Intelligent variable frequency dimming method and system

Abstract

The application discloses an intelligent frequency conversion dimming method and system, relates to the technical field of computer platform load balancing, and comprises the following steps: communication is established between a module and a gateway, a frequency mapping table, a duty cycle segmentation point, a safety threshold and a disabled frequency point table are loaded, and an initialization vector is generated in combination with driver and lamp parameters; current, voltage and optical brightness data are collected at typical brightness points to form a matrix, a risk value is calculated and a critical point is marked, a three-segment frequency mapping is generated in combination with the segmentation point and is corrected through interpolation; a PWM signal is generated according to the mapping table and a brightness instruction, the PWM signal is output after being subjected to slope limiting, edge shaping and micro-jitter frequency processing, and the frequency is corrected in a closed loop under real-time sampling. According to the method, multi-source data are collected, a stroboscopic risk model is introduced, critical point identification and three-segment frequency mapping are realized, interpolation and disabled frequency point constraints are combined to ensure frequency continuity and stability, and a PWM signal is generated and optimized, so that adaptive dimming is realized in a full brightness range.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent lighting dimming control, in particular to an intelligent frequency conversion dimming method and system. BACKGROUND

[0002] With the development of semiconductor lighting technology, LED-based lighting devices are widely used due to their high efficiency, long life and low energy consumption. In order to meet the lighting needs of different scenes, the PWM dimming method has become the mainstream solution, the core of which is to achieve brightness adjustment by changing the duty cycle of the driving signal. On this basis, researchers gradually explore modulation in a higher frequency range to reduce visible flicker and improve comfort. At the same time, the development of intelligent control technology promotes the combination of dimming and communication, sensing and feedback mechanisms, so that the dimming system not only provides multi-level brightness adjustment, but also has certain adaptive ability, thus evolving towards more fine and intelligent direction.

[0003] Although the existing PWM dimming and frequency modulation methods have been applied, there are still many deficiencies. First, the existing methods mostly use fixed frequency or simple frequency switching, lack dynamic correction mechanism based on environment and device state, and are easy to trigger flicker perceptible by human eyes when brightness is in low interval, and are easy to fall into driver resonance interval. Second, the existing system generally lacks the ability to model multi-dimensional sampling data, and its comprehensive judgment of current fluctuation, voltage deviation and brightness energy is insufficient, making it difficult to accurately identify critical points and effectively avoid them in real-time operation. Third, although some dimming devices try to introduce feedback mechanism, they are mostly limited to single closed-loop control of electrical parameters, and cannot realize comprehensive risk assessment combining optical data and frequency energy. In addition, in the construction of frequency mapping, the existing technology mostly fails to realize piecewise continuous interpolation control, resulting in non-smooth frequency transition, and even instability when switching between different brightness intervals. Finally, for abnormal situations such as over-temperature, over-current or output waveform distortion, the existing technology mostly adopts passive shutdown protection, lacks real-time adaptive adjustment and parameter write-back mechanism, and cannot realize long-term optimization and self-learning of the system. SUMMARY

[0004] In view of the above problems, the present application is proposed.

[0005] Therefore, the technical problem solved by the present application is that the existing PWM dimming and frequency conversion control methods have the problems of flicker and resonance caused by fixed frequency, lack of multi-dimensional parameter modeling and critical point identification ability, discontinuous mapping relationship and lack of dynamic correction mechanism, and how to realize intelligent frequency conversion dimming based on real-time sampling frequency flicker risk calculation, piecewise continuous frequency mapping and closed-loop adjustment.

[0006] To solve the above technical problems, the application provides the following technical scheme: an intelligent variable frequency dimming method, which comprises the following steps: a communication access relationship between a construction module and a gateway is established, a frequency mapping table, a duty cycle segmentation point, a safety threshold and a disabled frequency point table are loaded, an initialization vector is generated in combination with a driver parameter and a lamp parameter, a typical brightness point is selected, and current, voltage and optical brightness are synchronously sampled; based on a data matrix, current deviation, voltage deviation and brightness energy are output, a quantitative risk value is obtained in combination with a stroboscopic risk model, and a baseline table is formed by comparison with an initialization threshold; when the brightness point exceeds the threshold, the brightness point is marked as a critical point, and the critical point data is written into a parameter table and enters a three-stage frequency mapping generation together with the initial segmentation point; in the mapping process, the target frequency of each interval is corrected according to the critical point risk, and a continuous relationship is established through segmented interpolation; the result is simultaneously constrained by the disabled frequency point table; after the mapping table is output, a target brightness instruction is received and converted into a duty cycle, a PWM signal is generated in combination with the corrected frequency, and then slope limiting, edge shaping and micro-jitter frequency processing are performed to form a stable waveform; in the output process, the real-time sampling data is used to output a risk value again and input a closed-loop adjustment model to perform secondary correction on the frequency.

[0007] As a preferred scheme of the intelligent variable frequency dimming method, the disabled frequency point table comprises two parts of a preset frequency band and an on-site detection frequency band, and is loaded together when the initialization vector is generated.

[0008] As a preferred scheme of the intelligent variable frequency dimming method, the initialization vector comprises a communication mode, an initial frequency value, a duty cycle segmentation point, a safety threshold, a driver parameter and a lamp parameter.

[0009] As a preferred scheme of the intelligent variable frequency dimming method, the synchronous sampling of the current, voltage and optical brightness of the selected typical brightness point comprises the following steps: a band-pass filter is used to process a current signal, a sliding mean normalization is used to process a voltage signal, and a segmented frequency domain integral processing is used to process an optical brightness signal.

[0010] As a preferred scheme of the intelligent variable frequency dimming method, the three-stage frequency mapping generation comprises the following steps: a duty cycle interval is divided into three continuous intervals of a low brightness section, a medium brightness section and a high brightness section, and a segmented interpolation method is used to establish a corresponding relationship between a brightness point and a frequency in each interval.

[0011] As a preferred scheme of the intelligent variable frequency dimming method, the three-stage frequency mapping generation comprises the following steps: if the risk value of a brightness point exceeds the threshold in three samplings, the brightness point is marked as a critical point, and the frequency parameter of the partition where the critical point is located is corrected according to the critical point risk value.

[0012] As a preferred scheme of the intelligent variable frequency dimming method, the closed-loop adjustment model comprises collecting current, voltage, temperature and optical brightness data in real time while outputting the PWM signal, and comparing the sampling results with preset reference threshold values; when the monitoring results exceed the threshold values, the output frequency and duty cycle are dynamically corrected according to the risk deviation degree, and a hysteresis mechanism is introduced near the critical value to avoid repeated switching of the frequency near the critical point.

[0013] Another object of the present application is to provide an intelligent variable frequency dimming system, which can obtain a quantitative risk value based on the output current deviation, voltage deviation and brightness energy, combined with a stroboscopic risk model, and form a baseline by comparing with an initial threshold value, when the brightness point exceeds the threshold value, it is marked as a critical point, and the critical point data is written into a parameter table, together with the initial segmented point, to generate a three-segment frequency mapping, in the mapping process, the target frequency of each interval is corrected according to the risk of the critical point, and a continuous relationship is established through segmented interpolation, and the result is constrained by the disabled frequency point table, solving the problems that the current PWM dimming and variable frequency control method lack multi-dimensional parameter modeling and critical point identification capability, the mapping relationship is discontinuous and lacks dynamic correction mechanism.

[0014] As a preferred scheme of the intelligent variable frequency dimming system, the system comprises a parameter initialization and sampling module, a risk identification and frequency mapping module, and a PWM generation and closed-loop adjustment module; the parameter initialization and sampling module is used to establish a communication connection between the modules and the gateway, load the frequency mapping table, the duty cycle segmented point, the safety threshold value and the disabled frequency point table, generate an initialization vector combined with the parameters of the driver and the lamp, and perform synchronous sampling of the current, voltage and optical brightness at the typical brightness point to form a data matrix; the risk identification and frequency mapping module is used to calculate the current deviation, voltage deviation and brightness energy based on the data matrix, output the risk value combined with the stroboscopic risk model, identify and mark the critical point, and correct the target frequency according to the segmented point to form a continuous and effective frequency mapping table through interpolation and the disabled frequency point table; the PWM generation and closed-loop adjustment module is used to obtain the duty cycle and the mapping frequency according to the target brightness instruction, generate the PWM control signal, and perform slope limiting, edge shaping and micro-jitter frequency optimization in the output process, while collecting the running data in real time for closed-loop risk evaluation, dynamically correcting the frequency and the duty cycle when the parameters exceed the threshold value, and triggering the abnormal protection mechanism.

[0015] The intelligent variable frequency dimming method provided by the application has the beneficial effects that: in the initial stage of system operation, the module accesses and loads parameters through communication with the gateway, an initialization vector containing a frequency mapping table, a duty cycle segmentation point, a safety threshold, a disabled frequency point table and driver and lamp characteristics is formed, unified modeling of the operating environment is realized, a parameterized foundation is laid for subsequent data sampling and risk calculation; then, current, voltage and optical brightness data are synchronously collected at a typical brightness point to generate a data matrix, quantitative analysis is performed in combination with a stroboscopic risk model, a high-risk critical point can be identified in a multi-dimensional parameter space, and is recorded in a baseline table and a parameter table, so that a dynamic correction mechanism is introduced in the generation process of the three-section frequency mapping, the target frequency of each brightness interval not only continuously transitions with the segmentation point, but also is adaptively adjusted according to the risk of the critical point, and falls into a noise frequency band and a resonance area under the constraint of the disabled frequency point; on this basis, the system obtains the corresponding duty cycle and mapping frequency according to the target brightness instruction, generates a PWM signal optimized by limiting the slope, edge shaping and micro-jitter frequency, and collects electrical and optical data in real-time operation, continuously calculates the risk value and inputs the closed-loop regulation model, realizes dynamic secondary correction of the output frequency, and triggers protection and parameter backwriting under abnormal conditions, so that the entire method forms a complete chain from initialization, risk identification, frequency mapping to PWM generation and closed-loop control, and ensures that the method has adaptability and robustness in the whole process. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the application, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of these drawings.

[0017] Figure 1 The overall flowchart of the intelligent variable frequency dimming method provided for the first embodiment of the application. DETAILED DESCRIPTION

[0018] In order to make the above-mentioned purposes, features and advantages of the application more apparent and easy to understand, the specific embodiments of the application will be described in detail below with reference to the drawings of the specification. Obviously, the described embodiments are only a part of the embodiments of the application, rather than all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor should belong to the protection scope of the application.

[0019] Embodiment 1, refer to Figure 1 For an embodiment of the application, an intelligent variable frequency dimming method is provided, which comprises:

[0020] S1: The communication access relationship between the construction module and the gateway is established, and the frequency mapping table, the duty cycle segmentation point, the safety threshold and the disabled frequency point table are loaded, the initialization vector is generated combining the driver and the lamp parameters, and the typical brightness point is selected for synchronous sampling of current, voltage and optical brightness.

[0021] Further, in the initial stage of system operation, the PWM dimming module first accesses the control network in two ways. One is a short-distance wireless communication mode, which uses a Bluetooth module to pair and synchronize data with the gateway. The other is a wired communication mode, which uses an RS-485 bus to realize serial data interaction with the gateway. Both access modes need to complete level matching, clock synchronization and addressing configuration of the interface circuit at the hardware level to ensure stable communication between the module and the gateway after access.

[0022] After access is completed, the module automatically establishes a communication link with the gateway, and the gateway registers with the server through the network interface module. During the registration process, the module's unique identification code, hardware version number, firmware version number and device status are packaged into a data frame and uploaded. The server checks the registration information and generates a corresponding device profile. All subsequent dimming instructions and parameter downlink are managed based on this profile.

[0023] It should be noted that subsequently, the module enters the parameter initialization phase. In this phase, the module reads the pre-set frequency mapping table and duty cycle conversion point information from the local storage unit. The frequency mapping table defines the initial working frequency value corresponding to different brightness intervals, and the duty cycle conversion point subdivides the brightness percentage range into several discrete intervals to facilitate subsequent frequency matching and adjustment. At the same time, the module also loads a set of safety thresholds, including current peak threshold, voltage fluctuation threshold, temperature upper limit threshold, etc., as a basis for protection during subsequent operation.

[0024] After the parameters are loaded, the module also needs to confirm the information of the connected driver and lamp. By reading the rated voltage, rated current, starting characteristics, recommended frequency range, etc. of the driver, the module can establish a driver parameter table; at the same time, the design current, rated brightness and dimming compatibility of the lamp source are calibrated to form a lamp parameter table. The driver parameter table and the lamp parameter table together constitute the basic data of the device operating environment.

[0025] In the initialization process, the module also establishes a list of disabled frequencies. The list is composed of two parts: factory configuration and on-site detection. The factory configuration part contains audible frequency bands that can be perceived by human ears, such as 3kHz to 10kHz. The on-site detection part records frequency intervals that may cause resonance or interference by quickly scanning the response curve of the driver at different frequencies. The disabled frequency list will be called in subsequent frequency mapping calculations to constrain the value range of the frequency and ensure that the system avoids unstable regions during operation.

[0026] Finally, after all parameters are loaded and integrated, an initialization vector is formed. The vector contains multiple dimensions of data such as communication method, frequency initial value, duty cycle segmentation point, safety threshold, drive characteristics, and luminaire characteristics. In system design, the initialization vector is represented as:

[0027] ;

[0028] ;

[0029] where, is the system initialization parameter vector; is the normalization factor, used to keep the vector scale uniform; is the communication method selection parameter, determined by the module access mode; is the communication link characteristic factor, representing the transmission efficiency of different communication methods; is the communication link quality index, derived from the link signal strength and bit error rate; is the first duty cycle segmentation point percentage, defining the low-end limit of the brightness interval; is the second duty cycle segmentation point percentage, defining the high-end limit of the brightness interval; is the frequency initial value parameter, derived from the driver recommended frequency band or historical statistical data; is the frequency statistical scale parameter, representing the dispersion of frequency distribution; is the current threshold component, derived from the current peak limit in the safety threshold set; is the voltage threshold component, derived from the voltage fluctuation limit in the safety threshold set; is the temperature threshold component, derived from the temperature rise limit in the safety threshold set; is a small positive correction factor to avoid the case where the denominator normalization is zero.

[0030] S2: Based on the data matrix output current deviation, voltage deviation and brightness energy, combined with the strobe risk model to obtain the quantitative risk value, and compared with the initial threshold to form the baseline table, when the brightness point is over the threshold, it is marked as a critical point, and the critical point data is written into the parameter table, together with the initial segmentation point into the three-stage frequency mapping generation. In the mapping process, the target frequency of each interval is corrected according to the critical point risk, and then the continuous relationship is established through segmented interpolation. The result is also constrained by the disabled frequency point table.

[0031] Further, after the construction of the initialization parameter vector is completed, the baseline detection stage is entered. This stage relies on the formed communication mode probability, frequency normalization result and segmented point normalization parameter to determine the typical brightness point set to be detected. Usually, the duty cycle positions such as are selected as representative detection points with wide coverage. At these brightness points, the PWM dimming module maintains the initial frequency output, and the current sensor, voltage sampling circuit and optical brightness probe are used to synchronize the signal acquisition to establish a multi-source data set for analysis.

[0032] The collected data is first preprocessed to ensure that it can be connected with the generated parameter vector. The current signal is band-pass filtered to suppress noise, and then normalized; the voltage signal is removed by the sliding mean method; and the optical brightness sequence is segmented and integrated to obtain the sensitive frequency band energy index. These processing results together constitute the current mean, voltage mean and brightness energy, which are the inputs for subsequent risk calculation.

[0033] After establishing the multi-source input, the system calculates the corresponding strobe risk value for each brightness point. The risk value is given by the following formula:

[0034] ;

[0035] Where, is the current mean at the brightness point , is the current reference value, is the current scale factor, is the voltage mean at the brightness point , is the voltage reference value, is the voltage scale factor, is the energy of the optical brightness in the sensitive frequency band at the brightness point , is the brightness reference energy, is the brightness energy scale factor, is the Huber function threshold for current deviation, is the Huber function threshold for brightness energy deviation, and These are the Huber function and sp is the Softplus function. For the Sigmoid function, Brightness point The flicker risk value ranges from 0 to 1.

[0036] It should be noted that after the risk values ​​of all representative brightness points are calculated, the system stores the results in a baseline table. If the risk value of a certain brightness point consistently exceeds a set threshold in multiple detections, the system automatically marks it as a critical point. During this process, the system introduces a sliding window mechanism to perform a weighted average of the continuous sampling results to eliminate the influence of random fluctuations. Ultimately, the brightness points marked as critical points will simultaneously record their duty cycle position and flicker risk value. And related raw sampling data.

[0037] Furthermore, after completing module access and parameter initialization, the system has established an initialization parameter vector containing communication mode probabilities, initial frequency, duty cycle segment points, safety thresholds, and a list of disabled frequency points. This parameter vector provides a basic reference for subsequent frequency mapping. The system collects multi-source data on current, voltage, and optical brightness by detecting multiple typical brightness points, and based on... Risk quantification was performed on each brightness point to identify critical points. These critical points not only recorded the duty cycle position but also provided risk results related to the safety threshold, offering a dynamic basis for frequency correction.

[0038] Using segmentation point parameters Based on this, the entire brightness range is... It is divided into three consecutive intervals, corresponding to the low brightness segment, medium brightness segment, and high brightness segment, respectively. Each interval corresponds to a basic frequency during initialization. These values ​​can be generated through manual configuration or by modeling historical data. At this point, the system compares the critical point information identified in stage S2 with these fundamental frequencies. If a certain critical point... Falling in the range Within this range, the fundamental frequency needs to be adaptively corrected.

[0039] Frequency correction is expressed as:

[0040] ;

[0041] in, For the revised first Target frequency in the interval For the first time before the correction Initial target frequency of the interval This is a positive constant for the frequency correction factor. Critical brightness point The flicker risk value, This is the baseline value for risk.

[0042] After correcting the target frequency for each zone, the system needs to establish a continuous mapping relationship within each interval. At this point, a piecewise interpolation formula is used for any brightness point. The mapping is given as follows:

[0043] ;

[0044] in, Brightness point The corresponding target output frequency function, Input the percentage of brightness points, with a range of values. ; The first duty cycle segment percentage defines the boundary between the low-brightness segment and the medium-brightness segment; The second duty cycle segment percentage defines the boundary between the medium brightness segment and the high brightness segment; The target frequency after correction for the low brightness segment. The target frequency after correction for the mid-brightness range. The target frequency after correction for the high brightness segment. This represents the maximum allowed frequency limit of the system.

[0045] However, simple piecewise interpolation can still cause the mapping result to fall into a prohibited frequency band. To avoid this problem, the system uses the generated prohibited frequency point table for correction. If the mapping result... Falling into the range Then, projection correction is performed according to the following rules:

[0046] ;

[0047] in, The corrected target frequency function, Brightness point before correction The corresponding target frequency; To disable the lower limit frequency of the frequency band, Both define the unusable frequency range as the upper limit frequency of the disabled frequency band; To correct the offset, it is used to shift up or down when the frequency falls into the disabled range; condition This indicates that the current frequency is within the restricted frequency band; constraints This is used to determine if the frequency is closer to the upper boundary of the restricted frequency band, at which point the frequency is corrected to... ;condition This is used to determine if the frequency is closer to the lower boundary of the restricted frequency band, at which point the frequency is corrected to... If the frequency does not fall into the forbidden band range, it is directly kept unchanged.

[0048] It should be noted that after the frequency mapping table is completed, the system enters the PWM signal generation and output stage. The goal of this stage is to combine the brightness input value with the frequency mapping table, generate a PWM control waveform with accurate frequency and duty cycle in real time, and add necessary signal optimization mechanisms during the output process.

[0049] First, when the system receives a target brightness instruction from the user or control end , it will immediately call the three-section mapping table formed. According to the interval where the current brightness point is located, the table returns the corresponding frequency value . At the same time, the system uses the duty cycle segmentation points stored in the stage initialization vector to convert the target brightness instruction into a duty cycle control quantity . In this way, the PWM control module obtains two core parameters: target frequency and target duty cycle.

[0050] Subsequently, the system generates a basic PWM signal according to the target frequency and duty cycle. At this time, the PWM drive unit samples and divides the waveform in the time domain through a high-precision timer to form a rectangular wave sequence. In order to ensure the consistency and continuity of the waveform, the system introduces a segmented interpolation correction mechanism, so that when the user continuously adjusts the brightness, the frequency and duty cycle of the PWM can smoothly transition without jumping.

[0051] After generating the basic PWM waveform, the system further optimizes the signal. First, the slope constraint: by limiting the rising and falling edges of the waveform, it avoids electromagnetic interference caused by instantaneous mutations. Second, edge shaping processing: using zero-crossing detection and high-speed comparator circuit to modify the edges of the waveform twice, making it close to the ideal rectangular waveform. Third, micro jitter frequency strategy: introduce a small jitter near the target frequency, so that the output frequency fluctuates within a very small range, thereby reducing the triggering probability of driver resonance.

[0052] In this process, the system also dynamically calls the critical point risk value as a real-time correction factor. When it detects that the output waveform has potential risks near the critical point, the system will automatically adjust the amplitude of the micro jitter frequency or the change rate of the duty cycle, so that the PWM signal avoids coupling with the critical frequency point. In this way, the PWM output not only depends on the mapping result, but also forms a dynamic closed loop with the risk feedback.

[0053] ​Finally, the generated PWM signal will be output to the actual LED luminaire or related load through the drive module. During the entire output process, the system will record the frequency, duty cycle and waveform correction parameters at the same time, and compare them with the safety threshold parameters. If it is detected that the current, voltage or temperature is close to the threshold boundary, the system will automatically adjust the change step of the PWM duty cycle to ensure that the output remains within the safety interval.

[0054] S3: After outputting the mapping table, the target brightness instruction is received and converted into a duty cycle, combined with the corrected frequency to generate a PWM signal, followed by slope limiting, edge shaping and micro-jitter frequency processing to form a stable waveform. During the output process, real-time sampling data is output again to output risk values and input into a closed-loop adjustment model for secondary correction of the frequency.

[0055] Further, after completing the generation and optimization of the PWM signal, the system enters a closed-loop operating state. At this time, the output PWM signal has acted on the LED drive and luminaire body, but due to dynamic changes in the operating environment, such as power grid voltage fluctuations, device temperature rise, load disturbances, etc., the actual working state may deviate from the expected. In order to ensure system stability, S5 stage introduces closed-loop adjustment and abnormal protection mechanism.

[0056] First, the system samples the output state in real time through current, voltage, temperature and optical brightness sensors. These data are not only compared with safety thresholds, but also call to dynamically assess the risk level. When the real-time collected indicators show that the PWM output frequency or the duty cycle falls near the critical point, the system will trigger the closed-loop correction logic.

[0057] The closed-loop adjustment process uses a risk feedback function to couple real-time risk with the mapping frequency:

[0058] ;

[0059] where, is the actual output frequency after closed-loop correction, is the time variable, is the target frequency obtained by the three-stage mapping and the correction rule for the disabled frequency band for the target brightness instruction , is a positive constant for the frequency correction coefficient, is the risk value (R) calculated based on the real-time sampling according to the stroboscopic risk model, , is the energy fluctuation or equivalent energy index (relative quantity) obtained by integrating voltage and current within the current time window, is the energy reference value, is the energy scale factor for normalizing the denominator (a positive constant), The target luminance set point given for the control terminal.

[0060] The value range of Where is the minimum allowable driving frequency, is the maximum allowable frequency (e.g. 20 kHz).

[0061] When and , , the system output is stable.

[0062] When or significantly deviates from , the frequency will be suppressed or raised to circumvent flicker and instability risks.

[0063] After completing the frequency correction, the system will also perform a hysteresis process on the duty cycle When repeatedly crosses a certain critical threshold within a short period of time, the system will lock it within a hysteresis interval until a stable trend appears before allowing further adjustments, thus avoiding flicker phenomena caused by frequent switching.

[0064] Embodiment 2, an embodiment of the present application, provides an intelligent variable frequency dimming method. In order to verify the beneficial effects of the present application, economic benefit calculation and simulation experiments are used for scientific demonstration.

[0065] Firstly, the test objects are selected as the same type of LED downlights combined with constant current drivers, with a rated output of 350 mA and a recommended operating frequency band of 2-20 kHz. The test site is a standard darkroom equipped with three types of acquisition channels: current probes and differential voltage probes are connected to the acquisition card, and the optical brightness probe is placed at the center of the measured surface. The sampling frequency is 10 kHz, and the window time is 10 min. The control system is composed of a PWM dimming module, a gateway, and a server. The module has both Bluetooth and RS-485 access methods. At the beginning of implementation, the interface circuit is first matched in level, the clock is synchronized, and the addressing configuration is completed, so that the module establishes a link with the gateway in Bluetooth or RS-485 mode. The gateway registers the device file to the server, loads the module's unique identification code, hardware and firmware versions, and state information. Then the frequency mapping table, duty cycle segmentation points, safety threshold, and disabled frequency table are written into the module's local storage, the initial disabled frequency band is set to 3-10 kHz, and the response peak of the driver is recorded under the no-load scan to calibrate the on-site disabled area. The driver parameter table records the rated voltage, rated current, starting characteristics, and recommended frequency band; the lamp parameter table records the design current, rated brightness, and dimming compatibility. After generating the initialization vector based on the above items, three typical brightness points of 20%, 50%, and 80% are selected for synchronous sampling. The current and voltage channels use band-pass filtering and sliding mean DC removal, and the optical channel obtains the sensitive frequency band energy index through piecewise integration, which is combined into a structured data matrix. To compare different strategies, six objects are set: fixed frequency 2 kHz (Scheme A), fixed frequency 8 kHz (Scheme B), three segment mapping + disabled frequency band (Scheme C), three segment mapping + closed loop (Scheme D), three segment mapping + closed loop + micro-jitter frequency (Bluetooth, Scheme E), and three segment mapping + closed loop + micro-jitter frequency (RS-485, Scheme F). The mapping scheme uses B1 / B2 as the dividing point (initial value 30% / 70% or 28% / 68%), and the target frequency in each interval is corrected based on the initialization frequency and the critical point risk, and then the continuous frequency is generated by interpolation. In the execution phase, the brightness command is applied in the sequence of 20%→50%→80%→50%→20%, and the module obtains the target frequency from the mapping table and converts the duty cycle to output PWM; in schemes D-F, the closed loop sampling is also turned on, and the real-time data are input into the adjustment model to make a second correction to the frequency at a fixed period; schemes E and F apply a small amplitude jitter near the target frequency, and the jitter center is adjusted slightly according to the mapping result. All objects record risk-related indicators, waveforms, and statistics within the same time window, including typical brightness point risk values, mapping frequencies, frequency adjustment times, brightness fluctuation indices, audible noise event counts, temperature rise peak values, and sampling packet loss rates. After the test is completed, the data table of the same dimension is exported for horizontal comparison.

[0066] Table 1 Experimental data table

[0067]

[0068] From the perspective of the three indicators of "risk value R20 / R50 / R80", the risk value of fixed frequency 2 kHz (scheme A) at 50% brightness position is 0.62, which is significantly higher than 0.38 of fixed frequency 8 kHz (scheme B), indicating that increasing the working frequency can alleviate the risk at the median brightness. However, at 20% and 80% positions, the risk value of scheme B is still in the interval of 0.32-0.35, and it fails to differentiate the suppression for different brightness segments. After introducing three-section mapping and disabling frequency band constraints (scheme C), R20 / R50 / R80 decreases to 0.18 / 0.21 / 0.19, respectively, showing that the mapping strategy based on segmented points and disabled frequency bands is more suitable for covering the complex response of the full brightness interval. Continuing to add a closed loop on the basis of mapping (scheme D), R50 further decreases to 0.17, while R20 and R80 are 0.14 and 0.16, respectively, showing that the risk is more convergent at the three points, indicating that the real-time data-driven secondary correction can eliminate the running drift that static mapping cannot capture. Superimposing micro-frequency jitter on the closed-loop strategy (schemes E and F), under the two links of Bluetooth and RS-485, R50 reaches 0.15 and 0.14, respectively, and R20 and R80 also decrease synchronously, indicating that under the same mapping and closed-loop framework, micro-frequency perturbation helps to avoid the narrowband sensitive area, and the link latency stability of RS-485 is more conducive to control convergence.

[0069] For the "brightness fluctuation index" indicator, schemes A / B are 0.23 / 0.18, while schemes C / D / E / F decrease to 0.11 / 0.08 / 0.07 / 0.06, respectively, reflecting the gradual improvement path from fixed frequency to three-section mapping, then to closed loop and micro-jitter frequency. This indicator and "frequency adjustment times" form a complement: the adjustment times of static schemes are only 1 time / 10 min, which cannot respond quickly to disturbances; the adjustment frequency of mapping and closed-loop schemes increases to 4-7 times / 10 min, but the brightness fluctuation does not increase, but decreases, indicating that the adjustment is "directional correction" rather than noise introduction.

[0070] "Audible noise events" still exist 2-3 times / 10 min in schemes A / B, while from scheme C, it decreases to 0 times / 10 min, indicating that disabling frequency bands and mapping make the frequency avoid the audible area. The peak temperature decreases from 16.8°C (A) and 16.5°C (B) to 14.5-15.2°C (C-F), showing that under the premise of maintaining the target brightness, frequency selection and waveform shaping make the heat load distribution more balanced. The sampling packet loss rate decreases from 0.20% (A) and 0.18% (B) to the interval of 0.08-0.19%, among which the closed loop + RS-485 scheme (F) is the lowest, providing a more stable data basis for real-time decision-making.

[0071] In summary, the three-segment mapping and the introduction of the disabled frequency band solve the problem of inconsistent risks caused by the "one-size-fits-all" of fixed frequency in different brightness intervals; the closed-loop mechanism compensates for the defect that static mapping is not sensitive to environmental drift and device aging; and the micro-dithering further reduces the probability of falling into the narrowband sensitive area without changing the average frequency. Compared with the traditional fixed frequency scheme, the embodiment simultaneously improves the risk, fluctuation, noise, temperature rise, and data integrity through the chain design of "initialization-sampling modeling-segmented mapping-closed-loop correction-boundary constraint", which proves the operability and comprehensive advantages of the intelligent variable frequency dimming method in engineering scenarios.

[0072] In one embodiment of the present application, a kind of intelligent variable frequency dimming system is provided, including parameter initialization and sampling module, risk identification and frequency mapping module, PWM generation and closed-loop adjustment module.

[0073] The parameter initialization and sampling module is used to establish the communication connection between the module and the gateway, load the frequency mapping table, duty cycle segmentation point, safety threshold and disabled frequency point table, generate initialization vector in combination with the parameters of the driver and the lamp, and perform synchronous sampling of current, voltage and optical brightness at typical brightness points to form a data matrix.The risk identification and frequency mapping module is used to calculate current deviation, voltage deviation and brightness energy based on the data matrix, output risk value in combination with the stroboscopic risk model, identify and mark critical points, and then generate a three-segment frequency mapping relationship according to the segmentation points to correct the target frequency, and form a continuous and effective frequency mapping table through interpolation and the disabled frequency point table.The PWM generation and closed-loop adjustment module is used to obtain duty cycle and mapping frequency according to target brightness instruction, generate PWM control signal, and perform slope limiting, edge shaping and micro-dithering optimization during output process, while real-time collection of running data is performed for closed-loop risk assessment, dynamic correction of frequency and duty cycle when parameters exceed threshold, and triggering of abnormal protection mechanism.

[0074] If the functions are realized in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the parts that essentially contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product stored in a storage medium, including a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk, and various media that can store program codes.

[0075] The logic and / or steps represented in the flow diagrams and / or described herein, for example, can be considered as a sequence of executable instructions, and can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For purposes of this specification, a "computer-readable medium" can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-readable medium can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection (electronic) having one or more wires, a portable computer diskette (magnetic), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber (optical), and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, for example via an optical scanner, then compiled, interpreted, or otherwise processed, and stored in a computer memory in a form that can be later executed by a computer. In this context, a "computer-readable medium" can be any means that can store the program for use by or in connection with the instruction execution system, apparatus, or device.

[0076] The foregoing detailed description has set forth various embodiments of the devices and / or processes via the use of flowcharts, diagrams, and / or operational descriptions. Insofar as such individual embodiments contained in this disclosure are full functional devices and / or processes, it can be understood that each unit, operation, or block included in this disclosure can be implemented by computer program instructions and / or code configured to perform the functions recited by the individual embodiments. Embodiments disclosed in this

[0077] It should be understood that aspects of the application can be implemented in hardware, software, firmware or combinations thereof. In the above embodiments, various steps or methods can be implemented in software or firmware that is stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, and in another embodiment, any of the following can be used: a combination of discrete logic circuits having logic gates for implementing logic functions upon an application of data signals, application specific integrated circuits having logic gates, field-programmable gate arrays (FPGA), or other components, which are programmable by a user. It should be appreciated that the foregoing embodiments are merely exemplary and are not intended to limit the present application, and that such variations of the embodiments disclosed herein are possible and contemplated. For example, although the present application has been described in the context of a particular embodiment, it is recognized that those skilled in the art could readily make and use modifications to the present application without the application departing from the spirit and scope of the application. Accordingly, it is intended that the present application encompass all such variations as fall within the scope of the appended claims.

[0078] It should be noted that the above examples are only used to illustrate the technical solutions of the present application but not limit the present application. Although the present application is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or equivalently replaced, without departing from the spirit and scope of the technical solutions of the present application, which should be covered in the scope of the claims of the present application.

Claims

1. A smart frequency conversion dimming method, characterized in that, include: The module establishes the communication access relationship between itself and the gateway, and loads the frequency mapping table, duty cycle segment point, safety threshold and disabled frequency point table. It generates an initialization vector by combining the driver and lamp parameters, and selects typical brightness points for synchronous sampling of current, voltage and optical brightness. Based on the output current deviation, voltage deviation and brightness energy of the data matrix, a quantified risk value is obtained by combining the flicker risk model and compared with the initial threshold to form a baseline table. When the brightness point exceeds the threshold, it is marked as a critical point. The critical point data is written into the parameter table and enters the three-segment frequency mapping generation together with the initial segment points. During the mapping process, the target frequency of each interval is corrected according to the critical point risk, and then a continuous relationship is established through segmented interpolation. The result is also constrained by the disabled frequency point table. The three-segment frequency mapping generation includes: dividing the duty cycle interval into three continuous intervals: low brightness, medium brightness, and high brightness; and using a piecewise interpolation method to establish the correspondence between brightness points and frequencies in each interval; if the risk value of a brightness point exceeds the threshold in all three samplings, the brightness point is marked as a critical point, and the frequency parameters of the corresponding partition are corrected based on the risk value of the critical point. After outputting the mapping table, the target brightness command is received and converted into a duty cycle. This is combined with the correction frequency to generate a PWM signal. Subsequently, slope limiting, edge shaping, and micro-jitter processing are performed to form a stable waveform. During the output process, real-time sampled data is used to output the risk value again and input into the closed-loop adjustment model to perform a second correction on the frequency. The closed-loop regulation model includes real-time acquisition of current, voltage, temperature and optical brightness data while outputting the PWM signal, and comparing the sampling results with a preset benchmark threshold. When the monitoring results exceed the threshold, the output frequency and duty cycle are dynamically corrected according to the degree of risk deviation, and a hysteresis mechanism is introduced near the critical value to avoid repeated switching of the frequency near the critical point.

2. The intelligent frequency conversion dimming method as described in claim 1, characterized in that: The disabled frequency point table includes two parts: a preset frequency band and a field detection frequency band, which are loaded together when the initialization vector is generated.

3. The intelligent frequency conversion dimming method as described in claim 2, characterized in that: The initialization vector includes communication mode, initial frequency value, duty cycle segment point, safety threshold, driver parameters, and lamp parameters.

4. The intelligent frequency conversion dimming method as described in claim 3, characterized in that: The synchronous sampling of current, voltage, and optical brightness at typical brightness points is achieved by bandpass filtering the current signal, normalizing the voltage signal by moving average, and performing segmented frequency domain integration on the optical brightness signal.

5. A system employing the intelligent frequency conversion dimming method as described in any one of claims 1 to 4, characterized in that: This includes a parameter initialization and sampling module, a risk identification and frequency mapping module, and a PWM generation and closed-loop adjustment module; The parameter initialization and sampling module is used to establish a communication connection between the module and the gateway, load the frequency mapping table, duty cycle segment point, safety threshold and disabled frequency point table, generate an initialization vector in combination with driver and lamp parameters, and perform synchronous sampling of current, voltage and optical brightness at typical brightness points to form a data matrix; The risk identification and frequency mapping module is used to calculate current deviation, voltage deviation and brightness energy based on the data matrix, output risk value in combination with the flicker risk model, identify and mark critical points, generate a three-segment frequency mapping relationship based on the segment points, correct the target frequency, and form a continuous and effective frequency mapping table through interpolation and a disabled frequency point table. The PWM generation and closed-loop adjustment module is used to obtain the duty cycle and mapping frequency according to the target brightness command, generate PWM control signal, and perform slope limiting, edge shaping and micro-jitter optimization during the output process. At the same time, it collects running data in real time to perform closed-loop risk assessment. When the parameters exceed the threshold, it dynamically corrects the frequency and duty cycle and triggers the abnormal protection mechanism.

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