Wavelength adjustment method, device, equipment and storage medium for LED detection light source

Abstract

The present invention provides a wavelength adjustment method, device, equipment and storage medium for an LED detection light source. The method includes: emitting multi-band incident light through an LED light source array, and using a photodetector array to receive reflected light or transmitted light of a detection object to obtain spectral characteristic data of the detection object. According to the spectral characteristic data, the signal-to-noise ratio value and the characteristic response difference of each wavelength interval are calculated, and multi-target parameter optimization is performed in combination with the background noise coefficient of the detection object to obtain an optimal detection wavelength parameter group. Then, by controlling the driving current and chip temperature of the LED light source array in linkage, a ratio output signal of multiple groups of wavelengths is obtained. According to the compensated optimal detection wavelength parameter group, the LED light source array is wavelength adjusted. The method can perform adaptive wavelength adjustment according to the spectral characteristics of the detection object, optimize the light source output, improve the signal-to-noise ratio, and thus improve the detection accuracy, and has significant advantages in optical detection applications in complex environments.

Description

Technical Field

[0001] The present invention relates to the field of LED technology, and in particular to a wavelength adjustment method, device, equipment and storage medium for LED detection light sources. Background Art

[0002] In modern optical detection technology, LED detection light sources have been widely used in various detection scenarios such as material detection and surface analysis due to their advantages such as high stability, fast response and adjustable wavelength. However, factors such as the surface characteristics, material properties and environmental background noise of the detection object often have a significant impact on the spectral response, resulting in large differences in the reflection or transmission characteristic responses of LED light sources of different wavelengths to the detection object. Traditional LED light source wavelength adjustment methods mostly rely on fixed bands or preset wavelength combinations, and only adjust at a few wavelengths, which is difficult to adapt to the complexity and dynamic changes of the spectral characteristics of the detection object. In addition, it is difficult for existing methods to adaptively optimize the wavelength based on real-time spectral feature data, resulting in a significant decrease in the signal-to-noise ratio and limited detection accuracy in detection scenarios with complex background noise or multiple materials superimposed. Summary of the invention

[0003] The main purpose of the present invention is to solve the technical problem that the existing LED light source wavelength adjustment method is difficult to adaptively optimize the wavelength according to the spectral characteristics of the detection object, thereby resulting in a decrease in signal-to-noise ratio and insufficient detection accuracy;

[0004] A first aspect of the present invention provides a wavelength adjustment method for an LED detection light source, the wavelength adjustment method for an LED detection light source comprising:

[0005] The LED detection light source array emits multi-band incident light to the detection object, and a photodetector array is used to receive the reflected light or transmitted light of the detection object to obtain the spectral characteristic data of the detection object;

[0006] According to the spectral characteristic data, the signal-to-noise ratio value and the characteristic response difference of each wavelength interval are calculated, and the multi-objective parameter optimization operation is performed in combination with the background noise coefficient of the detection object to obtain the optimal detection wavelength parameter group;

[0007] According to the optimal detection wavelength parameter group, the driving current and chip temperature of the LED detection light source array are controlled in linkage to obtain a plurality of sets of wavelength matching output signals;

[0008] According to the ratio output signal, the optimal detection wavelength parameter group is compensated, and the wavelength of the LED detection light source array is adjusted according to the optimal detection wavelength parameter group after compensation.

[0009] Optionally, in a first implementation of the first aspect of the present invention, the LED detection light source array emits multi-band incident light to the detection object, and a photodetector array is used to receive reflected light or transmitted light of the detection object, and the spectral characteristic data of the detection object is obtained, which includes:

[0010] The wavelength band of the LED detection light source array is divided into equal intervals to obtain a wavelength detection sequence including multiple wavelength intervals, and the driving current of the LED detection light source array is adjusted in multiple stages according to the wavelength detection sequence;

[0011] Using a photodetector array to receive the reflected light or transmitted light of the detection object to obtain original spectral response data of the detection object;

[0012] The original spectral response data is subjected to denoising by Gaussian filtering, and the data of adjacent wavelength points in the original spectral response data after denoising are interpolated to obtain a continuous spectral characteristic curve of the detection object;

[0013] According to the continuous spectral characteristic curve, the absorption coefficient and reflection coefficient of the detection object at each wavelength point are calculated, a wavelength-response intensity mapping relationship is established, and the absorption coefficient, reflection coefficient and wavelength-response intensity mapping relationship are used as the spectral characteristic data of the detection object.

[0014] Optionally, in a second implementation of the first aspect of the present invention, the signal-to-noise ratio value and the characteristic response difference of each wavelength interval are calculated according to the spectral characteristic data, and a multi-objective parameter optimization operation is performed in combination with the background noise coefficient of the detection object to obtain the optimal detection wavelength parameter group, which includes:

[0015] Performing Fourier transformation on the spectral characteristic data to obtain a frequency domain characteristic spectrum, and separating the reflected light intensity signal of the detection object and the ambient light noise signal according to the frequency domain characteristic spectrum to obtain a signal-to-noise ratio value in each wavelength interval;

[0016] Calculating the difference in reflected light intensity at adjacent wavelength points based on the spectral characteristic data to obtain a characteristic response difference at each wavelength point;

[0017] A wavelength characteristic weight coefficient is obtained by performing a weighted calculation based on the signal-to-noise ratio value and the characteristic response difference in combination with a calibrated environmental noise threshold;

[0018] The wavelength characteristic weight coefficients are arranged in descending order according to their sizes, and the first three wavelength intervals with the largest weight coefficients are selected as the optimal detection wavelength parameter group.

[0019] Optionally, in a third implementation of the first aspect of the present invention, calculating the difference in reflected light intensity at adjacent wavelength points for the spectral characteristic data to obtain a characteristic response difference at each wavelength point includes:

[0020] Dividing the spectral characteristic data according to wavelength intervals, and extracting the reflected light intensity value of each wavelength point in each wavelength interval;

[0021] According to the reflected light intensity value, the intensity gradient of adjacent wavelength points in each wavelength interval is calculated to obtain the first-order difference value of each wavelength point;

[0022] The first-order difference values ​​are weighted averaged to obtain the characteristic response difference at each wavelength point.

[0023] Optionally, in a fourth implementation of the first aspect of the present invention, the driving current and chip temperature of the LED detection light source array are controlled in linkage according to the optimal detection wavelength parameter group to obtain a plurality of groups of wavelength ratio output signals, including:

[0024] Matching a corresponding LED detection light source unit to each wavelength interval in the optimal detection wavelength parameter group to obtain a light source unit driving parameter;

[0025] According to the driving parameters of the light source unit, a mapping relationship between the driving current and the chip temperature is established to obtain a temperature-current control curve;

[0026] Performing piecewise linearization processing on the temperature-current control curve to obtain a temperature compensation coefficient of each light source unit;

[0027] According to the temperature compensation coefficient, the driving current of the LED detection light source unit is corrected to obtain the ratio output signals of the multiple groups of wavelengths.

[0028] Optionally, in a fifth implementation of the first aspect of the present invention, matching each wavelength interval in the optimal detection wavelength parameter group with a corresponding LED detection light source unit to obtain a light source unit driving parameter includes:

[0029] Performing characteristic analysis on the wavelength intervals in the optimal detection wavelength parameter group to obtain the central wavelength value of each wavelength interval;

[0030] According to the central wavelength value, the wavelength characteristic of the LED detection light source array is calibrated to obtain the wavelength-power characteristic parameters of each light source unit;

[0031] Performing fitting analysis on the wavelength-power characteristic parameters to obtain the working point parameters of each light source unit;

[0032] According to the corresponding relationship between the working point parameters and the central wavelength value, the initial driving current value of each light source unit is calculated to obtain the driving parameters of the light source unit.

[0033] Optionally, in a sixth implementation of the first aspect of the present invention, the compensating the optimal detection wavelength parameter group according to the ratio output signal, and adjusting the wavelength of the LED detection light source array according to the compensated optimal detection wavelength parameter group includes:

[0034] Performing spectral analysis on the ratio output signal to obtain the real-time wavelength value of each LED detection light source unit and obtain wavelength deviation data;

[0035] Calculating the correction value of the current optimal detection wavelength parameter group according to the wavelength deviation data to obtain the compensated optimal detection wavelength parameter group;

[0036] Quantitatively analyzing the compensated optimal detection wavelength parameter group to obtain driving parameters of each LED detection light source unit;

[0037] According to the driving parameters, the driving current and chip temperature of the LED detection light source array are dynamically adjusted to complete the wavelength adjustment.

[0038] A second aspect of the present invention provides a wavelength adjustment device for an LED detection light source, the wavelength adjustment device for an LED detection light source comprising:

[0039] An incident receiving module is used to transmit multi-band incident light to a detection object through an LED detection light source array, and use a photodetector array to receive reflected light or transmitted light of the detection object to obtain spectral characteristic data of the detection object;

[0040] The optimal wavelength calculation module is used to calculate the signal-to-noise ratio value and the characteristic response difference of each wavelength interval according to the spectral characteristic data, and to perform multi-objective parameter optimization operation in combination with the background noise coefficient of the detection object to obtain the optimal detection wavelength parameter group;

[0041] A linkage control module, used to perform linkage control on the driving current and chip temperature of the LED detection light source array according to the optimal detection wavelength parameter group, so as to obtain a ratio output signal of multiple groups of wavelengths;

[0042] The wavelength adjustment module is used for the optimal wavelength calculation module to compensate the optimal detection wavelength parameter group according to the ratio output signal, and to adjust the wavelength of the LED detection light source array according to the optimal detection wavelength parameter group after compensation.

[0043] The third aspect of the present invention provides a wavelength adjustment device for an LED detection light source, comprising: a memory and at least one processor, wherein instructions are stored in the memory, and the memory and the at least one processor are interconnected via a line; the at least one processor calls the instructions in the memory so that the wavelength adjustment device for the LED detection light source performs the steps of the above-mentioned wavelength adjustment method for the LED detection light source.

[0044] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the steps of the above-mentioned method for adjusting the wavelength of an LED detection light source.

[0045] The wavelength adjustment method, device, equipment and storage medium of the above-mentioned LED detection light source emit multi-band incident light through the LED light source array, and use the photodetector array to receive the reflected light or transmitted light of the detection object to obtain the spectral characteristic data of the detection object. According to the spectral characteristic data, the signal-to-noise ratio value and the characteristic response difference of each wavelength interval are calculated, and the multi-target parameter optimization is performed in combination with the background noise coefficient of the detection object to obtain the optimal detection wavelength parameter group. Then, by controlling the driving current and chip temperature of the LED light source array in linkage, the ratio output signal of multiple groups of wavelengths is obtained. According to the compensated optimal detection wavelength parameter group, the wavelength of the LED light source array is adjusted. This method can perform adaptive wavelength adjustment according to the spectral characteristics of the detection object, optimize the light source output, improve the signal-to-noise ratio, and thus improve the detection accuracy, which has significant advantages in optical detection applications in complex environments.

[0046] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0047] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a schematic diagram of a first embodiment of a wavelength adjustment method of an LED detection light source in an embodiment of the present invention;

[0049] Figure 2 A schematic diagram of an embodiment of a wavelength adjustment device for an LED detection light source in an embodiment of the present invention;

[0050] Figure 3 It is a schematic diagram of an embodiment of a wavelength adjustment device of an LED detection light source in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] The terms "including" and "having" and any variations thereof mentioned in the embodiments of the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device end including a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or device ends.

[0053] To facilitate understanding of this embodiment, a wavelength adjustment method for an LED detection light source disclosed in an embodiment of the present invention is first described in detail. Figure 1 As shown, the method comprises the following steps:

[0054] 101. Emitting multi-band incident light to the detection object through an LED detection light source array, and using a photodetector array to receive reflected light or transmitted light of the detection object to obtain spectral characteristic data of the detection object;

[0055] In one embodiment of the present invention, the LED detection light source array emits multi-band incident light to the detection object, and a photodetector array is used to receive the reflected light or transmitted light of the detection object to obtain the spectral characteristic data of the detection object, including: dividing the band of the LED detection light source array at equal intervals to obtain a wavelength detection sequence including multiple wavelength intervals, and according to the wavelength detection sequence, multi-level adjustment of the driving current of the LED detection light source array; using a photodetector array to receive the reflected light or transmitted light of the detection object to obtain the original spectral response data of the detection object; performing denoising on the original spectral response data through Gaussian filtering, and interpolating the data of adjacent wavelength points in the original spectral response data after denoising to obtain a continuous spectral characteristic curve of the detection object; according to the continuous spectral characteristic curve, calculating the absorption coefficient and reflection coefficient of the detection object at each wavelength point, establishing a wavelength-response intensity mapping relationship, and using the absorption coefficient, reflection coefficient and wavelength-response intensity mapping relationship as the spectral characteristic data of the detection object.

[0056] Specifically, the band division of the LED detection light source array is first performed. The specific operation is to divide the visible light band of 380nm-780nm in an equidistant manner, and the division interval is set to 10nm, so as to obtain a wavelength detection sequence of multiple wavelength intervals, each interval containing a number of discrete wavelength points. The wavelength detection sequence is used as the wavelength control reference of the LED detection light source array. By adjusting the driving current of the LED detection light source array, its output wavelength corresponds to the wavelength point in the wavelength detection sequence one by one. The driving current adopts a multi-level adjustment method, and is adjusted step by step with 1mA in the range of 0-100mA. Each time the driving current is adjusted, the LED detection light source array will output a light of a specific wavelength. These output lights are sequentially irradiated onto the surface of the detection object according to the wavelength detection sequence to form multi-band incident light. The reason for selecting 10nm as the wavelength interval is that the interval can not only ensure the wavelength resolution, but also control the data collection amount within a reasonable range, and the driving current adopts a 1mA step size based on the wavelength tuning characteristics of the LED.

[0057] Specifically, in the process of the LED detection light source array emitting multi-band incident light to illuminate the detection object, a photodetector array is used to receive the light signal reflected or transmitted by the detection object. The photodetector array is composed of multiple photosensitive elements, each of which corresponds to a spatial position point, thereby forming a two-dimensional detection surface. When the incident light irradiates the surface of the detection object, part of the light is reflected or transmitted to the photodetector array. The photodetector array converts the received light signal into an electrical signal and simultaneously records the signal intensity value corresponding to each wavelength point. These original signal intensity values ​​are arranged in time sequence to form the original spectral response data of the detection object. During the data acquisition process, the sampling frequency of the photodetector array is set to 100 Hz, and data is collected 100 times at each wavelength point to eliminate the influence of random noise. The collected original spectral response data contains the reflection or transmission characteristic information of the detection object at different wavelengths.

[0058] Specifically, in order to reduce the noise interference in the original spectral response data, Gaussian filtering is used to process the data. Gaussian filtering smoothes the original data by setting appropriate window width and variance parameters to filter out high-frequency noise components. The data after Gaussian filtering is still discrete wavelength point data. In order to obtain a continuous spectral characteristic curve, it is necessary to interpolate the data of adjacent wavelength points. The interpolation adopts the cubic spline interpolation method, which can ensure the continuity of the first-order derivative and the second-order derivative of the interpolation curve at the node, thereby obtaining a smooth continuous spectral characteristic curve. The nodes selected in the interpolation calculation are the original sampling points, and the curves between the nodes are described by cubic polynomials. The coefficients of the interpolation polynomials are obtained by solving the cubic spline interpolation equation group, and then the complete continuous spectral characteristic curve of the detection object is obtained.

[0059] Specifically, the optical characteristic parameters of the detection object at each wavelength point are calculated based on the obtained continuous spectral characteristic curve. First, the absorption coefficient of the detection object is calculated. The absorption coefficient is determined by the logarithmic relationship between the incident light intensity and the transmitted light intensity. The calculation formula is a negative logarithmic ratio. Then, the reflection coefficient of the detection object is calculated. The reflection coefficient is determined by the ratio of the reflected light intensity to the incident light intensity. The absorption coefficient and the reflection coefficient are calculated for each wavelength point to obtain two sets of data on the coefficients varying with wavelength. At the same time, a corresponding relationship between wavelength and response intensity is established, namely, a wavelength-response intensity mapping relationship. This mapping relationship describes the light response characteristics of the detection object at each wavelength point. These three sets of data together constitute the spectral characteristic data of the detection object, among which the absorption coefficient reflects the absorption capacity of the detection object for light of different wavelengths, the reflection coefficient characterizes the reflection characteristics of the detection object, and the wavelength-response intensity mapping relationship integrates the overall spectral response characteristics of the detection object.

[0060] 102. According to the spectral characteristic data, the signal-to-noise ratio value and the characteristic response difference of each wavelength interval are calculated, and the multi-objective parameter optimization operation is performed in combination with the background noise coefficient of the detection object to obtain the optimal detection wavelength parameter group;

[0061] In one embodiment of the present invention, the signal-to-noise ratio and characteristic response difference of each wavelength interval are calculated according to the spectral characteristic data, and a multi-objective parameter optimization operation is performed in combination with the background noise coefficient of the detection object to obtain the optimal detection wavelength parameter group, including: performing Fourier transform on the spectral characteristic data to obtain a frequency domain characteristic spectrum, and separating the reflected light intensity signal and the ambient light noise signal of the detection object according to the frequency domain characteristic spectrum to obtain the signal-to-noise ratio of each wavelength interval; calculating the difference in reflected light intensity of adjacent wavelength points of the spectral characteristic data to obtain the characteristic response difference of each wavelength point; performing weighted calculation according to the signal-to-noise ratio and the characteristic response difference in combination with a calibrated ambient noise threshold to obtain a wavelength characteristic weight coefficient; arranging the wavelength characteristic weight coefficients in descending order according to size, and selecting the first three wavelength intervals with the largest weight coefficients as the optimal detection wavelength parameter group.

[0062] Specifically, the acquired spectral feature data is first subjected to Fourier transform processing. The specific execution process is to divide the spectral data into multiple data segments, and the length of each data segment is set to 1024 sampling points. Before the data is subjected to FFT processing, preprocessing is required, including removal of DC components and windowing. The removal of DC components is achieved by subtracting the average value of the data segment. The Hanning window function is selected for windowing, and the length of the window function is the same as the length of the data segment. The FFT algorithm is executed on the preprocessed data, and the sampling frequency is set to 100Hz, and the frequency domain characteristic spectrum is obtained by calculation. In the frequency domain characteristic spectrum, the amplitude spectrum and the phase spectrum need to be calculated. The amplitude spectrum is obtained by the square root of the sum of the squares of the real part and the imaginary part, and the phase spectrum is obtained by the inverse tangent of the imaginary part and the real part. Based on the frequency distribution characteristics of the frequency domain characteristic spectrum, a frequency threshold of 5Hz is set for signal separation, and the frequency domain signal below 5Hz is used as the reflected light signal, and the frequency domain signal above 5Hz is used as the ambient light noise signal. The two sets of separated frequency domain signals are subjected to inverse Fourier transform respectively. Before the inverse transform is performed, the signals need to be conjugate symmetric to ensure the real number characteristics of the reconstructed signal. The reconstructed time domain signal is the reflected light intensity signal and the ambient light noise signal. The ratio of these two sets of signals is calculated to obtain the signal-to-noise ratio. In order to ensure the calculation accuracy, when calculating the signal-to-noise ratio, the signal amplitude needs to be normalized, and a threshold is set to filter out the signal amplitude that is too small, and finally the signal-to-noise ratio value data for each wavelength interval in the 380-780nm band is obtained.

[0063] Specifically, when calculating the difference in reflected light intensity between adjacent wavelength points, the wavelength points are first divided into 10nm intervals in the 380-780nm band to obtain 41 discrete wavelength points. For each wavelength point, the corresponding reflected light intensity value is obtained, and these intensity values ​​come from the reflection coefficient in the spectral feature data. The calculation process adopts a sliding window method with a window size of 2 and a step size of 1 to perform a difference calculation on the reflected light intensity of two adjacent wavelength points in the window. The specific calculation formula is: Difference = reflected light intensity (λn) - reflected light intensity (λn+1), where λn represents the wavelength value of the nth wavelength point. In the difference calculation process, the validity of the data also needs to be considered. If the reflected light intensity value of a certain wavelength point is invalid or exceeds the preset range, the intensity value of the point needs to be corrected by a linear interpolation method. For the entire 380-780nm band, a total of 40 difference data points can be obtained. These difference data need to be standardized and mapped to a uniform numerical range. The standardization uses the Z-score method to convert the original differences by calculating the mean and standard deviation of the differences to obtain a standardized feature response difference data set.

[0064] Specifically, the weighted calculation process first normalizes the signal-to-noise ratio and the characteristic response difference, using the maximum and minimum normalization method. The normalization formula is: normalized value = (original value - minimum value) / (maximum value - minimum value), and this formula maps both the signal-to-noise ratio and the characteristic response difference to the [0,1] interval. The environmental noise threshold is a fixed parameter obtained through system calibration. The calibration process includes collecting 100 sets of environmental noise data without a detection object, calculating the mean and standard deviation of these data, and taking the mean plus two times the standard deviation as the environmental noise threshold. The calibration value is set to 0.1. The setting of the weight coefficient is based on the statistical analysis of a large amount of experimental data. The weight coefficient of the signal-to-noise ratio is set to 0.6, and the weight coefficient of the characteristic response difference is set to 0.4. The weighted calculation adopts a linear combination method. The specific calculation formula is: wavelength characteristic weight coefficient = 0.6 × normalized signal-to-noise ratio + 0.4 × normalized characteristic response difference - 0.1 × environmental noise threshold. This weighted calculation process is performed for each wavelength interval to obtain 40 wavelength characteristic weight coefficients.

[0065] Specifically, when the feature weight coefficients are arranged in descending order, an improved bubble sort algorithm is used. The improved bubble sort algorithm adds a flag to record whether an exchange occurs in each sorting. If no exchange occurs in a sorting, it means that the sequence is already ordered and the sorting process can be ended in advance. The sorting process maintains two arrays at the same time, one to store the weight coefficients and the other to store the corresponding wavelength interval index to ensure that the wavelength interval information will not be lost during the sorting process. After the sorting is completed, the first three wavelength intervals with the largest weight coefficients are extracted, and the central wavelengths of these three wavelength intervals are recorded as λ1, λ2, and λ3 respectively. In order to ensure the stability of the detection, the range of ±5nm is extended for each central wavelength as the effective detection range, that is, [λi-5nm, λi+5nm] (i=1,2,3). These three wavelength intervals and their corresponding ranges constitute the optimal detection wavelength parameter group, which includes parameters such as the central wavelength value, wavelength range, and weight coefficient. These parameters will be used in the subsequent LED detection light source wavelength adjustment process.

[0066] Furthermore, the calculation of the reflected light intensity difference of adjacent wavelength points of the spectral characteristic data to obtain the characteristic response difference of each wavelength point includes: dividing the spectral characteristic data according to wavelength intervals, and extracting the reflected light intensity value of each wavelength point in each wavelength interval; calculating the intensity gradient of adjacent wavelength points in each wavelength interval according to the reflected light intensity value to obtain the first-order difference value of each wavelength point; and performing weighted average calculation on the first-order difference value to obtain the characteristic response difference value of each wavelength point.

[0067] Specifically, when the spectral feature data is divided according to the wavelength interval, the reference parameters of the wavelength division are first determined, and the spectral range of 380-780nm is divided into 20 wavelength intervals at intervals of 20nm. The range of each interval is [λi,λi+20nm], where λi represents the starting wavelength of the i-th interval. In each wavelength interval, wavelength points are extracted according to the sampling interval of 2nm, so that each wavelength interval contains 10 wavelength points. For each wavelength point, the corresponding reflected light intensity value is extracted from the spectral feature data. The validity of the data needs to be considered during the extraction process. If the reflected light intensity value of a certain wavelength point is missing or abnormal, the interpolation of adjacent wavelength points is used to supplement it. The interpolation method uses cubic spline interpolation, and the missing data is filled by constructing a piecewise cubic polynomial function. After the data extraction is completed, the reflected light intensity value of each wavelength interval is normalized, and the maximum and minimum value normalization method is used to map the reflected light intensity value to the [0,1] interval, which is convenient for subsequent gradient calculation.

[0068] Specifically, after obtaining the reflected light intensity value, it is necessary to calculate the intensity gradient of adjacent wavelength points in each wavelength interval. The gradient calculation adopts the central difference method. For each wavelength point λk in the wavelength interval, the intensity gradient calculation formula is: gradient = (reflected light intensity (λk+1)-reflected light intensity (λk-1)) / (2×Δλ), where Δλ is the wavelength sampling interval, that is, 2nm. For the boundary points of the wavelength interval, the gradient is calculated by the forward difference or backward difference method. The forward difference formula is: gradient = (reflected light intensity (λk+1)-reflected light intensity (λk)) / Δλ, and the backward difference formula is: gradient = (reflected light intensity (λk)-reflected light intensity (λk-1)) / Δλ. The calculated gradient value is the first-order difference value of each wavelength point. In order to eliminate the influence of noise on the gradient calculation, the reflected light intensity value is Gaussian smoothed before calculating the gradient. The smoothing window size is set to 3 wavelength points, and the standard deviation of the Gaussian function is set to 1.

[0069] Specifically, when performing weighted average calculation on the first-order difference value, the weight coefficient is first determined. The setting of the weight coefficient takes into account two factors: the position of the wavelength point in the interval and the size of the gradient value. For each wavelength point in the wavelength interval, its position weight coefficient adopts the Gaussian function distribution, and the weight of the center point of the interval is the largest, and gradually decreases towards both ends. At the same time, the gradient value is amplitude weighted, and the wavelength point with a larger gradient value is given a higher weight. The specific weighted calculation formula is: characteristic response difference = Σ(position weight × amplitude weight × first-order difference value) / Σ(position weight × amplitude weight). The position weight is calculated using the Gaussian function w(x)=exp(-x² / 2σ²), where x represents the distance from the wavelength point to the center of the interval, and σ is set to 1 / 4 of the interval width. The amplitude weight is determined by the normalized amplitude of the first-order difference value, and the normalization is mapped using the sigmoid function. The weighted average calculation is performed on each of the 20 wavelength intervals, and finally the characteristic response difference of each wavelength point is obtained.

[0070] 103. According to the optimal detection wavelength parameter group, the driving current and chip temperature of the LED detection light source array are controlled in linkage to obtain a plurality of wavelength matching output signals;

[0071] In one embodiment of the present invention, the driving current and chip temperature of the LED detection light source array are linked and controlled according to the optimal detection wavelength parameter group to obtain the ratio output signal of multiple groups of wavelengths, including: matching the corresponding LED detection light source unit for each wavelength interval in the optimal detection wavelength parameter group to obtain the light source unit driving parameters; establishing a mapping relationship between the driving current and the chip temperature according to the light source unit driving parameters to obtain a temperature-current control curve; performing piecewise linearization processing on the temperature-current control curve to obtain the temperature compensation coefficient of each light source unit; and correcting the driving current of the LED detection light source unit according to the temperature compensation coefficient to obtain the ratio output signal of the multiple groups of wavelengths.

[0072] Specifically, when matching the LED detection light source unit for the wavelength interval in the optimal detection wavelength parameter group, a wavelength lookup table is first established, which contains the central wavelength and wavelength adjustment range of each light source unit in the LED detection light source array. The lookup table is constructed by measuring the output spectrum of each LED detection light source unit under different driving currents (0-100mA, step 1mA) and temperature conditions (15-45℃, step 0.5℃), recording the central wavelength value, and forming a wavelength-current-temperature three-dimensional characteristic table. According to the three wavelength intervals [λi-5nm, λi+5nm] (i=1,2,3) in the optimal detection wavelength parameter group, the LED detection light source unit covering these wavelength intervals is searched in the wavelength lookup table, and the light source unit with the closest wavelength coverage range is selected as the matching result. For each matched LED detection light source unit, its parameters such as nominal operating current, temperature coefficient, wavelength tuning coefficient, etc. are extracted, and these parameters constitute the driving parameter set of the light source unit.

[0073] Specifically, when establishing the mapping relationship between the driving current and the chip temperature, it is necessary to consider the coupling effect of the temperature characteristics and current characteristics of the LED detection light source. First, the wavelength of each LED detection light source unit is measured at different temperature points. The temperature range is 15-45°C, and the measurement interval is 0.5°C. The driving current value required to reach the target wavelength at different temperatures is recorded. The measurement process adopts temperature closed-loop control, and the temperature of the LED chip is maintained constant by a semiconductor refrigerator. The wavelength is measured after the temperature stabilizes (the temperature fluctuation is less than ±0.1°C). The measured temperature-current data points are fitted with a piecewise polynomial. The order of the fitting polynomial is determined according to the degree of nonlinearity of the data, and generally 3-5 orders are selected. The fitted polynomial function is the temperature-current control curve, which describes the driving current value required to maintain the target wavelength output at different temperatures.

[0074] Specifically, when the temperature-current control curve is piecewise linearized, the temperature range is first divided into multiple sub-intervals. The principle of division is to ensure that the curve segments in each sub-interval can be well approximated by a straight line. The specific division method is to calculate the second-order derivative of the curve at each temperature point. When the absolute value of the second-order derivative exceeds the set threshold, the point is used as the segmentation point. The temperature range of 15-45°C is usually divided into 6 sub-intervals, each sub-interval is about 5°C. In each sub-interval, the temperature-current data is linearly fitted using the least squares method to obtain the slope and intercept. The slope is the temperature compensation coefficient in this interval, which indicates the amount of driving current that needs to be adjusted when the temperature changes by 1°C. This piecewise linearization process is performed on each LED detection light source unit to obtain a set of temperature compensation coefficients, which reflect the temperature sensitivity of the LED detection light source in different temperature intervals.

[0075] Specifically, the process of correcting the driving current according to the temperature compensation coefficient is a real-time closed-loop control process. First, read the real-time temperature value of each LED detection light source unit, determine the current temperature range according to the temperature value, and select the corresponding temperature compensation coefficient. The calculation formula for the correction amount of the driving current is: correction amount = temperature compensation coefficient × (current temperature - reference temperature). Superimpose the correction amount on the reference driving current to obtain the corrected driving current value. For the three wavelength points to be output, calculate the corrected driving current of each LED detection light source unit respectively, and normalize the driving current according to the energy ratio requirements of the target wavelength. The normalized driving current value is sent to the LED driving circuit according to the set timing to form a ratio output signal of multiple groups of wavelengths. The ratio output signal contains the driving current value, temperature compensation parameters and output timing information of each LED detection light source unit.

[0076] Furthermore, matching each wavelength interval in the optimal detection wavelength parameter group with a corresponding LED detection light source unit to obtain the light source unit driving parameters includes: performing characteristic analysis on the wavelength intervals in the optimal detection wavelength parameter group to obtain the center wavelength value of each wavelength interval; calibrating the wavelength characteristics of the LED detection light source array according to the center wavelength value to obtain the wavelength-power characteristic parameters of each light source unit; performing fitting analysis on the wavelength-power characteristic parameters to obtain the working point parameters of each light source unit; and calculating the initial driving current value of each light source unit according to the corresponding relationship between the working point parameters and the center wavelength value to obtain the light source unit driving parameters.

[0077] Specifically, when the characteristic analysis of the wavelength interval in the optimal detection wavelength parameter group is performed, a mathematical model is first established to describe the characteristic distribution of the wavelength interval. A Gaussian function is used to fit each wavelength interval [λi-5nm, λi+5nm] (i=1,2,3), and the fitting function is f(λ)=A×exp(-(λ-μ)² / (2σ²)), where μ is the central wavelength value to be determined, σ is the standard deviation of the wavelength interval, and A is the normalization coefficient. The fitting process uses the least squares method, substitutes the sampling points in the wavelength interval into the equation, constructs the error function, and solves the values ​​of μ, σ and A through iterative optimization. In order to improve the fitting accuracy, the sampling points are selected in an adaptive interval manner, increasing the sampling density where the wavelength changes drastically and appropriately reducing the sampling points where the change is gentle. The μ value obtained by fitting is the central wavelength value of each wavelength interval, and these central wavelength values ​​will serve as the benchmark for the subsequent matching of LED detection light source units.

[0078] Specifically, after obtaining the central wavelength value, the wavelength characteristics of the LED detection light source array need to be calibrated. The calibration process first builds a calibration platform, including constant temperature control system, precision current source, spectrum analyzer and other equipment. The LED detection light source array is installed on the constant temperature control system with a temperature control accuracy of ±0.1°C. For each LED detection light source unit, measure its output spectrum at different drive currents (0-100mA, step 0.5mA), and record the central wavelength and output power. During the measurement process, keep the chip temperature constant at 25°C, and repeat sampling 10 times at each measurement point to take the average value to eliminate random errors. At the same time, record the voltage value of each measurement point and calculate the input electrical power. The electro-optical conversion efficiency of the light source unit under different driving conditions is obtained by the ratio of the output optical power to the input electrical power. These measurement data constitute the wavelength-power characteristic parameter set of the light source unit, which includes multiple parameters such as the central wavelength, output power, drive current, and operating voltage.

[0079] Specifically, when fitting and analyzing the wavelength-power characteristic parameters, a multivariable function model needs to be established. The model adopts a piecewise polynomial form, and polynomials of different orders are used for fitting in different working ranges. First, the characteristic parameters are grouped according to the working range, which are divided into low current area (0-20mA), medium current area (20-60mA) and high current area (60-100mA). The data of each interval are fitted with a polynomial function, and a quadratic polynomial is used in the low current area, a cubic polynomial is used in the medium current area, and a quartic polynomial is used in the high current area. The fitting process takes into account the coupling relationship between multiple parameters and constructs a multidimensional function space including wavelength, power, current and temperature. The polynomial coefficients are solved by numerical optimization methods to obtain a mathematical model describing the working characteristics of the LED. In each working range, the optimal working point is calculated according to the fitting model. The optimal working point is defined as the working state with the highest electro-optical conversion efficiency and the best wavelength stability. These working point parameters include the optimal driving current, the corresponding output power, the working temperature, etc.

[0080] Specifically, the initial driving current value of each light source unit is calculated according to the corresponding relationship between the working point parameters and the center wavelength value. The calculation process first establishes a lookup table to establish a mapping relationship between the working point parameters and the center wavelength value. For each center wavelength value to be achieved, the closest wavelength point is searched in the lookup table to extract the working point parameters corresponding to the wavelength point. If the target wavelength value falls between two working points, the corresponding driving parameters are calculated by interpolation. The interpolation uses cubic spline interpolation to ensure the smoothness of the parameter changes with wavelength. For each LED detection light source unit, the initial driving current value required to achieve the target wavelength is calculated according to its working point parameters. The calculation of the driving current also needs to consider temperature compensation. According to the difference between the current temperature and the calibration temperature, the driving current is corrected using the temperature coefficient. The driving parameters finally obtained include parameters such as the initial driving current value, the temperature compensation coefficient, and the working point temperature. These parameters will be used for subsequent LED detection light source control.

[0081] 104. Perform compensation processing on the optimal detection wavelength parameter group according to the ratio output signal, and adjust the wavelength of the LED detection light source array according to the optimal detection wavelength parameter group after compensation.

[0082] In one embodiment of the present invention, compensating the optimal detection wavelength parameter group according to the ratio output signal, and adjusting the wavelength of the LED detection light source array according to the compensated optimal detection wavelength parameter group includes: performing spectral analysis on the ratio output signal to obtain the real-time wavelength value of each LED detection light source unit to obtain wavelength deviation data; calculating the correction value of the current optimal detection wavelength parameter group according to the wavelength deviation data to obtain the compensated optimal detection wavelength parameter group; performing quantitative analysis on the compensated optimal detection wavelength parameter group to obtain the driving parameters of each LED detection light source unit; and dynamically adjusting the driving current and chip temperature of the LED detection light source array according to the driving parameters to complete the wavelength adjustment.

[0083] Specifically, when performing spectral analysis on the output signal of the ratio, the output spectrum of the LED detection light source array is first collected in real time by the spectrum analyzer. During the collection process, the optical signal is transmitted to the spectrum analyzer by optical fiber coupling. The scanning rate of the spectrum analyzer is set to 100Hz and the wavelength resolution is 0.1nm. The collected spectral data is preprocessed, including dark background subtraction and response calibration. Dark background subtraction is to collect the ambient spectrum when the LED light source is turned off and subtract it from the measured spectrum; response calibration is to calibrate the wavelength response characteristics of the spectrometer using a standard light source. The preprocessed spectral data is used to extract the central wavelength value through Gaussian fitting. The fitting process uses the least squares method to independently fit the output spectrum of each LED detection light source unit. The extracted real-time wavelength value is compared with the target wavelength value in the optimal detection wavelength parameter group to calculate the wavelength deviation. The wavelength deviation data contains the wavelength drift of each LED detection light source unit and its changing trend.

[0084] Specifically, when calculating the correction value of the optimal detection wavelength parameter group based on the wavelength deviation data, the dynamic characteristics of the wavelength drift need to be considered. First, a wavelength drift model is established, which includes two parts: temperature drift term and time drift term. The temperature drift term is obtained by measuring the relationship between the temperature of the LED chip and the wavelength deviation, and a temperature-wavelength deviation mapping function is established; the time drift term is obtained by tracking the change trend of the LED output wavelength for a long time, and is described by an exponential decay function. For each LED detection light source unit, according to its real-time temperature and operating time, the theoretical wavelength drift is substituted into the model to calculate the amount. The theoretical drift is compared with the measured wavelength deviation to obtain the correction coefficient. The correction coefficient acts on the optimal detection wavelength parameter group by weighted averaging, and the weight coefficient is determined according to the confidence of the wavelength drift. The corrected wavelength parameter needs to meet the wavelength accuracy required for the detection, and the wavelength deviation is generally required to be less than ±0.2nm.

[0085] Specifically, when quantitatively analyzing the optimal detection wavelength parameter group after compensation, the working characteristic model of the LED detection light source is first established. The model is based on the current-wavelength characteristics and temperature-wavelength characteristics of the LED and is stored in the form of a two-dimensional lookup table. The process of establishing the lookup table is to measure the output wavelength of the LED under different driving currents (0-100mA, step 0.5mA) and temperature conditions (15-45℃, step 0.5℃) to form a wavelength-current-temperature three-dimensional data space. Through the interpolation algorithm, the output wavelength at any working point can be calculated. For each target wavelength value after compensation, the best matching point is searched in the lookup table to extract the corresponding driving current value and operating temperature value. If the target wavelength value falls between the grid points, the driving parameters are calculated by bilinear interpolation. The driving parameters include the reference driving current, temperature setting value, current adjustment range, temperature adjustment range, etc.

[0086] Specifically, the process of dynamically adjusting the LED detection light source array according to the driving parameters adopts a double closed-loop control strategy. The inner loop is a temperature control loop, which uses a semiconductor cooler to achieve precise control of the LED chip temperature, with a control cycle of 100ms and a temperature control accuracy of ±0.1℃. The control algorithm adopts fuzzy PID control, and the control parameters are adaptively adjusted according to the temperature deviation and the deviation change rate. The outer loop is a wavelength control loop, which achieves precise wavelength adjustment by adjusting the driving current, with a control cycle of 10ms. The adjustment of the driving current adopts a segmented control strategy, using different control gains in different working ranges. When the wavelength deviation is large, a large step length is used for rapid adjustment; when the wavelength deviation is small, a small step length is used for fine adjustment. The output wavelength is monitored in real time through the spectral feedback signal, and the new driving parameters are calculated according to the wavelength deviation to form a closed-loop control. The system also includes a fault detection and protection mechanism, and automatically enters the protection mode when the temperature or current exceeds the safe range. The entire adjustment process continues until the output wavelength stabilizes near the target value and the wavelength drift is controlled within ±0.1nm.

[0087] Specifically, in this embodiment, a multi-band incident light is emitted by an LED light source array, and a photodetector array is used to receive the reflected light or transmitted light of the detection object to obtain the spectral characteristic data of the detection object. According to the spectral characteristic data, the signal-to-noise ratio value and the characteristic response difference of each wavelength interval are calculated, and the multi-target parameter optimization is performed in combination with the background noise coefficient of the detection object to obtain the optimal detection wavelength parameter group. Then, by controlling the driving current and chip temperature of the LED light source array in linkage, a ratio output signal of multiple groups of wavelengths is obtained. According to the compensated optimal detection wavelength parameter group, the wavelength of the LED light source array is adjusted. This method can perform adaptive wavelength adjustment according to the spectral characteristics of the detection object, optimize the light source output, improve the signal-to-noise ratio, and thus improve the detection accuracy, which has significant advantages in optical detection applications in complex environments.

[0088] The wavelength adjustment method of the LED detection light source in the embodiment of the present invention is described above. The wavelength adjustment device of the LED detection light source in the embodiment of the present invention is described below. Figure 2 , an embodiment of the wavelength adjustment device of the LED detection light source in the embodiment of the present invention includes:

[0089] The incident receiving module 201 is used to transmit multi-band incident light to the detection object through the LED detection light source array, and use the photodetector array to receive the reflected light or transmitted light of the detection object to obtain the spectral characteristic data of the detection object;

[0090] The optimal wavelength calculation module 202 is used to calculate the signal-to-noise ratio value and the characteristic response difference of each wavelength interval according to the spectral characteristic data, and perform multi-objective parameter optimization operation in combination with the background noise coefficient of the detection object to obtain the optimal detection wavelength parameter group;

[0091] A linkage control module 203 is used to perform linkage control on the driving current and chip temperature of the LED detection light source array according to the optimal detection wavelength parameter group to obtain a plurality of groups of wavelength matching output signals;

[0092] The wavelength adjustment module 204 is used for the optimal wavelength calculation module to compensate the optimal detection wavelength parameter group according to the ratio output signal, and adjust the wavelength of the LED detection light source array according to the optimal detection wavelength parameter group after compensation.

[0093] In an embodiment of the present invention, the wavelength adjustment device of the LED detection light source runs the wavelength adjustment method of the LED detection light source, and the wavelength adjustment device of the LED detection light source emits multi-band incident light through the LED light source array, and uses the photodetector array to receive the reflected light or transmitted light of the detection object to obtain the spectral characteristic data of the detection object. According to the spectral characteristic data, the signal-to-noise ratio value and the characteristic response difference of each wavelength interval are calculated, and the multi-objective parameter optimization is performed in combination with the background noise coefficient of the detection object to obtain the optimal detection wavelength parameter group. Then, by controlling the driving current and chip temperature of the LED light source array in linkage, the ratio output signal of multiple groups of wavelengths is obtained. According to the compensated optimal detection wavelength parameter group, the LED light source array is wavelength adjusted. This method can perform adaptive wavelength adjustment according to the spectral characteristics of the detection object, optimize the light source output, improve the signal-to-noise ratio, and thus improve the detection accuracy, which has significant advantages in optical detection applications under complex environments.

[0094] above Figure 2 The wavelength adjustment device of the LED detection light source in the embodiment of the present invention is described in detail from the perspective of modular functional entity. The wavelength adjustment device of the LED detection light source in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0095] Figure 3It is a structural schematic diagram of a wavelength adjustment device for an LED detection light source provided by an embodiment of the present invention. The wavelength adjustment device 300 for the LED detection light source may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 310 (for example, one or more processors) and a memory 320, and one or more storage media 330 (for example, one or more mass storage device terminals) storing application programs 333 or data 332. Among them, the memory 320 and the storage medium 330 can be short-term storage or permanent storage. The program stored in the storage medium 330 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the wavelength adjustment device 300 for the LED detection light source. Furthermore, the processor 310 may be configured to communicate with the storage medium 330, and execute a series of instruction operations in the storage medium 330 on the wavelength adjustment device 300 for the LED detection light source to implement the steps of the wavelength adjustment method for the above-mentioned LED detection light source.

[0096] The wavelength adjustment device 300 of the LED detection light source may also include one or more power supplies 340, one or more wired or wireless network interfaces 350, one or more input and output interfaces 360, and / or one or more operating systems 331, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. It can be understood by those skilled in the art that Figure 3 The structure of the wavelength adjustment device of the LED detection light source shown does not constitute a limitation on the wavelength adjustment device of the LED detection light source provided by the present invention, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0097] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the method for adjusting the wavelength of the LED detection light source.

[0098] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described system, device, or unit can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0099] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the whole or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0100] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A wavelength adjustment method for an LED detection light source, characterized in that: The wavelength adjustment method of the LED detection light source comprises: The LED detection light source array emits multi-band incident light to the detection object, and a photodetector array is used to receive the reflected light or transmitted light of the detection object to obtain the spectral characteristic data of the detection object; According to the spectral characteristic data, the signal-to-noise ratio value and the characteristic response difference of each wavelength interval are calculated, and the multi-objective parameter optimization operation is performed in combination with the background noise coefficient of the detection object to obtain the optimal detection wavelength parameter group; According to the optimal detection wavelength parameter group, the driving current and chip temperature of the LED detection light source array are controlled in linkage to obtain a plurality of wavelength matching output signals; the driving current and chip temperature of the LED detection light source array are controlled in linkage to obtain a plurality of wavelength matching output signals according to the optimal detection wavelength parameter group, including: matching the corresponding LED detection light source unit to each wavelength interval in the optimal detection wavelength parameter group to obtain the light source unit driving parameters; establishing a mapping relationship between the driving current and the chip temperature according to the light source unit driving parameters to obtain a temperature-current control curve; performing piecewise linearization processing on the temperature-current control curve to obtain a temperature compensation coefficient of each light source unit; and correcting the driving current of the LED detection light source unit according to the temperature compensation coefficient to obtain the plurality of wavelength matching output signals; According to the ratio output signal, the optimal detection wavelength parameter group is compensated, and the wavelength of the LED detection light source array is adjusted according to the optimal detection wavelength parameter group after compensation.

2. The wavelength adjustment method of the LED detection light source according to claim 1, characterized in that: The LED detection light source array emits multi-band incident light to the detection object, and a photoelectric detector array is used to receive the reflected light or transmitted light of the detection object to obtain the spectral characteristic data of the detection object, including: The wavelength band of the LED detection light source array is divided into equal intervals to obtain a wavelength detection sequence including a plurality of wavelength intervals, and the driving current of the LED detection light source array is adjusted in multiple stages according to the wavelength detection sequence; Using a photodetector array to receive the reflected light or transmitted light of the detection object to obtain original spectral response data of the detection object; The original spectral response data is subjected to denoising by Gaussian filtering, and data of adjacent wavelength points in the original spectral response data after denoising are interpolated to obtain a continuous spectral characteristic curve of the detection object; According to the continuous spectral characteristic curve, the absorption coefficient and reflection coefficient of the detection object at each wavelength point are calculated, a wavelength-response intensity mapping relationship is established, and the absorption coefficient, reflection coefficient and wavelength-response intensity mapping relationship are used as the spectral characteristic data of the detection object.

3. The wavelength adjustment method of the LED detection light source according to claim 1, characterized in that: The signal-to-noise ratio and characteristic response difference of each wavelength interval are calculated according to the spectral characteristic data, and a multi-objective parameter optimization operation is performed in combination with the background noise coefficient of the detection object to obtain the optimal detection wavelength parameter group, which includes: Performing Fourier transformation on the spectral characteristic data to obtain a frequency domain characteristic spectrum, and separating the reflected light intensity signal of the detection object and the ambient light noise signal according to the frequency domain characteristic spectrum to obtain a signal-to-noise ratio value in each wavelength interval; Calculating the difference in reflected light intensity at adjacent wavelength points based on the spectral characteristic data to obtain a characteristic response difference at each wavelength point; A wavelength characteristic weight coefficient is obtained by performing a weighted calculation based on the signal-to-noise ratio value and the characteristic response difference in combination with a calibrated environmental noise threshold; The wavelength characteristic weight coefficients are arranged in descending order according to their sizes, and the first three wavelength intervals with the largest weight coefficients are selected as the optimal detection wavelength parameter group.

4. The wavelength adjustment method of the LED detection light source according to claim 3, characterized in that: The calculation of the reflected light intensity difference of adjacent wavelength points based on the spectral characteristic data to obtain the characteristic response difference of each wavelength point includes: Dividing the spectral characteristic data according to wavelength intervals, and extracting the reflected light intensity value of each wavelength point in each wavelength interval; According to the reflected light intensity value, the intensity gradient of adjacent wavelength points in each wavelength interval is calculated to obtain the first-order difference value of each wavelength point; The first-order difference values ​​are weighted averaged to obtain characteristic response differences at each wavelength point.

5. The wavelength adjustment method of the LED detection light source according to claim 1, characterized in that: The step of matching each wavelength interval in the optimal detection wavelength parameter group with a corresponding LED detection light source unit to obtain the light source unit driving parameters comprises: Performing characteristic analysis on the wavelength intervals in the optimal detection wavelength parameter group to obtain the central wavelength value of each wavelength interval; According to the central wavelength value, the wavelength characteristic of the LED detection light source array is calibrated to obtain the wavelength-power characteristic parameters of each light source unit; Performing fitting analysis on the wavelength-power characteristic parameters to obtain the working point parameters of each light source unit; According to the corresponding relationship between the working point parameters and the central wavelength value, the initial driving current value of each light source unit is calculated to obtain the driving parameters of the light source unit.

6. The wavelength adjustment method of the LED detection light source according to claim 1, characterized in that: The method of compensating the optimal detection wavelength parameter group according to the ratio output signal, and adjusting the wavelength of the LED detection light source array according to the compensated optimal detection wavelength parameter group includes: Performing spectral analysis on the ratio output signal to obtain the real-time wavelength value of each LED detection light source unit and obtain wavelength deviation data; Calculating the correction value of the current optimal detection wavelength parameter group according to the wavelength deviation data to obtain the compensated optimal detection wavelength parameter group; Quantitatively analyzing the compensated optimal detection wavelength parameter group to obtain driving parameters of each LED detection light source unit; According to the driving parameters, the driving current and chip temperature of the LED detection light source array are dynamically adjusted to complete the wavelength adjustment.

7. A wavelength adjustment device for an LED detection light source, characterized in that: The wavelength adjustment device of the LED detection light source comprises: An incident receiving module is used to transmit multi-band incident light to a detection object through an LED detection light source array, and use a photodetector array to receive reflected light or transmitted light of the detection object to obtain spectral characteristic data of the detection object; The optimal wavelength calculation module is used to calculate the signal-to-noise ratio value and the characteristic response difference of each wavelength interval according to the spectral characteristic data, and to perform multi-objective parameter optimization operation in combination with the background noise coefficient of the detection object to obtain the optimal detection wavelength parameter group; A linkage control module, used for linkage control of the driving current and chip temperature of the LED detection light source array according to the optimal detection wavelength parameter group to obtain a plurality of wavelength ratio output signals; the linkage control of the driving current and chip temperature of the LED detection light source array according to the optimal detection wavelength parameter group to obtain a plurality of wavelength ratio output signals includes: matching the corresponding LED detection light source unit to each wavelength interval in the optimal detection wavelength parameter group to obtain the light source unit driving parameters; establishing a mapping relationship between the driving current and the chip temperature according to the light source unit driving parameters to obtain a temperature-current control curve; performing piecewise linearization processing on the temperature-current control curve to obtain a temperature compensation coefficient of each light source unit; and correcting the driving current of the LED detection light source unit according to the temperature compensation coefficient to obtain the plurality of wavelength ratio output signals; The wavelength adjustment module is used for the optimal wavelength calculation module to compensate the optimal detection wavelength parameter group according to the ratio output signal, and to adjust the wavelength of the LED detection light source array according to the optimal detection wavelength parameter group after compensation.

8. A wavelength adjustment device for an LED detection light source, characterized in that: The wavelength adjustment device of the LED detection light source comprises: a memory and at least one processor, wherein the memory stores instructions; The at least one processor calls the instructions in the memory to enable the wavelength adjustment device of the LED detection light source to perform the steps of the wavelength adjustment method of the LED detection light source as described in any one of claims 1-6.

9. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the steps of the wavelength adjustment method of the LED detection light source as described in any one of claims 1-6 are implemented.

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