LED display module and method thereof

Abstract

The invention discloses an LED display module and a method thereof, and relates to the field of intelligent tests.The method comprises the steps that firstly, a detection signal is sent to the LED display module, and after the module receives the signal, a display mode test is executed, and a state detection signal is generated; the system analyzes these signals to determine whether the module is in a normal operating state. And if the detection result is normal, the system receives a transmission control instruction from the application program of the terminal equipment, starts an image signal transmission mode, and transmits the display content of the terminal equipment to the LED display module for display. The process has the effects that the reliability and the stability of the LED display module are improved, the accuracy and the timeliness of the display content are ensured, and the user experience is improved.

Description

Technical Field

[0001] The present application relates to the field of intelligent detection, and more specifically, to an LED display module and a method thereof. Background Art

[0002] LED (light-emitting diode) display modules are widely used in various occasions, such as billboards, traffic sign screens, stage backgrounds, home theaters, etc. These applications place strict requirements on the reliability, stability and image quality of display modules. The traditional display method has a complex operation process, resulting in technical problems such as low display efficiency.

[0003] In this regard, patent CN117789646A discloses a display method, system and electronic device based on an LED display screen module, which first sends a status detection signal to the LED display screen module to confirm its working status, and ensures the normal operation of the module by responding to the detection signal. Subsequently, the application on the terminal device sends a first control signal to the control box to indicate the start of the image signal transmission mode. Finally, under the instruction of the first control signal, the control box transmits the display content of the terminal device to the LED display screen module for synchronous display.

[0004] However, due to environmental factors (such as temperature, humidity), aging caused by long-term use, power supply fluctuations, etc., the LED display module may fail or degrade in performance. Therefore, it is crucial to ensure that it is in normal working condition. In this patent, a status detection signal is sent to the LED display module and a mode display is performed. Only when the LED display module displays normally in all display modes, it indicates that the LED display module is working properly. However, the patented method can only detect obvious display anomalies. This method relies on human eye observation or simple automated detection, and there may be misjudgments, especially in low brightness or ambient light interference. In addition, some subtle but important problems may be overlooked, such as certain electrical problems or internal connection problems, which may not affect the display mode but will affect long-term stability and performance.

[0005] Therefore, a solution for optimizing the LED display module is desired. Summary of the invention

[0006] In order to solve the above technical problems, this application is proposed.

[0007] According to one aspect of the present application, a method for an LED display module is provided, comprising: sending a detection signal to the LED display module; the LED display module receiving the detection signal and performing a display mode test to obtain a state detection signal; analyzing the state detection signal to determine a working state detection result of the LED display module; in response to the working state detection result being a normal working state, receiving a transmission control instruction for starting image signal transmission issued by a target application of a terminal device; according to the transmission control instruction, transmitting display content of the terminal device to the LED display module for display; wherein analyzing the state detection signal to determine the working state detection result of the LED display module comprises:

[0008] Acquiring the status detection signal;

[0009] Extracting a set of state reference signals marked as normal working states from a background database;

[0010] Extracting a signal feature from the state detection signal to obtain a state detection signal feature;

[0011] Extracting signal features from each state reference signal marked as being in a normal working state in the set of state reference signals marked as being in a normal working state to obtain a set of state reference signal features;

[0012] Performing a fast positioning semantic dynamic query on the set of the state detection signal feature and the state reference signal feature to obtain a state detection signal query response semantic coding feature;

[0013] The working status detection result is obtained by querying the response semantic coding feature according to the status detection signal.

[0014] According to another aspect of the present application, an LED display module is provided, wherein the LED display module is used to execute the above-mentioned LED display module method.

[0015] Compared with the prior art, the present application provides an LED display module and method thereof, which obtains a state detection signal, and extracts a set of state reference signals marked as normal working states from a background database, uses AI-based data analysis and encoding to extract signal features from the state detection signal, and simultaneously extracts signal features from each state reference signal marked as a normal working state, thereby intelligently obtaining the working state detection result based on the fast positioning semantic query representation between the state detection signal feature and each state reference signal feature. The present application can accurately distinguish between normal and abnormal conditions under various lighting conditions, reducing the possibility of misjudgment due to environmental factors. In addition, by introducing a pre-stored state reference signal and comparing its features, subtle differences can be identified, thereby more accurately judging the working state of the LED display module. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] By describing the embodiments of the present application in more detail in conjunction with the accompanying drawings, the above and other purposes, features and advantages of the present application will become more apparent. The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation of the present application. In the accompanying drawings, the same reference numerals generally represent the same components or steps.

[0017] Figure 1 The figure is a flow chart of a method for displaying an LED module according to an embodiment of the present application.

[0018] Figure 2 Flow chart of step S130 in the method of the LED display module according to an embodiment of the present application.

[0019] Figure 3 Flow chart of step S135 in the method of the LED display module according to an embodiment of the present application.

[0020] Figure 4 Flow chart of step S1351 in the method of the LED display module according to an embodiment of the present application. DETAILED DESCRIPTION

[0021] The embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, but rather these embodiments are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0022] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0023] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0024] Therefore, in view of the problems in the above background technology, the present application proposes a method of LED display module. Figure 1 FIG. 1 is a flow chart of a method for displaying an LED module according to an embodiment of the present application. Figure 1 As shown, the method of the LED display module according to the embodiment of the present application includes: S110, sending a detection signal to the LED display module; S120, the LED display module receives the detection signal, and performs a display mode test to obtain a status detection signal; S130, analyzing the status detection signal to determine the working status detection result of the LED display module; S140, in response to the working status detection result being a normal working state, receiving a transmission control instruction for starting image signal transmission issued by a target application of a terminal device; S150, according to the transmission control instruction, delivering the display content of the terminal device to the LED display module for display.

[0025] Specifically, in step S110, a detection signal is sent to the LED display module. It should be understood that the control box sends a detection signal to the LED display module in response to a trigger from a user or a system (for example, by pressing a button on the control box or operating on a terminal device). This signal is to check whether the LED display module is in a normal working state.

[0026] Specifically, first, after the control system (usually refers to a control box or similar central processing unit connected to the LED display module) receives a trigger signal, it will prepare and send a specially designed detection signal to the LED display module. This signal is not a simple electrical signal, but an information packet containing multiple predefined modes, designed to allow the LED display module to perform self-detection according to predetermined rules. These predefined modes may include but are not limited to brightness adjustment, color expression, refresh rate, etc., and each mode corresponds to the working status of different components inside the LED display module. Therefore, by performing a series of such mode tests, you can fully understand the current operation of the LED display module.

[0027] Before sending the detection signal, the control system also needs to confirm that the communication link with the LED display module has been established and is in good condition. This usually involves an initialization phase, in which the control system attempts to establish a connection with the LED display module and verify whether the data transmission path between the two is unobstructed. Once the communication is confirmed to be normal, the control system begins to build the detection signal. During the construction process, the control system will encode the above-mentioned multiple detection modes into the signal according to the established protocol format to ensure that the LED display module can correctly interpret and respond.

[0028] Next, the control system sends the constructed detection signal to the LED display module through a physical interface (such as RS-232, RS-485, Ethernet or wireless communication module, etc.). In order to ensure the quality of signal transmission, the control system may use some error correction coding technologies, such as cyclic redundancy check (CRC), so that data integrity can be maintained as much as possible even in a poor network environment. In addition, in some cases, the control system will also set a timeout mechanism. If the LED display module fails to respond within the specified time, it is deemed that the detection signal has not been successfully received, and it is necessary to try to send it again or take other remedial measures.

[0029] Specifically, in step S120, the LED display module receives the detection signal and performs a display mode test to obtain a state detection signal. Accordingly, after receiving the detection signal, the LED display module will display in sequence according to several preset display modes (such as red light, green light, blue light, etc.). When the LED display module completes a series of self-tests in a predetermined mode, it will generate a state detection signal containing its own working state information and feed it back to the control system. These state detection signals can be changes in electrical parameters such as voltage and current, or more complex combination signals, which reflect the performance of the LED display module under different test modes.

[0030] Specifically, the changes in voltage and current are the most basic parameters that directly reflect the working status of the LED display module. For example, in the brightness adjustment test, the driver chip will change the current output to the LED lamp bead, and the change in the current signal can be detected on the corresponding detection circuit. This change is not only a key indicator for judging whether the LED lamp bead can adjust the brightness as expected, but also indirectly indicates the working efficiency of the power management circuit. Similarly, changes in voltage levels can help identify problems such as insufficient power supply or overvoltage, which may cause damage to the LED lamp bead or performance degradation. PWM signals are used to control the brightness and color of the LED. By changing the duty cycle of the PWM signal, fine adjustment of the LED brightness can be achieved. Therefore, the stability of the PWM signal is crucial to ensure image quality. If abnormal fluctuations in the PWM signal are found during the test, it may be caused by a control chip failure or external interference, which will directly affect the final display effect.

[0031] Specifically, in step S130, the state detection signal is analyzed to determine the working state detection result of the LED display module. It should be understood that the analysis of the state detection signal from the LED display module can confirm whether the LED display module can correctly respond to the instruction issued by the control box, which helps to eliminate any possible hardware failures or connection problems and ensure the quality of subsequent image signal transmission and display. Accordingly, in the working state analysis of the state detection signal to obtain the working state detection result, the technical concept of the present application is to obtain the state detection signal, and extract the set of state reference signals marked as normal working state from the background database, use AI-based data analysis and encoding methods to extract signal features from the state detection signal, and extract signal features from each state reference signal marked as normal working state, so as to intelligently obtain the working state detection result according to the fast positioning semantic query representation between the state detection signal feature and each state reference signal feature. The present application can accurately distinguish between normal and abnormal situations under various lighting conditions, reducing the possibility of misjudgment caused by environmental factors. And the introduction of the pre-stored state reference signal and the comparison of its features can identify subtle differences, so as to more accurately judge the working state of the LED display module.

[0032] Figure 2 FIG. 1 is a flow chart of step S130 in the method of the LED display module according to an embodiment of the present application. Specifically, in the embodiment of the present application, Figure 2As shown, the S130, analyzing the state detection signal to determine the working state detection result of the LED display module, includes: S131, acquiring the state detection signal; S132, extracting a set of state reference signals marked as normal working states from a background database; S133, extracting signal features from the state detection signal to obtain state detection signal features; S134, extracting signal features from each state reference signal marked as normal working state in the set of state reference signals marked as normal working states to obtain a set of state reference signal features; S135, performing fast positioning semantic dynamic query on the state detection signal features and the set of state reference signal features to obtain state detection signal query response semantic coding features; S136, obtaining the working state detection result according to the state detection signal query response semantic coding features.

[0033] In step S131, the state detection signal is obtained. It should be understood that the state detection signal is an electrical signal containing the working state information of the module fed back by the LED display module after receiving the detection signal and performing the display mode test. It can be a combination of multiple signals, such as voltage signals, current signals, pulse signals, etc. From a physical perspective, when the LED display module performs a display mode test, its internal circuit elements (such as LED lamp beads, driver chips, power management chips, etc.) will change their own working states according to the test requirements. This change in working state will cause the electrical parameters in the circuit to change, and these changes are reflected in the form of state detection signals. For example, when testing the brightness adjustment function of the LED lamp beads, the driver chip will change the current output to the lamp beads. At this time, the real-time change of the current signal can be detected on the corresponding detection circuit, and this changed current signal is part of the state detection signal.

[0034] After the LED display module receives the detection signal from the control system and performs the corresponding display mode test, the internal circuit components (such as LED lamp beads, driver chips, power management chips, etc.) will change their working state according to the test requirements. This change in working state will cause corresponding changes in electrical parameters in the circuit, such as an increase or decrease in voltage level, a change in current intensity, and an adjustment in the duty cycle of the PWM signal. These changes are ultimately reflected in the form of electrical signals on the communication line connecting the LED display module and the control system. At this point, the control system needs to be prepared to receive and process these feedback information from the LED display module.

[0035] In order to ensure that the received status detection signal is both accurate and complete, the control system will first make full preparations at the hardware level. This includes but is not limited to initializing the communication interface, configuring the appropriate baud rate and other transmission parameters, and setting the necessary error detection mechanisms, such as cyclic redundancy check (CRC). In this way, the possible bit errors or loss problems during data transmission can be minimized to ensure the integrity of the status detection signal. At the same time, the control system will also check whether the physical connection with the LED display module is stable and reliable to avoid signal reception failure due to poor contact.

[0036] Once it is confirmed that the communication link has been established and is in good condition, the control system begins to wait for the status detection signal from the LED display module. These signals may appear in different forms, depending on the specific detection mode and the communication protocol used. For example, in some cases, the status detection signal may be a continuous analog voltage or current waveform; in other cases, it may be a discrete digital encoded pulse sequence. Regardless of the form, the control system needs to have the corresponding decoding capability to correctly parse the information contained therein.

[0037] In addition to basic signal reception and decoding, the process of obtaining the status detection signal also includes preliminary processing of the raw data to remove noise interference and unnecessary redundant information. This is because there are inevitably various types of interference sources in the actual application environment, which may pollute the status detection signal and affect the accuracy of subsequent analysis. To this end, the control system often uses a filtering algorithm to smooth the part with large fluctuations, or uses a threshold judgment technology to remove obviously abnormal data points. In addition, in order to improve efficiency, the control system can also selectively retain the key features that best reflect the working status of the LED display module, such as maximum, minimum, average and other statistics, while ignoring the remaining unimportant details. Doing so will not only help simplify the subsequent data processing process, but also reduce storage requirements and computational complexity.

[0038] In step S132, a set of state reference signals marked as normal working state is extracted from the background database. Accordingly, it is considered that this is a set of signals pre-stored in the background database. Each of the signals is a state reference signal obtained by measurement and recording when the LED display module is in normal working state. These signals contain information such as normal voltage range, current mode, signal frequency, etc., and can represent various electrical characteristics and operating parameters of the LED display module when it is operating normally. Therefore, in order to use the state reference signal of the normal working state as a reference benchmark to effectively determine whether the working state of the current LED display module meets the expected standards, in the technical solution of the present application, a set of state reference signals marked as normal working state is extracted from the background database. This use of a large number of diversified state reference signals as a benchmark can enhance the accuracy of abnormal condition identification to confirm whether the module is operating in the best state.

[0039] Specifically, when the control system is ready to analyze the status detection signal, it needs a reliable benchmark to compare the currently detected signal characteristics to determine whether the LED display module is in normal working condition. To achieve this, the control system accesses a large amount of historical data pre-stored in the background database, from which it selects those status reference signals that are clearly marked as "normal working condition".

[0040] The backend database is a system that centrally stores and manages LED display modules and related test information, which contains equipment data from different batches, models and usage environments. These data are collected under various conditions, including but not limited to laboratory environments, actual application scenarios, and simulated extreme conditions. Each record describes in detail the working status of the LED display module at a specific point in time, including electrical parameters (such as voltage, current), optical properties (such as brightness, color), environmental factors such as temperature and humidity, and other variables that may affect its performance. Through long-term accumulation and continuous updating, the backend database has become a huge and rich knowledge base, providing a solid data foundation for subsequent status evaluation.

[0041] When the control system decides to start status detection of the LED display module, it will first initiate a query request in the background database, with the aim of finding records that have been clearly marked as "normal working status". This marking is usually based on strict quality control standards and technical specifications, and is completed by professional technicians before the equipment leaves the factory or during regular maintenance. For example, on the factory production line, each LED display module will undergo a series of rigorous tests, and only those devices that fully meet the preset indicators will be labeled as "normal working status" and their corresponding test data will be saved in the background database. In addition, users can also perform periodic health checks on the installed LED display modules according to actual conditions, and feedback the results to the manufacturer to further enrich the content of the background database.

[0042] Once the query scope is determined, the control system will use an efficient indexing mechanism to quickly locate records that meet the conditions. In order to speed up retrieval and improve accuracy, the background database usually adopts a multi-level index structure to classify and organize data according to different dimensions (such as device type, test date, geographic location, etc.). In this way, even in the face of a large amount of historical records, the control system can find the reference sample that is most similar to the current LED display module to be tested in a short time. At the same time, in order to ensure that the extracted state reference signal is representative, the control system will also consider some additional factors, such as the operating time and cumulative working hours of the equipment, and try to select those records that have been tested for a long time and maintain good performance as references.

[0043] It is worth noting that due to the complexity and diversity of the actual application environment, there may be certain differences between different batches or models of LED display modules. Therefore, relying solely on a single reference sample is often not enough to fully evaluate the working status of the current device. To this end, the control system will select multiple qualified records to form a set, the so-called "state reference signal set". By comprehensively analyzing the state reference signal feature coding vectors of all members in this set, a more comprehensive and accurate reference framework can be constructed to provide more reliable support for the final state assessment. In addition, with the development of new technologies and the emergence of new problems, the background database will continue to be updated and new reference samples will be added to adapt to the ever-changing application needs.

[0044] In step S133, signal features are extracted from the state detection signal to obtain state detection signal features. Specifically, in an embodiment of the present application, extracting signal features from the state detection signal to obtain state detection signal features includes: using a state signal feature extractor based on a deep separable convolutional network to process the state detection signal to obtain a state detection signal feature encoding vector as the state detection signal feature. It should be understood that considering that the state detection signal may be very complex, containing a large amount of time and frequency domain information, there are also some noise and background information interference and influence. Therefore, in order to focus more on the key features that best reflect the state of the LED display module to reflect the essential properties of the signal, in the technical solution of the present application, signal features are extracted from the state detection signal to obtain a state detection signal feature encoding vector. In particular, in a specific embodiment of the present application, the state detection signal can be processed by using a state signal feature extractor based on a deep separable convolutional network to efficiently and accurately extract the most representative features from the complex original signal to obtain a state detection signal feature encoding vector. It should be understood that a deep separable convolutional network is an improved structure of a convolutional neural network (CNN). The traditional convolution operation uses a convolution kernel to perform convolution on each channel of the input data, while the depthwise separable convolution divides this process into two steps. The first is the depthwise convolution, which uses a separate convolution kernel to perform convolution on each input channel, so that the features of each channel can be extracted independently. Then there is the pointwise convolution, which uses a 1x1 convolution kernel to integrate the information across channels after the depthwise convolution, so that the information between different channels can communicate with each other. Specifically, for the light signal of the LED display module group, it can first use a smaller convolution kernel to extract the light intensity change characteristics of the local pixel area, such as the light intensity gradient around a single LED lamp bead, and then use pointwise convolution to integrate these local features, so as to obtain a feature encoding vector that can better reflect the overall state of the display screen, such as the uniformity of the light intensity distribution, whether there are local bright spots or dark spots, and other features.

[0045] In step S134, signal features are extracted from each state reference signal in the set of state reference signals marked as being in a normal working state to obtain a set of state reference signal features. Specifically, in an embodiment of the present application, signal features are extracted from each state reference signal in the set of state reference signals marked as being in a normal working state to obtain a set of state reference signal features, including: using the state signal feature extractor based on the deep separable convolutional network to process each state reference signal in the set of state reference signals marked as being in a normal working state to obtain a set of state reference signal feature encoding vectors as the set of state reference signal features. Accordingly, considering that each state reference signal marked as being in a normal working state may contain a large amount of noise and unnecessary background information, directly using the original signal for comparison and analysis is inefficient and easily affected by interference factors such as noise. Based on this, in the technical solution of the present application, signal features are extracted from each state reference signal marked as a normal working state in the set of state reference signals marked as a normal working state to mine key feature information such as optical parameter signals, and a set of state reference signal feature coding vectors is obtained, so as to better reflect the essential characteristics of the normal working state of the LED display module. In particular, in a specific embodiment of the present application, each state reference signal marked as a normal working state can be processed by using a state signal feature extractor based on a deep separable convolutional network to ensure effective feature extraction while more efficiently processing these large numbers of reference signals, so that the set of extracted state reference signal feature coding vectors can accurately reflect the characteristics that the signal should have under the normal working state.

[0046] In step S135, a fast positioning semantic dynamic query is performed on the set of the state detection signal features and the state reference signal features to obtain the state detection signal query response semantic coding features. Further, considering that the state detection signal features represent the state feature information of the LED display module to be detected, and the set of state reference signal features reflects the feature conditions of many normal working states, these two features are semantically slightly related. However, the traditional simple comparison method is often difficult to fully explore the deep semantic associations and feature matching degrees between them. Based on this, the present application introduces a fast positioning semantic dynamic query mechanism to match the state detection signal features and the set of state reference signal features to obtain the state detection signal query response semantic coding features. That is, the mechanism can understand the information contained in these vectors from a semantic level, and quickly locate those state reference signal feature coding vectors that are most semantically relevant and have the highest feature matching degree with the state detection signal feature coding vector, so as to better cope with complex feature comparison and association analysis requirements.

[0047] Figure 3 FIG. 1 is a flow chart of step S135 in the method of the LED display module according to an embodiment of the present application. Specifically, in the embodiment of the present application, Figure 3 As shown, in step S135, a fast positioning semantic dynamic query is performed on the set of the state detection signal feature and the state reference signal feature to obtain the state detection signal query response semantic coding feature, including: S1351, determining the state reference signal fine-grained matching search window according to the state detection signal feature coding vector and the set of the state reference signal feature coding vector; S1352, according to the state reference signal fine-grained matching search window, performing a fine-grained query response on the state detection signal feature coding vector and each feature within the state reference signal fine-grained matching search window to obtain the state detection signal query response semantic coding vector as the state detection signal query response semantic coding feature.

[0048] Figure 4 FIG. 1 is a flow chart of step S1351 in the method of the LED display module according to an embodiment of the present application. More specifically, in the embodiment of the present application, Figure 4 As shown, in step S1351, according to the set of the state detection signal feature coding vector and the state reference signal feature coding vector, a state reference signal fine-grained matching search window is determined, including:

[0049] S13511, calculating the cross entropy of the state detection signal feature coding vector relative to each state reference signal feature coding vector in the set of the state reference signal feature coding vector to obtain a set of state detection-reference signal fast query positioning factors. This process can be expressed by the following formula:

[0050] D={d1,d2,...,d i ,...,d n}

[0051]

[0052] F={H(v a ,d1),H(v a ,d2),...,H(v a ,d i ),...,H(v a ,d n )}

[0053] Where D is the set of the state reference signal feature encoding vectors, d1, d2, d i and d nare the first, second, i-th and n-th state reference signal feature coding vectors in the set of state reference signal feature coding vectors, Yes i The eigenvalues ​​at each position in the a is the state detection signal feature encoding vector, Yes a The eigenvalues ​​of each position in , s is d i and v a The number of eigenvalues ​​in, log2 represents the logarithmic function value with base 2, H(v a ,d1),H(v a ,d2),H(v a ,d i ) and H(v a ,d n ) are the first, second, i-th and n-th state detection-reference signal fast query positioning factors in the set of state detection-reference signal fast query positioning factors, and F is the set of state detection-reference signal fast query positioning factors;

[0054] S13512, taking the state reference signal feature encoding vector corresponding to the minimum value in the set of the state detection-reference signal fast query positioning factor as the state reference signal positioning matching library feature vector. This process can be expressed by the following formula:

[0055]

[0056] Where D is the set of the state reference signal feature coding vectors, d i is the i-th state reference signal feature coding vector in the set of state reference signal feature coding vectors, H(v a ,d i ) is the i-th state detection-reference signal fast query positioning factor in the set of state detection-reference signal fast query positioning factors, argmin is the vector of the position where the minimum value is taken, d * Locating a matching library feature vector for a state reference signal;

[0057] S13513, determining the state reference signal fine-grained matching search window according to the state reference signal positioning matching library feature vector. This process can be expressed by the following formula:

[0058] W={d j-m / 2 ,d j-m / 2+1 ,...,d * ,...,d j+m / 2-1 ,d j+m / 2}

[0059]

[0060] Among them, d * Locate the matching library feature vector for the state reference signal, ||·|| 2 is the square of the vector norm, represents rounding down, m is the size of the state reference signal fine-grained matching search window, and W is the state reference signal fine-grained matching search window.

[0061] Specifically, in an embodiment of the present application, the vector at the center position of the state reference signal fine-grained matching search window is the state reference signal positioning matching library feature vector, and each state reference signal feature encoding vector in the state reference signal fine-grained matching search window is defined as a fine-grained query state reference signal feature vector.

[0062] It should be understood that the cross entropy of the state detection signal feature coding vector relative to each state reference signal feature coding vector is calculated to quantify the "distance" or "difference" between the two, and a set of state detection-reference signal fast query positioning factors is obtained. It should be understood that cross entropy is a commonly used measurement method that can reflect the distance between two distributions. The lower the cross entropy value, the higher the similarity between the two. This step aims to quickly screen out the closest state reference signal, thereby narrowing the scope of subsequent fine matching and improving efficiency. In particular, in the present technical solution, cross entropy is used as a key indicator to measure the difference in probability distribution between two vectors, which not only evaluates direct semantic similarity, but also implicitly captures context and semantic structure, improves retrieval efficiency and accuracy, and especially reduces computational burden in large-scale data sets.

[0063] Next, the state reference signal feature encoding vector corresponding to the minimum value in the set of state detection-reference signal fast query positioning factors is used as the state reference signal positioning matching library feature vector. That is, the state reference signal corresponding to the minimum value is considered to be the most similar to the current state detection signal. This operation helps to lock a preliminary best matching point and provide a basis for subsequent fine-grained analysis.

[0064] Then, a fine-grained matching search window is defined around the selected state reference signal positioning matching library feature vector to ensure that further analysis is concentrated in the most likely area and improve matching accuracy. In this way, more refined and in-depth feature matching and analysis can be performed within a relatively concentrated range that is highly correlated with the current detection signal, local subtle differences that may be ignored by a single vector comparison can be discovered, and the degree of fit between the current detection signal and the reference signal under normal working conditions at the feature level can be more comprehensively examined, thereby providing a richer and more detailed basis for more accurately judging the state of the LED display module.

[0065] Specifically, in step S1352, according to the state reference signal fine-grained matching search window, a fine-grained query response is performed on the state detection signal feature coding vector and each feature in the state reference signal fine-grained matching search window to obtain a state detection signal query response semantic coding vector, including: performing a linear transformation on the state detection signal feature coding vector to obtain a state detection signal query vector and a state detection signal value vector, and using each fine-grained query state reference signal feature vector in the state reference signal fine-grained matching search window as a key vector, inputting the state detection signal query vector, the state detection signal value vector and the key vector into a fine-grained query coding module based on a heterogeneous converter structure to obtain the state detection signal query response semantic coding vector, and the process can be expressed by the following formula:

[0066] v q =v a W q +b q

[0067] v v =v a W v +b v

[0068]

[0069] Among them, v a is the state detection signal feature encoding vector, m is the size of the state reference signal fine-grained matching search window, W q and b q is the state detection signal query embedding matrix and the state detection signal query bias vector, v q is the state detection signal query vector, W v and v b The state detection signal value embedding matrix and the state detection signal value bias vector, v v is the state detection signal value vector, d l is the lth fine-grained query state reference signal feature vector in the state reference signal fine-grained matching search window, is d l The transposed vector of d l Length, is matrix multiplication, softmax is the activation function, v r is the state detection signal query response semantic encoding vector.

[0070] Finally, the state detection signal feature coding vector is linearly transformed to obtain the state detection signal query vector and the state detection signal value vector, and each fine-grained query state reference signal feature vector is used as a key vector to input it into the fine-grained query coding module based on the heterogeneous converter structure so that the detection signal and the reference signal in the fine-grained matching search window can be deeply analyzed for feature interaction and semantic association, and the state detection signal query response semantic coding vector with rich semantic level understanding is obtained. In this way, from rough screening to fine-grained matching, and then to the final semantic coding, the matching accuracy and reliability are gradually improved, thereby ensuring that the state monitoring of the LED display module is both efficient and accurate.

[0071] In step S136, the working state detection result is obtained according to the semantic coding features of the state detection signal query response. Specifically, in an embodiment of the present application, the working state detection result is obtained according to the semantic coding features of the state detection signal query response, including: inputting the state detection signal query response semantic coding vector into a state detection module based on a classifier to obtain the working state detection result. That is, the state detection signal query response semantic coding features obtained by performing a fast semantic dynamic query using a set of the state detection signal feature coding vector and the state reference signal feature coding vector are classified and processed to intelligently obtain the working state detection result. In this way, normal and abnormal conditions can be accurately distinguished under various lighting conditions, reducing the possibility of misjudgment due to environmental factors. In addition, by introducing a pre-stored state reference signal and comparing its features, subtle differences can be identified, thereby more accurately judging the working state of the LED display module.

[0072] More specifically, in an embodiment of the present application, the state detection signal query response semantic coding vector is input into a state detection module based on a classifier to obtain the working state detection result, including: using the fully connected layer of the classifier to fully connect the state detection signal query response semantic coding vector to obtain the state detection signal query response semantic fully connected coding vector; inputting the state detection signal query response semantic fully connected coding vector into the Softmax classification function of the classifier to obtain the probability value of the optimized state detection signal query response semantic coding vector belonging to each classification label, the classification label including those for indicating a normal working state and those for indicating an abnormal normal working state; and determining the classification label corresponding to the largest of the probability values ​​as the working state detection result.

[0073] It should be understandable that, here, when the set of the state detection signal feature coding vector and the set of the state reference signal feature coding vector respectively represent the coding signal features of the state detection signal and the set of the state reference signal, when performing dynamic semantic query encoding based on the fast positioning mechanism, the misalignment of the source sample feature dynamic positioning mechanism will also cause the semantic query coding richness of the state detection signal query response semantic coding vector, resulting in repetition of unstructured probability mapping, affecting the accuracy of the classification results.

[0074] In a preferred example, inputting the state detection signal query response semantic coding vector into a classifier-based state detection module to obtain a working state detection result includes:

[0075] Determine the number of non-zero eigenvalues ​​in the state detection signal query response semantic coding vector, and subtract the number of non-zero eigenvalues ​​from the length of the state detection signal query response semantic coding vector to obtain a zero-dimensional value n of the state detection signal query response semantic coding;

[0076] Calculate the state detection signal query response semantic coding zero differentiable value (n-1) obtained by subtracting one from the state detection signal query response semantic coding zero-dimensional value by multiplying and dividing by the state detection signal query response semantic coding zero-dimensional value to obtain a first state detection signal query response semantic coding field fitting value (n-1)×n and a second state detection signal query response semantic coding field fitting value (n-1) / n;

[0077] Where n is the zero-dimensional value of the semantic encoding of the state detection signal query response;

[0078] Calculate the square root of the sum of squares of all eigenvalues ​​of the state detection signal query response semantic coding vector to obtain the state detection signal query response semantic coding mode representation value

[0079] Among them, v i is each feature value in the state detection signal query response semantic encoding vector;

[0080] Each eigenvalue v of the state detection signal query response semantic encoding vector is calculated using the zero differentiable value (n-1) of the state detection signal query response semantic encoding as an index. i The power function And multiply it by the first state detection signal query response semantic coding field fitting value (n-1)×n to obtain the state detection signal query response semantic coding local representation value v 1i ;

[0081] Among them, v 1i Yes iThe corresponding state detection signal query response semantic encoding local representation value;

[0082] Calculate each eigenvalue v of the state detection signal query response semantic encoding vector i The product of the second state detection signal query response semantic coding field fitting value (n-1) / n and the state detection signal query response semantic coding mode representation value α is obtained to obtain the state detection signal query response semantic coding center pointing value v 2i ;

[0083] Among them, v 2i Yes i The corresponding state detection signal query response semantic encoding center pointing value;

[0084] The state detection signal query response semantic encoding local representation value v 1i The state detection signal query response semantic encoding center points to the value v 2i The weighted difference v 12i =w1v 1i -w2v 2i Composing an optimized state detection signal query response semantic encoding vector;

[0085] Among them, v 12i Yes i The corresponding optimized eigenvalue, i.e., the eigenvalue of the i-th position in the optimized state detection signal query response semantic encoding vector;

[0086] The optimized state detection signal query response semantic coding vector is input into a classifier-based state detection module to obtain a working state detection result.

[0087] Therefore, based on the vector field fitting law of high-dimensional manifolds, the isolated zeros in the state detection signal query response semantic coding vector are used as the differentiable dimension of the high-dimensional manifold, so as to fix the normal direction pointing to the distribution center near the local coordinates represented by the eigenvalues ​​of the state detection signal query response semantic coding vector. In this way, the invalid repetition in the probability mapping process caused by the unstructured characteristics of the semantically rich distribution of the state detection signal query response semantic coding vector is avoided by effectively aligning the characteristic distribution pattern of the state detection signal query response semantic coding vector to the probability density differentiable field, thereby improving the accuracy of the working state detection result obtained by inputting the classifier-based state detection module.

[0088] In summary, step S130 is explained, which obtains a state detection signal, and extracts a set of state reference signals marked as normal working states from the background database, uses AI-based data analysis and encoding to extract signal features from the state detection signal, and extracts signal features from each state reference signal marked as a normal working state, thereby intelligently obtaining the working state detection result based on the fast positioning semantic query representation between the state detection signal feature and each state reference signal feature. The present application can accurately distinguish between normal and abnormal conditions under various lighting conditions, reducing the possibility of misjudgment due to environmental factors. And by introducing pre-stored state reference signals and comparing their features, subtle differences can be identified, thereby more accurately judging the working state of the LED display module.

[0089] Specifically, in step S140, in response to the working state detection result being a normal working state, a transmission control instruction for starting image signal transmission issued by a target application of the terminal device is received. It should be understood that once it is confirmed that the LED display module is working properly, the control box will wait for a control instruction issued by a target application on the terminal device (such as a smart phone, tablet computer, etc.), which is used to start the image signal transmission mode and prepare to transmit the content of the terminal device to the LED display module.

[0090] At this stage, the control system maintains a real-time connection with the terminal device (such as a smartphone, tablet or computer), waiting for the target application to send specific control instructions. These terminal devices usually run specially designed applications that allow users to select the content to be displayed through a graphical interface and set related parameters such as resolution and refresh rate. In order to ensure smooth and secure communication, a set of predefined communication protocols are used between the control system and the terminal device, which stipulates details such as the format of the data packet, the transmission method, and the error handling mechanism. For example, they may use a TCP / IP-based network protocol stack to establish a stable data connection through Wi-Fi or Ethernet; or use Bluetooth low energy (BLE) technology to achieve short-range wireless communication. In either case, both parties will follow the same rules to ensure the accuracy and consistency of information transmission.

[0091] When the user selects the content to be displayed on the terminal device and clicks the "Send" button, the target application generates a data packet containing the transmission control instructions. This data packet not only contains the command to start the transmission of the image signal, but also includes a series of necessary configuration information, such as image size, color mode, playback speed, etc. In addition, in order to improve the flexibility and adaptability of the system, the data packet can also carry some additional instructions, such as whether to enable automatic brightness adjustment, whether there are specific areas that need to be rendered in detail, etc. All of this information is carefully encoded into a binary format so that it can be quickly and reliably transmitted to the control system through the selected communication channel.

[0092] Once a complete data packet is received, the control system will first verify the content to ensure that it conforms to the expected format and is not damaged. This step is critical because it is directly related to the safety and effectiveness of subsequent operations. To this end, the control system checks the checksum (such as CRC) of the data packet and compares it with the standard template stored locally, and then continues processing after confirmation. If any abnormality is found, the control system will immediately return an error report to the terminal device, prompting the user to resend or adjust the settings. Only when the verification is passed will the control system officially accept the transmission control instruction and include it in the execution queue.

[0093] Specifically, in step S150, according to the transmission control instruction, the display content of the terminal device is transmitted to the LED display module for display. Accordingly, after receiving the instruction to start the image signal transmission, the control box starts to transmit the display content of the terminal device (such as pictures, videos or other information on the screen) to the LED display module, so that it can display these contents synchronously.

[0094] After receiving the transmission control instruction, the control system will first parse the specific parameters contained in the instruction, such as image size, color mode, playback speed, etc. These parameters determine the subsequent image processing method and the final presentation effect. For example, if the user selects a high-resolution picture or video file, the control system may pre-allocate more computing resources to ensure a smooth visual experience; if it is low-resolution content, the processing priority can be appropriately lowered to save energy. In addition, the instruction may also carry some additional information, such as whether to enable automatic brightness adjustment, whether there are specific areas that need to be rendered, etc. This information will be taken into consideration by the control system to achieve a more personalized display effect.

[0095] Next, the control system activates the internal image processing unit, loads the corresponding decoder and driver, and prepares to pre-process the image data to be received. This process includes but is not limited to a series of operations such as format conversion, color correction, denoising, and sharpening, which aims to improve image quality while ensuring that it meets the technical requirements of the LED display module. For dynamic video content, the control system also applies frame rate matching technology to coordinate the playback speed with the refresh rate of the LED display module to avoid screen tearing or stuttering. In order to adapt to different types of input signal sources, the control system supports a variety of standard and proprietary encoding formats (such as JPEG, PNG, H.264, HEVC, etc.), and converts them into a unified internal representation through a built-in decoder.

[0096] Once the preparations are completed, the control system officially starts the image signal transmission mode. At this point, it will gradually convert the image content on the terminal device into a format suitable for the output of the LED display module according to the parameters specified in the transmission control instruction, and send it out through a high-speed interface (such as HDMI, DisplayPort, etc.) or wireless transmission technology (such as Miracast, AirPlay, etc.). During the entire transmission process, the control system continuously monitors the status of the data stream to ensure that each pixel can be accurately presented on the screen. In order to further optimize performance, the control system may apply some advanced image processing technologies, such as edge enhancement, contrast adjustment, color saturation optimization, etc., to improve the final display quality.

[0097] In order to ensure that the image content can be perfectly reproduced on the LED display module, the control system will also make corresponding adjustments based on the current working environment (such as temperature, humidity, etc.). For example, operation in a high temperature environment may cause some components to age faster. The control system can maintain the best working condition by adjusting the fan speed or other heat dissipation measures; under high humidity conditions, moisture-proof protection measures need to be taken to prevent short circuit risks. In addition, the control system can also monitor the working status of the LED display module in real time, such as changes in electrical parameters such as voltage and current, and promptly detect potential problems and issue early warning prompts to ensure long-term stable operation.

[0098] When the image data is successfully transmitted to the LED display module, the latter will immediately start its own display engine and convert the received information into a visual image output. During this process, the circuit components inside the LED display module (such as LED lamp beads, driver chips, etc.) will accurately control the brightness and color of each light-emitting unit according to the instructions provided by the control system, thereby presenting a clear and vivid picture effect. In order to achieve the best display effect, the LED display module is also equipped with advanced optical design, such as evenly distributed backlight sources, efficient light diffusion plates, etc., to ensure that the entire screen surface presents consistent brightness and color.

[0099] In summary, the method of the LED display module based on the embodiment of the present application is explained, which first sends a detection signal to the LED display module, and the module performs a display mode test after receiving the signal to generate a status detection signal. The system analyzes these signals to determine whether the module is in a normal working state. If the test result is normal, the system will receive a transmission control instruction from the terminal device application, start the image signal transmission mode, and transmit the display content of the terminal device to the LED display module for display. The effect of this process is to improve the reliability and stability of the LED display module, ensure the accuracy and timeliness of the displayed content, and enhance the user experience.

[0100] According to an LED display module of an embodiment of the present application, the LED display module is used to execute the above-mentioned LED display module method.

[0101] Here, those skilled in the art can understand that the specific operations of each step in the above LED display module have been described in the above reference. Figures 1 to 4 The method of the LED display module has been described in detail, and therefore, its repeated description will be omitted.

[0102] As described above, the LED display module 100 according to the embodiment of the present disclosure can be implemented in various wireless terminals, such as a server having an algorithm of the LED display module. In a possible implementation, the LED display module 100 according to the embodiment of the present disclosure can be integrated into the wireless terminal as a software module and / or a hardware module. For example, the LED display module 100 can be a software module in the operating system of the wireless terminal, or can be an application developed for the wireless terminal; of course, the LED display module 100 can also be one of the many hardware modules of the wireless terminal.

[0103] Alternatively, in another example, the LED display module 100 and the wireless terminal may also be separate devices, and the LED display module 100 may be connected to the wireless terminal via a wired and / or wireless network, and transmit interactive information in accordance with an agreed data format.

[0104] The above is merely an example of the principles of the present disclosure, and various modifications may be made by those skilled in the art without departing from the scope of the present disclosure. The above embodiments are presented for the purpose of illustration rather than limitation. The present disclosure may also take many forms other than those explicitly described herein.

Claims

1. A method for LED display module, characterized in that: include: Sending a detection signal to the LED display module; The LED display module receives the detection signal and performs a display mode test to obtain a status detection signal; Analyzing the state detection signal to determine the working state detection result of the LED display module; in response to the working state detection result being a normal working state, receiving a transmission control instruction for starting image signal transmission issued by a target application of a terminal device; and transmitting the display content of the terminal device to the LED display module for display according to the transmission control instruction; wherein analyzing the state detection signal to determine the working state detection result of the LED display module includes: Acquiring the status detection signal; Extracting a set of state reference signals marked as normal working states from a background database; Extracting a signal feature from the state detection signal to obtain a state detection signal feature; Extracting signal features from each state reference signal marked as being in a normal working state in the set of state reference signals marked as being in a normal working state to obtain a set of state reference signal features; Performing a fast positioning semantic dynamic query on the set of the state detection signal feature and the state reference signal feature to obtain a state detection signal query response semantic coding feature; The working status detection result is obtained by querying the response semantic coding feature according to the status detection signal.

2. The method of LED display module according to claim 1, characterized in that: Extracting signal features from the state detection signal to obtain a state detection signal feature includes: using a state signal feature extractor based on a deep separable convolutional network to process the state detection signal to obtain a state detection signal feature encoding vector as the state detection signal feature.

3. The method of LED display module according to claim 2, characterized in that: Extracting signal features from each state reference signal marked as being in a normal working state in the set of state reference signals marked as being in a normal working state to obtain a set of state reference signal features, comprising: using the state signal feature extractor based on a deep separable convolutional network to process each state reference signal marked as being in a normal working state in the set of state reference signals marked as being in a normal working state to obtain a set of state reference signal feature encoding vectors as the set of state reference signal features.

4. The method of LED display module according to claim 3, characterized in that: Performing a fast positioning semantic dynamic query on the set of the state detection signal feature and the state reference signal feature to obtain a state detection signal query response semantic coding feature, including: Determine a state reference signal fine-grained matching search window according to a set of the state detection signal feature coding vector and the state reference signal feature coding vector; According to the state reference signal fine-grained matching search window, a fine-grained query response is performed on the state detection signal feature coding vector and each feature within the state reference signal fine-grained matching search window to obtain a state detection signal query response semantic coding vector as the state detection signal query response semantic coding feature.

5. The method of LED display module according to claim 4, characterized in that: Determining a state reference signal fine-grained matching search window according to a set of the state detection signal feature coding vector and the state reference signal feature coding vector, comprising: Calculating the cross entropy of the state detection signal feature coding vector relative to each state reference signal feature coding vector in the set of state reference signal feature coding vectors to obtain a set of state detection-reference signal fast query positioning factors; The state reference signal feature encoding vector corresponding to the minimum value in the set of the state detection-reference signal fast query positioning factor is used as the state reference signal positioning matching library feature vector; The state reference signal fine-grained matching search window is determined according to the state reference signal positioning matching library feature vector.

6. The method of LED display module according to claim 5, characterized in that: The vector at the center position of the state reference signal fine-grained matching search window is the state reference signal positioning matching library feature vector, and each state reference signal feature encoding vector in the state reference signal fine-grained matching search window is defined as a fine-grained query state reference signal feature vector.

7. The method of LED display module according to claim 6, characterized in that: According to the state reference signal fine-grained matching search window, a fine-grained query response is performed on the state detection signal feature coding vector and each feature within the state reference signal fine-grained matching search window to obtain a state detection signal query response semantic coding vector, including: performing a linear transformation on the state detection signal feature coding vector to obtain a state detection signal query vector and a state detection signal value vector, and using each fine-grained query state reference signal feature vector in the state reference signal fine-grained matching search window as a key vector, and inputting the state detection signal query vector, the state detection signal value vector and the key vector into a fine-grained query coding module based on a heterogeneous converter structure to obtain the state detection signal query response semantic coding vector.

8. The method of LED display module according to claim 7, characterized in that: Obtaining the working status detection result according to the state detection signal query response semantic coding feature includes: inputting the state detection signal query response semantic coding vector into a classifier-based state detection module to obtain the working status detection result.

9. An LED display module, characterized in that: The LED display module is used to execute the LED display module method as described in claims 1-8.

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