Master control board efficient detection method and device

Abstract

The application relates to the field of detection, in particular to a master control board efficient detection method and device, wherein the method can determine all hair cutting conditions through known hair quality states, thereby constructing a condition conversion chain for guiding condition conversion, reasonably judging each condition conversion chain, excluding unreasonable condition conversion chains, and then constructing a condition conversion matrix from the condition conversion chains with high reasonability, and regulating the condition signals injected into the master control board according to the condition changes in the condition conversion matrix, which can detect the performance of the master control board in specific hair cutting conditions and the performance of the master control board in condition conversion, so that the master control board can be fully detected to accurately represent the performance of the master control board.

Description

Technical Field

[0001] This invention relates to the field of testing, and in particular to a method and apparatus for high-efficiency testing of a main control board. Background Technology

[0002] As the core control component of the electric hair clipper, the main control board has the functions of receiving and processing information and issuing instructions, coordinating all components of the equipment to work in an orderly manner, and acting as the 'brain' in the electric hair clipper process. Therefore, the performance of the electric hair clipper main control board needs to be tested during the production process. Current performance testing of electric hair clipper control boards primarily involves inputting simulated operating condition signals and observing the response of the control board's output terminals (relays, indicator lights) to verify the logic control function. However, current simulated operating condition signals used in testing control boards mainly involve manually setting signal parameters for several extreme operating conditions (e.g., setting extremely high torque resistance for thick, dense hair), and then injecting these extreme operating condition signals into the control board under test to assess its handling performance. The signal setting logic is mainly to ensure that the control board can handle extreme conditions smoothly, and also handle other non-extreme conditions smoothly. However, in actual haircutting processes, due to the different hair types... Hair quality varies across different sections of the head, and the path a barber uses when applying electric clippers often crosses these sections, leading to sudden changes in operating conditions. In such cases, even without extreme hair quality conditions, the main control board may not respond promptly or slowly, causing problems such as hair jamming or short circuits. Furthermore, due to the uncertainty of hair quality distribution and the path the barber uses to apply the clippers, the probability of various sudden changes in operating conditions varies. Therefore, the current method of setting up simulated operating condition signals is insufficient to fully simulate potential sudden changes in operating conditions, resulting in incomplete test results and an inability to accurately characterize the performance of the main control board. Summary of the Invention

[0003] Therefore, it is necessary to provide a method and device for efficient detection of the main control board to address the above problems.

[0004] The present invention is implemented as follows: a high-efficiency detection method for a main control board, the method comprising: S1: Obtain all known hair texture states, where the hair texture parameters are not exactly the same for different hair texture states; S2: Determine all hair-cutting procedures based on the condition of each hair type; S3: Determine the probability distribution of hair quality status in each head section and all potential haircutting paths that cross the head section based on haircutting statistics; S4: Construct all the transition chains for each hairdressing condition to define the sequence of changes for each hairdressing condition; S5: For each work condition transition chain, determine the rationality of the change sequence represented by the constructed work condition transition chain based on the potential haircutting path and the probability distribution of hair quality status. S6: Determine if the reasonableness is higher than the set value. If so, retain the working condition transition chain; otherwise, exclude the working condition transition chain. S7: Construct a working condition transformation matrix based on the retained working condition transformation chain; S8: When the initial haircutting condition is received, the haircutting condition is transformed based on the initial haircutting condition and the condition transformation matrix. At each haircutting condition transformation, the corresponding condition signal is injected into the main control board to detect the performance of the main control board.

[0005] In one embodiment, the present invention provides a high-efficiency detection device for a main control board, the device comprising: The acquisition module is used to acquire all known hair quality states, where the hair quality parameters are not exactly the same for different hair quality states; The first processing module is used to determine all hair-cutting conditions based on the hair quality. The second processing module is used to determine the probability distribution of hair quality status in each head section and all potential haircutting paths that cross the head section based on haircutting statistics. The third processing module is used to construct all the condition transition chains based on each hairdressing condition, so as to define the change sequence of each hairdressing condition; The fourth processing module is used to determine the rationality of the change sequence represented by the constructed working condition transition chain for each working condition transition chain based on the probability distribution of potential haircutting paths and hair quality status. The judgment module is used to determine whether the reasonableness is higher than the set value. If so, the working condition transition chain is retained; otherwise, the working condition transition chain is excluded. The fifth processing module is used to construct a working condition transformation matrix based on the retained working condition transformation chain; The testing module is used to transform the hairdressing conditions based on the initial hairdressing conditions and the condition transformation matrix when the initial hairdressing conditions are received. At each time the hairdressing conditions are transformed, the module injects the condition signal corresponding to the adjusted hairdressing conditions into the main control board to detect the performance of the main control board.

[0006] This invention provides a high-efficiency detection method and apparatus for a main control board. The method includes: acquiring all known hair quality states; determining all hair-cutting conditions based on each hair quality state; determining the probability distribution of hair quality states in each head section and all potential hair-cutting paths crossing head sections based on hair-cutting statistics; constructing all condition transition chains based on each hair-cutting condition to define the change order of each hair-cutting condition; for each condition transition chain, determining the rationality of the change order represented by the constructed condition transition chain based on the potential hair-cutting paths and the probability distribution of hair quality states; judging whether the rationality is higher than a set value; if so, retaining the condition transition chain; otherwise, excluding the condition transition chain; constructing a condition transition matrix based on the retained condition transition chains; and when receiving an input initial hair-cutting condition, based on the initial hair-cutting condition... The system uses a working condition conversion matrix to switch between hair-cutting working conditions. Each time a hair-cutting working condition is switched, a working condition signal corresponding to the adjusted working condition is injected into the main control board to detect the main control board's performance. In this application, all hair-cutting working conditions can be determined based on known hair quality, thereby constructing a working condition conversion chain to guide changes in working conditions. The rationality of each working condition conversion chain is judged, and unreasonable working condition conversion chains are eliminated. The working condition conversion chains with high rationality are then constructed into a working condition conversion matrix. The working condition signal injected into the main control board is adjusted based on the changes in working conditions within the working condition conversion matrix. This allows for the detection of the main control board's performance under specific hair-cutting working conditions as well as its performance during working condition transitions, thus enabling comprehensive and thorough detection of the main control board to accurately characterize its performance. Attached Figure Description

[0007] Figure 1 A flowchart of a high-efficiency detection method for a main control board provided in one embodiment; Figure 2 This is an application environment diagram of a high-efficiency detection method for a main control board provided in one embodiment; Figure 3 This is a schematic diagram of the header partition of a high-efficiency detection method for a main control board provided in one embodiment; Figure 4 This is a module flowchart of a high-efficiency detection method for a main control board provided in one embodiment; Figure 5 This is a block diagram of the internal structure of a computer device in one embodiment. Detailed Implementation

[0008] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0009] It is understood that the terms "first," "second," etc., used in this invention may be used to describe various elements herein, but unless specifically stated otherwise, these elements are not limited by these terms. These terms are used only to distinguish one element from another. For example, without departing from the scope of this invention, a first script may be referred to as a second script, and similarly, a second script may be referred to as a first script.

[0010] like Figure 1 As shown, in one embodiment, a high-efficiency detection method for the main control board is proposed, the method comprising: S1: Obtain all known hair texture states, where the hair texture parameters are not exactly the same for different hair texture states; S2: Determine all hair-cutting procedures based on the condition of each hair type; S3: Determine the probability distribution of hair quality status in each head section and all potential haircutting paths that cross the head section based on haircutting statistics; S4: Construct all the transition chains for each hairdressing condition to define the sequence of changes for each hairdressing condition; S5: For each work condition transition chain, determine the rationality of the change sequence represented by the constructed work condition transition chain based on the potential haircutting path and the probability distribution of hair quality status. S6: Determine if the reasonableness is higher than the set value. If so, retain the working condition transition chain; otherwise, exclude the working condition transition chain. S7: Construct a working condition transformation matrix based on the retained working condition transformation chain; S8: When the initial haircutting condition is received, the haircutting condition is transformed based on the initial haircutting condition and the condition transformation matrix. At each haircutting condition transformation, the corresponding condition signal is injected into the main control board to detect the performance of the main control board.

[0011] In this embodiment, as Figure 2 As shown, this method is executed in a computer device, which can be an independent physical server or terminal, or a server cluster consisting of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud servers, cloud databases, cloud storage, and CDN. The computer device is connected to a logic analyzer and a signal generator, and the logic analyzer and signal generator are respectively connected to the main control board under test. Thus, the computer device can control the signal generator to inject the working condition signal corresponding to the hairdressing working condition into the main control board, and analyze the response signal of the main control board after receiving the working condition signal through the logic analyzer. Based on the analysis data of the logic analyzer, the computer device can deduce the performance of the main control board, thereby completing the test.

[0012] In this embodiment, known hair quality conditions are saved by staff to a cloud database, enabling computer devices to access them promptly; such as Figure 3 As shown, the head is divided into sections by the testing personnel based on the general distribution of human hair, such as the crown, forehead, sides, occipital region, and nape. Hair quality within the same section is generally similar, while hair quality in different sections often differs. Each hair quality corresponds to a hairdressing condition, which is the torque load associated with that condition. There are n sets of hairdressing statistics (e.g., 100 sets), each collected during a haircut for a customer, including the customer's hair quality parameters and the hairdresser's cutting path. Hair quality parameters can be detected using a scalp detector. Scanning methods include close-range scanning (…). The system employs both long-range and short-range scanning (1-2cm from the scalp) to capture images of the entire head, allowing for the determination of the head's overall size and the identification of the length of different sections (if some sections are obscured, the hairdresser can move the hair to make identification). Short-range scanning captures images of the scalp and hair roots, enabling the identification of hair density and diameter in those areas, thus determining the hair quality parameters of different sections of the head. During the haircut, a high-definition camera captures video of the hairdresser pushing the clippers, revealing the path the hairdresser takes to cut the hair. In this embodiment, the working condition transition chain is a sequence of multiple hairdressing working conditions linked together, used to guide the computer equipment to apply analog signals to the main control board according to the order of the working conditions in the working condition transition chain; the probability distribution of hair quality can characterize the probability distribution of hairdressing working conditions, and the potential hairdressing path can characterize the hairdresser's cutting habits and their probability of occurrence. Based on these two factors, the rationality of the constructed working condition transition chain can be accurately evaluated to exclude working condition transition situations that are difficult to occur in reality, so as to ensure that the change order of hairdressing working conditions represented by the working condition transition chain conforms to reality, thereby achieving a high degree of simulation in the detection. In this application, all hair-cutting conditions can be determined based on known hair quality, thereby constructing a condition transition chain to guide condition changes. The rationality of each condition transition chain is judged, irrational chains are eliminated, and highly rational chains are constructed into a condition transition matrix. The condition signals injected into the main control board are adjusted based on the condition changes in the transition matrix. This allows for the detection of the main control board's performance under specific hair-cutting conditions (i.e., performance before condition transition) as well as its performance during condition transitions, thus enabling comprehensive and thorough detection of the main control board to accurately characterize its performance.

[0013] In a preferred embodiment, the hair quality parameters include average diameter, average length, and average density; the hair cutting condition is the torque load; all hair cutting conditions are determined based on each hair quality condition, that is, the corresponding hair cutting condition is determined based on each acquired hair quality condition; the corresponding hair cutting condition is calculated for each acquired hair quality condition using the following formula: in, For torque load, and These are the fitting coefficients. For average length, For average density, The average diameter is denoted as .

[0014] In this embodiment, each hair quality parameter includes several parameter ranges, such as hair length 0~0.5cm, 0.5~1cm, 1~2cm, etc., which are divided into several length parameter ranges. If the average lengths corresponding to two hair quality states are in the same length parameter range, the two hair quality states can be regarded as the same in terms of length. If multiple hair quality states are regarded as the same in all three hair quality parameters, then only one hair quality state needs to be selected. In this embodiment, It is 0.02. The value is 0.005. The prediction model for torque load is obtained by conducting multiple experiments in advance and fitting the experimental data. For example, select multiple hair samples with different feature combinations (which can be wigs), use electric clippers to cut the samples to obtain the output torque that just cuts them, and then derive the torque load based on the output torque and transmission efficiency. This yields the correspondence between multiple hair sample features and torque loads, and then linear fitting is performed to obtain the prediction model for torque load.

[0015] In a preferred embodiment, the number of known hair quality states is q; there are n sets of haircut statistics data, each set of haircut statistics data includes the hair quality state of each head section, and the corresponding hairdresser's several haircutting paths; Determining the probability distribution of hair quality status in each head section includes: S31: Select a header partition; S32: For each hair type, calculate the probability of that hair type being distributed across a specific section of the head using the following formula: in, This represents the probability of this hair quality condition being distributed across a specific area of ​​the head. This represents the number of times this hair quality condition occurs in this section of the head. S33: Repeat steps S31 to S32 until the probability of each hair quality state being distributed in each head section is obtained; Identifying all potential haircutting paths that cross the head section includes: Determine the number of head sections that each haircut path passes through, and exclude haircut paths that pass through only one head section. The remaining haircutting paths in each set of barber behavior statistics are aggregated into a potential haircutting path set, where the number of potential haircutting paths included in the potential haircutting path set is r.

[0016] Based on each hairdressing work condition, all work condition transition chains are constructed, including: Determine the threshold m of the number of head sections that a haircut path can pass through; Determine the arrangement of all hair texture states, where the number of arrangements is... ; For each obtained hair quality state arrangement, the hair quality states are connected in series according to the order of the arrangement to obtain the corresponding working condition conversion chain.

[0017] In this embodiment, the threshold m for the number of head sections that a haircutting path can pass through can be determined by first determining the number of head sections that each haircutting path passes through, and then determining the maximum number as the threshold m. When the length of the condition transition chain reaches m, the haircutting path can be simulated most comprehensively. It can simulate both long and short paths (short paths can be regarded as a local segment of the condition transition chain). The hair quality status arrangement takes into account the different haircutting conditions of the haircutting path and the different order of the haircutting conditions, that is, it can reflect the changing order of all possible haircutting conditions.

[0018] As a preferred embodiment, the rationality of determining the sequence of changes represented by the constructed condition transition chain based on the probability distribution of potential haircutting paths and hair quality states includes: Select a working condition transition chain; Each pair of adjacent hairdressing conditions in the work condition transition chain is identified as a transition group, resulting in m-1 transition groups; For each conversion group, determine the contribution of that conversion group to the reasonableness. The rationality of the change sequence represented by the working condition transition chain is obtained by summing the contributions of each transition group to the rationality.

[0019] The contribution of this conversion group to the reasonableness is determined by: Determine the hairdressing conditions of the head regions traversed by each potential hairdressing path in the set of potential hairdressing paths; The conversion group is compared one by one with the potential haircut paths in the potential haircut path set to determine all matching haircut paths in the haircut path set. Among them, there are two adjacent head partitions in the head partitions traversed by the matching haircut path. The haircut conditions corresponding to these two adjacent head partitions are consistent with the haircut conditions in the conversion group and are in the same order. Calculate the ratio of the number of matching haircut paths to the total number of potential haircut paths. ,in, To match the number of haircut paths, The total number of potential haircut routes; For each matched haircut path, determine the probability that the corresponding haircut condition in the conversion group appears in the two matched head partitions traversed by the matched haircut path. , Calculate the overall probability ; The contribution of this conversion group to the rationality score is calculated using the following formula: in, This is the contribution of the conversion group to the rationality.

[0020] Reasonableness is calculated using the following formula: in, For the sake of reasonableness, Adjustment coefficient for reasonableness.

[0021] In this embodiment, for example, a work condition transition chain includes five hairdressing work conditions: A, B, C, D, and E, denoted as ABCDE, which includes four transition groups: AB, BC, CD, and DE. In this embodiment, since each set of haircut statistics includes the hair quality status of each head section and several haircutting paths of the corresponding hairdresser, the actual hair quality status of the head sections traversed by each potential haircutting path and the corresponding haircutting conditions can be determined. This allows for comparison of the actual haircutting condition sequence corresponding to the potential haircutting path with the haircutting conditions of the conversion group to determine the matching haircutting path. For example, for conversion group AB, if the haircutting condition sequence corresponding to a potential haircutting path is CABE, which includes AB, then this potential haircutting path is the matching haircutting path. The probability of the corresponding haircutting conditions in the conversion group appearing in the two matched head sections is... This is the probability that hairdressing condition A appears in the head partition corresponding to hairdressing condition A along the matched hairdressing path. That is, the probability that hairdressing condition B appears in the head partition corresponding to hairdressing condition B traversed by the matched hairdressing path; In this embodiment, The probability of the hairdressing conditions corresponding to the conversion group was determined from the perspective of hair distribution. This determines the probability of the hairdressing conditions corresponding to the conversion group from the perspective of the barber's operating habits. Combining these two probabilities can accurately reflect the overall probability of the hairdressing conditions corresponding to the conversion group, that is, the contribution value of the conversion group to the rationality; in addition, the rationality adjustment coefficient It can be set to 10 2 The setting value can be set to 70%; As a preferred embodiment, the operating condition transition chain is represented as follows: in, For operating condition transition chain, Let j be the j-th hairdressing condition in the condition transition chain, and m be the number of hairdressing conditions in the condition transition chain. The operating condition transformation matrix is ​​represented as follows: in, This is the operating condition transformation matrix. Let y be the kth working condition transition chain, and y be the number of working condition transition chains.

[0022] Based on the initial hairdressing conditions and the condition transformation matrix, the hairdressing conditions are transformed, and at each transformation, the corresponding condition signal for the adjusted hairdressing condition is injected into the main control board, including: Determine the working condition transition chain based on the initial hairdressing working condition in the working condition transition matrix; Locate the initial haircutting condition in the condition transition chain to determine the subsequent haircutting conditions. The haircutting conditions are switched one by one according to the determined sequence, and the corresponding condition signal is injected into the main control board at each switch.

[0023] In this embodiment, each row of the condition transition matrix represents a condition transition chain, thus presenting all condition transition chains with high rationality. The initial hairdressing condition can be a specific extreme condition input by the staff. After receiving the extreme condition, the computer device displays the condition transition chain including that condition in the condition transition matrix, and then performs detection based on each condition transition chain. When performing detection based on each condition transition chain, the signal can be injected from the starting condition of the condition transition chain, or the signal can be injected directly from the extreme condition (i.e., discarding the previous hairdressing condition). Each time a condition signal is injected, it is held for 10 seconds (or other duration) before transitioning to the next condition. The performance of the main control board under the specific condition can be detected during the condition holding period, and the performance of the main control board during the condition transition period can be detected during the condition transition period. In addition, the initial condition can be injected multiple times (each initial condition is different) to further improve the comprehensiveness of the detection.

[0024] like Figure 4 As shown, in one embodiment, a high-efficiency detection device for a main control board is provided, the device comprising: The acquisition module is used to acquire all known hair quality states, where the hair quality parameters are not exactly the same for different hair quality states; The first processing module is used to determine all hair-cutting conditions based on the hair quality. The second processing module is used to determine the probability distribution of hair quality status in each head section and all potential haircutting paths that cross the head section based on haircutting statistics. The third processing module is used to construct all the working condition transformation chains based on each hairdressing working condition, so as to define the change sequence of each hairdressing working condition; The fourth processing module is used to determine the rationality of the change sequence represented by the constructed working condition transition chain for each working condition transition chain based on the probability distribution of potential haircutting paths and hair quality status. The judgment module is used to determine whether the reasonableness is higher than the set value. If so, the working condition transition chain is retained; otherwise, the working condition transition chain is excluded. The fifth processing module is used to construct a working condition transformation matrix based on the retained working condition transformation chain; The testing module is used to transform the hairdressing conditions based on the initial hairdressing conditions and the condition transformation matrix when the initial hairdressing conditions are received. At each time the hairdressing conditions are transformed, the module injects the condition signal corresponding to the adjusted hairdressing conditions into the main control board to detect the performance of the main control board.

[0025] In this embodiment, the process by which each module in the high-efficiency detection device of the main control board provided in this application implements its respective function can be specifically referred to the foregoing. Figure 1 The description of the illustrated embodiment will not be repeated here.

[0026] Figure 5 An internal structural diagram of a computer device in one embodiment is shown. Figure 5 As shown, the computer device includes a processor, memory, network interface, input device, and display screen connected via a system bus. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and may also store a computer program. When executed by the processor, this computer program enables the processor to implement the efficient main control board detection method provided in this embodiment of the invention. The internal memory may also store a computer program, which, when executed by the processor, enables the processor to execute the efficient main control board detection method provided in this embodiment of the invention. The display screen of the computer device can be a liquid crystal display (LCD) or an electronic ink display. The input device of the computer device can be a touch layer covering the display screen, or buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse, etc.

[0027] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the computer device to which the present invention is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0028] In one embodiment, the high-efficiency detection device for the main control board provided by this invention can be implemented as a computer program, which can be implemented in the form of, for example... Figure 5 The computer device shown runs on this device. The computer device's memory can store the various program modules that make up the main control board's high-efficiency detection device, for example... Figure 4 The diagram shows an acquisition module, a first processing module, a second processing module, a third processing module, a fourth processing module, a judgment module, a fifth processing module, and a testing module. The computer program comprised of these modules causes the processor to execute the steps in the efficient detection method for the main control board of the various embodiments of the present invention described in this specification.

[0029] For example, Figure 5 The computer equipment shown can be used as follows Figure 4 The acquisition module in the high-efficiency detection device of the main control board shown executes step S1; the computer device can execute step S2 through the first processing module; the computer device can execute step S3 through the second processing module; the computer device can execute step S4 through the third processing module; the computer device can execute step S5 through the fourth processing module; the computer device can execute step S6 through the judgment module; the computer device can execute step S7 through the fifth processing module; and the computer device can execute step S8 through the test module.

[0030] In one embodiment, a computer device is provided, the computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, performs the following steps: S1: Obtain all known hair texture states, where the hair texture parameters are not exactly the same for different hair texture states; S2: Determine all hair-cutting procedures based on the condition of each hair type; S3: Determine the probability distribution of hair quality status in each head section and all potential haircutting paths that cross the head section based on haircutting statistics; S4: Construct all the transition chains for each hairdressing condition to define the sequence of changes for each hairdressing condition; S5: For each work condition transition chain, determine the rationality of the change sequence represented by the constructed work condition transition chain based on the potential haircutting path and the probability distribution of hair quality status. S6: Determine if the reasonableness is higher than the set value. If so, retain the working condition transition chain; otherwise, exclude the working condition transition chain. S7: Construct a working condition transformation matrix based on the retained working condition transformation chain; S8: When the initial haircutting condition is received, the haircutting condition is transformed based on the initial haircutting condition and the condition transformation matrix. At each haircutting condition transformation, the corresponding condition signal is injected into the main control board to detect the performance of the main control board.

[0031] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, causes the processor to perform the following steps: S1: Obtain all known hair texture states, where the hair texture parameters are not exactly the same for different hair texture states; S2: Determine all hair-cutting procedures based on the condition of each hair type; S3: Determine the probability distribution of hair quality status in each head section and all potential haircutting paths that cross the head section based on haircutting statistics; S4: Construct all the transition chains for each hairdressing condition to define the sequence of changes for each hairdressing condition; S5: For each work condition transition chain, determine the rationality of the change sequence represented by the constructed work condition transition chain based on the potential haircutting path and the probability distribution of hair quality status. S6: Determine if the reasonableness is higher than the set value. If so, retain the working condition transition chain; otherwise, exclude the working condition transition chain. S7: Construct a working condition transformation matrix based on the retained working condition transformation chain; S8: When the initial haircutting condition is received, the haircutting condition is transformed based on the initial haircutting condition and the condition transformation matrix. At each haircutting condition transformation, the corresponding condition signal is injected into the main control board to detect the performance of the main control board.

[0032] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0033] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0034] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0035] The embodiments described above are merely examples of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

Claims

1. A method for efficient detection of a main control board, characterized in that, The method includes: S1: Obtain all known hair texture states, where the hair texture parameters are not exactly the same for different hair texture states; S2: Determine all hair-cutting procedures based on the condition of each hair type; S3: Determine the probability distribution of hair quality status in each head section and all potential haircutting paths that cross the head section based on haircutting statistics; S4: Construct all the transition chains for each hairdressing condition to define the sequence of changes for each hairdressing condition; S5: For each work condition transition chain, determine the rationality of the change sequence represented by the constructed work condition transition chain based on the potential haircutting path and the probability distribution of hair quality status. S6: Determine if the reasonableness is higher than the set value. If so, retain the working condition transition chain; otherwise, exclude the working condition transition chain. S7: Construct a working condition transformation matrix based on the retained working condition transformation chain; S8: When the initial haircutting condition is received, the haircutting condition is transformed based on the initial haircutting condition and the condition transformation matrix. At each haircutting condition transformation, the corresponding condition signal of the adjusted haircutting condition is injected into the main control board to detect the performance of the main control board. The rationality of the sequence of changes represented by the constructed working condition transition chain, determined based on potential haircutting paths and the probability distribution of hair quality, includes: Select a working condition transition chain; Each pair of adjacent hairdressing conditions in the work condition transition chain is defined as a transition group, resulting in m-1 transition groups; where m is the number of hairdressing conditions in the work condition transition chain. For each conversion group, determine the contribution of that conversion group to the reasonableness. The rationality of the change sequence represented by the working condition transition chain is obtained by summing the contribution values ​​of each transition group to the rationality. The contribution of this conversion group to the reasonableness is determined by: Determine the hairdressing conditions of the head regions traversed by each potential hairdressing path in the set of potential hairdressing paths; The conversion group is compared one by one with the potential haircut paths in the potential haircut path set to determine all matching haircut paths in the haircut path set. Among them, there are two adjacent head partitions in the head partitions traversed by the matching haircut path. The haircut conditions corresponding to these two adjacent head partitions are consistent with the haircut conditions in the conversion group and are in the same order. Calculate the ratio of the number of matching haircut paths to the total number of potential haircut paths. ,in, To match the number of haircut paths, The total number of potential haircut routes; For each matched haircut path, determine the probability that the corresponding haircut condition in the conversion group appears in the two matched head partitions traversed by the matched haircut path. , Calculate the overall probability ; The contribution of this conversion group to the rationality score is calculated using the following formula: in, This represents the contribution of the conversion group to the level of reasonableness. Reasonableness is calculated using the following formula: in, For the sake of reasonableness, Adjustment coefficient for reasonableness.

2. The method according to claim 1, characterized in that, Hair quality parameters include average diameter, average length, and average density; hair cutting conditions are torque loads; all hair cutting conditions are determined based on each hair quality condition, that is, the corresponding hair cutting conditions are determined based on each acquired hair quality condition. The corresponding hairdressing conditions are determined by calculating each hair quality condition obtained using the following formula: in, For torque load, and These are the fitting coefficients. For average length, For average density, The average diameter is denoted as .

3. The method according to claim 1, characterized in that, The number of known hair quality states is q; there are n sets of haircut statistics, each set of haircut statistics includes the hair quality state of each head section and the corresponding hairdresser's several haircutting paths; Determining the probability distribution of hair quality status in each head section includes: S31: Select a header partition; S32: For each hair type, calculate the probability of that hair type being distributed across a specific section of the head using the following formula: in, This represents the probability of this hair quality condition being distributed across a specific area of ​​the head. This represents the number of times this hair quality condition occurs in this section of the head. S33: Repeat steps S31 to S32 until the probability of each hair quality state being distributed in each head section is obtained; Identifying all potential haircutting paths that cross the head section includes: Determine the number of head sections that each haircut path passes through, and exclude haircut paths that pass through only one head section. The remaining haircutting paths in each set of barber behavior statistics are aggregated into a potential haircutting path set, where the number of potential haircutting paths included in the potential haircutting path set is r.

4. The method according to claim 3, characterized in that, Based on each hairdressing work condition, all work condition transition chains are constructed, including: Determine the threshold N for the number of head regions that a haircut path can pass through; Determine the arrangement of all hair texture states, where the number of arrangements is... ; For each obtained hair quality state arrangement, the hair quality states are connected in series according to the order of the arrangement to obtain the corresponding working condition conversion chain.

5. The method according to claim 4, characterized in that, The operating condition transition chain is represented as follows: in, For operating condition transition chain, Let j be the j-th hairdressing condition in the condition transition chain, and m be the number of hairdressing conditions in the condition transition chain. The operating condition transformation matrix is ​​represented as follows: in, This is the operating condition transformation matrix. Let y be the kth working condition transition chain, and y be the number of working condition transition chains.

6. The method according to claim 4, characterized in that, Based on the initial hairdressing conditions and the condition transformation matrix, the hairdressing conditions are transformed, and at each transformation, the corresponding condition signal for the adjusted hairdressing condition is injected into the main control board, including: Determine the working condition transition chain based on the initial hairdressing working condition in the working condition transition matrix; Locate the initial haircutting condition in the condition transition chain to determine the subsequent haircutting conditions. The haircutting conditions are switched one by one according to the determined sequence, and the corresponding condition signal is injected into the main control board at each switch.

7. A high-efficiency detection device for a main control board, characterized in that, The device includes: The acquisition module is used to acquire all known hair quality states, where the hair quality parameters are not exactly the same for different hair quality states; The first processing module is used to determine all hair-cutting conditions based on the hair quality. The second processing module is used to determine the probability distribution of hair quality status in each head section and all potential haircutting paths that cross the head section based on haircutting statistics. The third processing module is used to construct all the working condition transformation chains based on each hairdressing working condition, so as to define the change sequence of each hairdressing working condition; The fourth processing module is used to determine the rationality of the change sequence represented by the constructed working condition transition chain for each working condition transition chain based on the probability distribution of potential haircutting paths and hair quality status. The judgment module is used to determine whether the reasonableness is higher than the set value. If so, the working condition transition chain is retained; otherwise, the working condition transition chain is excluded. The fifth processing module is used to construct a working condition transformation matrix based on the retained working condition transformation chain; The testing module is used to transform the hairdressing conditions based on the initial hairdressing conditions and the condition transformation matrix when the initial hairdressing conditions are received. At each time the hairdressing conditions are transformed, the module injects the condition signal corresponding to the adjusted hairdressing conditions into the main control board to detect the performance of the main control board. The rationality of the sequence of changes represented by the constructed working condition transition chain, determined based on potential haircutting paths and the probability distribution of hair quality, includes: Select a working condition transition chain; Each pair of adjacent hairdressing conditions in the work condition transition chain is defined as a transition group, resulting in m-1 transition groups; where m is the number of hairdressing conditions in the work condition transition chain. For each conversion group, determine the contribution of that conversion group to the reasonableness. The rationality of the change sequence represented by the working condition transition chain is obtained by summing the contribution values ​​of each transition group to the rationality. The contribution of this conversion group to the reasonableness is determined by: Determine the hairdressing conditions of the head regions traversed by each potential hairdressing path in the set of potential hairdressing paths; The conversion group is compared one by one with the potential haircut paths in the potential haircut path set to determine all matching haircut paths in the haircut path set. Among them, there are two adjacent head partitions in the head partitions traversed by the matching haircut path. The haircut conditions corresponding to these two adjacent head partitions are consistent with the haircut conditions in the conversion group and are in the same order. Calculate the ratio of the number of matching haircut paths to the total number of potential haircut paths. ,in, To match the number of haircut paths, The total number of potential haircut routes; For each matched haircut path, determine the probability that the corresponding haircut condition in the conversion group appears in the two matched head partitions traversed by the matched haircut path. , Calculate the overall probability ; The contribution of this conversion group to the rationality score is calculated using the following formula: in, This represents the contribution of the conversion group to the level of reasonableness. Reasonableness is calculated using the following formula: in, For the sake of reasonableness, Adjustment coefficient for reasonableness.

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