LED lamp attenuation compensation method, intelligent electrical appliance and intelligent extractor hood

Abstract

This application relates to an LED lamp attenuation compensation method, a smart appliance, and a smart range hood. The method acquires a current sampling signal; the current sampling signal is detected by a current transformer installed on the LED lamp's power line; a detection amplitude at a specific frequency point is extracted from the current sampling signal; based on the detection amplitude and a preset standard amplitude, an attenuation characteristic value at the specific frequency point is calculated; based on the attenuation characteristic value at the specific frequency point, the original driving signal of the LED lamp is compensated to adjust the LED lamp to emit light normally. This solves the problem of poor reliability in LED attenuation compensation, and combines current signal frequency domain analysis with an LED light decay compensation mechanism, realizing a new path for low-cost, high-reliability intelligent lighting control.

Description

Technical Field

[0001] This application relates to the field of LED lamp attenuation compensation, and in particular to LED lamp attenuation compensation methods, smart appliances, and smart range hoods. Background Technology

[0002] LEDs, also known as light-emitting diodes, have advantages such as using low-voltage power supplies, low energy consumption, wide applicability, high stability, short response time, no environmental pollution, and multi-color emission. They are widely used in mobile phones, desk lamps, home appliances, and machinery manufacturing. However, LEDs inevitably experience light decay over long-term use, meaning their brightness gradually decreases over time, severely impacting user experience and lighting quality.

[0003] In existing technologies, fixed compensation curves are often used for brightness compensation. However, different usage methods can affect the decay rate and degree of LEDs. Fixed compensation curves are difficult to accurately adapt to the actual decay state of LEDs, which can easily lead to insufficient or excessive compensation and make it impossible to achieve fine control.

[0004] There is currently no effective solution to the problem of poor reliability of LED attenuation compensation in related technologies. Summary of the Invention

[0005] This embodiment provides an LED light attenuation compensation method, a smart appliance, and a smart range hood to solve the problem of poor reliability of LED attenuation compensation in related technologies.

[0006] Firstly, this embodiment provides an LED lamp attenuation compensation method, the method comprising:

[0007] Acquire a current sampling signal; the current sampling signal is detected by a current transformer installed on the power supply line of the LED lamp;

[0008] Extract the detection amplitude at a specific frequency point from the current sampling signal; calculate the attenuation characteristic value at the specific frequency point based on the detection amplitude and a preset standard amplitude;

[0009] Based on the attenuation characteristic value at the specific frequency point, the original driving signal of the LED is compensated to adjust the LED to emit light normally.

[0010] In some embodiments, extracting the detection amplitude at a specific frequency point from the current sampling signal includes:

[0011] Based on the current sampling signal and the preset window signal, a windowing signal is obtained;

[0012] The windowed signal is subjected to spectral analysis based on Fast Fourier Transform to extract the detection amplitude corresponding to a specific frequency point.

[0013] In some embodiments, the original driving signal of the LED is compensated based on the attenuation characteristic value at the specific frequency point to adjust the LED to emit light normally, including:

[0014] The attenuation degree of the LED lamp is evaluated based on the attenuation characteristic value at the specific frequency point; wherein, the specific frequency point includes a first frequency point reflecting the state of the lamp bead and a second frequency point reflecting the switching characteristics of the circuit;

[0015] If the attenuation is slight, the original driving signal is compensated based on the characteristic value corresponding to the first frequency point to adjust the LED to emit light normally.

[0016] If the attenuation level is severe, an alert signal will be output and a safety protection mechanism will be activated.

[0017] In some embodiments, the attenuation degree of the LED lamp is evaluated based on the attenuation characteristic value at the specific frequency point, including:

[0018] Construct a feature vector from the attenuation feature values ​​corresponding to each specific frequency point;

[0019] The feature vector is input into a fully trained neural network model to evaluate the attenuation level of the LED light;

[0020] The fully trained neural network model is used to perform multi-dimensional state analysis on the LED light based on the received feature vector, and obtain multi-dimensional analysis results; based on the multi-dimensional analysis results, the attenuation degree of the LED light is evaluated.

[0021] In some embodiments, based on the received feature vector, a multi-dimensional state analysis is performed on the LED light to obtain multi-dimensional analysis results, including:

[0022] Based on the feature vectors and various state analysis parameters, multi-dimensional analysis results are calculated.

[0023] The various state analysis parameters are obtained by training the neural network model for harmonic attenuation analysis, switching characteristic analysis, high-frequency component analysis, and health benchmark comparison analysis, respectively.

[0024] In some embodiments, the attenuation of the LED light is evaluated based on the results of the multi-dimensional analysis, including:

[0025] Based on the multi-dimensional analysis results and various evaluation parameters, evaluation values ​​for each degree of decay are calculated; wherein, each evaluation parameter is obtained by training the neural network model for three degrees of decay: normal state, mild decay, and severe decay.

[0026] Based on the evaluation values ​​of each degree of attenuation, the degree of attenuation of the LED light is determined, including the normal state, the slight attenuation, and the severe attenuation.

[0027] In some embodiments, the specific frequency point further includes: a third frequency point reflecting the overall attenuation level and a fourth frequency point reflecting the health of the PCB substrate.

[0028] In some of these embodiments, the first frequency point reflecting the state of the LED includes a blue light frequency point and a white light frequency point.

[0029] Secondly, this embodiment provides a smart appliance, which includes an LED light and a control module;

[0030] The LED light includes a driving circuit, LED beads, and a current transformer, wherein the current transformer is disposed on the power line between the driving circuit and the LED beads.

[0031] The control module, connected to the drive circuit and the current transformer, is used to perform the steps of the LED lamp attenuation compensation method described in any one of the first aspects.

[0032] In some of these embodiments, the smart appliance includes a smart range hood.

[0033] Compared with related technologies, the LED lamp attenuation compensation method, smart appliance, and smart range hood provided in this embodiment acquire a current sampling signal; the current sampling signal is detected by a current transformer installed on the LED lamp power line; the detection amplitude at a specific frequency point is extracted from the current sampling signal; based on the detection amplitude and a preset standard amplitude, the attenuation characteristic value at the specific frequency point is calculated; based on the attenuation characteristic value at the specific frequency point, the original driving signal of the LED lamp is compensated to adjust the LED lamp to emit light normally. This solves the problem of poor reliability of LED attenuation compensation, combines current signal frequency domain analysis with LED light decay compensation mechanism, and realizes a new path for low-cost and high-reliability intelligent lighting control.

[0034] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0035] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0036] Figure 1 This is a hardware structure block diagram of the terminal of the LED lamp attenuation compensation method in one embodiment;

[0037] Figure 2 This is a flowchart illustrating an LED lamp attenuation compensation method in one embodiment;

[0038] Figure 3 This is a schematic diagram of a current transformer detecting the power supply line of an LED lamp in one embodiment.

[0039] Figure 4 This is a schematic diagram illustrating the evaluation of attenuation state based on attenuation feature values ​​in one embodiment;

[0040] Figure 5 This is a schematic diagram illustrating the evaluation of attenuation state based on attenuation characteristic values ​​in another embodiment;

[0041] Figure 6 This is a schematic diagram illustrating the relative installation of the smart range hood with the stove, cooking utensils, and range hood lighting in one embodiment.

[0042] Figure 7 This is a flowchart illustrating an LED lamp attenuation compensation method in a preferred embodiment.

[0043] Figure 8 This is a structural block diagram of an LED lamp attenuation compensation device in one embodiment.

[0044] Reference numerals: 102, processor; 104, memory; 106, transmission device; 108, input / output device; 81, sampling module; 82, feature analysis module; 83, attenuation compensation module. Detailed Implementation

[0045] To better understand the purpose, technical solution, and advantages of this application, the application is described and illustrated below in conjunction with the accompanying drawings and embodiments.

[0046] Unless otherwise defined, the technical or scientific terms used in this application shall have the general meaning understood by one of ordinary skill in the art to which this application pertains. Words such as “a,” “an,” “an,” “the,” “the,” and “these” used in this application do not indicate quantitative limitation and may be singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or modules (units) is not limited to the listed steps or modules (units) but may include steps or modules (units) not listed, or may include other steps or modules (units) inherent to these processes, methods, products, or devices. Words such as “connected,” “linked,” and “coupled” used in this application are not limited to physical or mechanical connections but may include electrical connections, whether direct or indirect. “Multiple” used in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. Normally, the character " / " indicates that the objects before and after it are in an "or" relationship. The terms "first," "second," "third," etc., used in this application are merely to distinguish similar objects and do not represent a specific order of objects.

[0047] The method embodiments provided in this example can be executed on a terminal, computer, or similar computing device. For example, it can run on a terminal. Figure 1 This is a hardware structure block diagram of the terminal of the LED lamp attenuation compensation method in this embodiment. For example... Figure 1 As shown, a terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 and a memory 104 for storing data are also included. The processor 102 may be, but is not limited to, a microprocessor (MCU) or a programmable logic device (FPGA). The terminal may also include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that… Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the terminal described above. For example, the terminal may also include components that are larger than... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown are illustrated.

[0048] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the LED lamp attenuation compensation method in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0049] The transmission device 106 is used to receive or send data via a network. This network includes a wireless network provided by the terminal's communication provider. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 can be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0050] This embodiment provides a method for compensating for LED lamp attenuation. Figure 2 This is a flowchart of the LED lamp attenuation compensation method in this embodiment, as follows: Figure 2 As shown, the process includes the following steps:

[0051] Step S210: Acquire current sampling signal; the current sampling signal is detected by a current transformer installed on the power supply line of the LED lamp.

[0052] Specifically, the circuit system of an LED light can be likened to a mechanical vibration system. When "parts wear out" (LED chip decay), the system emits unique "abnormal vibration signals" (electromagnetic harmonics). We use a "stethoscope" (current transformer) to capture these signals in order to further identify fault characteristics. The LED light power supply line refers to the driver power supply directly connected to the LED chip string, and its function is to input the drive current. For example... Figure 3 As shown, the drive power supply line connecting the LED driver chip and LED beads in series is the LED lamp power supply line, and the ring device wrapped around the drive power supply line is the current transformer. The current transformer detects the current change in the drive power supply line through electromagnetic induction and outputs an induced signal, thereby obtaining a current sampling signal. This embodiment can perform non-invasive detection while maintaining normal lighting conditions, without affecting the lighting, and without requiring the LED lamp to enter an additional detection state.

[0053] Step S220: Extract the detection amplitude at a specific frequency point from the current sampling signal; calculate the attenuation characteristic value at the specific frequency point based on the detection amplitude and the preset standard amplitude.

[0054] Specifically, the current sampling signal is sequentially filtered, amplified, and converted by an ADC to obtain a sampling sequence. Based on the sampling sequence, the frequency components of the vibration wave are analyzed, and the detection amplitude at a specific frequency point is extracted from the analysis results. The specific frequency point includes at least a first frequency point reflecting the state of the LED and a second frequency point reflecting the switching characteristics of the circuit. The first frequency point is preferably a blue light frequency point, but it may also include a white light frequency point. The specific frequency point may also further include a third frequency point reflecting the overall attenuation level and a fourth frequency point reflecting the health of the PCB substrate. For example, the selection of specific frequency points is shown in Table 1 below.

[0055] Table 1:

[0056]

[0057] The selection criteria for each frequency point are explained as follows: Blue LEDs commonly use InGaN materials with small junction capacitance Cj (~50pF), fast switching speed, and rich high-frequency harmonics, typically corresponding to 150MHz; White LEDs contain a phosphor layer, have large heat capacity, and the change in thermal resistance dominates the 180MHz response; A typical LED driver chip (such as PT4115) has a switching frequency of 600kHz, and its 35th harmonic is exactly around 210MHz (600kHz×35=210MHz); Aging of all LED chips will lead to an increase in the circuit quality factor, forming a resonance peak around 240MHz; The skin effect of PCB copper foil is significant at >250MHz, and aging and cracking will change the high-frequency loss characteristics, corresponding to 270MHz.

[0058] In addition, the harmonic fingerprint database stores the reference electromagnetic characteristics of LED lights in a brand-new state, including the reference harmonic data collected when the LED lights are operating in a brand-new, healthy state, as shown in Table 1, with standard amplitudes at each characteristic frequency point (150MHz, 180MHz, 210MHz, 240MHz, 270MHz). The required standard amplitudes are extracted from the preset harmonic fingerprint database. These standard amplitudes are used to provide the reference values ​​for calculating attenuation characteristic values, essentially acting as an "electromagnetic ID card" for the healthy state.

[0059] The attenuation characteristic value can be obtained based on the ratio of the detected amplitude to the standard amplitude, i.e., the attenuation ratio, calculated as follows:

[0060] ;

[0061] ;

[0062] Among them, H 150 H represents the detected amplitude at a blue light frequency point. 150_初始 H represents the standard amplitude of a blue light frequency point. 210 H represents the detected amplitude at the second frequency point, reflecting the switching characteristics of the circuit. 210_初始 This represents the standard amplitude at a second frequency point that reflects the switching characteristics of the circuit. R>1 indicates that the frequency component is enhanced (similar to an increase in amplitude at a specific wear frequency); R<1 indicates that the frequency component is weakened. In other embodiments, the attenuation characteristic value can also be calculated based on algorithms such as the absolute difference, relative difference, and logarithmic ratio between the detected amplitude and the standard amplitude.

[0063] Step S230: Based on the attenuation characteristic value at a specific frequency point, the original driving signal of the LED lamp is compensated to adjust the LED lamp to emit light normally.

[0064] Specifically, based on the attenuation characteristic value corresponding to the first frequency point, its "operating time percentage" is increased to compensate for the original drive signal. For example, the calculation formula is as follows: D new =D0×(1+α×△R), where D0 is the initial duty cycle (e.g., 30%); α is the compensation coefficient (determined experimentally, typically 0.5); △R is the corresponding LED attenuation level, for example △R=R 150 -1, where R 150 This represents the attenuation characteristic value at the blue light frequency point.

[0065] In this embodiment, a current sampling signal is acquired; the current sampling signal is detected by a current transformer installed on the power line of the LED lamp; the detection amplitude at a specific frequency point is extracted from the current sampling signal; based on the detection amplitude and a preset standard amplitude, the attenuation characteristic value at the specific frequency point is calculated; based on the attenuation characteristic value at the specific frequency point, the original driving signal of the LED lamp is compensated to adjust the LED lamp to emit light normally. This solves the problem of poor reliability of LED attenuation compensation. By combining the frequency domain analysis of the current signal with the LED light decay compensation mechanism, a new path for low-cost and high-reliability intelligent lighting control is realized.

[0066] In some embodiments, extracting the detection amplitude at a specific frequency point from the current sampling signal includes:

[0067] Step S310: Based on the current sampling signal and the preset window signal, a windowed signal is obtained.

[0068] Specifically, the current sampling signal is filtered, allowing only signals in the 30-300MHz range to pass through; the filtered current sampling signal is amplified to a measurable range, and the analog signal is converted into a digital signal to obtain the sampling sequence s[n]; the sampling sequence s[n] is then windowed, for example using a Blackman-Harris window, by multiplying the sampling sequence s[n] with the window signal w[n] to obtain the windowed signal s w [n]. Directly truncating the signal will cause spectral leakage (similar to the "truncation effect" in mechanical vibration testing). Processing with a window function (i.e., a window signal) can avoid this problem. It is equivalent to adding a buffer to the vibration signal to avoid false frequency components caused by sudden truncation, thereby reducing spectral sidelobes and improving frequency resolution.

[0069] Step S320: Perform spectral analysis on the windowed signal based on Fast Fourier Transform to extract the detection amplitude corresponding to a specific frequency point.

[0070] Specifically, the Fast Fourier Transform (FFT) is equivalent to a "spectrum analyzer," decomposing the windowed signal s. w The frequency components of [n] can output the amplitude values ​​of multiple (e.g., 256) frequency points, from which the specific frequencies of interest can be extracted.

[0071] In this embodiment, the detection amplitude corresponding to a specific frequency point is quickly and accurately extracted through windowing and spectrum analysis.

[0072] In some embodiments, the original driving signal of the LED is compensated based on the attenuation characteristic value at a specific frequency point to adjust the LED to emit light normally, including:

[0073] Step S410: Evaluate the attenuation level of the LED lamp based on the attenuation characteristic value at a specific frequency point; wherein, the specific frequency point includes a first frequency point reflecting the state of the LED bead and a second frequency point reflecting the switching characteristics of the circuit.

[0074] Specifically, the attenuation feature values ​​at specific frequency points are input into a fully trained neural network model to classify them and predict their attenuation degree. In other implementations, such as... Figure 4 As shown, the attenuation characteristic value R at the second frequency point is determined. 210 Does it exceed the first rule threshold of 1.25? If yes, it is determined to be severe attenuation; if no, the attenuation characteristic value R at the first frequency point is determined. 150If the frequency exceeds the second rule threshold of 1.1, it is considered a slight attenuation; otherwise, it is considered normal. The second frequency point (210MHz) is most sensitive to the aging of switching components, similar to the vibration frequency in mechanical equipment. The preferred first frequency point is the blue light frequency point (150MHz). Blue light LEDs have a 30% shorter lifespan than white light LEDs, and blue light LEDs generally attenuate first; therefore, blue light is used as a representative for judgment.

[0075] In step S420, if the attenuation is slight, the original driving signal is compensated based on the characteristic value corresponding to the first frequency point to adjust the LED to emit light normally.

[0076] Specifically, PWM compensation control is executed during slight attenuation, and the new drive signal D... new The calculation formula is D new =D0×(1+α×△R), where D0 is the initial duty cycle (e.g., 30%); α is the compensation coefficient (determined experimentally, typically 0.5); △R is the corresponding LED attenuation level, for example △R=R 150 -1, where R 150 This represents the attenuation characteristic value at the blue light frequency point.

[0077] In step S430, if the attenuation level is severe, an alert signal is output and a safety protection mechanism is activated.

[0078] Specifically, after entering the safety protection mechanism, the cumulative timer begins recording the duration of the severe degradation state. If it exceeds 8 hours, the warm light mode (3000K) is automatically locked. Since the warm light mode is least sensitive to degradation, it extends the lifespan of the LED light, allowing it to be repaired or replaced by the user.

[0079] Step S440: If the attenuation level is normal, perform attenuation detection again after a preset sleep time.

[0080] In this embodiment, adaptive adjustment of the LED light is achieved, improving the user experience.

[0081] In some of these embodiments, the attenuation level of the LED lamp is evaluated based on attenuation characteristic values ​​at a specific frequency point, including:

[0082] Step S510: Construct a feature vector from the attenuation feature values ​​corresponding to each specific frequency point.

[0083] Specifically, taking a feature vector Fv composed of 5 dimensional feature values ​​as an example, Fv=[R 150 R 180 R 210 R 240 R 270 ], where R 150R represents the attenuation characteristic value at a blue light frequency point; 180 R represents the attenuation characteristic value at a frequency point of white light. 210 R represents the attenuation characteristic value at the second frequency point. 240 R represents the attenuation characteristic value at the third frequency point. 270 This represents the attenuation characteristic value at the fourth frequency point.

[0084] Step S520: Input the feature vector into the fully trained neural network model to evaluate the attenuation level of the LED light; wherein, the fully trained neural network model is used to perform multi-dimensional state analysis on the LED light based on the received feature vector to obtain multi-dimensional analysis results; based on the multi-dimensional analysis results, evaluate the attenuation level of the LED light.

[0085] For details, see Figure 5 The fully trained neural network model includes an input layer, hidden layers, and an output layer. The input layer takes feature vectors as input; the hidden layer calculates multi-dimensional analysis results based on the feature vectors and various state analysis parameters; and the output layer uses these multi-dimensional analysis results to evaluate the attenuation level of the LED light. The hidden layer includes multiple computation nodes, each calculating a diagnostic dimension. For example, node 1 is used for harmonic attenuation analysis, node 2 for switching characteristic analysis, node 3 for high-frequency component analysis, and node 4 for health benchmark comparison analysis. The output layer also includes multiple computation nodes, each corresponding to a specific attenuation level, such as a normal state calculation node, a mild attenuation calculation node, and a severe attenuation calculation node. Each node predicts the probability that the multi-dimensional analysis result belongs to its corresponding attenuation level. The degree of LED light attenuation can then be determined based on the probabilities of each attenuation level.

[0086] In this embodiment, a "fault diagnosis expert system" based on neural networks is used to improve the accuracy of analysis.

[0087] In some embodiments, based on the received feature vectors, a multi-dimensional state analysis is performed on the LED light to obtain multi-dimensional analysis results, including:

[0088] Step S521: Based on the feature vector and each state analysis parameter, multi-dimensional analysis results are calculated; wherein, each state analysis parameter is obtained by training the neural network model for the functions of harmonic attenuation analysis, switching characteristic analysis, high frequency component analysis and health benchmark comparison analysis.

[0089] Specifically, the hidden layer includes at least four computational nodes: a harmonic attenuation analysis node, a switching characteristic analysis node, a high-frequency component analysis node, and a health benchmark comparison analysis node. The computational mechanism of the hidden layer is shown in Table 2, where W1, W2, and W3 are the weight matrices of each node (obtained by training the neural network model), B1, B2, and B3 are the bias phases of each node, X is the input feature vector Fv, X0 is the initial health state benchmark value, and h1, h2, h3, and h4 are the analysis structures of each node, forming a multi-dimensional analysis result H=[h1, h2, h3, h4].

[0090] Table 2:

[0091]

[0092] In some of these embodiments, the attenuation of LED lights is evaluated based on multi-dimensional analysis results, including:

[0093] Step S522: Based on the multi-dimensional analysis results and various evaluation parameters, the evaluation values ​​for each degree of decay are calculated respectively; wherein, each evaluation parameter is obtained by training a neural network model for three degrees of decay: normal state, mild decay and severe decay.

[0094] Step S523: Based on the evaluation values ​​of each attenuation level, determine the attenuation level of the LED light. The attenuation level includes normal state, slight attenuation and severe attenuation.

[0095] Specifically, the calculation of the output layer of a fully trained neural network model is as follows:

[0096] ;

[0097] Among them, P i z represents the probability value for each state (normal, mild decay, and severe decay); i z represents the evaluation value for each degree of attenuation. i =w i ·H+b i H represents the multi-dimensional analysis results output by the hidden layer, and w i and b i For each attenuation evaluation parameter, w1, w2, and w3 are weight vectors, with the dimension of each weight vector corresponding to the dimension of the multi-dimensional analysis result. b1, b2, and b3 are bias terms. Each z... i The same H vector is used in the calculation, but different weight vectors and bias terms are used.

[0098] Compare probability values ​​P i(i=1,2,3), the state corresponding to the highest probability value is taken as the degree of LED light degradation. For example, if P1 corresponds to normal state, P2 corresponds to slight degradation, and P3 corresponds to severe degradation, and the calculated probability evaluation values ​​are: [P1=0.05; P2=0.25; P3=0.70], then it is determined to be severe degradation. It is recommended to confirm that P is satisfied during comparison. max If the value is greater than 0.5, a review mechanism will be triggered to recalculate the probability assessment.

[0099] This embodiment provides a smart appliance, which includes an LED light and a control module. The LED light includes a driver circuit, LED beads, and a current transformer, with the current transformer disposed on the power line between the driver circuit and the LED beads. The control module, connected to the driver circuit and the current transformer, is used to execute the steps of the LED light attenuation compensation method in any of the above embodiments. The smart appliance includes one of the following: a smart range hood, a smart steam oven, a smart refrigerator, etc.

[0100] In this embodiment, a current sampling signal is acquired; the current sampling signal is detected by a current transformer installed on the power line of the LED lamp; the detection amplitude at a specific frequency point is extracted from the current sampling signal; based on the detection amplitude and a preset standard amplitude, the attenuation characteristic value at the specific frequency point is calculated; based on the attenuation characteristic value at the specific frequency point, the original driving signal of the LED lamp is compensated to adjust the LED lamp to emit light normally. This solves the problem of poor reliability of LED attenuation compensation. By combining the frequency domain analysis of the current signal with the LED light decay compensation mechanism, a new path for low-cost and high-reliability intelligent lighting control is realized.

[0101] The present embodiment will now be described and illustrated through preferred embodiments.

[0102] The detection principle and core idea of ​​this preferred embodiment are as follows: the LED circuit system is likened to a mechanical vibration system. When "parts wear out" (LED chip decay), the system emits unique "abnormal vibration signals" (electromagnetic harmonics). We capture these signals using a "stethoscope" (current transformer) and identify fault characteristics using a "spectrum analyzer" (FFT algorithm). The core physical relationships involved are as follows:

[0103] (1) When the LED light beads decay, the PN junction capacitance C j Decrease:

[0104] ;

[0105] Where: C j0 V is the initial junction capacitance (F); R V is the reverse bias voltage (V); biis the built-in potential (V); m is the gradient coefficient (calibrated by actual measurement before design or delivery, generally between 0.3 and 0.5).

[0106] (2) Harmonic variation mechanism: Switching transient current Fourier transform:

[0107] ;

[0108] C j Reducing the switching speed will increase the high-frequency harmonic components H in the current. n Enhancement:

[0109] ;

[0110] Where k is the electromagnetic coupling coefficient; β is the dielectric attenuation coefficient; and n is the harmonic order (n≥5).

[0111] This preferred embodiment can be applied to intelligent range hoods. Figure 6 This diagram illustrates the relative installation of a smart range hood with the cooktop, cooking appliances, and range hood lighting. Figure 6 The intelligent range hood includes an LED light and a control module. The LED light includes a driver circuit, LED beads, and a current transformer, with the current transformer positioned on the power line between the driver circuit and the LED beads. The control module is connected to the driver circuit and the current transformer and is used for steps in the LED light attenuation compensation method, such as... Figure 7 As shown, the specific process of this LED lamp attenuation compensation method is as follows:

[0112] S1. Load the harmonic fingerprint database; the harmonic fingerprint database stores the reference harmonic data collected when the LED light is working in a brand new and healthy state, such as the standard amplitude of each characteristic frequency point (150MHz, 180MHz, 210MHz, 240MHz, 270MHz) in Table 1 above.

[0113] S2. Acquire the current sampling signal; the current sampling signal is obtained by a current transformer installed on the power supply line of the LED lamp.

[0114] S3. The current sampling signal is filtered, amplified, and converted by an ADC in sequence to obtain the sampling sequence s[n]; the sampling sequence s[n] is then windowed to obtain the windowed signal s. w [n].

[0115] S4. Windowed signal s based on Fast Fourier Transform w[n] Perform spectrum analysis to extract the detection amplitude corresponding to specific frequency points. Specific frequency points include the first frequency point reflecting the status of the LED beads (150MHz for blue light and 180MHz for white light), the second frequency point reflecting the switching characteristics of the circuit (210MHz), the third frequency point reflecting the overall attenuation level (240MHz), and the fourth frequency point reflecting the health of the PCB substrate (270MHz).

[0116] S5. Based on the detected amplitude and the preset standard amplitude, calculate the attenuation characteristic value at a specific frequency point, and construct the attenuation characteristic value corresponding to each specific frequency point as a feature vector Fv=[R 150 R 180 R 210 R 240 R 270 ]. Among them, R 150 R represents the attenuation characteristic value at a blue light frequency point; 180 R represents the attenuation characteristic value at a frequency point of white light. 210 R represents the attenuation characteristic value at the second frequency point. 240 R represents the attenuation characteristic value at the third frequency point. 270 This represents the attenuation characteristic value at the fourth frequency point.

[0117] S6. Input the feature vector into the fully trained neural network model to evaluate the attenuation level of the LED light; wherein, the fully trained neural network model is used to perform multi-dimensional state analysis on the LED light based on the received feature vector to obtain multi-dimensional analysis results; based on the multi-dimensional analysis results, evaluate the attenuation level of the LED light.

[0118] S7. If the attenuation is slight, the original drive signal is compensated based on the characteristic value corresponding to the first frequency point to adjust the LED to emit light normally, and the attenuation detection is restarted after the current sampling period Δt ends; if the attenuation is severe, a prompt signal is output and a safety protection mechanism is activated, and the attenuation detection is restarted after the current sampling period Δt ends; if the attenuation is normal, the attenuation detection is restarted after a preset sleep time.

[0119] In this preferred embodiment, there is no need to modify the optical path or add optical sensors, simplifying the structural setup; multi-band parameters are used to comprehensively judge the attenuation of the LED beads, improving the judgment accuracy; the PWM duty cycle is dynamically adjusted to maintain the target color temperature or brightness, achieving adaptive compensation; the problem of traditional optical detection schemes being easily contaminated and having reduced accuracy in oil fume environments is solved, and long-term stable monitoring under harsh working conditions is achieved.

[0120] It should be noted that the steps shown in the above process or in the flowchart of the accompanying figures can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0121] This embodiment also provides an LED lamp attenuation compensation device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. The terms "module," "unit," "subunit," etc., used below refer to combinations of software and / or hardware that achieve a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0122] Figure 8 This is a structural block diagram of the LED lamp attenuation compensation device in this embodiment, as shown below. Figure 8 As shown, the device includes: a sampling module 81, a feature analysis module 82, and an attenuation compensation module 83.

[0123] The sampling module 81 is used to acquire the current sampling signal; the current sampling signal is detected by the current transformer installed on the power supply line of the LED lamp;

[0124] The feature analysis module 82 is used to extract the detection amplitude at a specific frequency point from the current sampling signal; and to calculate the attenuation characteristic value at the specific frequency point based on the detection amplitude and the preset standard amplitude.

[0125] The attenuation compensation module 83 compensates the original driving signal of the LED lamp based on the attenuation characteristic value at a specific frequency point in order to adjust the LED lamp to emit light normally.

[0126] It should be noted that the above modules can be functional modules or program modules, and can be implemented through software or hardware. For modules implemented through hardware, the above modules can reside in the same processor; or the above modules can be located in different processors in any combination.

[0127] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated in this embodiment.

[0128] Furthermore, in conjunction with the LED lamp attenuation compensation method provided in the above embodiments, this embodiment can also provide a storage medium for implementation. This storage medium stores a computer program; when executed by a processor, the computer program implements any one of the LED lamp attenuation compensation methods in the above embodiments.

[0129] It should be understood that the specific embodiments described herein are merely illustrative of the application and not intended to limit it. All other embodiments derived by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application.

[0130] Obviously, the accompanying drawings are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar situations based on these drawings without any creative effort. Furthermore, it is understood that although the work done in this development process may be complex and lengthy, for those skilled in the art, certain design, manufacturing, or production modifications made based on the technical content disclosed in this application are merely conventional technical means and should not be considered as insufficient disclosure of this application.

[0131] The term "embodiment" in this application refers to a specific feature, structure, or characteristic described in connection with an embodiment that may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily imply the same embodiment, nor does it imply that it is mutually exclusive with or independent of other embodiments. It will be clearly or implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0132] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of patent protection. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the appended claims.

Claims

1. A method for compensating LED lamp attenuation, characterized in that, The method includes: Acquire a current sampling signal; the current sampling signal is detected by a current transformer installed on the power supply line of the LED lamp; Extract the detection amplitude at a specific frequency point from the current sampling signal; calculate the attenuation characteristic value at the specific frequency point based on the detection amplitude and a preset standard amplitude; Based on the attenuation characteristic value at the specific frequency point, the original driving signal of the LED is compensated to adjust the LED to emit light normally.

2. The LED lamp attenuation compensation method according to claim 1, characterized in that, Extracting the detection amplitude at a specific frequency point from the current sampling signal includes: Based on the current sampling signal and the preset window signal, a windowing signal is obtained; The windowed signal is subjected to spectral analysis based on Fast Fourier Transform to extract the detection amplitude corresponding to a specific frequency point.

3. The LED lamp attenuation compensation method according to claim 1, characterized in that, Based on the attenuation characteristic value at the specific frequency point, the original driving signal of the LED is compensated to adjust the LED to emit light normally, including: The attenuation degree of the LED lamp is evaluated based on the attenuation characteristic value at the specific frequency point; wherein, the specific frequency point includes a first frequency point reflecting the state of the lamp bead and a second frequency point reflecting the switching characteristics of the circuit; If the attenuation is slight, the original driving signal is compensated based on the characteristic value corresponding to the first frequency point to adjust the LED to emit light normally. If the attenuation level is severe, an alert signal will be output and a safety protection mechanism will be activated.

4. The LED lamp attenuation compensation method according to claim 3, characterized in that, The attenuation degree of the LED lamp is evaluated based on the attenuation characteristic value at the specific frequency point, including: Construct a feature vector from the attenuation feature values ​​corresponding to each specific frequency point; The feature vector is input into a fully trained neural network model to evaluate the attenuation level of the LED light; The fully trained neural network model is used to perform multi-dimensional state analysis on the LED light based on the received feature vector, and obtain multi-dimensional analysis results; based on the multi-dimensional analysis results, the attenuation degree of the LED light is evaluated.

5. The LED lamp attenuation compensation method according to claim 4, characterized in that, Based on the received feature vector, a multi-dimensional state analysis is performed on the LED light to obtain multi-dimensional analysis results, including: Based on the feature vectors and various state analysis parameters, multi-dimensional analysis results are calculated. The various state analysis parameters are obtained by training the neural network model for harmonic attenuation analysis, switching characteristic analysis, high-frequency component analysis, and health benchmark comparison analysis, respectively.

6. The LED lamp attenuation compensation method according to claim 4, characterized in that, Based on the multi-dimensional analysis results, the attenuation level of the LED light is evaluated, including: Based on the multi-dimensional analysis results and various evaluation parameters, evaluation values ​​for each degree of decay are calculated; wherein, each evaluation parameter is obtained by training the neural network model for three degrees of decay: normal state, mild decay, and severe decay. Based on the evaluation values ​​of each degree of attenuation, the degree of attenuation of the LED light is determined, including the normal state, the slight attenuation, and the severe attenuation.

7. The LED lamp attenuation compensation method according to claim 4, characterized in that, The specific frequency points also include: a third frequency point reflecting the overall attenuation level and a fourth frequency point reflecting the health of the PCB substrate.

8. The LED lamp attenuation compensation method according to claim 3, characterized in that, The first frequency point reflecting the state of the LED includes the blue light frequency point and the white light frequency point.

9. A smart appliance, characterized in that, The smart appliance includes LED lights and a control module. The LED light includes a driving circuit, LED beads, and a current transformer, wherein the current transformer is disposed on the power line between the driving circuit and the LED beads. The control module, connected to the drive circuit and the current transformer, is used to execute the steps of the LED lamp attenuation compensation method according to any one of claims 1 to 8.

10. The intelligent electrical appliance according to claim 9, characterized in that, Smart appliances include smart range hoods.

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