Light splitting partition control method and system of multicolor infinite mirror surface cooling fan

Abstract

The invention provides a light splitting partition control method and system of a multicolor infinite mirror surface cooling fan, and relates to the technical field of signal control. The method comprises the following steps: acquiring lightening control data, and performing lightening signal mapping analysis based on position information to form theoretical lightening signal position matching data; historical rotation motion data is collected, feature information influencing the lighting position is extracted, and lighting position influence feature information is formed; and in combination with the theoretical lighting signal position matching data and the lighting position influence feature information, carrying out real-time matching analysis on lighting signals of different lamp beads to form lighting signal real-time matching data. According to the method, more accurate lamp bead lightening signal matching is realized through reasonable data analysis.

Description

Technical Field

[0001] This invention relates to the field of signal control technology, and more specifically, to a method and system for controlling the spectral partitioning of a multi-color infinite mirror cooling fan. Background Technology

[0002] The multi-color infinite mirror cooling fan's airflow zoning design is an innovative design that combines optical effects with heat dissipation performance. It mainly achieves a visual "infinite extension" effect through LED lighting, mirror reflection, and zoning control technology, while optimizing the visual characteristics of the heat dissipation airflow.

[0003] Currently, the main problem with the light and shadow zoning of multi-color infinite mirror cooling fans is that signal delay affects the accuracy of the LEDs' lighting signal, making it impossible to achieve accurate light zoning processing and causing significant inconvenience to users.

[0004] Therefore, designing a multi-color infinite mirror cooling fan with a spectral partitioning control method and system, and achieving more accurate matching of LED lighting signals through reasonable data analysis, is an urgent problem to be solved. Summary of the Invention

[0005] The purpose of this invention is to provide a method for controlling the zoning of a multi-color infinite mirror cooling fan. By analyzing the lighting control data, the lighting signal value at a fixed position point is determined under time-varying conditions, establishing theoretical lighting signal position matching data. At the same time, historical data is used to determine the fan rotation characteristic information under the current state. Then, by combining the matching data and characteristic information, the position deviation caused by the signal delay under real-time conditions is reasonably analyzed and considered to form lighting information position matching data that meets the current situation. This effectively ensures the accurate matching of lighting information with LED beads, making the zoning control more accurate and reasonable.

[0006] The present invention also aims to provide a beam splitting and zoning control system for a multi-color infinite mirror cooling fan. This system determines the change of required lighting information at a specific location over time using a lighting requirement data unit. A feature extraction unit establishes feature information that can predict the impact on nearby light control. A real-time matching unit then accurately confirms the position of the LED beads to match appropriate and accurate lighting information values. The different units are closely interconnected, forming a unified whole that realizes beam splitting and zoning control, which is a crucial material basis for fully realizing this control system.

[0007] In a first aspect, the present invention provides a method for beam splitting and zone control of a multi-color infinite mirror cooling fan, comprising: acquiring lighting control data, performing lighting signal mapping analysis based on position information to form theoretical lighting signal position matching data; collecting historical rotational motion data, extracting feature information affecting the lighting position to form lighting position influence feature information; and combining the theoretical lighting signal position matching data and the lighting position influence feature information to perform real-time matching analysis of lighting signals for different LED beads to form real-time lighting signal matching data.

[0008] In this invention, the method determines the lighting signal value of a fixed position point under time-varying conditions by analyzing the lighting control data, establishes theoretical lighting signal position matching data, and uses historical data to determine the fan rotation characteristic information under the current state. Then, by combining the matching data and characteristic information, the method reasonably analyzes and considers the position deviation caused by the signal delay under real-time conditions to form lighting information position matching data that meets the current conditions, effectively ensuring the accurate matching of lighting information with LED beads, making the beam splitting and zoning control more accurate and reasonable.

[0009] One possible implementation involves acquiring lighting control data, performing lighting signal mapping analysis based on position information, and forming theoretical lighting signal position matching data. This includes: establishing a lighting mapping angular coordinate system with the fan's rotation center as the origin and the plane where the LEDs are located as the coordinate plane; determining the corresponding lighting signals for different positions within the lighting mapping angular coordinate system over the entire lighting control duration based on the lighting control data, and forming a theoretical lighting matching mapping function F for the position points. n (θ n L n S n (t)), θ n L represents the angle value determined by the position point numbered n in the illumination mapping angular coordinate system. n S represents the length of the position point numbered n relative to the origin of the coordinate system in the illumination mapping angle coordinate system. n (t) represents the lighting signal value at position n, determined by the angle and length values, which varies with the fan running time; the theoretical lighting matching mapping function F for all position points is also included. n (θ n L n S n (t)) forms the theoretical lighting signal position matching data.

[0010] In this invention, it should be noted that the position points determined in the angular coordinate system are not the positions of the LEDs installed on the fan, but rather fixed positions that do not move with the fan's rotation. However, since these fixed positions have different lighting parameter values ​​at different locations, the lighting parameter values ​​corresponding to any position in the angular coordinate system are different. This ensures that the overall lighting effect of the LEDs is continuous and aesthetically pleasing. Because the lighting parameter values ​​are also inherently continuous with the time parameter, the lighting signal values ​​mapped and matched at different positions also have temporal characteristics, thus demonstrating the true validity of the lighting signal values ​​over time.

[0011] One possible approach is to collect historical rotational motion data, extract feature information affecting the lighting position, and form lighting position influence feature information. This includes: extracting rotational operation data after M fan starts based on historical rotational motion data, and performing rotational feature extraction and analysis for different operation stages to form rotational feature data corresponding to different operation stages; and combining the rotational feature data corresponding to different operation stages to form lighting position influence feature information.

[0012] In this invention, feature extraction from historical rotational motion data essentially determines the fan's rotational speed change under current conditions. It's understandable that in the initial stages of use, the fan's rotational speed change closely matches the theoretical data. However, as usage time increases and environmental influences affect the equipment, the actual rotational speed change gradually deviates from the theoretical data. Therefore, using theoretical data to determine the lighting information for each LED will result in significant errors due to this data deviation. The most effective method is to determine the actual rotational speed change of the current fan. This requires reasonable extraction and analysis of recent operational data. Considering that fan rotation involves three main processes—acceleration, stable operation, and deceleration—a phased analysis is more reasonable and ensures more accurate feature extraction. Of course, the appropriate value (M) for recent historical data can be selected based on actual conditions.

[0013] As one possible implementation, based on historical rotational motion data, rotational operation data after M fan starts is extracted, and rotational feature extraction and analysis are performed for different operation stages to form rotational feature data corresponding to different operation stages. This includes: setting a stable speed fluctuation difference and a stage judgment window duration, and dividing the operation stages of the rotational operation data after each fan start in the following way: for the rotational operation data after each fan start, starting from the time point when the fan starts rotating, the stage judgment window duration is used as the judgment time period. The window slides over the entire operation time of the fan. When the maximum difference of the fan speed within the time interval defined by the first stage judgment window duration is not greater than the stable speed fluctuation difference, the corresponding time interval is considered complete. The entire runtime before the start-up phase is defined as the startup phase. If the maximum difference in fan speed within the time interval defined by the last phase judgment window is not greater than the stable speed fluctuation difference, then the entire runtime of the corresponding time interval after the start-up phase is defined as the shutdown phase. The time interval between the startup phase and the shutdown phase is defined as the intermediate operation phase. For the speed motion data in the startup phase, rotation feature extraction and analysis based on startup characteristics are performed to form startup rotation feature data. For the speed motion data in the intermediate operation phase, rotation feature extraction and analysis based on stable operation characteristics are performed to form stable rotation feature data. For the speed motion data in the shutdown phase, rotation feature extraction and analysis based on shutdown operation characteristics are performed to form shutdown rotation feature data.

[0014] In this invention, the rotational characteristics of the fan differ at different operating stages, especially the variation characteristics of its speed. To ensure that the acquired feature data can more accurately and effectively provide matching mapping between lighting and position information, phased feature extraction is the most effective analysis method. Regarding the division of operating stages, this application considers that the fan speed changes relatively significantly during startup and shutdown, while the speed changes are stable during the operating stages. Based on this, a reasonable window sliding confirmation over the time dimension can quickly and efficiently divide the operating stages. The stable speed fluctuation difference and the stage judgment window duration are determined according to the actual situation.

[0015] As one possible implementation, the rotational speed data during the startup phase is extracted from the rotational operation data after each fan start-up. Rotational feature extraction and analysis based on startup characteristics are then performed to form startup rotational feature data. This includes: extracting the corresponding speed change data for each startup operation phase to form a corresponding sub-term startup speed change function. Functions for the change of starting speed for different sub-terms The following fitting method is used to form the characteristic variation function of the starting rotation speed. Preset start-up rotation speed characteristic change function The unknown parameters are determined, and the same number of different terms of the starting speed change function are arbitrarily extracted based on the total number of unknown parameters. A fitting analysis was performed to determine the initial starting rotational speed characteristic variation function; the remaining starting rotational speed characteristic variation functions were then analyzed. According to the order of the corresponding sub-items, the cumulative deviation between the initial starting rotation speed characteristic change function and the corresponding time interval is confirmed. If the cumulative deviation is not less than the cumulative deviation limit, then the corresponding starting rotation speed characteristic change function is... The initial starting rotational speed characteristic change function is averaged over the corresponding time interval and smoothed over the entire time period. This process is repeated for each starting rotational speed characteristic change function. Perform comparative processing until the remaining start-up rotation speed characteristic change function is used up. The resulting change function is calibrated as the characteristic change function of the starting rotation speed.

[0016] In this invention, the fan speed change during the startup phase is mainly affected by the fan's lifespan. Processing historical data allows for a reasonable analysis of the fan's current startup performance, providing more accurate fan speed change data reflecting the current state. This provides a reference for subsequent startup speed changes. The method for obtaining the characteristic data of startup speed changes is to fit historical speed change curves. Although the historical data of the secondary item has a chronological order, and closer is better, earlier historical data should also be considered for determining basic performance. Therefore, during analysis, historical data is first arbitrarily extracted for fitting. This allows for the rapid establishment of more reasonable characteristic information and reduces the amount of data processing by using the remaining historical data of the secondary item for precise time-directed improvement. Since the arbitrarily extracted data also includes relatively recent historical data, the initial characteristic data already has a certain degree of accuracy. This ensures that the accumulated deviation of the remaining secondary item data, especially earlier data, during comparative analysis will not exceed the limit and thus lose its adjustment significance, reducing the amount of data analysis. It should also be noted that the fitting of the remaining sub-term data mainly involves averaging. This allows for a more average data format to predict speed changes during the startup phase, ensuring that the feature data does not deviate significantly from the predicted startup speed changes. Simultaneously, it ensures that the feature data has a certain time span representativeness and does not quickly lose its significance in accurately predicting speed changes. Regarding the fitting analysis, it should also be noted that the quantities of unknown parameters, including the highest power of the fitting function, can be set as needed.

[0017] As one possible implementation, rotational feature extraction and analysis based on stable operation characteristics is performed on the rotational speed motion data of the intermediate operation phase to form stable rotational feature data. This includes: for each corresponding intermediate operation phase, obtaining the secondary stable rotational speed feature change function in the following way: dividing each intermediate operation phase into time periods, ensuring that the difference in the cumulative rotational speed between each time period is not greater than the cumulative difference limit of the stable cycle, then determining the corresponding time period as the stable change cycle, and obtaining the secondary periodic stable rotational speed change function within each stable change cycle; averaging the secondary periodic stable rotational speed change functions corresponding to all stable change cycles in each phase to form the corresponding secondary stable rotational speed feature change function. The characteristic change function of the stable rotational speed corresponding to the earliest term. Based on the basic data, determine the characteristic change function of the stable rotational speed of the other terms. The difference relative to the baseline data is used to determine the average unit time difference, and these differences are arranged in chronological order. Based on the average unit time difference and the baseline data, a characteristic variation function of the stable rotational speed is formed.

[0018] In this invention, for the stable operation of the fan, it is understood that within a certain time period, due to structural wear and other factors, the fan speed will exhibit repetitive and stable fluctuations in one revolution. Therefore, to extract this stable and repetitive fluctuation simply and reasonably, the rotation period of the stable operation phase is determined by judging the rotation period. Since the difference between periodic data for a single item is very small and basically remains unchanged, the representative periodic operation data of the sub-item is formed by averaging the speed curve function over the period. Considering that the time span between different sub-items is large, the periodic stable operation data will change. This change is mainly reflected in the speed curve as an overall curve shift or lengthening and compression. Therefore, it is reasonable and accurate to use the difference in periodic data of adjacent sub-items to confirm the change pattern. Here, the difference is mainly the difference in the cumulative speed over the period, while the average unit time difference determines the influence of the time length between sub-items on the speed change when a stable speed change occurs in different sub-items. Using the characteristic change function, a reasonable increment can be determined based on the time of the subsequent sub-item relative to the basic data, and then averaged into the basic data to form the predicted stable speed change curve of the next sub-item.

[0019] As one possible implementation, rotational feature extraction and analysis based on the characteristics of the stopping operation is performed on the rotational speed motion data during the stopping phase to form stopping rotational feature data. This includes: extracting the corresponding rotational speed change data for each corresponding stopping phase to form a corresponding sub-term stopping rotational speed change function. The stop speed change function for different terms The following fitting method is used to form the characteristic change function of the rotational speed at rest. Preset stop rotation speed characteristic change function The unknown parameters are determined, and the same number of different terms of the stop speed variation function are arbitrarily extracted based on the total number of unknown parameters. A fitting analysis was performed to determine the initial stop rotation speed characteristic change function; the remaining stop rotation speed characteristic change functions were then analyzed. According to the order of the corresponding sub-items, the cumulative deviation of the corresponding time interval is confirmed with the initial stop rotation speed characteristic change function. If the cumulative deviation is not less than the cumulative deviation limit, then the corresponding stop rotation speed characteristic change function is... The initial stop rotation speed characteristic change function is averaged over the corresponding time interval and smoothed over the entire time period. This process is repeated for each stop rotation speed characteristic change function. Perform comparative processing until the remaining characteristic change function of the stop rotation speed is exhausted. The resulting change function is calibrated as the characteristic change function of the rotational speed at a standstill.

[0020] In this invention, the extraction method for characteristic speed change data during the shutdown phase is the same as that during the startup phase. Characteristic change data with near-predictive capabilities is formed by reasonably utilizing secondary data for fitting processing.

[0021] As one possible implementation, by combining theoretical lighting signal position matching data and lighting position influence characteristic information, real-time matching analysis of lighting signals for different LED beads is performed to form real-time lighting signal matching data, including: based on the characteristic change function of the starting rotation speed. The corresponding start-up limit duration and stop rotation speed characteristic change function The stop limit duration and the real-time estimated total running time are used to determine the real-time stable estimated running time. Determine the duration of the current fan operation relative to the baseline data, and combine this with the characteristic change function of the stable rotational speed. and real-time stable estimated runtime Determine the real-time stable rotational speed variation function Based on the characteristic change function of the starting rotation speed Characteristic change function of rotational speed at stop and the estimated runtime in real-time stability Corresponding real-time stable rotational speed change function Smoothing is performed to generate a real-time speed change function. Determine the real-time lighting signal time ttime Acquire signal extended duration t delay And combined with the real-time speed change function Perform position matching analysis to generate real-time matching data for the lighting signal.

[0022] In this invention, matching the real-time lighting signal data of the LED beads needs to consider the entire duration of the image to be displayed. This is the basis for determining the duration of the fan's stable operation, thus forming predicted speed change data for the entire duration. This allows for corresponding analysis of the actual LED bead changes based on the lighting signal sent for each change in the LED bead's light control. This more accurately and reasonably determines the correct lighting signal that the LED beads need to receive, avoiding unexpected angle changes or incorrect display of the resulting pattern.

[0023] As one possible implementation, the real-time lighting signal time t is determined. time Acquire signal extended duration t delay And combined with the real-time speed change function Perform position matching analysis to generate real-time matching data for the lighting signal, including: based on the real-time lighting signal time t. time Determine the non-delay position parameters of the LED. k is the sequential number of the different LED beads, and This indicates that the LED with the number k is lit up during the real-time signal time t. time The corresponding angle value, and L k This indicates that the LED with the number k is lit up during the real-time signal time t. time The length of the current location relative to the origin; based on the signal duration t. delay and real-time speed change function Determine the angle of delay change in, Based on the non-delay position parameters of the LEDs and delay change angle Determine the real-time position parameters of the LED beads in, This represents the real-time angle value of the LED with the number n, and Based on the real-time position parameters of the LED beads And combine the position point theory to illuminate the matching mapping function F n (θ n L n S n (t)) determines the duration of the LED bead in time t. time +t delay The corresponding lighting signal value; collect the lighting signal values ​​corresponding to all LED beads to form real-time lighting signal matching data.

[0024] In this invention, to determine the actual lighting signal that each LED needs to receive, it is necessary to determine the actual position of the LED before sending the lighting signal and the data on the change in LED position caused by the signal delay in sending the lighting signal. After determining the actual position of the LED, the corresponding lighting information values ​​at different positions can be used to match the LEDs, thereby determining the matching relationship for sending lighting signals to a specific LED in advance, ensuring the accuracy and rationality of the light splitting and zoning control.

[0025] Secondly, the present invention provides a beam-splitting and partitioning control system for a multi-color infinite mirror cooling fan, comprising: a lighting requirement data unit for acquiring lighting control data, performing lighting signal mapping analysis based on position information, and forming theoretical lighting signal position matching data; a feature extraction unit for collecting historical rotational motion data, extracting feature information affecting the lighting position, and forming lighting position influence feature information; and a real-time matching unit for performing real-time matching analysis of lighting signals for different LED beads based on the theoretical lighting signal position matching data formed by the lighting requirement data unit and the lighting position influence feature information formed by the feature extraction unit, and forming real-time lighting signal matching data.

[0026] In this invention, the system determines the change of required lighting information at a specific location over time using a lighting requirement data unit. A feature extraction unit then establishes feature information that can predict the impact on nearby light control. Finally, a real-time matching unit accurately confirms the position of the LED beads to match appropriate and accurate lighting information values. These interconnected units form a cohesive whole for achieving beam splitting and zoning control, forming a crucial material basis for fully realizing this control.

[0027] The beneficial effects of the multi-color infinite mirror cooling fan's light-splitting and zone-control method and system provided by this invention are as follows:

[0028] This method analyzes the lighting control data to determine the lighting signal value at a fixed position point under time-varying conditions, establishes theoretical lighting signal position matching data, and uses historical data to determine the fan rotation characteristic information under the current state. Then, it combines the matching data and characteristic information to reasonably analyze and consider the position deviation caused by the signal delay under real-time conditions, forming lighting information position matching data that meets the current situation. This effectively ensures the accurate matching of lighting information with LED beads, making the beam splitting and zoning control more accurate and reasonable.

[0029] This system determines the changes in required lighting information over time at a specific location using a lighting requirement data unit. A feature extraction unit then establishes predictive feature information that can influence nearby light control. Finally, a real-time matching unit accurately confirms the position of the LEDs to match appropriate and accurate lighting information values. These interconnected units form a cohesive whole for achieving beam splitting and zoning control, forming a crucial material foundation for its full realization. Attached Figure Description

[0030] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments of the present invention will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 A step diagram illustrating a method for controlling the spectral partitioning of a multi-color infinite mirror cooling fan, provided in an embodiment of the present invention;

[0032] Figure 2 This is a schematic diagram of the structure of a multi-color infinite mirror cooling fan's light-splitting and partitioning control system provided in an embodiment of the present invention;

[0033] Figure 3 An exploded view of the cooling fan structure of a multi-color infinite mirror cooling fan spectral partitioning control system provided in an embodiment of the present invention;

[0034] Figure 4 This is a schematic diagram of the cooling fan structure assembly for a multi-color infinite mirror cooling fan spectral partitioning control system provided in an embodiment of the present invention. Detailed Implementation

[0035] The technical solutions of the present invention will now be described with reference to the accompanying drawings in the embodiments of the present invention.

[0036] The multi-color infinite mirror cooling fan's airflow zoning design is an innovative design that combines optical effects with heat dissipation performance. It mainly achieves a visual "infinite extension" effect through LED lighting, mirror reflection, and zoning control technology, while optimizing the visual characteristics of the heat dissipation airflow.

[0037] Currently, the main problem with the light and shadow zoning of multi-color infinite mirror cooling fans is that signal delay affects the accuracy of the LEDs' lighting signal, making it impossible to achieve accurate light zoning processing and causing significant inconvenience to users.

[0038] refer to Figures 1-2This invention provides a method for controlling the zoning of a multi-color infinite mirror cooling fan. This method determines the lighting signal value of a fixed position point under time-varying conditions by analyzing the lighting control data, establishes theoretical lighting signal position matching data, and uses historical data to determine the fan rotation characteristic information under the current state. Then, it combines the matching data and characteristic information to reasonably analyze and consider the position deviation caused by the signal delay under real-time conditions to form lighting information position matching data that meets the current situation. This effectively ensures the accurate matching of lighting information with LED beads, making the zoning control more accurate and reasonable.

[0039] The method for controlling the light distribution and zoning of a multi-color infinite mirror-finish cooling fan includes the following steps:

[0040] S1: Acquire lighting control data, perform lighting signal mapping analysis based on location information, and form theoretical lighting signal position matching data.

[0041] Acquire lighting control data, perform lighting signal mapping analysis based on position information, and form theoretical lighting signal position matching data. This includes: establishing a lighting mapping angular coordinate system with the fan's rotation center as the origin and the plane where the LED is located as the coordinate plane; determining the corresponding lighting signal for different positions within the lighting mapping angular coordinate system over the entire lighting control duration based on the lighting control data, and forming a theoretical lighting matching mapping function F for the position points. n (θ n L n S n (t)), θ n L represents the angle value determined by the position point numbered n in the illumination mapping angular coordinate system. n S represents the length of the position point numbered n relative to the origin of the coordinate system in the illumination mapping angle coordinate system. n (t) represents the lighting signal value at position n, determined by the angle and length values, which varies with the fan running time; the theoretical lighting matching mapping function F for all position points is also included. n (θ n L n S n (t)) forms the theoretical lighting signal position matching data.

[0042] It should be noted that the positions determined in the angular coordinate system are not the positions of the LEDs installed on the fan, but rather fixed positions that do not move with the fan's rotation. However, since these fixed positions have different lighting parameter values ​​at different locations, the lighting parameter values ​​corresponding to any position in the angular coordinate system are different. This ensures that the overall lighting effect of the LEDs is continuous and aesthetically pleasing. Because the lighting parameter values ​​are also inherently continuous with the time parameter, the lighting signal values ​​mapped and matched at different positions also have temporal characteristics, demonstrating the true validity of the lighting signal values ​​over time.

[0043] S2: Collect historical rotational motion data, extract feature information that affects the lighting position, and form feature information that affects the lighting position.

[0044] Historical rotational motion data is collected, and feature information affecting the lighting position is extracted to form the lighting position influence feature information. This includes: extracting rotational operation data after M fan starts based on historical rotational motion data, and performing rotational feature extraction and analysis for different operation stages to form rotational feature data corresponding to different operation stages; and combining the rotational feature data corresponding to different operation stages to form the lighting position influence feature information.

[0045] Feature extraction from historical rotational motion data essentially involves determining the fan's rotational speed variation under current conditions. It's understandable that in the initial stages of use, the fan's rotational speed variation closely matches the theoretical data. However, as usage time increases and environmental influences affect the equipment, the actual rotational speed variation gradually deviates from the theoretical data. Therefore, using theoretical data to determine the lighting information for each LED will introduce significant errors due to this data deviation. The most effective approach is to determine the actual rotational speed variation of the current fan. This requires reasonable extraction and analysis of recent operational data. Considering that fan rotation involves three main processes—acceleration at startup, stable operation, and deceleration to stop—a phased analysis is more reasonable and ensures more accurate feature extraction. Of course, the appropriate value (M) for recent historical data can be selected based on actual conditions.

[0046] Based on historical rotational motion data, rotational operation data after M fan starts were extracted, and rotational feature extraction and analysis were performed for different operation stages to form rotational feature data corresponding to different operation stages. This included: setting a stable speed fluctuation difference and a stage judgment window duration; and dividing the operation data after each fan start into operation stages in the following way: For each fan start-up operation data, starting from the time the fan begins to rotate, the stage judgment window duration is used as the judgment time period. The window slides over the entire operation time of the fan. When the maximum difference in fan speed within the time interval defined by the first stage judgment window duration is not greater than the stable speed fluctuation difference, the entire operation of the corresponding time interval is considered complete. The duration of each run is defined as the start-up phase. If the maximum difference in fan speed within the time interval defined by the last phase judgment window is not greater than the stable speed fluctuation difference, then the entire running duration following the corresponding time interval is defined as the stop phase. The time interval between the start-up phase and the stop phase is defined as the intermediate running phase. For the speed motion data in the start-up phase, rotation feature extraction and analysis based on start-up characteristics are performed to form start-up rotation feature data. For the speed motion data in the intermediate running phase, rotation feature extraction and analysis based on stable running characteristics are performed to form stable rotation feature data. For the speed motion data in the stop running phase, rotation feature extraction and analysis based on stop running characteristics are performed to form stop rotation feature data.

[0047] The rotational characteristics differ for different fan operating stages, especially the variation characteristics of fan speed. To ensure that the acquired feature data can more accurately and effectively provide matching and mapping between lighting and position information, phased feature extraction is the most effective analysis method. Regarding the division of operating stages, this application considers that the fan speed change is relatively large during startup and shutdown, while the speed change is stable during the operating stages. Based on this, a reasonable window sliding confirmation over the time dimension can quickly and efficiently divide the operating stages. The stable speed fluctuation difference and the stage judgment window duration are determined according to the actual situation.

[0048] For each fan startup, the rotational speed data during the startup phase is extracted, and rotational feature extraction analysis based on startup characteristics is performed to form startup rotational feature data. This includes: extracting the corresponding speed change data for each startup phase to form a corresponding sub-term startup speed change function. Functions for the change of starting speed for different sub-terms The following fitting method is used to form the characteristic variation function of the starting rotation speed. Preset start-up rotation speed characteristic change function The unknown parameters are determined, and the same number of different terms of the starting speed change function are arbitrarily extracted based on the total number of unknown parameters. A fitting analysis was performed to determine the initial starting rotational speed characteristic variation function; the remaining starting rotational speed characteristic variation functions were then analyzed. According to the order of the corresponding sub-items, the cumulative deviation between the initial starting rotation speed characteristic change function and the corresponding time interval is confirmed. If the cumulative deviation is not less than the cumulative deviation limit, then the corresponding starting rotation speed characteristic change function is... The initial starting rotational speed characteristic change function is averaged over the corresponding time interval and smoothed over the entire time period. This process is repeated for each starting rotational speed characteristic change function. Perform comparative processing until the remaining start-up rotation speed characteristic change function is used up. The resulting change function is calibrated as the characteristic change function of the starting rotation speed.

[0049] The fan speed variation during the startup phase of the secondary item is mainly affected by the fan's lifespan. Processing historical data allows for a reasonable analysis of the fan's current startup performance, providing more accurate fan speed variation data reflecting the current state. This provides a reference for subsequent startup speed variation. The method for obtaining the characteristic data of startup speed variation in this application involves fitting historical speed variation curves. Although the historical data of the secondary item is chronologically ordered, and closer is better, earlier historical data should also be considered for determining basic performance. Therefore, during analysis, historical data is first arbitrarily extracted for fitting. This allows for the rapid establishment of more reasonable characteristic information and reduces the amount of data processing by using the remaining historical data of the secondary item for precise time-oriented improvement processing. After all, the arbitrarily extracted data also includes relatively recent historical data, ensuring that the initial characteristic data already has a certain degree of accuracy. This prevents the accumulated deviation of the remaining secondary item data, especially earlier data, from exceeding the limit and thus losing its adjustment significance, reducing the amount of data analysis. It should also be noted that the fitting of the remaining sub-term data mainly involves averaging. This allows for a more average data format to predict speed changes during the startup phase, ensuring that the feature data does not deviate significantly from the predicted startup speed changes. Simultaneously, it ensures that the feature data has a certain time span representativeness and does not quickly lose its significance in accurately predicting speed changes. Regarding the fitting analysis, it should also be noted that the quantities of unknown parameters, including the highest power of the fitting function, can be set as needed.

[0050] For the rotational speed data during intermediate operation phases, rotational feature extraction and analysis based on stable operation characteristics are performed to form stable rotational feature data. This includes: for each corresponding intermediate operation phase, the secondary stable rotational speed feature change function is obtained in the following way: each intermediate operation phase is divided into time periods, ensuring that the difference in cumulative rotational speed between each time period is not greater than the cumulative difference limit of the stable cycle. The corresponding time period is then determined as the stable change cycle, and the secondary periodic stable rotational speed change function within each stable change cycle is obtained; the secondary periodic stable rotational speed change function corresponding to all stable change cycles in each phase is averaged to form the corresponding secondary stable rotational speed feature change function. The characteristic change function of the stable rotational speed corresponding to the earliest term. Based on the basic data, determine the characteristic change function of the stable rotational speed of the other terms. The difference relative to the baseline data is used to determine the average unit time difference, and these differences are arranged in chronological order. Based on the average unit time difference and the baseline data, a characteristic variation function of the stable rotational speed is formed.

[0051] For fan operation in the stable phase, it is understandable that within a certain time period, due to structural wear and other factors, the fan speed will exhibit repetitive and stable fluctuations in one revolution. Therefore, to extract this stable and repetitive fluctuation simply and reasonably, the rotation cycle is determined by judging the rotation cycle of the stable operation phase. Since the difference between the periodic data for a single term is very small and basically remains unchanged, the representative periodic operation data of the term is formed by averaging the speed curve function over the period. Considering that the time span between different terms is large, the stable periodic operation data will change. This change is mainly reflected in the speed curve as an overall curve shift or lengthening / compression. Therefore, it is reasonable and accurate to use the difference in the periodic data of adjacent terms to confirm the change pattern. Here, the difference is mainly the difference in the cumulative speed over the period, while the average unit time difference determines the influence of the time length between different terms on the speed change when a stable speed change occurs. Using the characteristic change function, a reasonable increment can be determined based on the duration of the subsequent term relative to the basic data, and then averaged into the basic data to form the predicted stable speed change curve of the next term.

[0052] For the rotational speed data during the stopping phase, rotational feature extraction and analysis based on the characteristics of stopping operation are performed to form stopping rotational feature data, including: extracting the corresponding rotational speed change data for each corresponding stopping phase to form the corresponding sub-term stopping rotational speed change function. The stop speed change function for different terms The following fitting method is used to form the characteristic change function of the rotational speed at rest. Preset stop rotation speed characteristic change function The unknown parameters are determined, and the same number of different terms of the stop speed variation function are arbitrarily extracted based on the total number of unknown parameters. A fitting analysis was performed to determine the initial stop rotation speed characteristic change function; the remaining stop rotation speed characteristic change functions were then analyzed. According to the order of the corresponding sub-items, the cumulative deviation of the corresponding time interval is confirmed with the initial stop rotation speed characteristic change function. If the cumulative deviation is not less than the cumulative deviation limit, then the corresponding stop rotation speed characteristic change function is... The initial stop rotation speed characteristic change function is averaged over the corresponding time interval and smoothed over the entire time period. This process is repeated for each stop rotation speed characteristic change function. Perform comparative processing until the remaining characteristic change function of the stop rotation speed is exhausted. The resulting change function is calibrated as the characteristic change function of the rotational speed at a standstill.

[0053] The extraction method for characteristic speed change data during the shutdown phase is the same as that during the startup phase. By reasonably utilizing the secondary data for fitting processing, characteristic change data with near-term predictive power is formed.

[0054] S3: Combining theoretical lighting signal position matching data and lighting position influence characteristic information, perform real-time matching analysis of lighting signals for different LED beads to form real-time lighting signal matching data.

[0055] Combining theoretical lighting signal position matching data and lighting position influence characteristics, real-time lighting signal matching analysis is performed for different LED beads, generating real-time lighting signal matching data, including: based on the characteristic change function of the starting rotation speed. The corresponding start-up limit duration and stop rotation speed characteristic change function The stop limit duration and the real-time estimated total running time are used to determine the real-time stable estimated running time. Determine the duration of the current fan operation relative to the baseline data, and combine this with the characteristic change function of the stable rotational speed. and real-time stable estimated runtime Determine the real-time stable rotational speed variation function Based on the characteristic change function of the starting rotation speed Characteristic change function of rotational speed at stop and the estimated runtime in real-time stability Corresponding real-time stable rotational speed change function Smoothing is performed to generate a real-time speed change function. Determine the real-time lighting signal time t time Acquire signal extended duration t delay and conclusion

[0056] Combined real-time speed change function Perform position matching analysis to generate real-time matching data for the lighting signal.

[0057] Matching the real-time illumination signal data of the LEDs requires considering the entire duration of the displayed image. This is the basis for determining the duration of the fan's stable operation, thus generating predicted speed change data for the entire duration. This allows for corresponding analysis of the actual LED changes based on the illumination signal sent for each change in LED light control. This more accurately and reasonably determines the correct illumination signal the LEDs need to receive, avoiding unexpected angle changes or incorrect display of the resulting pattern.

[0058] Determine the real-time lighting signal time t time Acquire signal extended duration t delay And combined with the real-time speed change function Perform position matching analysis to generate real-time matching data for the lighting signal, including: based on the real-time lighting signal time t. time Determine the non-delay position parameters of the LED. k is the sequential number of the different LED beads, and This indicates that the LED with the number k is lit up during the real-time signal time t. time The corresponding angle value, and L k This indicates that the LED with the number k is lit up during the real-time signal time t. time The length of the current location relative to the origin; based on the signal duration t. delay and real-time speed change function Determine the angle of delay change in, Based on the non-delay position parameters of the LEDs and delay change angle Determine the real-time position parameters of the LED beads in, This represents the real-time angle value of the LED with the number n, and Based on the real-time position parameters of the LED beads And combine the position point theory to illuminate the matching mapping function F n (θ n L n S n(t)) determines the duration of the LED bead in time t. time +t delay The corresponding lighting signal value; collect the lighting signal values ​​corresponding to all LED beads to form real-time lighting signal matching data.

[0059] To determine the actual lighting signal that each LED needs to receive, it is necessary to determine the actual position of the LED before sending the lighting signal and the data on the change in LED position caused by the signal delay during the sending of the lighting signal. After determining the actual position of the LED, the corresponding lighting information values ​​at different positions can be used to match the LEDs, thereby determining the matching relationship for sending lighting signals to a specific LED in advance, ensuring the accuracy and rationality of the beam splitting and zoning control.

[0060] This invention also provides a beam splitting and zoning control system for a multi-color infinite mirror cooling fan. The system includes: a lighting requirement data unit for acquiring lighting control data, performing lighting signal mapping analysis based on position information, and forming theoretical lighting signal position matching data; a feature extraction unit for collecting historical rotational motion data, extracting feature information affecting the lighting position, and forming lighting position influence feature information; and a real-time matching unit for performing real-time matching analysis of lighting signals for different LED beads based on the theoretical lighting signal position matching data formed by the lighting requirement data unit and the lighting position influence feature information formed by the feature extraction unit, and forming real-time lighting signal matching data.

[0061] In addition, for the multi-color infinite mirror cooling fan, the light-splitting and zone control of this application can also be improved by setting LED screens on not only the fan blades, but also on the side of the fan frame to display synchronized animation images, so as to coordinate with the changes of the fan's LED beads and achieve better visual effects.

[0062] For details, please refer to Figures 3-4 The illustrated embodiment of the multi-color infinite mirror cooling fan includes a semi-transparent mirror, a second light source full-face mirror, a first light source full-face mirror, light guide fan blades, a light shield, a multi-light source zone control component, and a fan frame base. The resulting cooling fan can be applied to high-performance computer cooling systems, gaming peripherals, and industrial equipment cooling. Through the coordinated design of the optical and thermodynamic systems, it achieves a multi-color infinite mirror visual effect while ensuring cooling efficiency, meeting users' dual needs for high-performance cooling and personalized RGB lighting effects. Furthermore, through zoned light design, combined with an anti-mixing light shield and multi-zone independently controllable LED light sources, a dynamic multi-color, multi-zone infinite mirror effect is achieved while ensuring that cooling efficiency is not affected by the optical structure.

[0063] This system determines the changes in required lighting information over time at a specific location using a lighting requirement data unit. A feature extraction unit then establishes predictive feature information that can influence nearby light control. Finally, a real-time matching unit accurately confirms the position of the LEDs to match appropriate and accurate lighting information values. These interconnected units form a cohesive whole for achieving beam splitting and zoning control, forming a crucial material foundation for its full realization.

[0064] In summary, the beneficial effects of the multi-color infinite mirror cooling fan's light-splitting and zone-control method and system provided in this embodiment of the invention are as follows:

[0065] This method analyzes the lighting control data to determine the lighting signal value at a fixed position point under time-varying conditions, establishes theoretical lighting signal position matching data, and uses historical data to determine the fan rotation characteristic information under the current state. Then, it combines the matching data and characteristic information to reasonably analyze and consider the position deviation caused by the signal delay under real-time conditions, forming lighting information position matching data that meets the current situation. This effectively ensures the accurate matching of lighting information with LED beads, making the beam splitting and zoning control more accurate and reasonable.

[0066] This system determines the changes in required lighting information over time at a specific location using a lighting requirement data unit. A feature extraction unit then establishes predictive feature information that can influence nearby light control. Finally, a real-time matching unit accurately confirms the position of the LEDs to match appropriate and accurate lighting information values. These interconnected units form a cohesive whole for achieving beam splitting and zoning control, forming a crucial material foundation for its full realization.

[0067] In the embodiments of this application, "instruction" can include direct and indirect instructions, as well as explicit and implicit instructions. The information indicated by a certain piece of information is called the information to be instructed. In the specific implementation process, there are many ways to instruct the information to be instructed, such as, but not limited to, directly instructing the information to be instructed, such as the information to be instructed itself or its index. It can also indirectly instruct the information to be instructed by instructing other information, where there is a relationship between the other information and the information to be instructed. It can also instruct only a part of the information to be instructed, while the other parts are known or pre-agreed upon. For example, the instruction of specific information can be achieved by using a pre-agreed (e.g., protocol-defined) arrangement of various pieces of information, thereby reducing instruction overhead to some extent. At the same time, common parts of various pieces of information can be identified and uniformly indicated to reduce the instruction overhead caused by individually indicating the same information.

[0068] Furthermore, the specific indication method can also be any existing indication method, such as, but not limited to, the above-mentioned indication methods and their various combinations. Specific details of various indication methods can be found in existing technologies, and will not be repeated here. As described above, for example, when multiple pieces of information of the same type need to be indicated, the indication methods for different pieces of information may differ. In the specific implementation process, the required indication method can be selected according to specific needs. This application embodiment does not limit the selected indication method; therefore, the indication methods involved in this application embodiment should be understood to cover various methods that enable the party to be indicated to obtain the information to be indicated.

[0069] It should be understood that the information to be indicated can be sent as a whole or divided into multiple sub-information messages sent separately, and the sending period and / or timing of these sub-information messages can be the same or different. The specific sending method is not limited in this application embodiment. The sending period and / or timing of these sub-information messages can be predefined, for example, according to a protocol, or configured by the sending device by sending configuration information to the receiving device.

[0070] "Predefined" or "pre-configured" can be achieved by pre-saving corresponding codes, tables, or other means that can be used to indicate relevant information in the device. This application does not limit the specific implementation method. "Saving" can refer to saving in one or more memories. These memories can be separate installations or integrated into the encoder, decoder, processor, or communication device. Alternatively, some memories can be separately installed, while others are integrated into the decoder, processor, or communication device. The type of memory can be any form of storage medium, and this application does not limit this.

[0071] The “protocol” mentioned in the embodiments of this application may refer to a protocol family in the field of communication, a standard protocol with a similar protocol family frame structure, or a related protocol applied to future communication systems. The embodiments of this application do not specifically limit this.

[0072] In the embodiments of this application, descriptions such as "when," "under the circumstances," "if," and "if" all refer to the device making corresponding processing under certain objective circumstances, and are not limited to a specific time. They do not require the device to make a judgment action during implementation, nor do they imply any other limitations.

[0073] In the description of the embodiments of this application, unless otherwise stated, " / " indicates that the objects before and after are in an "or" relationship. For example, A / B can represent A or B. "And / or" in the embodiments of this application is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone, where A and B can be singular or plural. Furthermore, in the description of the embodiments of this application, unless otherwise stated, "multiple" refers to two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple. Additionally, to facilitate a clear description of the technical solutions of the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first," "second," etc., do not limit the quantity or order of execution, and that "first," "second," etc., are not necessarily different. Furthermore, in the embodiments of this application, words such as "exemplary" or "for example" are used to indicate that something is being used as an example, illustration, or description. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner for ease of understanding.

[0074] It should be understood that the processor in the embodiments of this application can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0075] It should also be understood that the memory in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DRRAM).

[0076] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0077] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0078] In this application, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or multiple items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0079] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0080] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0081] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0082] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0083] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0084] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0085] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0086] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for controlling the light distribution and zoning of a multi-color infinite mirror-finish cooling fan, characterized in that, include: Acquire lighting control data, perform lighting signal mapping analysis based on location information, and generate theoretical lighting signal position matching data; Collect historical rotational motion data, extract feature information that affects the lighting position, and form lighting position influence feature information; By combining the theoretical lighting signal position matching data and the lighting position influence feature information, real-time matching analysis of lighting signals for different LED beads is performed to form real-time lighting signal matching data.

2. The method for beam splitting and zone control of a multi-color infinite mirror cooling fan according to claim 1, characterized in that, The process of acquiring lighting control data, performing lighting signal mapping analysis based on location information, and forming theoretical lighting signal position matching data includes: With the center of fan rotation as the origin and the plane where the LED beads are located as the coordinate plane, establish a lighting mapping angle coordinate system; Based on the lighting control data, determine the lighting signals corresponding to different positions in the lighting mapping angular coordinate system over the entire lighting control duration, and form the theoretical lighting matching mapping function F for the position points. n (θ n L n S n (t)), θ n L represents the angle value determined by the position point numbered n in the illumination mapping angular coordinate system. n S represents the length of the coordinate origin of the position point numbered n in the illumination mapping angular coordinate system. n (t) represents the lighting signal value at position n, determined by the angle and length values, which changes over the fan's running time; The theoretical lighting matching mapping function F for all location points is set. n (θ n L n S n (t)) forms the theoretical lighting signal position matching data.

3. The method for beam splitting and zone control of a multi-color infinite mirror cooling fan according to claim 2, characterized in that, The historical rotational motion data is collected, and feature information affecting the lighting position is extracted to form lighting position influence feature information, including: Based on the historical rotational motion data, the rotational operation data after the fan started M times is extracted, and rotational feature extraction and analysis are performed for different operation stages to form rotational feature data corresponding to different operation stages. The rotation feature data corresponding to different operating stages are collected to form the lighting position influence feature information.

4. The method for beam splitting and zone control of a multi-color infinite mirror cooling fan according to claim 3, characterized in that, The step involves extracting rotational operation data after M fan starts based on the historical rotational motion data, and performing rotational feature extraction and analysis for different operation stages to form rotational feature data corresponding to different operation stages, including: Set a stable speed fluctuation difference and a stage judgment window duration, and divide the operation stage of the rotation data after each fan start-up into the following manner: For each fan start-up operation data, starting from the time the fan starts rotating, the window duration is used as the judgment time period. The window slides over the entire running time of the fan. When the maximum difference in fan speed within the time interval defined by the first stage judgment window duration is not greater than the stable speed fluctuation difference, the entire running time before the corresponding time interval is determined as the start-up stage. When the maximum difference in fan speed within the time interval defined by the last stage judgment window duration is not greater than the stable speed fluctuation difference, the entire running time after the corresponding time interval is determined as the stop stage. The time period between the start-up stage and the stop stage is determined as the intermediate running stage. The rotational motion data during the startup phase are analyzed by extracting rotational features based on startup characteristics to form startup rotational feature data. For the rotational speed motion data during the intermediate operation phase, rotational feature extraction and analysis based on stable operation characteristics are performed to form stable rotational feature data; The rotational motion data during the stationary phase are analyzed by extracting rotational features based on the characteristics of stationary operation, thus forming stationary rotational feature data.

5. The method for beam splitting and zone control of a multi-color infinite mirror cooling fan according to claim 4, characterized in that, The process involves extracting rotational speed data during the startup phase from the rotational operation data after each fan startup, performing rotational feature extraction and analysis based on startup characteristics, and forming startup rotational feature data, including: For each corresponding startup and operation phase, extract the corresponding speed change data to form the corresponding sub-term startup speed change function. The starting speed change function corresponding to different sub-terms The following fitting method is used to form the characteristic variation function of the starting rotation speed. The preset start-up rotation speed characteristic change function The unknown parameters are determined, and the same number of different sub-terms of the starting speed change function are arbitrarily extracted based on the total number of unknown parameters. A fitting analysis was performed to determine the characteristic variation function of the initial starting rotational speed; For the remaining start-up rotation speed characteristic change function According to the order of the corresponding sub-items, the cumulative deviation of the corresponding time interval is confirmed with the initial start-up rotation speed characteristic change function. If the cumulative deviation is not less than the cumulative deviation limit, then the corresponding start-up rotation speed characteristic change function is... The initial starting rotation speed characteristic change function is averaged over the corresponding time interval and smoothed over the entire time period. This process is repeated for each of the initial starting rotation speed characteristic change functions. The comparison process continues until the remaining starting rotation speed characteristic change function is exhausted. The resulting change function is calibrated as the characteristic change function of the starting rotation speed.

6. The method for beam splitting and zone control of a multi-color infinite mirror cooling fan according to claim 5, characterized in that, The rotational motion data during the intermediate operation phase is subjected to rotational feature extraction and analysis based on stable operation characteristics to form stable rotational feature data, including: For each corresponding intermediate running stage, the characteristic change function of the stable rotational speed of the secondary term is obtained in the following way: Each intermediate operation phase is divided into time periods to ensure that the difference in the cumulative speed between each time period is not greater than the cumulative difference limit of the stable cycle. Then, the corresponding time period is determined as the stable change cycle, and the sub-term period stable speed change function within each stable change cycle is obtained. For each of the stable change cycles, the mean value is applied to the periodic stable rotational speed change function corresponding to the second term, resulting in the corresponding characteristic change function of the stable rotational speed. The characteristic change function of the stable rotational speed of the term corresponding to the earliest term. Based on the basic data, determine the characteristic change function of the stable rotational speed of the other terms. The difference relative to the basic data is used to determine the average unit time difference by arranging the differences in chronological order of the sub-items. Based on the average unit time difference and the basic data, the characteristic change function of the stable rotational speed is formed.

7. The method for beam splitting and zone control of a multi-color infinite mirror cooling fan according to claim 6, characterized in that, The rotational motion data during the stopped operation phase is subjected to rotational feature extraction and analysis based on the characteristics of the stopped operation to form stopped rotational feature data, including: For each corresponding stop operation phase, extract the corresponding speed change data to form the corresponding stop speed change function. The stop speed change function corresponding to different terms The following fitting method is used to form the characteristic change function of the rotational speed at rest. The preset stop rotation speed characteristic change function The unknown parameters are determined, and the same number of different sub-terms of the stop speed change function are arbitrarily extracted based on the total number of unknown parameters. A fitting analysis was performed to determine the characteristic change function of the initial stop rotation speed; For the remaining characteristic change function of the stop rotation speed According to the order of the corresponding sub-items, the cumulative deviation of the corresponding time interval is confirmed with the initial stop rotation speed characteristic change function. If the cumulative deviation is not less than the cumulative deviation limit, then the corresponding stop rotation speed characteristic change function is... The initial stop rotation speed characteristic change function is averaged over the corresponding time interval and smoothed over the entire time period. This process is repeated for each of the stop rotation speed characteristic change functions. The comparison process continues until the remaining characteristic change function of the stop rotation speed is exhausted. The resulting change function is calibrated as the characteristic change function of the stop rotation speed.

8. The method for beam splitting and zone control of a multi-color infinite mirror cooling fan according to claim 7, characterized in that, The process involves combining the theoretical lighting signal position matching data and the lighting position influence feature information to perform real-time lighting signal matching analysis for different LED beads, forming real-time lighting signal matching data, including: According to the starting rotation speed characteristic change function The corresponding start-up limit duration and the characteristic change function of the stop rotation speed. The stop limit duration and the real-time estimated total running time are used to determine the real-time stable estimated running time. Determine the duration of the current fan operation relative to the baseline data, and combine it with the stable rotation speed characteristic change function. and the real-time stable estimated runtime Determine the real-time stable rotational speed variation function According to the starting rotation speed characteristic change function The characteristic change function of the rotational speed at which the rotation stops and the expected real-time stable runtime The corresponding real-time stable rotation speed change function Smoothing is performed to generate a real-time speed change function. Determine the real-time lighting signal time t time Acquire signal extended duration t delay And combined with the real-time rotation speed change function Position matching analysis is performed to generate real-time matching data for the lighting signal.

9. The method for beam splitting and zone control of a multi-color infinite mirror cooling fan according to claim 8, characterized in that, The determination of the real-time lighting signal time t time Acquire signal extended duration t delay And combined with the real-time rotation speed change function Perform position matching analysis to generate real-time matching data for the lighting signal, including: According to the real-time lighting signal time t time Determine the non-delay position parameters of the LED. k is the sequential number of the different LED beads, and This indicates that the LED with the number k is lit during the real-time lighting signal time t. time The corresponding angle value, and L k This indicates that the LED with the number k is lit during the real-time lighting signal time t. time The length of the current location point relative to the origin of the coordinate system; Based on the signal extension time t delay and the real-time rotation speed change function Determine the angle of delay change in, Based on the non-delay position parameters of the LED beads and the delay change angle Determine the real-time position parameters of the LED beads in, This represents the real-time angle value of the LED with the number n, and According to the real-time position parameters of the LED beads And combine the aforementioned position point theory to illuminate the matching mapping function F n (θ n L n S n (t)) determines the duration of the LED bead in time t. time +t delay The corresponding lighting signal value; The lighting signal values ​​corresponding to all LED beads are collected to form real-time matching data for the lighting signal.

10. A spectral partitioning control system for a multi-color infinite mirror cooling fan, employing the spectral partitioning control method for a multi-color infinite mirror cooling fan as described in any one of claims 1-9, characterized in that... include: The lighting requirement data unit is used to acquire lighting control data, perform lighting signal mapping analysis based on location information, and form theoretical lighting signal position matching data. The feature extraction unit is used to collect historical rotational motion data, extract feature information that affects the lighting position, and form lighting position influence feature information. The real-time matching unit is used to perform real-time matching analysis of lighting signals for different LED beads based on the theoretical lighting signal position matching data formed by the lighting requirement data unit and the lighting position influence feature information formed by the feature extraction unit, and to form real-time matching data of lighting signals.

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