Nonlinear correction device and method of spectrum acquisition system
By employing a nonlinear correction device for the light source module, diffuser, and control module, and by gradually reducing the integration time and fitting a four-parameter logarithmic function equation, the problem of low energy efficiency of silicon detectors is solved, achieving efficient and low-cost correction of the spectral acquisition system and improving detection accuracy and consistency.
Patent Information
- Application Number
- CN202511042008.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-28
- Publication Date
- 2025-11-14
AI Technical Summary
The energy efficiency of silicon detectors in existing spectrometers is low in the short-wave infrared band, resulting in serious nonlinear response problems in absorbance measurement. Traditional calibration methods are costly, cumbersome, and difficult to meet the needs of large-scale production.
A nonlinear correction device consisting of a light source module, a diffuser, and a control module is used to acquire spectral data by gradually reducing the integration time. The data is then normalized and fitted with a four-parameter logarithmic function equation to perform system-level correction on the spectral acquisition system.
It achieves an ideal linear response in the spectral acquisition system, improves overall consistency and detection accuracy, reduces calibration costs and complexity, and is suitable for large-scale production.
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Figure CN120947814A_ABST
Abstract
Description
Technical Field
[0001] This application relates to a nonlinear correction device and method for a spectral acquisition system, belonging to the field of spectral detection technology. Background Technology
[0002] A spectrometer is used to disperse incident composite light (containing multiple wavelengths) into a spectrum of its constituent wavelengths and accurately measure the light intensity at each wavelength. A spectrometer includes a silicon detector on the image plane to receive the dispersed monochromatic light and convert the intensity information of the received monochromatic light into an electrical signal, which is then output to subsequent circuitry and a data acquisition system for processing. Due to the low energy efficiency of silicon detectors in the short-wave infrared (850nm-1050nm) range, absorbance measurements exhibit nonlinear effects. That is, the electrical signal output by the silicon detector deviates from the ideal linear proportional relationship with the incident light intensity. Therefore, nonlinear correction is required for the spectral acquisition system.
[0003] Traditional nonlinear correction methods typically rely on complex systems built using integrating spheres and traceable standard light sources to implement the correction process. This process includes: first, constructing a correction optical system using silicon detectors and integrating spheres; then, illuminating the correction optical system with a standard light source at different wavelengths to collect the detector's raw response data; next, performing step-by-step correction on the detector's response at each wavelength based on the collected data; and finally, repeatedly verifying the correction effect. If the expected results are not achieved, the calibration model is readjusted, and calibration and correction are performed again.
[0004] However, the aforementioned calibration technologies face significant challenges in mass production. Firstly, the procurement cost of calibration optical systems is high, and they also require specific site conditions, environmental conditions, and highly skilled operators, significantly increasing the technological application threshold and maintenance costs. Secondly, the calibration process involves numerous and cumbersome steps, from system setup and data acquisition to model adjustment and repeated verification, making it time-consuming and difficult to meet the high-efficiency calibration needs of large-scale production scenarios. Thirdly, focusing on individual silicon detector calibration neglects performance changes caused by differences in optical paths and equipment compatibility after the detector module is installed in the overall optical path. Therefore, even after detector calibration is completed, system-level calibration of the entire system is still required, which undoubtedly increases the complexity and cost of the calibration process and reduces calibration efficiency and accuracy. Summary of the Invention
[0005] This application provides a nonlinear correction device and method for a spectral acquisition system, which can solve the problem of low energy efficiency of silicon detectors in the 850nm-1050nm range, leading to severe nonlinear response in absorbance measurement. Through a correction algorithm, the spectral acquisition system is calibrated at the system level, making the system response closer to ideal linearity, improving the overall consistency and final detection performance. This application provides the following technical solution:
[0006] In a first aspect, a nonlinear correction device for a spectral acquisition system is provided, the device comprising:
[0007] Light source module, used to generate light sources;
[0008] A diffuser and a spectral acquisition system to be nonlinearly corrected are sequentially located at the output end of the light source module; wherein the diffuser is used to homogenize the light source; and,
[0009] The control module connected to the spectral acquisition system is used for:
[0010] The spectral acquisition system is controlled to start spectral acquisition from the integration time corresponding to the saturation energy, and the integration time is gradually reduced with a preset step size until the energy of the whole pixel is lower than the dark noise, so as to obtain the spectral data of each pixel at different integration times.
[0011] Normalize the spectral data of each pixel at different integration times to obtain the normalization coefficients of each pixel at different energies;
[0012] Based on the energy of each pixel and the normalization coefficient corresponding to the energy, a four-parameter logarithmic function equation is fitted, and the spectral acquisition system is nonlinearly corrected based on the fitted four-parameter logarithmic function equation.
[0013] Optionally, the step of normalizing the spectral data of each pixel at different integration times to obtain the normalization coefficients of each pixel at different energies includes:
[0014] For each pixel, the maximum energy of the pixel at different integration times is determined from the spectral data corresponding to the pixel at different integration times.
[0015] The normalization coefficients of the pixel at different energies are obtained by dividing the energy of the pixel at different integration times by the maximum energy.
[0016] Optionally, the four-parameter logarithmic function equation is expressed by the following formula:
[0017] y = a * ln(x + b) + (1 - a)(c * x + d)
[0018] Where x represents the energy of each pixel, y represents the normalization coefficient corresponding to the energy, and a, b, c, and d represent the parameters to be fitted to the four-parameter logarithmic function equation.
[0019] Optionally, the step of gradually reducing the integration time with a preset step size includes:
[0020] The integration time is gradually reduced with a preset step size of 5ms.
[0021] Optionally, after gradually reducing the integration time with a preset step size, the method further includes:
[0022] Divide the collected spectral data by the corresponding integration time to obtain normalized spectral data for each pixel at different integration times.
[0023] Optionally, before controlling the spectral acquisition system to start spectral acquisition from the integration time corresponding to the saturation energy, the method further includes:
[0024] The light source module is preheated for a preset time.
[0025] In a second aspect, a nonlinear correction method for a spectral acquisition system is provided, used in the nonlinear correction device described in the first aspect, the method comprising:
[0026] The spectral acquisition system is controlled to start spectral acquisition from the integration time corresponding to the saturation energy, and the integration time is gradually reduced with a preset step size until the energy of the whole pixel is lower than the dark noise, so as to obtain the spectral data of each pixel at different integration times.
[0027] Normalize the spectral data of each pixel at different integration times to obtain the normalization coefficients of each pixel at different energies;
[0028] Based on the energy of each pixel and the normalization coefficient corresponding to the energy, a four-parameter logarithmic function equation is fitted, and the spectral acquisition system is nonlinearly corrected based on the fitted four-parameter logarithmic function equation.
[0029] Thirdly, a nonlinear correction device for a spectral acquisition system is provided, used in the aforementioned nonlinear correction device, the device comprising:
[0030] The data acquisition module is used to control the spectral acquisition system to start spectral acquisition from the integration time corresponding to the saturation energy, and gradually reduce the integration time with a preset step size until the energy of the whole pixel is lower than the dark noise, so as to obtain the spectral data of each pixel at different integration times.
[0031] The normalization processing module is used to normalize the spectral data of each pixel at different integration times to obtain the normalization coefficients of each pixel at different energies.
[0032] The data fitting module is used to fit a four-parameter logarithmic function equation based on the energy of each pixel and the normalization coefficient corresponding to the energy, and to perform nonlinear correction on the spectral acquisition system based on the fitted four-parameter logarithmic function equation.
[0033] Fourthly, a controller is provided, the controller including a processor and a memory; the memory stores a program, the program being loaded and executed by the processor to implement the nonlinear correction method of the spectral acquisition system described in the second aspect.
[0034] Fifthly, a computer-readable storage medium is provided, wherein a program is stored therein, the program being loaded and executed by the processor to implement the nonlinear correction method of the spectral acquisition system described in the second aspect.
[0035] The beneficial effects of this application include: by controlling the spectral acquisition system to start spectral acquisition from the integration time corresponding to the saturation energy, and gradually reducing the integration time with a preset step size until the energy of the entire pixel is lower than the dark noise, the spectral data corresponding to each pixel at different integration times are obtained; the spectral data corresponding to each pixel at different integration times are normalized to obtain the normalization coefficient corresponding to each pixel at different energies; based on the energy of each pixel and the corresponding normalization coefficient, a four-parameter logarithmic function equation is fitted, and the spectral acquisition system is nonlinearly corrected based on the fitted four-parameter logarithmic function equation; the system-level correction of absorbance nonlinearity caused by silicon detectors can be achieved; at the same time, the nonlinear fitting accuracy is high, the nonlinear correction device is low-cost, and the method is simple and efficient.
[0036] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, the preferred embodiments of this application are described in detail below with reference to the accompanying drawings. Attached Figure Description
[0037] Figure 1 This is a schematic diagram of a nonlinear correction device for a spectral acquisition system provided in one embodiment of this application;
[0038] Figure 2 This is a schematic diagram comparing spectral data before and after correction of a nonlinear correction device provided in one embodiment of this application;
[0039] Figure 3 This is a flowchart of a nonlinear correction method for a spectral acquisition system provided in one embodiment of this application;
[0040] Figure 4 This is a block diagram of a nonlinear correction device for a spectral acquisition system provided in one embodiment of this application;
[0041] Figure 5 This is a block diagram of a nonlinear correction device for a spectral acquisition system provided in another embodiment of this application. Detailed Implementation
[0042] The specific embodiments of this application will be described in further detail below with reference to the accompanying drawings and examples. The following examples are used to illustrate this application, but are not intended to limit the scope of this application.
[0043] Figure 1 This is a schematic diagram of a nonlinear correction device for a spectral acquisition system provided in one embodiment of this application. The device includes: a light source module 101, a diffuser 102, and a spectral acquisition system 103 to be nonlinearly corrected.
[0044] A light source module 101 is used to generate a light source. Exemplarily, the light source module 101 includes, in sequence along the optical path propagation direction, a halogen tungsten lamp (e.g., 20W), a filter, and a lens. The halogen tungsten lamp generates the light source, the filter is used to select light of a specific wavelength to ensure that the target wavelength of light continues to propagate along the optical path, and the lens works in conjunction with the filter to ensure that the light propagates accurately along the optical path.
[0045] Optionally, the light source module may also include other components, such as a cooling fan. This embodiment does not limit the implementation method of the light source module.
[0046] The diffuser 102 and the spectral acquisition system 103 are located sequentially at the output end of the light source module 101. The diffuser 102 is used to homogenize the light source; in other words, the diffuser 102 replaces the integrating sphere in a conventional calibration device to perform the homogenization function. For example, the diffuser 102 can be implemented using frosted glass.
[0047] The spectral acquisition system 103 is used to acquire the spectral data of the target substance. The target substance is the material placed between the light source module 101 and the diffuser 102. For example, the target substance may be a reference standard substance used to provide a reference spectrum; or the target substance may be a sample to be acquired spectrally. In this case, a sample receiving cavity is also included between the light source module 101 and the diffuser 102. The sample may be a substance such as soybeans that requires spectral acquisition. This embodiment does not limit the type of sample.
[0048] Optionally, to ensure light transmittance, a light-transmitting window is provided between the reference standard and the sample container cavity to provide a protective window for the light path. For example, the light-transmitting window is installed at the light-inlet end of the sample container cavity.
[0049] The control module is connected to the spectral acquisition system 103 to control the spectral acquisition system 103 and acquire the spectral data acquired by the spectral acquisition system 103.
[0050] In this embodiment, by setting the complete spectral acquisition system 103 in the optical path, the nonlinearity caused by each device in the spectral acquisition system 103 can be corrected.
[0051] Specifically, the control module is used for:
[0052] The spectral acquisition system 103 starts spectral acquisition from the integration time corresponding to the saturation energy and gradually reduces the integration time with a preset step size until the energy of the whole pixel is lower than the dark noise, thus obtaining the spectral data of each pixel at different integration times.
[0053] Normalize the spectral data of each pixel at different integration times to obtain the normalization coefficients of each pixel at different energies;
[0054] Based on the energy of each pixel and the corresponding normalization coefficient, a four-parameter logarithmic function equation is fitted, and the spectral acquisition system 103 is nonlinearly corrected based on the fitted four-parameter logarithmic function equation.
[0055] Saturation energy refers to the incident light intensity at which the detector output reaches its maximum value. Once saturation energy is reached, even if the light intensity is further increased, the detector output signal will no longer rise. Integration time refers to the duration of the detector's exposure sampling, typically measured in milliseconds (ms).
[0056] Optionally, the integration time is gradually reduced with a preset step size, including: gradually reducing the integration time with a preset step size of 5ms. In other embodiments, the preset step size can be larger or smaller; this embodiment does not limit the value of the preset step size.
[0057] Dark noise refers to the electrical signal generated by the detector itself when there is no light (such as electrical signals caused by hot electrons). In this embodiment, by stopping spectral data acquisition when the energy of all pixels is lower than the dark noise, the use of meaningless and unusable spectral data for equation fitting can be avoided, thus ensuring the accuracy and efficiency of nonlinear correction.
[0058] Spectral data refers to the raw electrical signal matrix output by the detector, that is, the quantized value of the light intensity received by each pixel at the corresponding wavelength position. For example, spectral data collected at different integration times can be represented as: {t1: [x1,x2…,xn], t2: [x1,x2…,xn], t3: [x1,x2…,xn], …}; where t1, t2, and t3 represent the integration time, and x1, x2…, xn represent the electrical signals corresponding to the n pixels (n wavelength positions) output by the detector.
[0059] Optionally, after gradually reducing the integration time with a preset step size, the acquired spectral data can be preprocessed, that is, the acquired spectral data can be divided by the corresponding integration time to obtain normalized spectral data for each pixel at different integration times. Then, the normalized spectral data for each pixel at different integration times is saved to the corresponding folder as input data for subsequent processing.
[0060] For example, normalizing the spectral data of each pixel at different integration times to obtain the normalization coefficients of each pixel at different energies includes: for each pixel, determining the maximum energy of the pixel at different integration times from the spectral data of the pixel at different integration times; determining the value of the pixel's energy at different integration times divided by the maximum energy to obtain the normalization coefficients of the pixel at different energies.
[0061] For example: for any pixel k (i.e., the kth wavelength position), extract its electrical signal (i.e., energy) at different integration times from the spectral data to obtain the energy sequence of pixel k; determine the maximum energy value from the energy sequence to obtain the maximum energy of pixel k at different integration times; divide the energy sequence of pixel k by the value of the maximum energy to obtain the normalization coefficient of the energy sequence at different energies.
[0062] For example, the four-parameter logarithmic function equation is expressed by the following formula:
[0063] y = a * ln(x + b) + (1 - a)(c * x + d)
[0064] Where x represents the energy of each pixel, y represents the normalization coefficient corresponding to the energy, and a, b, c, and d represent the parameters to be fitted (or nonlinear correction coefficients) of the four-parameter logarithmic function equation.
[0065] Optionally, before the spectral acquisition system 103 starts spectral acquisition from the integration time corresponding to the saturation energy, it further includes preheating the light source module 101. The preheating time is the duration that can eliminate the disturbance of thermal effects on the optical system, such as 10 minutes, 20 minutes, or 30 minutes. In other embodiments, the preheating time can also be longer or shorter. This embodiment does not limit the preheating time of the light source module 101.
[0066] In other embodiments, the nonlinear correction device may also include other components required for the nonlinear correction process, such as: power supply, switch buttons (e.g., ...). Figure 1 The data collection buttons, touch screens, etc., are not listed here in this embodiment.
[0067] Taking the aforementioned nonlinear correction device applied to a soybean spectral acquisition system as an example, by performing overall calibration on the spectral acquisition system and writing the nonlinear correction coefficients of a four-parameter logarithmic function equation into the system, soybean spectra with the same protein content are acquired for comparison. Figure 2 As shown. According to Figure 2 It can be seen that after 1000nm, the abnormal upward tilt of the absorbance spectrum caused by nonlinear effect is significantly improved, the sample energy and absorbance spectrum shape are normal, and the nonlinear correction effect is good.
[0068] In summary, the nonlinear correction device of the spectral acquisition system provided in this embodiment can improve the nonlinear correction effect of the sample spectrum.
[0069] Figure 3 This is a flowchart of a nonlinear correction method for a spectral acquisition system provided in one embodiment of this application. This embodiment uses this method for... Figure 1 The nonlinear correction device of the spectral acquisition system shown is used as an example for illustration. This method includes at least the following steps:
[0070] Step 301: Control the spectral acquisition system to start spectral acquisition from the integration time corresponding to the saturation energy, and gradually reduce the integration time with a preset step size until the energy of the whole pixel is lower than the dark noise, so as to obtain the spectral data of each pixel at different integration times.
[0071] Step 302: Normalize the spectral data of each pixel at different integration times to obtain the normalization coefficients of each pixel at different energies;
[0072] Step 303: Based on the energy of each pixel and the normalization coefficient corresponding to the energy, fit a four-parameter logarithmic function equation, and perform nonlinear correction on the spectral acquisition system based on the fitted four-parameter logarithmic function equation.
[0073] For detailed descriptions, please refer to the above-described device embodiments.
[0074] In summary, the nonlinear correction method for the spectral acquisition system provided in this embodiment can improve the nonlinear correction effect of the sample spectrum.
[0075] Figure 4 This is a block diagram of a nonlinear correction device for a spectral acquisition system provided in one embodiment of this application. This embodiment uses this device for... Figure 1 The nonlinear correction device of the spectral acquisition system shown is used as an example for illustration. This device includes at least the following modules: data acquisition module 410, normalization processing module 420, and data fitting module 430.
[0076] The data acquisition module 410 is used to control the spectral acquisition system to start spectral acquisition from the integration time corresponding to the saturation energy, and gradually reduce the integration time with a preset step size until the energy of the whole pixel is lower than the dark noise, so as to obtain the spectral data of each pixel at different integration times.
[0077] The normalization processing module 420 is used to normalize the spectral data of each pixel at different integration times to obtain the normalization coefficients of each pixel at different energies.
[0078] The data fitting module 430 is used to fit a four-parameter logarithmic function equation based on the energy of each pixel and the normalization coefficient corresponding to the energy, and to perform nonlinear correction on the spectral acquisition system based on the fitted four-parameter logarithmic function equation.
[0079] For relevant details, please refer to the above embodiments.
[0080] It should be noted that the nonlinear correction device for the spectral acquisition system provided in the above embodiments is only illustrated by the division of the functional modules described above when performing nonlinear correction of the spectral acquisition system. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the nonlinear correction device for the spectral acquisition system can be divided into different functional modules to complete all or part of the functions described above. In addition, the nonlinear correction device for the spectral acquisition system provided in the above embodiments and the nonlinear correction method embodiments for the spectral acquisition system belong to the same concept, and the specific implementation process is detailed in the method embodiments, which will not be repeated here.
[0081] Figure 5 This is a block diagram of a controller provided in one embodiment of this application. The device includes at least a processor 501 and a memory 502.
[0082] Processor 501 may include one or more processing cores, such as a quad-core processor or an octa-core processor. Processor 501 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Processor 501 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 501 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, processor 501 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.
[0083] The memory 502 may include one or more computer-readable storage media, which may be non-transitory. The memory 502 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 502 are used to store at least one instruction, which is executed by the processor 501 to implement the nonlinear correction method of the spectral acquisition system provided in the method embodiments of this application.
[0084] In some embodiments, the nonlinear correction device of the spectral acquisition system may optionally include: a peripheral device interface and at least one peripheral device. The processor 501, memory 502, and peripheral device interface can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface via a bus, signal line, or circuit board. Indicatively, peripheral devices include, but are not limited to: radio frequency circuits, touch screens, audio circuits, and power supplies.
[0085] Of course, the nonlinear correction device of the spectral acquisition system may include fewer or more components, and this embodiment does not limit this.
[0086] Optionally, this application also provides a computer-readable storage medium storing a program that is loaded and executed by a processor to implement the nonlinear correction method of the spectral acquisition system described in the above method embodiments.
[0087] Optionally, this application also provides a computer product including a computer-readable storage medium storing a program that is loaded and executed by a processor to implement the nonlinear correction method of the spectral acquisition system described in the above method embodiments.
[0088] Optionally, this application also provides an electric compressor that includes a computer-readable storage medium storing a program loaded and executed by a processor to implement the nonlinear correction method of the spectral acquisition system described in the above method embodiments.
[0089] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0090] 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 the invention patent. 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 protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.
Claims
1. A nonlinear correction device for a spectral acquisition system, characterized in that, The device includes: Light source module, used to generate light sources; A diffuser and a spectral acquisition system to be nonlinearly corrected are sequentially located at the output end of the light source module; wherein the diffuser is used to homogenize the light source; and, The control module connected to the spectral acquisition system is used for: The spectral acquisition system is controlled to start spectral acquisition from the integration time corresponding to the saturation energy, and the integration time is gradually reduced with a preset step size until the energy of the whole pixel is lower than the dark noise, so as to obtain the spectral data of each pixel at different integration times. Normalize the spectral data of each pixel at different integration times to obtain the normalization coefficients of each pixel at different energies; Based on the energy of each pixel and the normalization coefficient corresponding to the energy, a four-parameter logarithmic function equation is fitted, and the spectral acquisition system is nonlinearly corrected based on the fitted four-parameter logarithmic function equation.
2. The method according to claim 1, characterized in that, The normalization process for the spectral data of each pixel at different integration times, to obtain the normalization coefficients for each pixel at different energies, includes: For each pixel, the maximum energy of the pixel at different integration times is determined from the spectral data corresponding to the pixel at different integration times. The normalization coefficients of the pixel at different energies are obtained by dividing the energy of the pixel at different integration times by the maximum energy.
3. The method according to claim 1, characterized in that, The four-parameter logarithmic function equation is expressed by the following formula: y = a * ln(x + b) + (1 - a)(c * x + d) Where x represents the energy of each pixel, y represents the normalization coefficient corresponding to the energy, and a, b, c, and d represent the parameters to be fitted to the four-parameter logarithmic function equation.
4. The method according to claim 1, characterized in that, The stepwise reduction of integration time with a preset step size includes: The integration time is gradually reduced with a preset step size of 5ms.
5. The method according to claim 1, characterized in that, After gradually reducing the integration time with a preset step size, the method further includes: The collected spectral data is divided by the corresponding integration time to obtain the normalized spectral data of each pixel at different integration times.
6. The method according to claim 1, characterized in that, Before controlling the spectral acquisition system to start spectral acquisition from the integration time corresponding to the saturation energy, the method further includes: The light source module is preheated for a preset time.
7. A nonlinear correction method for a spectral acquisition system, characterized in that, In the nonlinear correction apparatus according to any one of claims 1 to 6, the method comprises: The spectral acquisition system is controlled to start spectral acquisition from the integration time corresponding to the saturation energy, and the integration time is gradually reduced with a preset step size until the energy of the whole pixel is lower than the dark noise, so as to obtain the spectral data of each pixel at different integration times. Normalize the spectral data of each pixel at different integration times to obtain the normalization coefficients of each pixel at different energies; Based on the energy of each pixel and the normalization coefficient corresponding to the energy, a four-parameter logarithmic function equation is fitted, and the spectral acquisition system is nonlinearly corrected based on the fitted four-parameter logarithmic function equation.
8. A nonlinear correction device for a spectral acquisition system, characterized in that, For use in any one of the nonlinear correction devices according to claims 1 to 6, the device comprises: The data acquisition module is used to control the spectral acquisition system to start spectral acquisition from the integration time corresponding to the saturation energy, and gradually reduce the integration time with a preset step size until the energy of the whole pixel is lower than the dark noise, so as to obtain the spectral data of each pixel at different integration times. The normalization processing module is used to normalize the spectral data of each pixel at different integration times to obtain the normalization coefficients of each pixel at different energies. The data fitting module is used to fit a four-parameter logarithmic function equation based on the energy of each pixel and the normalization coefficient corresponding to the energy, and to perform nonlinear correction on the spectral acquisition system based on the fitted four-parameter logarithmic function equation.
9. A controller, characterized in that, The controller processor and memory; the memory stores a program, which is loaded and executed by the processor to implement the nonlinear correction method of the spectral acquisition system as described in any one of claims 1 to 6.
10. A computer-readable storage medium, characterized in that, The storage medium stores a program, which is loaded and executed by the processor to implement the nonlinear correction method of the spectral acquisition system as described in any one of claims 1 to 6.