An LED display HUB board communication detection method and system

Abstract

The present invention discloses a communication detection method and system for an LED display HUB board, which relates to the technical field of communication detection. The method includes collecting a first communication signal of a serial communication interface on the HUB board and generating first feature data by matching preset signal feature parameters; collecting a second communication signal sent by a controller received by the HUB board and extracting second feature data according to the second communication signal; performing difference analysis on the first feature data and the second feature data to obtain a comprehensive difference index, and forming an abnormal identifier when the comprehensive difference index exceeds an adaptive threshold; displaying a corresponding fault type code on an indicator light set on the HUB board based on the abnormal identifier, and transmitting the fault type code back to the controller through a spare communication port of the HUB board. The present invention can effectively identify the abnormal signal type and severity through adaptive decision-making and hierarchical classification, and visually display it in the form of a fault type code, improving the real-time performance and reliability of communication fault detection.

Description

Technical Field

[0001] The present invention relates to the technical field of communication detection, and particularly to a communication detection method and system for an LED display HUB board. Background Art

[0002] As an efficient and flexible display technology, LED displays have been widely used in fields such as advertising, stage performances, and public information displays. One of its core components, the HUB board, as a communication bridge connecting the display unit and the controller, is mainly responsible for receiving the display data sent by the controller and transmitting it to the LED module. With the development of LED displays towards high definition and large scale, higher requirements are put forward for the communication stability, reliability, and fault diagnosis ability of the HUB board. In the prior art, the communication detection of the HUB board usually relies on manual detection or one-way communication feedback based on the controller. However, these detection methods are limited by poor real-time performance, insufficient detection accuracy, and the inability to comprehensively cover communication anomalies, which easily lead to a long problem troubleshooting cycle and increase the maintenance cost.

[0003] In the existing HUB board communication detection technology, the following deficiencies mainly exist: On the one hand, traditional methods often only focus on the connectivity of the communication link, and fail to effectively identify the anomalies in the communication data itself, such as hidden problems like signal distortion or data packet loss. This limitation may lead to the failure to detect anomalies in a timely manner, thus affecting the normal operation of the display screen. On the other hand, due to the lack of accurate classification and real-time feedback of communication faults, operators often need to troubleshoot fault points one by one during actual maintenance, with low efficiency. In addition, for some complex communication scenarios, such as interference problems during parallel operation of multiple HUB boards, the existing technology lacks a systematic solution and is difficult to meet the high reliability requirements of modern LED displays. Therefore, improving the real-time performance, accuracy, and visualization degree of HUB board communication detection technology has become an important research direction in the industry. Summary of the Invention

[0004] In view of the problems existing in the prior art, the present invention proposes a communication detection method and system for an LED display HUB board.

[0005] Therefore, the present invention provides a communication detection method for an LED display HUB board, which can solve the problems mentioned in the background art.

[0006] To solve the above technical problems, the present invention provides the following technical solutions:

[0007] In the first aspect, an embodiment of the present invention provides a communication detection method for an LED display HUB board, which includes,

[0008] Collect the first communication signal of the serial communication interface on the acquisition HUB board, and generate first characteristic data by matching preset signal characteristic parameters;

[0009] Collect the second communication signal sent by the receiving controller of the HUB board, and extract second characteristic data according to the second communication signal;

[0010] Perform difference analysis on the first characteristic data and the second characteristic data to obtain a comprehensive difference index, and form an anomaly flag when the comprehensive difference index exceeds the adaptive threshold;

[0011] Based on the anomaly flag, the indicator light set on the HUB board displays the corresponding fault type code, and the fault type code is returned to the controller through the spare communication port of the HUB board.

[0012] As a preferred solution of the communication detection method for the LED display HUB board of the present invention, wherein: the generation of the first characteristic data includes:

[0013] The first communication signal of the serial communication interface is sampled in real time through the signal sampling circuit of the HUB board at a predetermined sampling frequency to obtain a digital sequence;

[0014] Perform time-domain correlation analysis on the digital sequence and the standard communication waveform template stored in the preset signal characteristic parameter library, and calculate the matching degree between the digital sequence and the standard communication waveform template;

[0015] Extract the timing characteristics, amplitude characteristics, and jump characteristics of the communication waveform corresponding to the digital sequence to form the first characteristic data.

[0016] As a preferred solution of the communication detection method for the LED display HUB board of the present invention, wherein: the time-domain correlation analysis is represented by the following formula:

[0017]

[0018] Wherein, W m is the standard waveform template, τ is the time shift amount, t is the sampling time point, S n (t) is the sampling value of the digital sequence to be analyzed;

[0019] The matching degree between the digital sequence and the standard communication waveform template is calculated as follows:

[0020]

[0021] Wherein, λ1, λ2, and λ3 are weight coefficients, ΔT is the bit period deviation, T0 is the standard bit period, ΔV is the level deviation, and V0 is the standard level value.

[0022] As a preferred solution of the communication detection method for the LED display HUB board according to the present invention, wherein: the generation of the second characteristic data includes:

[0023] After the second communication signal is processed by the differential signal receiving circuit, signal conditioning is performed through a band-pass filter;

[0024] Performing dynamic threshold decision on the filtered signal;

[0025] According to the threshold decision result, extracting the waveform characteristics of the second communication signal;

[0026] Performing time-domain jitter analysis on the second communication signal;

[0027] Combining the waveform characteristics and the time-domain jitter analysis result through weighting to form the second characteristic data.

[0028] As a preferred solution of the communication detection method for the LED display HUB board according to the present invention, wherein: the time-domain jitter analysis result is a periodic jitter index, which is calculated by the following formula:

[0029]

[0030] where, θ i is the jitter amount of each period, t i is the occurrence time of the jitter, t0 is the reference time, τ j is the jitter decay time constant, J t is the periodic jitter index;

[0031] The waveform characteristic is a waveform distortion factor, which is calculated by the following formula:

[0032]

[0033] where, V i is the sampling point level value, V m is the average level value, N is the number of sampling points, and D(t) is the waveform distortion factor.

[0034] As a preferred solution of the communication detection method for the LED display HUB board according to the present invention, wherein: the difference analysis includes amplitude difference evaluation, phase difference evaluation and morphological difference evaluation;

[0035] Among them, the amplitude difference evaluation is based on the mean, variance and peak value of the characteristic data as shown in the following formula:

[0036]

[0037] The phase difference evaluation is determined by the peak position of the cross-correlation function, as shown in the following formula:

[0038]

[0039] The morphological difference evaluation uses the dynamic time warping algorithm to calculate the waveform similarity, as shown in the following formula:

[0040] D s = min{∑d[x(i), y(j)]w(i, j)} / ∑w(i, j)

[0041] where μ x , μ y are the arithmetic means of the first and second characteristic data sequences respectively, σ x , σ y are the standard deviations of the first and second characteristic data sequences respectively, P x , P y are the peaks of the first and second characteristic data sequences respectively, α1, α2, α3 are weight coefficients, D a is the amplitude difference index, θ c is the phase difference corresponding to the position of the cross-correlation peak, φ x (ω) is the spectral phase, W(ω) is the frequency weight function, β1, β2 are weight coefficients, D p is the phase difference index, d[x(i), y(j)] is the local distance metric, D s is the morphological difference index, w(i, j) is the path weight.

[0042] As a preferred solution of the LED display HUB board communication detection method described in the present invention, wherein: the determination of the fault type code includes:

[0043] Establish a hierarchical classification system of fault types according to the indexes obtained from the difference analysis. Each feature is divided into four levels according to the severity, and the final fault type code is determined through feature combination;

[0044] First, detect whether there are critical level features. If so, directly determine the corresponding main category; if there are no critical level features, detect the quantity and combination pattern of severe level features; when multiple severe level features exist simultaneously, determine the dominant feature according to the feature correlation analysis, and then determine the main category; if only moderate or minor level features exist, calculate the comprehensive score by superimposing the feature weights, and determine the main category according to the score range;

[0045] After the main category is determined, conduct the sub-category determination; the sub-category determination is based on the secondary feature combination, and according to the temporal relevance and evolution trend of the features, combined with the preset feature combination template, determine the specific sub-category;

[0046] Combine the fault level, the main category, the sub-category and the temporal relevance and evolution trend of the features to generate the fault type code.

[0047] As a preferred solution of the communication detection method for the LED display HUB board according to the present invention, wherein: the path weight is represented by the following formula:

[0048]

[0049] Wherein, λ is the path constraint coefficient, x′(i) and y′(j) are the normalized values of the first sequence at position i and the second sequence at position j, respectively.

[0050] In a second aspect, an embodiment of the present invention provides a communication detection system for an LED display HUB board, which includes:

[0051] An acquisition module, configured to acquire a first communication signal of a serial communication interface on the HUB board, and acquire a second communication signal sent by the receiving controller of the HUB board;

[0052] A feature extraction module, configured to generate first feature data by matching preset signal feature parameters according to the first communication signal, and extract second feature data according to the second communication signal;

[0053] An anomaly analysis module, configured to perform a difference analysis on the first feature data and the second feature data to obtain a comprehensive difference index, and form an anomaly identifier when the comprehensive difference index exceeds an adaptive threshold;

[0054] A fault code generation module, configured to display a corresponding fault type code on an indicator light set on the HUB board based on the anomaly identifier, and transmit the fault type code to the controller through a spare communication port of the HUB board.

[0055] The beneficial effects of the present invention are as follows: through high-precision sampling and multi-dimensional feature extraction technologies, combined with time-domain correlation analysis and dynamic threshold decision-making, accurate feature extraction and difference analysis of serial communication signals are realized; through the adaptive decision-making and hierarchical classification of the comprehensive difference index, the types and severity of abnormal signals can be effectively identified, and are intuitively displayed and transmitted in the form of fault type codes, improving the accuracy, real-time performance and reliability of communication fault detection. Description of the Drawings

[0056] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. Among them:

[0057] Figure 1It is a flowchart of a communication detection method for an LED display HUB board. Detailed implementation manners

[0058] To make the above objects, features, and advantages of the present invention more apparent and understandable, the following provides a detailed description of the specific implementation manners of the present invention in conjunction with the accompanying drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0059] In the following description, many specific details are set forth to facilitate a thorough understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art can make similar generalizations without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0060] Secondly, the so-called "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation manner of the present invention. The appearances of "in one embodiment" in different places in this specification do not all refer to the same embodiment, nor are they separate or alternative embodiments that exclude each other with other embodiments.

[0061] The present invention is described in detail in conjunction with schematic diagrams. When detailing the embodiments of the present invention, for ease of explanation, the cross-sectional views showing the device structure will be enlarged locally not in accordance with the general scale, and the schematic diagrams are only examples and should not limit the scope of protection of the present invention herein. In addition, in actual production, three-dimensional spatial dimensions including length, width, and depth should be included.

[0062] Meanwhile, in the description of the present invention, it should be noted that the orientation or positional relationships indicated by terms such as "upper, lower, inner, and outer" are based on the orientation or positional relationships shown in the drawings, and are only for facilitating the description of the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention. In addition, the terms "first, second, or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0063] Unless otherwise clearly defined and limited in the present invention, the terms "mounted, connected, and coupled" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may also be a mechanical connection, an electrical connection, or a direct connection, or may be indirectly connected through an intermediate medium, or may be the internal communication of two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0064] Example 1

[0065] Reference Figure 1 , which is the first embodiment of the present invention. This embodiment provides a method for detecting the communication of the LED display HUB board, including:

[0066] S1: Collect the first communication signal of the serial communication interface on the HUB board, and generate the first feature data by matching the preset signal feature parameters;

[0067] When collecting the first communication signal of the serial communication interface on the HUB board, first, the signal sampling circuit of the HUB board is used to perform real-time sampling on the level state of the serial communication interface at a predetermined sampling frequency; wherein, the predetermined sampling frequency is 8 times the communication baud rate, and the sampling circuit converts the collected level state into a digital sequence.

[0068] Next, perform time-domain correlation analysis on the digital sequence and the standard communication waveform template stored in the preset signal feature parameter library; wherein, the signal feature parameter library includes the standard waveform features of the communication start bit, data bit, parity bit, and end bit; wherein, the calculation of the time-domain correlation coefficient is shown in the following formula:

[0069]

[0070] Where W m is the standard waveform template, τ is the time shift amount, t is the sampling time point, S n (t) is the sampling value of the digital sequence to be analyzed; the signal feature parameter library includes the standard waveform features of the communication start bit, data bit, parity bit, and end bit;

[0071] Then, calculate the matching degree between the digital sequence and the standard communication waveform template, which is represented by the following formula:

[0072]

[0073] Where λ1, λ2, and λ3 are weight coefficients, and λ1 + λ2 + λ3 = 1, ΔT is the bit period deviation, T0 is the standard bit period, ΔV is the level deviation, and V0 is the standard level value.

[0074] Extract the timing features, amplitude features, and transition features of the communication waveform, and combine the timing features, the amplitude features, and the transition features to form the first feature data; wherein, the timing features include the bit period deviation value and the phase offset amount, the amplitude features include the signal peak value and the root mean square value, and the transition features include the rising edge time and the falling edge time. Their calculations are respectively:

[0075]

[0076] Among them, ω1 to ω6 are characteristic weight coefficients, and ∑ωi = 1, Δφ is the phase offset, V p is the signal peak value, V rms is the root mean square value, t r is the rising edge time, t f is the falling edge time.

[0077] Finally, combine the timing feature, the amplitude feature, and the jump feature to form the first feature data D, and its calculation formula is:

[0078]

[0079] Among them, β1 to β6 are combination weight coefficients, and ∑βi = 1, are the change rates of each feature respectively.

[0080] S2: The HUB board receives the second communication signal sent by the controller and extracts the second feature data according to the second communication signal;

[0081] The HUB board receives the second communication signal sent by the controller through the communication receiving module. The communication receiving module is provided with a differential signal receiving circuit, and the differential signal receiving circuit includes a differential amplifier, a common mode rejection circuit, and an impedance matching network; among them, the common mode rejection ratio of the differential amplifier is not less than 60 dB, the common mode rejection circuit uses a capacitive coupling method to eliminate the common mode interference signal, and the impedance matching network realizes automatic impedance matching through the parallel combination of adjustable resistors and capacitors.

[0082] After the second communication signal is processed by the differential signal receiving circuit, it is signal-conditioned by a band-pass filter. The passband range of the band-pass filter covers the signal fundamental frequency and its third harmonic frequency. The stopband attenuation characteristic of the band-pass filter is greater than 40 dB / octave, and the group delay fluctuation of the band-pass filter within the passband is less than 100 microseconds; more specifically, the transfer function of the band-pass filter is:

[0083]

[0084] Among them, K is the gain coefficient, ω1 and ω2 are the low-frequency and high-frequency cut-off angular frequencies respectively, and ω2 = γω1, where γ is the bandwidth coefficient.

[0085] Perform dynamic threshold decision on the filtered signal. The dynamic threshold value is adaptively adjusted according to the statistical distribution characteristics of the signal amplitude. The threshold adjustment process includes three sub-processes: signal envelope detection, noise level estimation, and threshold dynamic tracking. Among them, the signal envelope detection adopts a combination of peak holding and exponential decay. The noise level estimation is based on the variance calculation during the signal silence period. The response time of the threshold dynamic tracking is adaptively adjusted according to the signal mutation degree. Then, the calculation of the threshold value is shown in the following formula:

[0086]

[0087] Where, V ref is the reference level, μ is the threshold adjustment coefficient, σ(t) is the signal standard deviation, and τ is the time constant.

[0088] According to the threshold decision result, extract the waveform characteristics of the second communication signal and calculate the waveform distortion factor:

[0089]

[0090] Where, V i is the sampling point level value, V m is the average level value, and N is the number of sampling points.

[0091] Perform time-domain jitter analysis on the second communication signal and calculate the periodic jitter index Jt:

[0092]

[0093] Where, θ i is the jitter amount of each period, t i is the jitter occurrence time, t0 is the reference time, and τ j is the jitter decay time constant.

[0094] Finally, perform weighted combination on the waveform characteristics and the time-domain jitter analysis result to form the second feature data. In the weighted combination process, the weight coefficients of each feature parameter are optimally set according to the actual requirements of the communication system, and the sum of the weight coefficients is 1. At the same time, the change rate information of each feature parameter is also incorporated into the calculation process of the feature data to reflect the dynamic change law of the signal characteristics. As shown in the following formula:

[0095]

[0096] Where, η1~η6 are feature combination coefficients, and ∑ηi = 1, is the threshold acceleration, is the distortion change rate, is the jitter change rate.

[0097] S3: Compare the difference value between the first feature data and the second feature data, and form an anomaly flag when the difference value exceeds a preset threshold;

[0098] When comparing the difference value between the first feature data and the second feature data, first perform time series alignment on the first feature data and the second feature data, and calculate the correlation coefficient of the time series alignment:

[0099]

[0100] where X(n) and Y(n) are the first and second feature data respectively, and k is the time shift amount; the optimal alignment position k opt satisfies:

[0101]

[0102] where N is the length of the feature sequence;

[0103] Perform multi-dimensional difference analysis on the time-aligned feature data. The difference analysis includes amplitude difference evaluation, phase difference evaluation, and morphological difference evaluation; among them, the amplitude difference evaluation is based on the mean, variance, and peak value of the feature data, the phase difference evaluation is determined by the peak position of the cross-correlation function, and the morphological difference evaluation uses the dynamic time warping algorithm to calculate the waveform similarity; they are respectively represented by the following formulas:

[0104]

[0105]

[0106] D s = min{∑d[x(i),, y(j)]w(i,j)} / ∑w(i,j)

[0107] where μ x , μ y are the arithmetic means of the first and second feature data sequences respectively, σ x , σ y are the standard deviations of the first and second feature data sequences respectively, P x , P y are the peaks of the first and second feature data sequences respectively, α1, α2, α3 are weight coefficients, D a is the amplitude difference index, θ c is the phase difference corresponding to the cross-correlation peak position, φ x (ω) is the spectral phase, W(ω) is the frequency weight function, β1, β2 are weight coefficients, D p is the phase difference index, d[x(i),y(j)] is the local distance metric, Ds is the morphological difference index, and w(i, j) is the path weight, satisfying:

[0108]

[0109] where λ is the path constraint coefficient, and x' and y' are signal derivatives.

[0110] Perform hierarchical weighted combination on the results of the multi-dimensional difference analysis to obtain a comprehensive difference index; in the hierarchical weighting process, first perform first-level weighting on the difference indices of the same type, and then perform second-level weighting on the weighted results of different types.

[0111] Further perform adaptive threshold decision on the comprehensive difference index. The adaptive threshold includes a static reference threshold and a dynamic adjustment amount; among them, the static reference threshold is determined through statistical analysis of historical data, and the dynamic adjustment amount is adaptively adjusted according to changes in environmental temperature, signal strength, and communication load; the dynamic adjustment process adopts a fuzzy control strategy to calculate the adjustment amount based on the membership function of environmental parameters.

[0112] When the comprehensive difference index exceeds the adaptive threshold, start the abnormal classification and judgment process; the abnormal classification and judgment is based on the time-frequency distribution characteristics of the difference features, and the abnormal types are divided into transient abnormalities, cumulative abnormalities, and periodic abnormalities; among them, the transient abnormal feature is manifested as a sudden jump in the difference index, the cumulative abnormal feature is manifested as a continuous drift of the difference index, and the periodic abnormal feature is manifested as a regular fluctuation of the difference index; obtain the abnormal degree index E, and its calculation is as follows:

[0113]

[0114] where τ1 is the time constant, is the difference change rate, δ is the periodic weight, and T p is the characteristic period.

[0115] Generate an abnormal identifier including an abnormal type code and an abnormal level according to the abnormal type and the severity of the comprehensive difference index; the abnormal level is divided into four levels, where level one represents a minor abnormality, level two represents a moderate abnormality, level three represents a severe abnormality, and level four represents a critical abnormality; the abnormal identifier also includes the timestamp information of the abnormal occurrence and the relevant environmental parameter information;

[0116] S4: Based on the abnormal identifier, set the corresponding fault type code on the indicator light on the HUB board.

[0117] When the indicator light set on the HUB board based on the anomaly identifier displays the fault type code, a dynamic mapping table is first established. The mapping table establishes a hierarchical classification system for fault types according to the multi-dimensional characteristics of the difference value. Among them, the multi-dimensional characteristics include amplitude deviation, timing deviation, waveform distortion degree, and jitter index. Each characteristic is divided into four levels according to the severity, and the final fault type code is determined through characteristic combination:

[0118] First, it is detected whether there are critical level characteristics. If there are, it is directly determined as the corresponding main category. If there are no critical level characteristics, the quantity and combination pattern of severe level characteristics are detected. When multiple severe level characteristics exist simultaneously, the dominant characteristic is determined through characteristic correlation analysis, and then the main category is determined. If only medium or minor level characteristics exist, the comprehensive score is calculated through characteristic weight superposition, and the main category is determined according to the score interval.

[0119] After the main category is determined, the sub-category determination is carried out. The sub-category determination is based on the secondary characteristic combination, considering the timing correlation and evolution trend of the characteristics. The timing correlation is determined through the cross-correlation analysis of the characteristic sequence to identify the causal relationship of characteristic changes. The evolution trend is calculated through the time derivative and cumulant of the characteristics to predict the development direction of the fault. Based on these analysis results, combined with the preset characteristic combination template, the specific sub-category is determined.

[0120] The generation of the fault type code adopts a segmented coding method. The first segment is the fault level code, determined by the highest level characteristic; the second segment is the main category code, determined according to the dominant characteristic combination; the third segment is the sub-category code, determined based on the secondary characteristic combination; the fourth segment is the attribute code, including the timing characteristics and development trend information of the fault. Check bits are set between each segment of the coding to ensure the reliability of the coding.

[0121] S5: The fault type code is transmitted back to the controller through the spare communication port of the HUB board, and the controller adjusts the communication parameters according to the fault type code.

[0122] First, when the HUB board transmits the fault type code back to the controller through the spare communication port, a hierarchical encapsulation communication protocol structure is adopted. At the physical layer, differential signal transmission is used, and electrical isolation is achieved through optoelectronic isolation; at the data link layer, an improved HDLC protocol is used to achieve reliable data frame transmission; at the transport layer, a customized data packet format is used, including the fault type code, timestamp, status flag, and check information.

[0123] The operating modes of the spare communication port include a normal mode and an emergency mode. In the normal mode, the spare port periodically transmits status detection information at a low rate; when a fault is detected, it automatically switches to the emergency mode, increases the transmission rate, and establishes a priority channel. The emergency mode has an enhanced anti-interference mechanism and uses forward error correction coding and data interleaving techniques to improve transmission reliability.

[0124] After receiving the fault type code, the controller first performs data validity verification, including format check, checksum verification, and timing analysis. After passing the verification, it parses each field of the fault type code and extracts information such as the fault level, type, and attributes. Based on the parsing results, the controller starts the communication parameter adaptive adjustment process.

[0125] Furthermore, this embodiment also provides an LED display HUB board communication detection system, including:

[0126] An acquisition module, configured to acquire the first communication signal of the serial communication interface on the HUB board and acquire the second communication signal received by the HUB board from the controller;

[0127] A feature extraction module, configured to generate first feature data by matching preset signal feature parameters according to the first communication signal and extract second feature data according to the second communication signal;

[0128] An anomaly analysis module, configured to perform a difference analysis on the first feature data and the second feature data to obtain a comprehensive difference index, and form an anomaly identifier when the comprehensive difference index exceeds the adaptive threshold;

[0129] A fault code generation module, configured to display the corresponding fault type code on the indicator light set on the HUB board based on the anomaly identifier and transmit the fault type code back to the controller through the spare communication port of the HUB board.

[0130] This embodiment also provides a computer device applicable to the case of the LED display HUB board communication detection method, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the LED display HUB board communication detection method proposed in the above embodiment.

[0131] The computer device may be a terminal, which includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a carrier network, NFC (Near Field Communication), or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or may be a button, a trackball, or a touchpad provided on the outer shell of the computer device, or may also be an external keyboard, touchpad, or mouse, etc.

[0132] This embodiment also provides a storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the method for detecting the communication of the LED display screen HUB board as proposed in the above embodiment.

[0133] The storage medium proposed in this embodiment and the data storage method proposed in the above embodiment belong to the same inventive concept. For technical details not described in detail in this embodiment, reference can be made to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0134] Embodiment 2

[0135] This is the second embodiment of the present invention. This embodiment provides a method for detecting the communication of the LED display screen HUB board. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0136] This embodiment conducts experimental verification on the communication signal feature extraction and fault diagnosis of a certain LED display screen HUB control board. The experimental platform includes an LED display screen HUB control board (model: HUB-L2000), an LED display screen main controller (model: MC-V800), and supporting signal analysis equipment. Among them, the HUB-L2000 control board uses a high-performance 32-bit processor (main frequency 200MHz), integrates 16 serial communication interfaces, can simultaneously drive 16 LED display unit modules, and supports 32-level gray scale display control.

[0137] The signal acquisition system uses a high-precision 16-bit ADC (model ADS8867), configured with a sampling frequency of 1.8432 MHz (equivalent to 8 times the standard communication rate of 230.4 kbps) to ensure capturing waveform details. The signal conditioning circuit includes a low-pass filter with a bandwidth of 2 MHz to suppress high-frequency interference generated by switching power supplies and LED drivers. To adapt to the actual application environment of the LED display, the characteristic parameter library pre-sets 200 groups of standard waveform templates, covering communication waveform characteristics under different ambient temperatures (-20°C to 70°C), different communication rates (9600 bps to 230.4 kbps), and different load conditions.

[0138] The experimental process is divided into the following stages:

[0139] Reference data acquisition stage:

[0140] Under the standard working environment (temperature 25°C, humidity 45%), set the main controller to send LED display data to the HUB board at a baud rate of 230.4 kbps. The data frame format is: 1 start bit + 8 data bits + 1 parity bit + 1 stop bit. The data content includes LED grayscale control information, scan timing control information, and system status information. Continuously acquire 2000 frames of communication data as reference samples to establish a normal communication reference feature model.

[0141] Fault simulation and data acquisition stage:

[0142] Use a professional communication fault simulator (model: CFT-3000) to simulate 8 common communication abnormal conditions in the LED display system:

[0143] Signal amplitude attenuation fault (set attenuation amounts to 60%, 40%, and 20% respectively)

[0144] Bit period jitter fault (set jitter amplitudes to ±10%, ±20%, and ±35% respectively)

[0145] Waveform distortion fault (set distortion degrees to 15%, 30%, and 45% respectively)

[0146] Ground wire interference fault (set common-mode interference voltages to 1V, 2V, and 3V respectively)

[0147] Power supply fluctuation fault (set power supply ripples to 5%, 10%, and 15% respectively)

[0148] Impedance mismatch fault (set impedance mismatch degrees to 20%, 40%, and 60% respectively)

[0149] EMI interference fault (inject electromagnetic interference from 100 kHz to 1 MHz, with intensities of 60 dBμV, 80 dBμV, and 100 dBμV respectively)

[0150] Temperature drift fault (ambient temperature is set to -10°C, 45°C and 65°C respectively)

[0151] For each fault condition, the system continuously collects 1000 frames of data as samples. At the same time, auxiliary parameters such as ambient temperature, power supply voltage, and communication load rate are recorded.

[0152] Feature extraction and fault diagnosis stage:

[0153] Based on the algorithm in the invention content, the collected data is processed as follows:

[0154] Perform time-domain correlation analysis and calculate the waveform matching degree

[0155] Extract timing features (bit period deviation, phase shift)

[0156] Extract amplitude features (signal peak value, root mean square value)

[0157] Extract jump features (rise edge, fall edge time)

[0158] Calculate the comprehensive feature index

[0159] Perform anomaly detection and classification judgment

[0160] Verification and optimization stage:

[0161] By changing the LED display content (all white, all black, gradient gray scale, etc.), display brightness levels (25%, 50%, 75%, 100%) and environmental conditions, verify the stability and reliability of the fault diagnosis algorithm. Conduct statistical analysis on the detection results, optimize the feature extraction parameters and judgment thresholds, and improve the diagnostic accuracy of the system.

[0162] The following experimental data are obtained through the above experiments:

[0163] Table 1 Experimental data table

[0164]

[0165]

[0166] By analyzing the experimental data table, it can be concluded that:

[0167] For signal attenuation fault: when the signal attenuates by 60%, the waveform matching degree drops sharply to 0.685, and the time-domain correlation coefficient drops to 0.721. The system can reliably detect this type of fault, with a detection rate of 98.56% and a misjudgment rate of only 1.25%.

[0168] For the bit period jitter fault: A jitter of ±35% results in an increase in the bit period deviation to 42.8 ns, which is 3.4 times the normal value, and the system exhibits excellent jitter detection ability.

[0169] For the waveform distortion fault: A distortion of 45% causes the waveform matching degree to drop to 0.756, and the rise time and fall time increase to 68.9 ns and 65.7 ns respectively. The system can accurately identify the distortion characteristics.

[0170] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A communication detection method for an LED display HUB board, characterized in that: Including: Collect the first communication signal of the serial communication interface on the HUB board, and generate first feature data by matching preset signal feature parameters; Collect the second communication signal sent by the receiving controller of the HUB board, and extract second feature data according to the second communication signal; Perform difference analysis on the first feature data and the second feature data to obtain a comprehensive difference index, and form an anomaly flag when the comprehensive difference index exceeds the adaptive threshold; Based on the anomaly flag, display the corresponding fault type code on the indicator light set on the HUB board, and send the fault type code back to the controller through the spare communication port of the HUB board; The difference analysis includes amplitude difference evaluation, phase difference evaluation and morphological difference evaluation; Among them, the amplitude difference evaluation is based on the mean, variance and peak value of the feature data as shown in the following formula: ， The phase difference evaluation is determined by the peak position of the cross-correlation function, as shown in the following formula: ， The morphological difference evaluation uses the dynamic time warping algorithm to calculate the waveform similarity, as shown in the following formula: ， wherein, are the arithmetic means of the first and second characteristic data sequences respectively, are the standard deviations of the first and second characteristic data sequences respectively, are the peaks of the first and second characteristic data sequences respectively, 、 、 are weight coefficients, is the amplitude difference index, is the phase difference corresponding to the cross-correlation peak position, is the spectral phase, is the frequency weight function, 、 are weight coefficients, is the phase difference index, is the local distance metric, is the morphological difference index, is the path weight.

2. The communication detection method of the LED display HUB board according to claim 1, wherein: The generation of the first feature data includes: Real-time sample the first communication signal of the serial communication interface through the signal sampling circuit of the HUB board at a predetermined sampling frequency to obtain a digital sequence; Perform time-domain correlation analysis on the digital sequence and the standard communication waveform template stored in the preset signal feature parameter library, and calculate the matching degree between the digital sequence and the standard communication waveform template; Extract the timing feature, amplitude feature and jump feature of the communication waveform corresponding to the digital sequence to form the first feature data.

3. The communication detection method of the LED display HUB board according to claim 2, characterized in that: The time-domain correlation analysis is represented by the following formula: ， Among them, is the standard waveform template, is the time shift amount, is the sampling time point, is the digital sequence sampling value to be analyzed; The matching degree calculation between the digital sequence and the standard communication waveform template is shown in the following formula: ， Among them, , , are weighting coefficients, is the bit period deviation, is the standard bit period, is the level deviation, is the standard level value.

4. The communication detection method of the LED display HUB board according to claim 1, wherein: The generation of the second feature data includes: After processing the second communication signal through the differential signal receiving circuit, perform signal conditioning through a band-pass filter; Perform dynamic threshold decision on the filtered signal; According to the threshold decision result, extract the waveform feature of the second communication signal; Perform time-domain jitter analysis on the second communication signal; Perform weighted combination on the waveform feature and the time-domain jitter analysis result to form the second feature data.

5. The communication detection method of the LED display HUB board according to claim 4, characterized in that: The time-domain jitter analysis result is a periodic jitter index, which is calculated by the following formula: ， wherein, is the jitter amount of each period, is the occurrence time of the jitter, is the reference time, is the jitter decay time constant, is the periodic jitter index; The waveform feature is a waveform distortion factor, which is calculated by the following formula: ， Among them, is the sampled point level value, is the average level value, is the number of sampling points, is the waveform distortion factor.

6. The communication detection method of the LED display HUB board according to claim 5, characterized in that: The determination of the fault type code includes: Establish a hierarchical classification system for fault types according to the indicators obtained from the difference analysis. Each feature is divided into four levels according to the severity, and the final fault type code is determined through feature combination; First, detect whether there are critical level features. If so, directly determine the corresponding main category; if there are no critical level features, detect the quantity and combination mode of severe level features; when multiple severe level features exist simultaneously, determine the dominant feature according to the feature correlation analysis, and then determine the main category; if only moderate or mild level features exist, calculate the comprehensive score through feature weight superposition, and determine the main category according to the score range; After the main class is determined, the subclass determination is carried out; the subclass determination is based on the secondary feature combination. According to the temporal correlation and evolution trend of the features, combined with the preset feature combination template, the specific subcategory is determined. The fault type code is generated by combining the fault level, the main category, the subcategory, and the temporal correlation and evolution trend of the features.

7. The communication detection method of the LED display HUB board according to claim 6, characterized in that: The path weight is expressed by the following formula: ， Among them, is the path constraint coefficient, and are respectively the normalized values of the first sequence at position , and the normalized value of the second sequence at position .

8. An LED display HUB board communication detection system, based on the LED display HUB board communication detection method according to any one of claims 1 to 7, characterized in that: Including: A collection module, configured to collect a first communication signal of a serial communication interface on the HUB board, and collect a second communication signal sent by the receiving controller of the HUB board; A feature extraction module, configured to generate first feature data by matching preset signal feature parameters according to the first communication signal, and extract second feature data according to the second communication signal; An anomaly analysis module, configured to perform a difference analysis on the first feature data and the second feature data to obtain a comprehensive difference index, and form an anomaly flag when the comprehensive difference index exceeds the adaptive threshold; A fault code generation module, configured to display the corresponding fault type code on an indicator light set on the HUB board based on the anomaly flag, and transmit the fault type code back to the controller through a spare communication port of the HUB board.

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