Intelligent variable frequency dimming method and system

Abstract

The invention discloses an intelligent variable-frequency dimming method and system, and relates to the technical field of computer platform load balancing, and the method comprises the steps: establishing communication between a module and a gateway, loading a frequency mapping table, a duty ratio segmentation point, a safety threshold and a forbidden frequency point table, and generating an initialization vector in combination with parameters of a driver and a lamp; collecting current, voltage and optical brightness data at typical brightness points to form a matrix, calculating a risk value and marking a critical point, generating three-section type frequency mapping by combining segmentation points, and performing interpolation correction; and receiving a brightness instruction according to the mapping table to generate a PWM signal, performing slope limiting, edge shaping and micro-jitter frequency processing and outputting, and performing closed-loop frequency correction under real-time sampling. According to the method, by collecting multi-source data and introducing a stroboscopic risk model, critical point identification and three-section type frequency mapping are realized, and frequency continuity and stability are ensured by combining interpolation and forbidden frequency point constraint; on the basis, a PWM signal is generated and optimized, so that self-adaptive dimming is realized in a full-brightness interval.

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, forms 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, realizes unified modeling of the operating environment, lays a parameterized foundation for subsequent data sampling and risk calculation, then synchronously collects current, voltage and optical brightness data at a typical brightness point and generates a data matrix, combines with a stroboscopic risk model for quantitative analysis, can identify a high-risk critical point in a multi-dimensional parameter space, and records in a baseline table and a parameter table, so that a dynamic correction mechanism is introduced in the three-stage frequency mapping generation process, the target frequency of each brightness interval not only continuously transitions with the segmentation point, but also adaptively adjusts 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 slope, edge shaping and micro-jitter frequency, 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 backwrite 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 by 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 be within 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: S1: The communication access relationship between the construction module and the gateway is established, and the frequency mapping table, duty cycle segmentation point, safety threshold and disabled frequency point table are loaded, and the initialization vector is generated combining the driver and lamp parameters, and the typical brightness point is selected for synchronous sampling of current, voltage and optical brightness.

[0020] 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.

[0021] 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.

[0022] 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 value of the operating frequency in 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.

[0023] 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.

[0024] 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.

[0025] 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: ; ; is the system initialization parameter vector; is the normalization factor, used to maintain the uniformity of the vector scale; 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.

[0026] ​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 a continuous relationship is established through segmented interpolation. The result is also constrained by the disabled frequency point table.

[0027] Further, after completing the construction of the initialization parameter vector, enter the baseline detection stage. 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 a 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.

[0028] 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, etc. Key quantities as input for subsequent risk calculation.

[0029] 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: ; 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 Huber function, sp is Softplus function, Sigmoid function, is the luminance point of the stroboscopic risk value, the value range is between 0 to 1.

[0030] It should be noted that when the risk value of all representative luminance points is calculated, the system stores the results in the baseline table. If the risk value of a certain luminance point continuously exceeds the set threshold in multiple detections, the system automatically marks it as a critical point. In this process, the system introduces a sliding window mechanism to perform a weighted average of consecutive sampling results to eliminate the influence of accidental fluctuations. Finally, the luminance point marked as a critical point will record the duty cycle position, stroboscopic risk value and related raw sampling data.

[0031] Furthermore, after completing the module access and parameter initialization, the system has established an initial parameter vector containing the communication mode probability, the initial frequency, the duty cycle segmentation point, the safety threshold and the disabled frequency point table. This parameter vector provides a basic reference for subsequent frequency mapping. The system collects multi-source data of current, voltage and optical brightness based on the detection of multiple typical luminance points, and quantifies the risk of each luminance point to identify critical points. Critical points not only record the duty cycle position, but also give the risk results related to the safety threshold, providing a dynamic basis for frequency correction.

[0032] Taking the segmentation point parameter as the basis, the entire luminance interval is divided into three consecutive intervals, corresponding to the low luminance segment, the medium luminance segment and the high luminance segment. Each interval corresponds to a basic frequency at initialization, which can be generated by manual configuration or historical data modeling. At this time, the system compares the critical point information identified in the S2 stage with these basic frequencies. If a certain critical point falls within the interval , the basic frequency of that interval needs to be adaptively corrected.

[0033] The frequency correction is represented as: ; wherein, is the corrected target frequency of the interval, is the initial target frequency of the interval before correction, is a positive constant of the frequency correction coefficient, is the stroboscopic risk value of the critical luminance point , is the risk benchmark.

[0034] After the correction of the target frequency of each partition, the system needs to construct a continuous mapping relationship within each interval. At this time, the piecewise interpolation formula is adopted, and for any brightness point The mapping is given as: ; wherein, is the input brightness point corresponding to the target output frequency function, is the input brightness point percentage, with a value range of ; is the first duty cycle segment point percentage, defining the boundary between the low brightness segment and the medium brightness segment; is the second duty cycle segment point percentage, defining the boundary between the medium brightness segment and the high brightness segment; is the corrected target frequency of the low brightness segment, is the corrected target frequency of the medium brightness segment, is the corrected target frequency of the high brightness segment, is the maximum frequency upper limit allowed by the system.

[0035] However, simple piecewise interpolation may still result in the mapping result falling into the disabled frequency band. To avoid this problem, the system uses the generated disabled frequency point table for correction. If the mapping result falls into the interval , the projection correction is performed by the following rules: ; wherein, is the corrected target frequency function, is the target frequency corresponding to the brightness point before correction; is the lower limit frequency of the disabled frequency band, is the upper limit frequency of the disabled frequency band, both of which define the unusable frequency band range; is the correction offset, used to shift upwards or downwards when the frequency falls into the disabled interval; condition indicates that the current frequency is located within the disabled frequency band interval; constraint is used to judge whether the frequency is closer to the upper boundary of the disabled frequency band, at which time the frequency is corrected to ; condition is used to judge whether the frequency is closer to the lower boundary of the disabled frequency band, at which time the frequency is corrected to . If the frequency does not fall into the disabled frequency band range, the remains unchanged.

[0036] It should be noted that after the frequency mapping table is constructed, 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 to generate a PWM control waveform with accurate frequency and duty cycle in real time, and to incorporate necessary signal optimization mechanisms during the output process.

[0037] First, the system receives the target brightness command from the user or control terminal. Upon that time, the generated three-segment mapping table will be invoked immediately. This table returns the corresponding frequency value based on the interval where the current brightness point is located. At the same time, the system uses the duty cycle segment points stored in the stage initialization vector to convert the target brightness command into a duty cycle control quantity. In this way, the PWM control module obtains two core parameters: the target frequency and the target duty cycle.

[0038] Subsequently, the system generates a basic PWM signal based on the target frequency and duty cycle. At this time, the PWM drive unit samples and segments the waveform in the time domain using a high-precision timer to form a rectangular wave sequence. To ensure the consistency and continuity of the waveform, the system introduces a piecewise interpolation correction mechanism, so that when the user continuously adjusts the brightness, the frequency and duty cycle of the PWM can transition smoothly without any abrupt changes.

[0039] After generating the basic PWM waveform, the system further optimizes the signal. First, it implements slope constraint: limiting the rising and falling edges of the waveform avoids electromagnetic interference caused by sudden changes. Second, it performs edge shaping: using zero-crossing detection and a high-speed comparator circuit, it performs secondary correction on the waveform edges to approximate an ideal rectangular waveform. Third, it employs a micro-jitter strategy: introducing minute jitter near the target frequency causes the output frequency to fluctuate within a very small range, thereby reducing the probability of driver resonance.

[0040] During this process, the system also dynamically uses the critical point risk value as a real-time correction factor. When a potential risk is detected in the output waveform near the critical point, the system automatically adjusts the amplitude or duty cycle change rate of the micro-jitter frequency to prevent the PWM signal from coupling with the critical frequency. In this way, the PWM output not only depends on the mapping result but also forms a dynamic closed loop with the risk feedback.

[0041] Finally, the generated PWM signal is output to the actual LED light fixture or related load through the driver module. Throughout the output process, the system simultaneously records the frequency, duty cycle, and waveform correction parameters, and compares them with safety threshold parameters. If the current, voltage, or temperature is detected to be close to the threshold boundary, the system will automatically adjust the step size of the PWM duty cycle to ensure that the output remains within the safe range.

[0042] S3: After outputting the mapping table, it receives the target brightness command and converts it into a duty cycle. It then combines the command with the correction frequency to generate a PWM signal. Subsequently, it performs slope limiting, edge shaping, and micro-jitter processing to form a stable waveform. During the output process, the real-time sampled data outputs the risk value again and inputs it into the closed-loop adjustment model to perform a second correction on the frequency.

[0043] Furthermore, after completing the PWM signal generation and optimization, the system enters a closed-loop operation state. At this point, the output PWM signal has been applied to the LED driver and the lamp body, but due to dynamic changes in the operating environment, such as mains voltage fluctuations, device temperature rise, and load disturbances, the actual operating state may deviate from expectations. To ensure system stability, a closed-loop regulation and anomaly protection mechanism is introduced in stage S5.

[0044] First, the system samples the output status in real time using current, voltage, temperature, and optical brightness sensors. This data is not only compared to safety thresholds, but also... To dynamically assess the risk level. When the real-time collected metrics display the PWM output frequency... or duty cycle When the system falls near the critical point, it will trigger closed-loop correction logic.

[0045] The closed-loop control process employs a risk feedback function that couples real-time risk with the mapped frequency: ; in, This is the actual output frequency after closed-loop correction. For time variables, For the target brightness command, a three-segment mapping and disabled frequency band correction rule is used. The target frequency obtained, This is a positive constant for the frequency correction factor. The risk value calculated based on the real-time sampling and flicker risk model ( ), This refers to the electrical energy fluctuation or equivalent energy index (relative quantity) obtained by integrating voltage and current within the current time window. This is an energy reference value. (The energy scale factor is used to normalize the denominator to a positive constant). The target brightness setpoint given by the control terminal.

[0046] The range of values ​​is ,in The lowest permissible drive frequency, The maximum permissible frequency (e.g., 20kHz).

[0047] when and Time, , the system output is stable.

[0048] When or significantly deviates , the frequency will be suppressed or raised to evade flicker and instability risks.

[0049] After completing the frequency correction, the system will also perform hysteresis processing 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.

[0050] 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 carried out for scientific demonstration.

[0051] 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 profile 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 modified 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 at a fixed period to make a second correction to the frequency; 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.

[0052] Table 1 Experimental data table

[0053] 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.

[0054] 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.

[0055] "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 rise 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.

[0056] 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.

[0057] In one embodiment of the present application, the intelligent variable frequency dimming system comprises a parameter initialization and sampling module, a risk identification and frequency mapping module, and a PWM generation and closed-loop adjustment module.

[0058] 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 segmentation points, safety threshold, and disabled frequency point table, generate an 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 values in combination with the stroboscopic risk model, identify and mark critical points, generate a three-segment frequency mapping relationship according to the segmentation points, 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 the duty cycle and mapping frequency according to the target brightness instruction, generate a PWM control signal, and perform slope limiting, edge shaping, and micro-dithering optimization during output, while collecting running data in real time for closed-loop risk assessment, dynamically correcting the frequency and duty cycle when the parameters exceed the threshold, and triggering an abnormal protection mechanism.

[0059] If the functions are implemented 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 a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0060] The logic and / or steps represented in the flow diagrams or otherwise 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.

[0061] 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

[0062] 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.

[0063] 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, The application comprises: 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 the current, voltage and optical brightness; Based on the data matrix output current deviation, voltage deviation and brightness energy, the quantitative risk value is obtained combining the stroboscopic risk model, and compared with the initialization threshold to form the baseline table, when the brightness point exceeds the threshold, it is marked as a critical point, and the critical point data is written into the parameter table, and the initial segmentation point is entered 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 piecewise interpolation, and the result is constrained by the disabled frequency point table at the same time; After the mapping table is output, the target brightness instruction is received and converted into the duty cycle, combined with the corrected frequency to generate the PWM signal, then the slope limiting, edge shaping and micro-jitter frequency processing are carried out to form a stable waveform, in the output process, the real-time sampling data is output again to output the risk value and input the closed-loop adjustment model to make a second correction to the frequency.

2. The intelligent variable frequency dimming method of claim 1, wherein: The disabled frequency point table comprises two parts of the preset frequency band and the on-site detection frequency band, and is loaded together when the initialization vector is generated.

3. The intelligent variable frequency dimming method of claim 2, wherein: The initialization vector comprises the communication mode, the frequency initial value, the duty cycle segmentation point, the safety threshold, the driver parameters and the lamp parameters.

4. The intelligent variable frequency dimming method of claim 3, wherein: The synchronous sampling of the current, voltage and optical brightness at the typical brightness point comprises band-pass filtering of the current signal, sliding mean normalization of the voltage signal and segmented frequency domain integral processing of the optical brightness signal.

5. The intelligent variable frequency dimming method of claim 4, wherein: The three-stage frequency mapping generation comprises dividing the duty cycle interval into three continuous intervals of low brightness segment, medium brightness segment and high brightness segment, and establishing the corresponding relationship between the brightness point and the frequency in each interval by using the piecewise interpolation method.

6. The intelligent variable frequency dimming method of claim 5, wherein: The three-stage frequency mapping generation comprises marking the brightness point as a critical point if the risk value of the brightness point exceeds the threshold in three samplings, and correcting the frequency parameters of the partition according to the critical point risk value.

7. The intelligent variable frequency dimming method of claim 6, wherein: The closed-loop adjustment model comprises collecting the current, voltage, temperature and optical brightness data in real time while outputting the PWM signal, and comparing the sampling results with the preset reference threshold; When the monitoring result exceeds the threshold, the output frequency and the duty cycle are dynamically corrected according to the risk deviation, and a hysteresis mechanism is introduced near the critical value to avoid repeated switching of the frequency near the critical point.

8. A system employing the intelligent variable frequency dimming method as claimed in any one of claims 1 to 7, characterized in that: The application comprises parameter initialization and sampling module, risk identification and frequency mapping module, PWM generation and closed-loop adjustment module; The parameter initialization and sampling module is used for establishing the communication connection between the module and the gateway, loading the frequency mapping table, the duty cycle segmentation point, the safety threshold and the disabled frequency point table, generating the initialization vector combining the driver and the lamp parameters, and performing synchronous sampling of the current, voltage and optical brightness at the typical brightness point to form the data matrix. The risk identification and frequency mapping module is used for calculating current deviation, voltage deviation and brightness energy based on a data matrix, outputting a risk value in combination with a stroboscopic risk model, identifying and marking a critical point, generating a three-section frequency mapping relationship according to a segmentation point, correcting a target frequency, and forming a continuous and effective frequency mapping table through interpolation and a disabled frequency point table; The PWM generation and closed-loop regulation module is used for acquiring a duty ratio and a mapping frequency according to a target brightness instruction, generating a PWM control signal, performing slope limiting, edge shaping and micro-jitter frequency optimization in an output process, simultaneously collecting running data for closed-loop risk evaluation, dynamically correcting the frequency and the duty ratio when parameters exceed a threshold, and triggering an abnormal protection mechanism.

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