereof.

[0092] The computer program in this embodiment includes program code for performing all the aforementioned methods. The program code may include instructions corresponding to the method steps provided in the above embodiments. The computer program can be downloaded from a computer-readable storage medium to various computing / processing devices, or downloaded to an external computer or external storage device via a network (e.g., the Internet, a local area network, a wide area network, and / or a wireless network). The computer program can be executed entirely on the user's computer as a standalone software package.

[0093] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

[0094] Additionally, it should be understood that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

Claims

1. A method for intelligent fault diagnosis of multiple video transmission links, characterized in that, Performed by an integrated diagnostic module within the video adapter cable, the method includes: Real-time monitoring of the operating current of each branch channel of the video adapter cable; Based on the operating current, the status indicator device corresponding to the branch channel performs an action that matches the operating current.

2. The method according to claim 1, characterized in that, Based on the operating current, the status indication device corresponding to the branch channel performs an action matching the operating current, including: When the operating current is in the first normal range, the branch channel is in normal condition, and the green light of the status indicator device illuminates. When the operating current is lower than the first threshold, the branch channel is in an open circuit state, and the status indicator device is turned off. When the operating current exceeds the second threshold and triggers the protection mechanism, the branch channel is in a short-circuit state, and both the red and green lights of the status indicator device illuminate. Wherein, the first threshold is less than the lower limit of the first normal range, and the second threshold is greater than the upper limit of the first normal range.

3. The method according to claim 1, characterized in that, It also includes an onboard main control chip, which is connected to the integrated diagnostic module. The method is executed by the onboard video main control chip. When at least two branch channels are simultaneously determined to be faulty, the method further includes: Obtain the fault type and fault occurrence time for each fault channel; Based on the pre-stored physical topology of each branch channel, determine whether the faulty channels are physically adjacent or share a link. A correlation analysis is performed based on the fault type, the fault occurrence time, and the physical topology to infer common fault sources; wherein the correlation analysis includes at least one of the following rules: If two physically adjacent channels are simultaneously determined to be open circuits, it is inferred that the common link of those adjacent channels is open circuit. If one channel is determined to be short-circuited, and one or more other channels are determined to be abnormal voltage or power failure within a preset time, it is inferred that the power supply system is subjected to short-circuit disturbance. If all channels are simultaneously determined to have the same current anomaly, it is inferred that there is a fault in the main power input or the main grounding circuit. Based on the inference results, a prompt message containing the location of the common fault source is generated and reported.

4. The method according to claim 3, characterized in that, The method further includes: During the preset learning period after the camera is first powered on or installed, monitor and record the current timing data of each branch channel in typical working mode as learning data. Based on the learning data, a dynamic reference curve characterizing the normal current variation of the branch channel is generated through modeling processing. In subsequent operation, the real-time operating current will be compared with the dynamic reference curve. If the real-time operating current deviates from the dynamic reference curve by more than the adaptive tolerance range, but has not yet reached the open circuit state or the open circuit state, it is determined as a latent fault warning.

5. The method according to claim 4, characterized in that, The exceeding of the adaptive tolerance range includes sudden abnormal deviation and gradual abnormal deviation. If the real-time operating current deviates from the dynamic reference curve beyond the adaptive tolerance range, but has not yet reached the open circuit state, it is determined as a latent fault warning, including: For each sampling time, perform the following steps: Obtain the expected value of the reference current and the standard deviation of the reference current corresponding to the current sampling time from the dynamic reference curve; Calculate the standard instantaneous deviation between the sampled current and the expected value of the reference current, where the standard instantaneous deviation = |sampled current - expected value of reference current| / standard deviation of reference current; Within a preset analysis window, calculate the moving average and / or cumulative excess area of ​​the standard instantaneous deviation, wherein the cumulative excess area is the integral of the portion of the standard instantaneous deviation that exceeds a preset static threshold. If the standard instantaneous deviation continues to exceed the first dynamic threshold and reaches the first time period, it is determined to be a sudden abnormal deviation; If the moving average value continuously exceeds the second dynamic threshold and reaches the second time period, or if the cumulative area exceeding the standard exceeds the area threshold within the third time period, it is determined to be a gradual abnormal deviation.

6. The method according to claim 4 or 5, characterized in that, The process of generating a dynamic baseline curve characterizing the normal current variation of the branch channel based on the learned data through modeling includes: The learning data is divided according to different working conditions; For the learning data under each of the identified typical operating conditions, an independent dynamic benchmark sub-curve is established; wherein each dynamic benchmark sub-curve contains a benchmark current expected value sequence and a benchmark current standard deviation sequence corresponding to the time series of the operating condition. The comparison of the real-time operating current with the dynamic reference curve includes: Establish a mapping table from system operating conditions to the corresponding dynamic reference sub-curves; Based on the current system operating conditions, query the mapping relationship table and select the corresponding dynamic baseline sub-curve for comparison.

7. The method according to claim 4 or 5, characterized in that, If the problem is determined to be a latent fault warning, the method further includes: Based on the magnitude of the instantaneous deviation of the standard, the duration of the gradual abnormal deviation, or the growth rate of the cumulative area exceeding the standard, the hidden fault warning is divided into multiple warning levels. Based on the warning level, perform at least one of the following differentiated response actions: The status indicator device is controlled to indicate in a mode corresponding to the warning level; When the warning level is Level 1, log the information locally. When the warning level is the second level, a log is recorded locally, and the warning information is actively sent to the upper-level system through the wireless communication unit; When the warning level reaches the third level, a log is recorded locally, and the warning information and suggested maintenance window period are actively sent to the superior system through the wireless communication unit. The warning levels of the first level, the second level, and the third level increase sequentially.

8. An intelligent video transmission system for implementing the method according to any one of claims 1-7, characterized in that, This includes video adapter cables, integrated diagnostic modules, and onboard main control chips; The video adapter cable includes a main cable and at least one branch channel for connecting the video source and the display device; The integrated diagnostic module is encapsulated in the connector or middle of the video adapter cable, and includes a current detection circuit, a multi-state indicator, and a self-resetting fuse, performing the method as described in any one of claims 1-2; The vehicle-mounted video main control chip is electrically connected to the integrated diagnostic module and configured to perform the method as described in any one of claims 3-7.

9. A computer-readable storage medium, characterized in that, The computer program is stored that can be loaded by a processor and execute the method as described in any one of claims 1 to 7.

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