System for controlling mosquito killer lamp based on sound frequency and control method thereof

Abstract

The invention belongs to the technical field of sound wave control, and discloses a system for controlling a mosquito killer lamp based on sound frequency and a control method thereof, and the system comprises a sound pressure response calibration module, a rhythm section screening module, a frequency band conflict recognition module, a rhythm drift rearrangement module, and a mosquito killer lamp control sequence scheduling module. According to the invention, the response capability of the sound wave control system is optimized by accurately analyzing the time synchronization of the frequency and the illumination behavior, the scheme can adjust the frequency triggering sequence and the illumination response in real time, false triggering caused by frequency overlapping is avoided, and the accuracy of the sound wave control system is improved by refining the cooperative relationship between the frequency fluctuation and the illumination change. The system can sensitively adjust the trigger time sequence when the frequency fluctuates, ensures the accurate coordination of the working states of the mosquito killing lamp and the fan, improves the matching degree of the frequency and the illumination response, enhances the control accuracy and the system stability, effectively improves the mosquito killing efficiency, and reduces the energy consumption.

Description

Technical Field

[0001] The present invention belongs to the technical field of acoustic control, and specifically, relates to a system for controlling a mosquito killing lamp based on sound frequency and its control method. Background Art

[0002] The technical field of acoustic control includes various technologies that use sound waves with specific frequencies or frequency variations to intervene or regulate objects, environments, or biological behaviors; the core content of this technical field is to control the sound propagation process and its affected objects by modulating parameters such as the frequency, intensity, and waveform of sound waves; acoustic control can be applied to biological attraction, remote detection, sound source identification, frequency interference, etc., covering technical contents such as sound source generation, frequency detection, and sound wave propagation path design; the acoustic control field usually combines methods such as spectrum analysis, acoustic wave identification, frequency modulation, and analysis to implement specific control behaviors on target objects within the range of acoustic wave action, with characteristics such as non-contact and controllable range, forming an application system in multiple directions such as pest control, intelligent interaction, and environmental regulation.

[0003] Among them, the system for controlling a mosquito killing lamp based on sound frequency refers to a device and its operation plan that detect and discriminate the sound wave frequency within a specific range and control the start and stop states of the mosquito killing lamp according to the discrimination result; the patent theme mainly covers the determination logic of the working state of the mosquito killing lamp, the sound wave acquisition method, and the setting of the audio threshold. Specifically, the sound wave in the range of 250 Hz to 600 Hz is used as the source of the discrimination signal, and the time period matching rule is used to identify whether there is a target sound source, and the start and stop of the blowing mechanism and the lamp body are executed in combination with the control port; this solution determines whether to execute or turn off power equipment such as the fan by setting the time determination range and detecting the sound wave value multiple times, based on whether the sound wave frequency meets the set value and time conditions, thus completing the full process description of the control behavior of the mosquito killing lamp.

[0004] In practical applications, the existing technology has the problem of poor frequency adaptability, which is mainly reflected in the insufficiently fine processing of the relationship between frequency changes and lighting control; traditional solutions usually rely on single frequency detection and do not fully consider the dynamic interaction between different frequencies, which makes the system insufficiently responsive to rapid changes in the ambient frequency and may lead to unnecessary mis-triggering of the lamp body or fan; for example, when the ambient noise suddenly changes, the existing technology may not be able to adjust the frequency control strategy in time, resulting in untimely turning on or off of the mosquito lamp, affecting the mosquito killing efficiency and system stability; in addition, the existing solutions are relatively simple in dealing with frequency band conflicts and cannot effectively identify the offsets in rhythm changes and the overlapping relationship of frequencies, which makes it difficult for the system to optimize and adjust the response order in the case of a dense frequency band, resulting in lag or advance of the response and inability to achieve precise control; generally speaking, the existing technology relies on relatively rough time period matching and frequency detection methods and fails to optimize the coordination between frequency control and lighting behavior in detail, resulting in the system being prone to errors when dealing with complex environments and reducing the overall effect and efficiency of the system. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a system and its control method for controlling a mosquito lamp based on sound frequency, which accurately analyzes the time synchronization between frequency and lighting behavior, optimizes the response ability of the sound wave control system, adjusts the frequency trigger sequence and lighting response in real time, avoids mis-triggering caused by frequency overlap, and through refining the coordination relationship between frequency fluctuation and lighting change, can sensitively adjust the trigger timing when the frequency fluctuates, ensure the precise coordination of the working states of the mosquito lamp and the fan, improve the matching degree of frequency and lighting response, enhance the control accuracy and system stability, and effectively improve the mosquito killing efficiency and reduce energy consumption.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: A system for controlling a mosquito lamp based on sound frequency includes: The sound pressure response calibration module acquires sound pressure waveform data, extracts the starting point and peak value of the continuous rising segment, analyzes the coordination relationship between the frequency growth process and the duration extension process, screens the periodic response segments, and obtains the sound frequency linkage recognition segments; The beat section screening module, based on the sound frequency linkage recognition segments, extracts the brightness response time and aligns it with the segment boundary, analyzes the time synchronization relationship between the continuous process of lighting change and the frequency fluctuation, and identifies the control response paragraphs of the rhythm characteristics to obtain the beat linkage response section table; The frequency band conflict identification module, based on the beat linkage response section table, identifies the beats with overlapping start and end times, extracts the difference between the starting points of adjacent beats and analyzes the signal interference conditions to obtain the control conflict mark list; The rhythm drift rearrangement module extracts the frequency order of the non-conflicting beat segments based on the control conflict marker list, identifies the rhythm offset in the time interval, adjusts the response order, and updates the beat sequence to obtain the beat rhythm reconstruction order table; The mosquito killing lamp control sequence scheduling module arranges the lighting response trigger positions based on the frequency sorting in the beat rhythm reconstruction order table, and summarizes the lighting control paths corresponding to the beat triggers to obtain the mosquito killing response state sequence under sound control drive.

[0007] The following is a further optimization of the above technical solution of the present invention: The audio frequency linkage recognition segment is specifically the synchronism of the starting point of the continuous rising segment, the peak position, the frequency growth process, the duration extension process, and the periodic response characteristics. The beat linkage response section table is specifically the brightness response time, the start and end points of the segment, the lighting change process, the frequency fluctuation synchronization relationship, and the rhythm characteristic control response paragraph. The control conflict marker list is specifically the beat sequence number, the staggered starting point, the overlapping relationship between beats, the starting position difference, and the signal interference trigger condition. The beat rhythm reconstruction order table is specifically the frequency order, the response time interval between adjacent frequency segments, the rhythm offset, the updated response order, and the beat sequence. The mosquito killing response state sequence is specifically the frequency control signal access process, the lighting response trigger position, the lighting control path, and the lighting response behavior execution order.

[0008] Further optimization: The sound pressure response calibration module includes: The sound pressure segment extraction sub-module extracts the starting point and peak position of the continuous rising segment based on the sound pressure waveform change generated by the mosquito killing lamp under the control of the sound frequency during operation, records the starting point and peak point positions of the rising segment on the time axis, and obtains the sound pressure rising segment coordinate set; The change section identification sub-module identifies the arrangement order of the continuous sound pressure rising segments on the time axis based on the sound pressure rising segment coordinate set, extracts the connection trend and frequency value change direction between adjacent rising segments, and obtains the frequency change continuous section set; The periodic trend screening sub-module extracts the distribution order of the fluctuation segments in the time series based on the frequency change continuous section set, identifies the spacing fitting degree and the change rule repeatability between multiple continuous frequency segments, and screens the sound pressure segments showing periodic stability characteristics to obtain the audio frequency linkage recognition segment.

[0009] Further optimization: The beat section screening module includes: The brightness time extraction sub-module extracts the brightness response time during the lighting change process based on the audio frequency linkage recognition segment, obtains the start and end boundary time points of the audio frequency segment, performs time alignment of the brightness change starting point and the start and end points of the audio frequency segment, and generates the brightness frequency band alignment information set; The response corresponding recognition sub-module analyzes the continuous performance of the lighting output change within the corresponding audio frequency segment based on the luminance frequency band pair information set, identifies the frequency change direction and fluctuation trend within the continuous lighting change time period, summarizes the corresponding distribution of the two types of data on the time axis, and generates a luminance frequency synchronization feature group; The rhythm paragraph screening sub-module extracts the audio frequency band numbers with synchronization features based on the luminance frequency synchronization feature group, identifies the audio frequency control behavior paragraphs corresponding to the rhythm features in the lighting response, and obtains a beat linkage response section table.

[0010] Further optimization: The frequency band conflict recognition module includes: The time overlap extraction sub-module extracts the beat segment combinations with time overlap by comparing the start and end time positions of the beat segments based on the beat content in the beat linkage response section table, identifies the cross region and start and end order of the combinations on the time axis, and obtains a beat overlap time period set; The difference relationship recognition sub-module extracts the start and end intervals of the beat segments during the overlap period based on the beat overlap time period set, calculates the covered time length of the beat segments during the overlap period, analyzes the concentration degree of the distribution of the covered time lengths, identifies the influence boundary of the beat segments on adjacent control behaviors, and generates a beat coverage duration index group; The conflict sequence marking sub-module identifies the beat numbers with a coverage duration higher than that of adjacent segments based on the beat coverage duration index group, extracts the staggered response positions between the beat segments, and obtains a control conflict marking list.

[0011] Further optimization: The specific calculation formula for the covered time length of the beat segments during the overlap period is: ; Wherein, represents the weighted covered time length of the th beat segment during all overlap periods, represents the number of overlap time periods included in the th beat segment, represents the covered time length of the th beat segment during the th overlap period, that is, the difference between the start and end times, represents the overlap intensity weight of the th beat segment during the th overlap period, represents the absolute value of the difference between the control behavior time interval corresponding to the th beat segment during the th overlap period and the average value of the corresponding time intervals of all overlap periods of this beat segment, represents the th beat segment and the adjacent beat segment during the The start time difference between the start points of overlapping periods represents the beat number difference within the th overlapping period for the

[0012] Further optimization: The rhythm drift rearrangement module includes: The frequency order extraction sub-module extracts the frequency trigger order corresponding to the beat segments without interference based on the control conflict flag list, records the frequency value and trigger time point of each beat segment, organizes them into a frequency order data table, and generates a frequency trigger order list; The response interval detection sub-module checks the response time interval of adjacent frequency segments on the time axis based on the frequency trigger order list, analyzes the time response change situation between frequency segments, identifies the time fluctuation trend, and obtains a time fluctuation response feature set; The beat order adjustment sub-module calculates the response offset direction of the beat segments on the time axis based on the time fluctuation response feature set, adjusts the activation order of the beat segments according to the offset direction, and reorganizes the order of the lighting control responses to obtain a beat rhythm reconstruction order table.

[0013] Further optimization: The calculation formula for the response offset direction of the beat segments on the time axis is specifically: ; where, represents the response offset direction of the th beat segment on the time axis, represents the number of sampling points included in the th beat segment, represents the original trigger time of the th sampling point in the th beat segment, represents the average trigger time of all sampling points in the th beat segment, represents the th sampling point in the th beat segment in the trigger time dimension weight factor, represents the th sampling point in the th beat segment time fluctuation response amplitude, represents the average value of the time fluctuation response amplitude in the th beat segment, represents the th sampling point in the th beat segment forward offset residual value, represents the th beat segment in the Local trigger density factor of each sampling point Represents a very small positive real constant used to avoid a zero denominator.

[0014] Further optimization: The mosquito killing lamp control sequence scheduling module includes: The response position sorting sub-module arranges the response trigger positions in the lighting control based on the frequency sorting result in the beat rhythm reconstruction sequence table, and generates a response trigger position table; The control signal generation sub-module generates a frequency control signal access process based on the response trigger position table, analyzes the control signal paths of each trigger point, and obtains a frequency modulation signal path diagram; The behavior execution order recording sub-module records the lighting action response path based on the frequency modulation signal path diagram, arranges the execution order of the response behaviors along the time axis, and obtains the mosquito killing response behavior execution order.

[0015] The present invention also provides a control method for a mosquito killing lamp based on sound frequency. Based on the above system for controlling a mosquito killing lamp based on sound frequency, it includes the following steps: S1: Obtain the change in sound pressure waveform generated during the operation of the sound frequency-controlled mosquito killing lamp, extract the starting point and peak position of the continuously rising section, identify the relationship between the sound pressure change and the time duration in the frequency fluctuation section, analyze the synchronization between the frequency value growth process and the duration extension process, and screen out the response audio segments that exhibit periodic stability characteristics in the synchronization relationship to obtain the audio linkage recognition segments; S2: Based on the audio linkage recognition segments, extract the brightness response time during the lighting change process and align it with the start and end points of the segments, analyze the continuous response process of the lighting output change within the segments, distinguish the synchronous correspondence relationship between the brightness change process and the frequency fluctuation process during the audio frequency change stage, and identify the control response paragraphs that exhibit rhythm characteristics to obtain the beat linkage response section table; S3: Based on the beat content in the beat linkage response section table, identify the overlapping relationship between the beats by comparing the start and end time positions, extract the starting position differences between several beat segments within the lighting response stage, analyze the trigger conditions of signal control conflicts based on the difference range, and record the beat sequence numbers and overlapping starting points with sequential interference to obtain a control conflict mark list; S4: Based on the control conflict mark list, extract the trigger order of the frequencies corresponding to the non-interfering beat segments, check the response time intervals between adjacent frequency segments on the time axis, identify the offset characteristics in the change trend of the response time intervals, adjust the activation order of the corresponding beat segments according to the offset direction, and reorganize the control sequence in the lighting response to obtain a beat rhythm reconstruction sequence table; S5: Reconstruct the frequency sorting result in the sequence table based on the beat rhythm, arrange the response trigger positions in the lighting control, establish the access process of the frequency control signal according to the rearranged order, summarize the lighting action response path triggered by the beat segment, and record the execution order of the lighting response behavior corresponding to the frequency on the time axis to obtain the mosquito-killing response state sequence under sound control.

[0016] The present invention adopts the above technical solutions and has at least the following beneficial effects: In the present invention, by accurately analyzing the time synchronization between the frequency and the lighting behavior, the response ability of the sound wave control system is optimized. This solution can adjust the frequency trigger order and lighting response in real time, avoiding mis-triggering caused by frequency overlap. By refining the coordination relationship between frequency fluctuations and lighting changes, the system can sensitively adjust the trigger timing when the frequency fluctuates, ensuring the precise coordination of the working states of the mosquito-killing lamp and the fan. The optimized system improves the matching degree between the frequency and the lighting response, enhances the control accuracy and system stability, effectively improves the mosquito-killing efficiency and reduces the energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is the system flow chart of the embodiment of the present invention; Figure 2 is the system block diagram of the embodiment of the present invention; Figure 3 is the step flow chart of the control method in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the drawings and embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0019] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as limiting the present invention; in addition, in the description of the present invention, the meaning of "a plurality" is two or more unless otherwise specifically defined.

[0020] Please refer to Figure 1 , a system for controlling a mosquito-killing lamp based on sound frequency, comprising: The sound pressure response calibration module obtains the change in the sound pressure waveform generated by the mosquito killing lamp during operation under sound frequency control, extracts the starting point and peak position of the continuously rising segment, identifies the relationship between the sound pressure change and the time duration in the frequency fluctuation section, analyzes the synchronization between the frequency value growth process and the duration extension process, screens out the response audio frequency segments showing periodic stability characteristics in the synchronization relationship, and obtains the audio frequency linkage recognition segments; The beat section screening module, based on the audio frequency linkage recognition segments, extracts the brightness response time during the lighting change process and aligns it with the start and end points of the segments, analyzes the continuous response process of the lighting output change within the segments, distinguishes the synchronous correspondence relationship between the brightness change process and the frequency fluctuation process in the audio frequency change stage, and identifies the control response paragraphs showing rhythm characteristics, obtaining the beat linkage response section table; The frequency band conflict identification module, based on the beat content in the beat linkage response section table, identifies the overlapping relationship between beats by comparing the start and end time positions, extracts the start position differences between several beat segments within the lighting response stage, analyzes the triggering conditions of signal control conflicts according to the difference range, and records the beat sequence numbers and staggered starting points with sequential interference, obtaining the control conflict mark list; The rhythm drift rearrangement module, based on the control conflict mark list, extracts the triggering order of the frequencies corresponding to the non-interfering beat segments, checks the response time intervals of adjacent frequency segments on the time axis, identifies the offset characteristics in the change trend of the response time intervals, adjusts the activation order of the corresponding beat segments according to the offset direction, reorganizes the control sequence in the lighting response, and obtains the beat rhythm reconstruction order table; The mosquito killing lamp control sequence scheduling module, based on the frequency sorting result in the beat rhythm reconstruction order table, arranges the response trigger positions in the lighting control, establishes the access process of the frequency control signal according to the rearrangement order, summarizes the lighting action response path triggered by the beat segments, and records the execution order of the lighting response behavior corresponding to the frequency on the time axis, obtaining the mosquito killing response state sequence under sound control drive.

[0021] The audio frequency linkage recognition segments include the starting point of the continuously rising segment, the peak position, the frequency growth process, the synchronization of the duration extension process, and the periodic response characteristics; the beat linkage response section table includes the brightness response time, the start and end points of the segments, the lighting change process, the frequency fluctuation synchronization relationship, and the rhythm characteristic control response paragraphs; the control conflict mark list includes the beat sequence number, the staggered starting point, the overlapping relationship between beats, the start position difference, and the signal interference triggering conditions; the beat rhythm reconstruction order table includes the frequency order, the response time intervals of adjacent frequency segments, the rhythm offset, the updated response order, and the beat sequence; the mosquito killing response state sequence includes the access process of the frequency control signal, the lighting response trigger position, the lighting control path, and the execution order of the lighting response behavior.

[0022] Please refer to Figure 1 andFigure 2 , the sound pressure response calibration module includes: The sound pressure segment extraction sub-module extracts the starting point and peak position of the continuously rising segment based on the change of the sound pressure waveform generated by the mosquito killer lamp during operation, records the starting point and peak point positions of the rising segment on the time axis, and obtains the sound pressure rising segment coordinate set.

[0023] First, the rising segment in the sound pressure waveform needs to be identified; in specific operations, by comparing the point-by-point numerical changes of the waveform, the continuously rising trend part is identified, and the "rising segment" is defined as the part where the sound pressure value rises smoothly from a lower point to the peak, and the time span of the rising process should remain stable; for each rising segment, its starting point and peak position will be extracted from the time axis, where the starting point is the moment when the sound pressure value first increases significantly, and the peak position is the moment when the maximum value of the sound pressure value in this segment appears; this process gradually records the starting point and peak point of each rising segment through real-time signal acquisition and data processing; to ensure the accuracy of the results, a threshold range is set, usually when the sound pressure value rises to a certain fixed percentage (such as 30%), it is calibrated as the starting point; for example, assuming the initial sound pressure is 20dB and the threshold is 30%, then when the sound pressure reaches 26dB, this point is regarded as the starting point of the rising segment; the peak position is the maximum value within the entire rising segment, and at this time the sound pressure reaches the maximum value and no longer rises; through this process, it is possible to accurately capture the starting time and peak time of each sound pressure rising segment, generate a relevant data list, and obtain the sound pressure rising segment coordinate set.

[0024] The change section identification sub-module identifies the arrangement order of the continuous sound pressure rising segments on the time axis based on the sound pressure rising segment coordinate set, extracts the connection trend and frequency value change direction between adjacent rising segments, and obtains the frequency change continuous section set.

[0025] First, use the sound pressure rising segment coordinate set as the input data set. These data sets contain the starting points and peak points of each continuous rising segment from the initial sound pressure to the peak. Next, by sorting the timestamps of these rising segments, identify their arrangement order on the time axis. This process first requires extracting the timestamps of the starting point and peak point of each rising segment, and then arranging them in ascending order of timestamps to obtain the order of the rising segments in time. Through this sorting, the positional relationship of each rising segment on the time axis can be clearly identified, and the time intervals between rising segments can be identified. In practical applications, assume that the timestamps of the sound pressure rising segments are T1 (starting point), T2 (peak), and T3 (next starting point). By sorting these timestamps, it can be obtained how these rising segments are closely connected in time. For example, if T1 = 0.5 seconds, T2 = 0.8 seconds, and T3 = 1.2 seconds, the time interval is T3 - T2 = 0.4 seconds, that is, the time interval between rising segment 1 and rising segment 2 is 0.4 seconds. Next, further extract the rules between these time intervals and analyze whether there are specific connection trends, such as whether the time intervals are stable or whether there are periodic fluctuations. For these trends, conduct relevant analyses, such as setting a threshold range to identify whether there are significant interval changes or periodic changes. For example, if the time intervals between adjacent rising segments are always less than 0.5 seconds and have strong regularity, it can be determined that these rising segments are continuous frequency fluctuation segments and there may be periodic changes. On the contrary, if the time interval is greater than 0.5 seconds, it may be a non-periodic fluctuation. Then, based on the analysis results of these data, screen out the sections that meet certain conditions to obtain the set of continuous frequency change sections.

[0026] Based on the set of continuous frequency change sections, the periodic trend screening sub-module extracts the distribution order of the fluctuation segments in the time series, identifies the spacing fitting degree and the repeatability of the change rules between multiple continuous frequency segments, screens out the sound pressure segments showing periodic stable characteristics, and obtains the audio-frequency linkage recognition segments. First, by analyzing the set of continuous frequency change segments, each frequency segment can be segmented and identified. The continuous frequency change segments are extracted one by one, and their distribution order in the time series is recorded. Specifically, first, the starting point and ending point of each frequency segment are calibrated. Based on these calibration points, the duration and frequency fluctuation range of each frequency change segment are extracted. Then, by comparing the time intervals between multiple continuous frequency segments, their connection relationships and trends are identified. In this process, parameters such as the starting point, ending point, and time interval between frequency segments need to be compared to determine whether these segments form a periodic fluctuation. For example, if the time interval between two adjacent frequency segments is short and their change rules are similar, it is judged that they may belong to the fluctuation segments within the same period. To further confirm the periodic characteristics of the fluctuation, a goodness-of-fit analysis is performed on the change rules between multiple frequency segments. At this time, according to parameters such as historical data, duration, and frequency value changes, appropriate criteria are used to evaluate whether the changes in these frequency segments have periodic stability. For example, assume that the duration of the first segment is 2 seconds, and the frequency change range is from 20 Hz to 30 Hz. The duration of the second segment is 2.1 seconds, and the frequency change range is from 20.5 Hz to 30.5 Hz. The durations and frequency fluctuation ranges of the two segments are similar, and the time interval is short. Therefore, these two frequency segments are determined to have a periodic change rule. In practice, by statistically analyzing the time intervals, frequency fluctuation ranges, durations, etc. between multiple frequency segments, the sound pressure segments that exhibit periodic stability characteristics can be identified. According to these criteria, the qualified segments are screened out to obtain the audio-linked recognition segments.

[0027] Please refer to Figure 1 and Figure 2 , the beat section screening module includes: The brightness time extraction sub-module extracts the brightness response time during the lighting change based on the audio-linked recognition segments, obtains the start and end boundary time points of the audio segments, performs time alignment between the starting point of the brightness change and the start and end points of the audio segments, and generates a brightness frequency band alignment information set.

[0028] First, based on the audio-linked recognition segments, the start time point and end time point of each audio segment need to be corresponded to the brightness response time of the lighting change; specifically, first, the start and end times of each frequency band will be extracted from the audio-linked recognition segments, and their positions on the time axis will be recorded; for example, if an audio segment ranges from time point T1 to T2, then the corresponding lighting response also needs to start from time T1 and end at T2; then, by comparing the response waveforms of the lighting brightness, the brightness changes of the lighting between these time points will be extracted; if the lighting brightness starts to change and remains continuous within a certain period of time, record the start point of the brightness change corresponding to the start point of the audio segment; at the same time, the end point of the brightness change is docked with the end time point of the audio segment to ensure a complete match between the two; for example, assume that the start point of the audio segment is T1 = 0.5 seconds and the end point is T2 = 1 second, and the corresponding lighting brightness starts to change from T1, the brightness at T1 is 20%, and reaches 100% at 1 second; identify this brightness response process and align it with the time axis of the audio segment to obtain an exact match between the brightness change and the audio segment within the time range [0.5 seconds, 1 second]; further, record the corresponding information of all the start and end points of the brightness and the start and end points of the audio segments, and generate a time alignment information set for each matched alignment data; this process accurately locates the start and end time points of the brightness change by comparing the lighting response time and the time stamps of the audio segments, so that the two signals have a completely synchronous relationship in time; for example, assume that the recorded audio segment and the brightness change time are respectively from T1 = 0.5 seconds to T2 = 1 second and the brightness change from 0.5 seconds to 1 second, and the start and end times of the two signals are completely aligned, generating a brightness frequency band alignment information set.

[0029] Based on the brightness frequency band alignment information set, the response corresponding recognition sub-module analyzes the continuous performance of the lighting output change within the corresponding audio segment, identifies the frequency change direction and fluctuation trend within the continuous lighting change time period, summarizes the corresponding distribution of the two types of data on the time axis, and generates a brightness frequency synchronization feature group.

[0030] First, it is necessary to identify the changes in lighting output and determine the brightness changes of lighting in each time segment and their corresponding audio segments. In specific operations, according to the start and end time points in the brightness frequency position information set, the start point of the lighting change is aligned with the start point of the audio segment to ensure their synchronous relationship in time. For example, assume that the start point of an audio segment is 0.5 seconds and the lighting brightness starts to change during this period. Align the start point of the brightness change with the start time point of the audio segment and record the moment and duration when the brightness starts to change. At this time, the brightness change trend of the lighting can be analyzed in multiple time periods, the brightness value changes and frequency fluctuations in each period are identified, and they are stored as synchronous data of lighting and frequency. Next, analyze the frequency change direction and fluctuation trend in these lighting change time periods. By calculating the relative relationship between the brightness change of the lighting and the corresponding frequency fluctuation, judge the impact of the increase or decrease of the frequency on the lighting. For example, assume that the brightness of the lighting increases from 20% to 60% between 0.5 seconds and 1 second, and during this period, the frequency of the audio changes from 100 Hz to 150 Hz. Judge that in this time period, the change directions of the lighting and the frequency are consistent (that is, the lighting brightens when the frequency increases). This analysis can be achieved by calculating the synchrony of the frequency and brightness changes, comparing the change directions and fluctuation trends of the frequencies in two time periods, and identifying the regularity therein. For example, if the brightness of the lighting steadily increases or decreases under a certain frequency change, it indicates that there is a consistent trend between the two. Summarize these data to generate a brightness frequency synchronization feature group.

[0031] Based on the brightness frequency synchronization feature group, the rhythm paragraph screening sub-module extracts the audio frequency band numbers with synchronization features, identifies the audio frequency control behavior paragraphs corresponding to the rhythm features in the lighting response, and obtains the beat linkage response section table.

[0032] First, it is necessary to screen the data in the brightness frequency synchronization feature group to extract the frequency band numbers corresponding to the lighting output. At this time, all the audio frequency bands with synchronization features are sorted according to their positions on the time axis, and it is judged one by one whether they are synchronized with the brightness change process of the lighting. For each extracted frequency band, according to the time synchronization relationship between the audio frequency and the lighting, it is determined whether it belongs to a control paragraph with rhythm features. For example, assume that the number of a frequency band is F1. During the time period of the lighting brightness change, from T1 to T2, the frequency of the audio frequency remains stable, while the lighting brightness gradually increases. It is judged that there is a synchronization relationship between this frequency change and the brightness change, and the frequency band number F1 is used as a control paragraph that conforms to the rhythm features. In this process, pay attention to the direction of the frequency change, and also judge whether the frequency change conforms to the undulating trend of the lighting brightness, such as whether the increase or decrease of the frequency is consistent with the change direction of the brightness. Next, according to these audio frequency bands that conform to the synchronization features, the distribution relationship of these paragraphs on the time axis is summarized. For example, if multiple audio frequency bands are connected to each other in time, and during this period the lighting brightness and the change direction of the audio frequency are the same, these paragraphs are classified into a control behavior paragraph. The connection method of these paragraphs is based on the order of the start and end times of the frequency bands to ensure that the triggering and control behaviors of each paragraph are coherent. In practical applications, assume that within a certain time period, the frequency gradually increases from 100 Hz to 200 Hz, and the lighting brightness increases from 10% to 90%. The synchronization relationship between the two indicates that the frequency change and the brightness change are consistent during this period. Therefore, the frequency band and the lighting paragraph during this period are classified into the same rhythm control paragraph. Finally, these rhythm paragraphs that conform to the synchronization features will be sorted out and recorded to obtain the beat linkage response section table.

[0033] Please refer to Figure 1 and Figure 2 , the frequency band conflict identification module includes: Based on the beat content in the beat linkage response section table, the time overlap extraction sub-module checks the start and end time positions of the beat segments, extracts the combination of beat segments with time overlap, identifies the cross-region and start-stop order of the combination on the time axis, and obtains the set of beat overlap time periods.

[0034] First, according to the start and end times of each beat segment in the beat linkage response section table, extract all combinations of beat segments with time overlap; for each beat segment, determine its time range from its start time to its end time, and compare with the start and end times of other beat segments; if there is an intersection in the time ranges of these two time periods, then these beat segments are considered to be an overlapping combination; for example, assume that the time range of beat A is from T1 to T2, and the time range of beat B is from T1.5 to T3, since there is an intersection in their time periods (from T1.5 to T2), so they form an overlapping beat segment combination; record this overlapping relationship and determine the position of these beat segment combinations on the time axis; next, further analyze the cross-region and start-end order of these overlapping beat segment combinations on the time axis; by comparing the start and end positions of the overlapping regions, the cross-region of each group of overlapping beat segments can be accurately identified; for example, assume that the overlapping region of beat A and beat B is between T1.5 and T2, mark this region as their cross-region, and according to their start and end times, determine whether the overlapping order is that beat A precedes beat B, or vice versa; to further optimize the time overlap recognition process, consider the duration of the overlapping time, if the duration of the overlapping region is short, then classify it as a weak overlapping relationship, otherwise, determine it as a strong overlapping relationship; set different processing priorities for different types of overlapping beat segment combinations; finally, all beat segment combinations that meet the overlapping conditions will be collected to obtain the beat overlap time period set.

[0035] Based on the beat overlap time period set, the difference relationship recognition sub-module extracts the start and end intervals of the beat segments in the overlapping period, calculates the covered time length of the beat segments in the overlapping period, analyzes the degree of concentration in the distribution of the covered time lengths, identifies the influence boundaries of the beat segments on adjacent control behaviors, and generates a beat coverage duration index group.

[0036] The specific calculation formula for the covered time length of the beat segments in the overlapping period is: ; Where represents the weighted covered time length of the th beat segment in all overlapping periods, represents the number of overlapping time periods included in the th beat segment, represents the covered time length of the th beat segment in the th overlapping period, that is, the difference between the start and end times, represents the overlapping intensity weight of the th beat segment in the th overlapping period, represents the th beat segment in the The absolute value of the difference between the control behavior time interval corresponding to a specific overlapping period and the average of the corresponding time intervals of all overlapping periods in this beat segment. represents the th beat segment and the starting time difference between the adjacent beat segment at the starting point of the th overlapping period. represents the th beat segment and the absolute value of the beat number difference within the th overlapping period.

[0037] The specific calculation process is as follows: Set ; The set values are as follows: The first segment: starting at 0.15 seconds and ending at 0.42 seconds, then ; The second segment: starting at 0.35 seconds and ending at 0.6 seconds, then ; The third segment: starting at 0.55 seconds and ending at 0.9 seconds, then ; , , ; , , ; , , ; , , ; Substitute the above values into the formula and expand the calculation as follows: Calculate item by item: The first item: ; The second item: ; The third item: ; Calculate the total value: ; The result shows that the overall coverage feature intensity value of the current beat segment in its overlapping interval is 2.843. This value, as a quantitative index in the beat coverage duration index group, is used to reflect the superposition influence degree of this beat segment in the time sequence and is called by subsequent control boundary recognition or behavior rhythm modeling processes.

[0038] The conflict sequence marking sub-module identifies the beat numbers with a coverage duration higher than that of the adjacent segments based on the beat coverage duration metric group, extracts the interleaved response positions between the beat segments, and obtains the control conflict marking list.

[0039] First, extract the duration of each beat from the beat coverage duration metric group and compare it with the duration of the adjacent beat segments to identify those beats with a coverage duration higher than that of the adjacent beat segments; through comparison, those beats that occupy a longer time period in time can be accurately found, and these beats are considered stronger control beats in subsequent analysis; for example, assume that the time of beat A is 10 seconds, the time of beat B is 8 seconds, and the time of beat C is 5 seconds; compare the time difference between beat A and beat B and find that the duration of beat A exceeds that of beat B, then beat A will be marked as the dominant beat, and then the time relationship between beat A and beat C will be further analyzed; then, extract the interleaved response positions between these beat segments, that is, the start and end time points of the intersection; by recording the time overlapping areas between beats A, B, and C, clearly mark the interleaved areas of each beat segment with other beat segments; for example, if beat A starts at 0 seconds and ends at 10 seconds, and beat B starts at 5 seconds and ends at 15 seconds, then their overlapping area is between 5 seconds and 10 seconds, and record this interleaved position; further, associate these interleaved areas with the sequence of beat segment numbers that cause interference to form a control conflict marking list.

[0040] Please refer to Figure 1 and Figure 2 , the rhythm drift rearrangement module includes: The frequency order extraction sub-module extracts the frequency trigger order corresponding to the beat segments that do not cause interference based on the control conflict marking list, records the frequency value and trigger time point of each beat segment, organizes them into a frequency order data table, and generates a frequency trigger order list.

[0041] First, extract all non-interfering beat segments from the control conflict marker list. These beat segments are those without time overlap or conflict; each beat segment has a specific frequency value and trigger time point, which are obtained in the previous analysis; by screening these beat segments, exclude all beat segments that interfere or overlap with other beat segments, ensuring that only non-conflicting beat segments are considered; for example, assume that the frequency of beat A is 100 Hz, the trigger time point is 3 seconds, the frequency of beat B is 120 Hz, the trigger time point is 5 seconds, and the frequency of beat C is 110 Hz, the trigger time point is 7 seconds; if there is no overlap between beat A and B, and there is no overlap between B and C, then beat A, B, and C will be extracted for subsequent processing; then, record the frequency values of these extracted beat segments and the corresponding trigger time points; this process is carried out by comparing the start and end times of each beat to confirm the trigger time point of the beat and ensure that the frequency value of each beat segment is correctly recorded; for example, assume that the frequency of beat A is 100 Hz, the trigger time point is 3 seconds, record this information, and record the frequency and trigger time for beat B and C respectively; then, organize the recorded frequency values and time points into a frequency order data table to ensure that each beat segment is arranged in order on the time axis; this data table contains the frequency of each beat segment and its corresponding trigger time point, generating a frequency trigger order list.

[0042] Based on the frequency trigger order list, the response interval detection sub-module checks the response time intervals of adjacent frequency segments on the time axis, analyzes the time response changes between frequency segments, identifies the time fluctuation trend, and obtains the time fluctuation response feature set.

[0043] First, obtain adjacent frequency segments from the frequency trigger order list and check the response time intervals between them on the time axis; in this process, analyze the trigger time points of each frequency segment and calculate the time differences between adjacent frequency segments; these time differences are the response time intervals, which are important data for subsequent analysis; for example, assume the trigger time of beat A is 3 seconds, the trigger time of beat B is 5 seconds, and the trigger time of beat C is 7 seconds, then the time interval between beat A and B is 2 seconds, and the time interval between beat B and C is 2 seconds; in this way, obtain the response time intervals between adjacent frequency segments and record them to form a time interval data set; then, further analyze the time response change situation between frequency segments and identify the time fluctuation trend between different frequency segments; specifically, compare the values of each time interval to determine whether there are regular changes; for example, in the above example, the time interval between beat A and B is 2 seconds, and the time interval between beat B and C is also 2 seconds, which indicates that the change of the response time is stable during this period, and this trend can be regarded as normal fluctuation; then, identify the time fluctuation trend and analyze whether there are significant fluctuations or irregular change situations; if the change of the time interval is too drastic, record these fluctuations and mark them as abnormal fluctuation regions in the data set; this process helps to ensure that subsequent control can handle different types of time fluctuations; for example, assume the trigger time of beat D is 9 seconds, the trigger time of beat E is 12 seconds, and the trigger time of beat F is 15 seconds; if the time interval between beat D and E is 3 seconds, and the time interval between beat E and F is 5 seconds, identify this difference in the time interval and mark it as a fluctuation trend, and obtain a time fluctuation response feature set according to the time fluctuation trend.

[0044] Based on the time fluctuation response feature set, the beat sequence adjustment sub-module calculates the response offset direction of the beat segment on the time axis, adjusts the activation order of the beat segment according to the offset direction, reorganizes the order of the lighting control response, and obtains a beat rhythm reconstruction order list.

[0045] The specific calculation formula for the response offset direction of the beat segment on the time axis is: ; Where, represents the response offset direction of the th beat segment on the time axis, represents the number of sampling points included in the th beat segment, represents the original trigger time of the rd sampling point in the th beat segment, represents the average trigger time of all sampling points in the th beat segment, represents the The weight factor of the th sampling point in the th beat segment in the trigger time dimension, th beat segment represents the amplitude of the time fluctuation response of the th sampling point, the mean value of the time fluctuation response amplitude in the th beat segment represents the th beat segment of the forward offset residual value of the th sampling point, the local trigger density factor of the th sampling point in the th beat segment represents a very small positive real constant used to avoid a zero denominator.

[0046] The specific calculation process is as follows: Suppose a beat segment contains 5 sampling points, and the original data collected by the high-frequency sampler is as follows: Trigger time ; Time fluctuation response amplitude ; Forward offset residual value ; Local trigger density factor ; Constant to avoid zero denominator ; Calculate the mean trigger time : ; Quantify non-numerical data: The trigger time deviation is converted to a numerical value by taking the absolute value and used as the weight denominator, and then the weight factor is calculated ; ; Calculation process of the numerator (sum of weighted offset amounts in the response offset direction): ; ; ; Calculation process of the denominator (square root of the sum of squares of the composite change rates of the response amplitude and the residual): First, calculate the mean response amplitude: ; Calculate the combined difference terms item by item: The first item: ; Item 2: ; Item 3: ; Item 4: ; Item 5: ; Sum of squares and then take the square root: ; ; ; Finally calculate the response offset direction value: ; The result shows that the response offset direction value of the beat segment on the time axis is 3.996. This value represents that the activation timing of the sampling points of this beat segment is shifted backward as a whole. A positive value indicates that the offset direction is the positive direction of the time axis, and the offset amount is significant. This value will be used as one of the judgment indicators for adjusting the activation order and locate the new serial number position of this beat segment in the beat rhythm reconstruction order table.

[0047] Please refer to Figure 1 and Figure 2 , the mosquito killing lamp control sequence scheduling module includes: The response position sorting sub-module arranges the response trigger positions in the lighting control based on the frequency sorting result in the beat rhythm reconstruction order table to generate a response trigger position table.

[0048] First, by analyzing the frequency sorting results in the beat rhythm reconstruction sequence table, obtain the trigger time corresponding to each beat segment and sort it; the frequency sorting results provide a clear time axis to help understand the accurate position of each beat segment in time; to further clarify the trigger order, it will be arranged in the time order of frequency sorting, which ensures that the response trigger position in lighting control can be accurately determined according to the frequency arrangement of the beat segments; for example, assume that in the beat rhythm reconstruction sequence table, the frequency of beat A is 10Hz, beat B is 12Hz, and beat C is 15Hz. First, arrange these three beat segments in ascending order of frequency to form a time order, thereby obtaining the trigger positions of the beat segments; according to the sorting, the trigger position of beat A is at the earliest position, followed by beat B, and finally beat C; at this time, sort the time positions of these three triggers and form a preliminary arrangement of the response trigger positions; next, based on the results after frequency sorting, match the trigger order of the beat segments with the response positions in lighting control; the frequency of each beat segment corresponds to a trigger time point of a lighting behavior. In this way, it can be ensured that the trigger order of lighting is consistent with the order of the beats; this step ensures the efficient execution of the response trigger and avoids any unnecessary delays or conflicts; for example, assume that the trigger time of beat A is 1 second, beat B is 1.2 seconds, and beat C is 1.5 seconds. Execute the lighting control signals according to this time order to ensure seamless docking of the response of each beat segment with lighting control; organize the trigger time points of all beat segments to generate a response trigger position table.

[0049] Based on the response trigger position table, the control signal generation sub-module generates a frequency control signal access process, analyzes the control signal paths of each trigger point, and obtains a frequency modulation signal path diagram.

[0050] First, extract the trigger time and its corresponding frequency information for each beat segment from the response trigger position table; the control signal paths corresponding to each beat segment will be arranged in the order of the trigger time; to ensure that the response of the lighting control can be precisely synchronized with the trigger of each beat segment, sort the frequencies corresponding to these trigger points in chronological order, and analyze the control signal paths for each frequency point; for example, assume that the trigger position table shows that the trigger time of beat A is 1 second and the frequency is 10 Hz, and the trigger time of beat B is 1.5 seconds and the frequency is 12 Hz, generate a frequency modulation signal path based on these time points, and ensure that the response order of beat A and beat B is consistent with the scheduling of their corresponding frequencies according to the relationship between the trigger time and the frequency; next, generate a frequency control signal access process according to the frequency value of each trigger point and the corresponding time point, that is, arrange the order and time points of the control signals according to the frequency order; in the further analysis process, refine the signal paths for each trigger point, check the time intervals between each frequency segment, and ensure the smoothness of the signal paths; for example, assume that there is a 0.5-second interval between the frequency value of beat A and the frequency value of beat B, incorporate this interval into the frequency scheduling process to ensure uniform response times between trigger points and avoid any signal delays or overlaps; finally, through this series of analyses and arrangements, obtain the frequency modulation signal path diagram.

[0051] Based on the frequency modulation signal path diagram, the behavior execution order recording sub-module records the lighting action response path and arranges the execution order of the response behaviors along the time axis to obtain the execution order of the mosquito control response behaviors.

[0052] First, extract the specific time and frequency values of each response trigger point from the frequency modulation signal path diagram, and generate the execution order of response behaviors based on these time points. Specifically, analyze the trigger times recorded in the frequency modulation signal path diagram and arrange these trigger points in chronological order. For example, assume that the frequency modulation signal path diagram shows that a response with a trigger frequency of 10 Hz occurs at 1 second, and a response with a trigger frequency of 12 Hz occurs at 1.5 seconds. First, record the trigger point at 1 second, and then the trigger point at 1.5 seconds to ensure that the response behaviors are arranged in chronological order. Next, match the lighting actions corresponding to each response trigger point with the time points. For example, assume that the action of turning on the mosquito lamp is triggered at 1 second, and the action of turning off the mosquito lamp is triggered at 1.5 seconds. Correlate the execution order of these lighting actions with the time points one by one to form a complete list of response behavior orders. During the analysis process, it is necessary to ensure that there are no conflicts between all trigger points and their corresponding lighting actions. At the same time, the trigger times and frequency values of each response behavior should meet the predetermined time axis requirements. In the further analysis process, check the time intervals between each response behavior to ensure that they are physically feasible and avoid execution conflicts or lags caused by too short or too long time intervals. For example, check whether the frequency interval meets the established time standard. If the interval time is too short, it may be necessary to adjust the response order to avoid conflicts. If the interval time is too long, it may be necessary to adjust the execution speed to obtain the execution order of the mosquito control response behavior.

[0053] Please refer to Figure 3 , a control method for a mosquito lamp based on sound frequency control. Based on the above system for controlling a mosquito lamp based on sound frequency, it includes the following steps: S1: Obtain the change in sound pressure waveform generated by the mosquito lamp controlled by sound frequency during operation, extract the starting point and peak position of the continuously rising segment, identify the relationship between sound pressure change and time duration in the frequency fluctuation section, analyze the synchrony between the frequency value growth process and the duration extension process, and screen out the response audio segments that exhibit periodic stability characteristics in the synchronous relationship to obtain the audio linkage recognition segments. S2: Based on the audio linkage recognition segments, extract the brightness response time during the lighting change process and align it with the start and end points of the segments, analyze the continuous response process of the lighting output change within the segments, distinguish the synchronous correspondence relationship between the brightness change process and the frequency fluctuation process during the audio frequency change stage, and identify the control response paragraphs that exhibit rhythm characteristics to obtain the beat linkage response section table. S3: Based on the beat content in the beat linkage response section table, identify the overlapping relationship between beats by comparing the start and end time positions, extract the difference in the start positions between several beat segments within the lighting response stage, and analyze the trigger conditions for signal control conflicts based on the difference range. Record the beat sequence numbers and staggered starting points with sequential interference to obtain the control conflict mark list. S4: Based on the control conflict tag list, extract the triggering order of the frequencies corresponding to the non-interfering beat segments, check the response time intervals of adjacent frequency segments on the time axis, identify the offset characteristics in the changing trend of the response time intervals, adjust the activation order of the corresponding beat segments according to the offset direction, reorganize the control sequence in the lighting response, and obtain the beat rhythm reconstruction order table; S5: Based on the frequency sorting results in the beat rhythm reconstruction order table, arrange the response trigger positions in the lighting control, establish the access process of the frequency control signal according to the rearranged order, summarize the lighting action response path triggered by the beat segments, and record the execution order of the lighting response behavior corresponding to the frequency on the time axis to obtain the mosquito killing response state sequence under sound control drive.

[0054] The above is only the preferred embodiment of the present invention, and does not limit the present invention in other forms. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution content of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A system for controlling a mosquito-killing lamp based on sound frequency, characterized in that: The system includes: The sound pressure response calibration module obtains sound pressure waveform data, extracts the starting point and peak value of the continuous rising segment, analyzes the synergistic relationship between the frequency growth process and the duration extension process, screens the periodic response segments, and obtains the audio-frequency linkage recognition segments; The beat section screening module is based on the audio-frequency linkage recognition segments, extracts the brightness response time and the segment boundaries for alignment, analyzes the time synchronization relationship between the continuous process of lighting change and the frequency fluctuation, and identifies the control response paragraphs of the rhythm characteristics to obtain the beat linkage response section table; The frequency band conflict recognition module is based on the beat linkage response section table, identifies the beats with overlapping start and end times, extracts the difference between the starting points of adjacent beats and analyzes the signal interference conditions to obtain the control conflict mark list; The rhythm drift rearrangement module extracts the frequency order of the non-conflicting beat segments based on the control conflict mark list, identifies the rhythm offset in the time interval, adjusts the response order and updates the beat sequence to obtain the beat rhythm reconstruction order table; The mosquito killing lamp control sequence scheduling module arranges the lighting response trigger positions based on the frequency sorting in the beat rhythm reconstruction order table, summarizes the lighting control paths corresponding to the beat triggers, and obtains the mosquito killing response state sequence under sound control drive.

2. The system for controlling a mosquito killing lamp based on sound frequency according to claim 1, wherein: The audio-frequency linkage recognition segments include the starting point of the continuous rising segment, the peak position, the frequency growth process, the synchrony of the duration extension process, and the periodic response characteristics; the beat linkage response section table includes the brightness response time, the start and end points of the segment, the lighting change process, the time synchronization relationship of the frequency fluctuation, and the control response paragraphs of the rhythm characteristics; the control conflict mark list includes the beat sequence number, the staggered starting point, the overlapping relationship between beats, the difference in the starting position, and the signal interference trigger condition; The beat rhythm reconstruction order table includes the frequency order, the response time interval between adjacent frequency segments, the rhythm offset, the updated response order, and the beat sequence; the mosquito killing response state sequence includes the frequency control signal access process, the lighting response trigger position, the lighting control path, and the execution order of the lighting response behavior.

3. The system for controlling a mosquito killing lamp based on sound frequency according to claim 1, wherein: The sound pressure response calibration module includes: The sound pressure segment extraction sub-module extracts the starting point and the peak position of the continuous rising segment based on the sound pressure waveform change generated by the mosquito killing lamp under the control of the sound frequency during operation, records the starting point and the peak point positions of the rising segment on the time axis, and obtains the sound pressure rising segment coordinate set; The change segment recognition sub-module is based on the sound pressure rising segment coordinate set, recognizes the arrangement order of the continuous sound pressure rising segments on the time axis, extracts the connection trend between adjacent rising segments and the change direction of the frequency value, and obtains the frequency change continuous segment set; The periodic trend screening sub-module is based on the frequency change continuous segment set, extracts the distribution order of the fluctuation segments in the time series, recognizes the spacing fitting degree and the repeatability of the change law between multiple continuous frequency segments, and screens the sound pressure segments showing periodic stability characteristics to obtain the audio-frequency linkage recognition segments.

4. The system for controlling a mosquito killing lamp based on sound frequency according to claim 1, wherein: The beat section screening module includes: The brightness time extraction sub-module extracts the brightness response time during the lighting change process based on the audio-frequency linkage recognition segments, obtains the start and end boundary time points of the audio-frequency segments, performs time alignment of the brightness change starting point and the start and end points of the audio-frequency segments, and generates the brightness frequency band alignment information set; The response corresponding recognition sub-module analyzes the continuous performance of the lighting output change within the corresponding audio frequency segment based on the luminance frequency band bit information set, recognizes the frequency change direction and fluctuation trend within the continuous lighting change time period, summarizes the corresponding distribution of the two types of data on the time axis, and generates a luminance frequency synchronization feature group; The rhythm paragraph screening sub-module extracts the audio frequency band numbers with synchronization features based on the luminance frequency synchronization feature group, recognizes the audio frequency control behavior paragraphs corresponding to the rhythm features in the lighting response, and obtains a beat linkage response section table.

5. The system for controlling a mosquito killing lamp based on sound frequency according to claim 1, wherein: The frequency band conflict recognition module includes: The time overlap extraction sub-module extracts the beat segment combinations with time overlap by comparing the start and end time positions of the beat segments based on the beat content in the beat linkage response section table, recognizes the cross region and start and end order of the combinations on the time axis, and obtains a beat overlap time period set; The difference relationship recognition sub-module extracts the start and end intervals of the beat segments during the overlap period based on the beat overlap time period set, calculates the coverage time length of the beat segments during the overlap period, analyzes the concentration degree of the distribution of the coverage time lengths, recognizes the influence boundary of the beat segments on adjacent control behaviors, and generates a beat coverage duration index group; The conflict sequence marking sub-module recognizes the beat numbers with a coverage duration higher than that of adjacent segments based on the beat coverage duration index group, extracts the staggered response positions between the beat segments, and obtains a control conflict marking list.

6. The system for controlling a mosquito killing lamp based on sound frequency according to claim 5, wherein: The specific calculation formula for the coverage time length of the beat segments during the overlap period is: ； Among them, represents the weighted coverage time length of the th beat segment within all overlapping time periods, represents the number of overlapping time periods included in the th beat segment, represents the coverage time length (i.e., the difference between the start and end times) of the th beat segment within the th overlapping time period, represents the overlapping intensity weight of the th beat segment within the th overlapping time period, represents the absolute value of the difference between the control behavior time interval corresponding to the th beat segment within the th overlapping time period and the average value of the corresponding time intervals of all overlapping time periods of this beat segment, represents the start time difference between the th beat segment and the adjacent beat segment at the start point of the th overlapping time period, represents the absolute value of the difference in beat numbers of the th beat segment within the th overlapping time period.

7. The system for controlling a mosquito killing lamp based on sound frequency according to claim 1, wherein: The rhythm drift rearrangement module includes: The frequency order extraction sub-module extracts the frequency trigger order corresponding to the beat segments without interference based on the control conflict marking list, records the frequency value and trigger time point of each beat segment, organizes them into a frequency order data table, and generates a frequency trigger order list; The response interval detection sub-module checks the response time interval between adjacent frequency segments on the time axis based on the frequency trigger order list, analyzes the time response change situation between the frequency segments, recognizes the time fluctuation trend, and obtains a time fluctuation response feature set; The beat order adjustment sub-module calculates the response offset direction of the beat segments on the time axis based on the time fluctuation response feature set, adjusts the activation order of the beat segments according to the offset direction, and reorganizes the order of the lighting control response to obtain a beat rhythm reconstruction order table.

8. The system for controlling a mosquito killing lamp based on sound frequency according to claim 7, wherein: The specific calculation formula for the response offset direction of the beat segments on the time axis is: ； Among them, represents the response offset direction of the th beat segment on the time axis, represents the number of sampling points included in the th beat segment, represents the original trigger time of the th sampling point in the th beat segment, represents the average trigger time of all sampling points in the th beat segment, represents the weight factor of the th sampling point in the th beat segment in the trigger time dimension, represents the time fluctuation response amplitude of the th sampling point in the th beat segment, represents the average value of the time fluctuation response amplitudes in the th beat segment, represents the forward offset residual value of the th sampling point in the th beat segment, represents the local trigger density factor of the th sampling point in the th beat segment, represents a very small positive real constant used to avoid a zero denominator.

9. The system for controlling a mosquito killing lamp based on sound frequency according to claim 1, wherein: The mosquito killing lamp control sequence scheduling module includes: The response position sorting sub-module arranges the response trigger positions in the lighting control based on the frequency sorting result in the beat rhythm reconstruction order table, and generates a response trigger position table; The control signal generation sub-module generates a frequency control signal access process based on the response trigger position table, analyzes the control signal path of each trigger point, and obtains a frequency modulation signal path diagram; The behavior execution order recording sub-module records the lighting action response path based on the frequency modulation signal path diagram, arranges the execution order of the response behaviors along the time axis, and obtains the mosquito killing response behavior execution order.

10. A control method for a mosquito killing lamp based on sound frequency control, characterized in that, A system for controlling a mosquito killing lamp based on sound frequency according to any one of claims 1-9, comprising the following steps: S1: Obtain the change in the sound pressure waveform generated by the sound frequency-controlled mosquito lamp during operation, extract the starting point and the position of the peak in the continuously rising segment, identify the relationship between the sound pressure change and the time duration in the frequency fluctuation section, analyze the synchronization between the frequency value growth process and the duration extension process, screen out the response audio frequency segments that exhibit periodic stability characteristics in the synchronization relationship, and obtain the audio frequency linkage recognition segments; S2: Based on the audio frequency linkage recognition segments, extract the brightness response time during the lighting change process and align it with the start and end points of the segments, analyze the continuous response process of the lighting output change within the segments, distinguish the synchronous correspondence relationship between the brightness change process and the frequency fluctuation process in the audio frequency change stage, identify the control response paragraphs that exhibit rhythm characteristics, and obtain the beat linkage response section table; S3: Based on the beat content in the beat linkage response section table, identify the overlapping relationship between the beats by comparing the start and end time positions, extract the difference in the start positions between several beat segments within the lighting response stage, analyze the triggering conditions of signal control conflicts according to the difference range, and record the beat sequence numbers and staggered starting points with sequential interference to obtain the control conflict mark list; S4: Based on the control conflict mark list, extract the triggering order of the frequencies corresponding to the non-interfering beat segments, check the response time interval between adjacent frequency segments on the time axis, identify the offset characteristics in the change trend of the response time interval, adjust the activation order of the corresponding beat segments according to the offset direction, and reorganize the control sequence in the lighting response to obtain the beat rhythm reconstruction order table; S5: Based on the frequency sorting result in the beat rhythm reconstruction order table, arrange the response trigger positions in the lighting control, establish the access process of the frequency control signal according to the rearranged order, summarize the lighting action response path triggered by the beat segments, and record the execution order of the lighting response behavior corresponding to the frequency on the time axis to obtain the mosquito-killing response state sequence under sound control.

Images