Multispectral infrared photoelectric detection system, method and equipment and storage medium

Abstract

The invention discloses a multispectral infrared photoelectric detection system and a multispectral infrared photoelectric detection method, and relates to the field of photoelectric detection. The optical focusing modules are symmetrically arranged on the two sides of the light source module and converge probe light and target reflected light emitted by a light source, an optical filter and a polarizing film are arranged in the interference suppression module, and the target reflected light and the probe light with the target wavelength are filtered and output and sent to the multi-channel detection module. The multi-channel detection module comprises a plurality of infrared detectors, and each detector is connected with a pre-amplifier and is used for converting a sent spectral signal into an electric signal; and the signal processing module is used for carrying out noise reduction and feature parameter extraction on the down-converted electric signal of each channel, and calculating and outputting a detection result through feature fusion. According to the scheme, environmental stray light interference is effectively filtered and multi-dimensional data fusion is realized through a multi-channel synchronous detection and interference suppression technology, and the method has the advantages of improving environmental interference resistance, enhancing multi-dimensional detection precision and realizing high-speed dynamic response.

Description

Technical Field

[0001] This application relates to the field of photoelectric detection, and in particular to a multispectral infrared photoelectric detection system, method, device and storage medium. Background Technology

[0002] Infrared photoelectric detection technology, due to its core advantages of being "non-contact, non-destructive, and capable of penetrating some media," has become a key technology in fields such as industrial quality control, environmental monitoring, and medical diagnosis. Currently, the mainstream infrared detection devices on the market are mainly single-band infrared detection systems, with a core structure of "single-band infrared light source + single detector + silicon-based signal processing circuit." Their working principle is based on the absorption or reflection characteristics of infrared radiation. 1. Infrared light sources emit infrared light of specific wavelengths (such as 8-14µm mid-wave infrared) to irradiate target objects; 2. The absorption / reflection signal of infrared light by the target object is captured by the detector and converted into an electrical signal; 3. After being amplified and filtered, the electrical signal is transmitted to the processing circuit to calculate the target parameters (such as crack depth and gas concentration).

[0003] Such devices or systems can achieve basic detection functions in a single stable scenario (such as a laboratory environment), with a quantum efficiency (QE) ≥ 65% and a dark current density as low as 1 × 10⁻⁷ A / cm². However, they still have significant technical shortcomings in complex real-world scenarios, mainly manifested as follows: 1. Severe ambient light interference: Visible light and near-infrared stray light (such as workshop lighting and sunlight) in the detection scene can easily enter the detection optical path, resulting in a decrease in the signal-to-noise ratio (SNR) of the detector output signal. In outdoor or strong light industrial environments, the false detection rate is as high as 15%-30%, which cannot meet the requirements of high-precision detection. Second, the detection accuracy of a single band is insufficient. A single band infrared light source can only identify a single infrared feature of the target, making it difficult to distinguish between the "target signal" and the "background interference signal" (such as the difference in infrared radiation between the oxide layer and cracks on the metal surface, and the overlap of the absorption peaks of CO gas and water vapor), resulting in a detection error of ≥±5%FS. Third, signal processing is lagging. The traditional "single detector + single channel signal acquisition" architecture cannot acquire multi-dimensional data simultaneously, and the dynamic response time is ≥10ms. In dynamic scenarios with pipeline speed >0.5m / s, it is difficult to meet the real-time detection requirements. Summary of the Invention

[0004] This application provides a multispectral infrared photoelectric detection system and detection method, which has the advantages of improving the ability to resist environmental interference, enhancing the accuracy of multidimensional detection, and achieving high-speed dynamic response.

[0005] On the one hand, this application provides a multispectral infrared photoelectric detection system, including a cascaded light source module, an optical focusing module, an interference suppression module, a multi-channel detection module, and a signal processing module; The optical focusing module is symmetrically arranged on both sides of the light source module to converge the probe light and the target reflected light emitted by the light source. The interference suppression module has built-in filters and polarizers to filter the target reflected light and probe light of the target wavelength and send them to the multi-channel detection module. The multi-channel detection module includes several infrared detectors, and each detector is connected to a preamplifier to convert the input spectral signal into an electrical signal. The signal processing module performs noise reduction and extracts feature parameters for the down-converted electrical signals of each channel, and calculates and outputs the detection results through feature fusion.

[0006] Specifically, the light source module is an infrared light source array, which includes at least three sub-light source units, which respectively output 1.5-3μm short-wave infrared, 3-5μm mid-wave infrared and 8-14μm long-wave infrared; InGaAsP chips are used for short-wave infrared fabrication, and HgCdTe chips are used for long-wave infrared fabrication. Both have built-in pulse drive circuits, and the output power of 10-100mW and the pulse frequency of 1-10kHz are adjusted through the control module. During fabrication, the light source array is wavelength calibrated to ensure that the center wavelength deviation of the three bands is ≤±5nm and the power stability is ≤±2% / h.

[0007] Specifically, the optical focusing module includes a double parabolic reflector and a convex lens group; the parabolic reflector is symmetrically arranged on both sides of the light source module to converge the detection light emitted by the light source; the convex lens group is arranged between the reflector and the target object to converge the target reflected light and the detection light into the same optical path; During fabrication, the optical path coaxiality is calibrated using a laser interferometer, and the diameter of the focused spot is adjustable from 0.5 to 2 mm via a control module, with a spot uniformity ≥90%.

[0008] Specifically, the interference suppression module includes a narrowband filter group and a rotatable polarizer. The narrowband filter group contains three filters corresponding to the wavelengths of the sub-light source. The bandwidth of the filters is ≤50nm, the transmittance is ≥85%, and they are switched by an electric slide rail. The electric slide rail includes a stepper motor, a guide rail, and a position sensor, with a positioning accuracy of ≤±0.1mm. The polarizer is driven by a rotating motor and the angle can be adjusted from 0 to 90°. During the fabrication process, wavelength matching tests must be performed on the filter group to ensure that the wavelength deviation with the light source module is ≤ ±3nm.

[0009] Specifically, the multi-channel detection module includes three independent infrared detectors, with response wavelengths matched to 1.5-3μm shortwave infrared, 3-5μm midwave infrared, and 8-14μm longwave infrared, respectively. The infrared detector uses a mercury cadmium telluride (HgCdTe) detector. Each detector is connected to a preamplifier, which consists of an operational amplifier, resistors, and capacitors. The gain is adjustable from 10 to 1000 times, and the noise figure is ≤1.5dB.

[0010] Specifically, the signal processing module is built on an FPGA chip and fuses and outputs spectral data; The control module is built using an STM32H743 microcontroller and communicates with the light source module, interference suppression module, multi-channel detection module, and signal processing module via an SPI interface. It controls the light source parameters, filter switching, detector gain control, and data fusion trigger control, respectively.

[0011] On the other hand, this application provides a multispectral infrared photoelectric detection method, the method comprising: The control module selects preset parameters according to the detection scenario, drives the electric slide rail to switch the narrowband filter to the target band, and controls the rotary motor to adjust the polarizer to the target angle; The target object is placed in the detection optical path, and the control module triggers the light source module to emit multi-band detection light; the infrared light reflected by the target object and the detection light are converged by the optical focusing module, and then pass through the interference suppression module to filter stray light before entering the detector field of view of the multi-channel detection module. The multi-channel detection module synchronously acquires optical signals of different wavelengths through various detectors, converts them into electrical signals through a preamplifier, and sends them to the signal processing module. The signal processing module retrieves the acquired signal, performs noise reduction and feature extraction, combines the data with calibration coefficients for data fusion, and outputs the detection results.

[0012] Specifically, before selecting preset parameters, an initial calibration is performed, including: The light source module outputs infrared light of various bands to illuminate the standard calibration piece; the multi-channel detection module synchronously collects the calibration signals of infrared light of various bands, transmits them to the signal processing module for noise reduction and feature extraction, and calculates the calibration coefficients of each band.

[0013] Specifically, when the standard calibration piece is a steel test block with a known crack depth, the extracted feature parameter is the integral area of ​​the crack depth in each band, the calibration coefficient represents the linearity coefficient between the crack depth and the signal peak value, and the detection result is the crack depth. When the standard calibration component is a standard gas of known concentration, the extracted feature parameter is the integral area of ​​gas concentration in each band, the calibration coefficient represents the ratio of gas concentration to signal integral area, and the detection result is gas concentration.

[0014] Specifically, detection results under n-band signal detection The calculation is as follows:

[0015]

[0016] to This represents the feature parameters extracted from n bands. to This represents the calibration coefficients corresponding to n bands.

[0017] The beneficial effects of the technical solution provided in this application include at least the following: This application significantly reduces the impact of ambient light interference on signal quality in complex detection scenarios, improves target parameter recognition accuracy through multispectral feature fusion, and shortens system response time using a multi-channel parallel processing architecture. This enables the system to stably output high-precision detection results in dynamic scenarios such as high-speed detection on industrial production lines and outdoor environmental monitoring. Attached Figure Description

[0018] Figure 1 A schematic diagram of a multispectral infrared photoelectric detection system is shown. Figure 2 A schematic diagram of the interference suppression module is shown. Figure 3 A flowchart of the multispectral infrared photoelectric detection method is shown; Figure 4 The flowchart of the multispectral data fusion algorithm is shown; Figure 5 A structural block diagram of a computer device provided in an exemplary embodiment of this application is shown. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0020] In this article, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0021] To address the aforementioned technical issues, some solutions suppress interference by adding fixed filters or light shields, but these only block stray light of specific wavelengths and cannot adapt to interference in various scenarios (such as the spectral differences between strong workshop light and outdoor sunlight). Other solutions attempt dual-band detection, but without data fusion processing, they remain limited by the constraints of single features and cannot overcome accuracy bottlenecks. Still other solutions reduce noise by increasing detector sensitivity, but this increases device costs by 3-5 times, making large-scale application difficult. Therefore, there is an urgent need for an infrared photoelectric detection solution that is "strongly anti-interference, enables simultaneous detection of multiple features, offers high real-time performance, and is cost-controllable" to fill the technological gap in complex scenarios.

[0022] To address the aforementioned issues, firstly, to mitigate ambient light interference, a composite optical filtering mechanism is introduced into the optical path to improve the purity of the target signal through multi-level physical filtering. Secondly, to overcome the limitations of single-band feature extraction, a multispectral collaborative detection strategy is proposed, enhancing target recognition capabilities through multi-dimensional data correlation analysis. Finally, to address signal processing lag, a multi-channel parallel acquisition architecture is designed to achieve synchronous conversion and processing of spectral signals. During this process, it is necessary to balance optical path convergence efficiency with stray light suppression capabilities, while ensuring the temporal consistency of multi-channel signals.

[0023] Therefore, this application provides a multispectral infrared photoelectric detection system. Figure 1 A schematic diagram of a multispectral infrared photoelectric detection system is shown, including a light source module 1, an optical focusing module 2, an interference suppression module 3, a multi-channel detection module 4, and a signal processing module 5, cascaded in sequence. In some embodiments, a control module 6 and a display screen 9 can also be added to control the operation of other modules. The light source module can emit multi-band infrared light, for example, by using an array structure containing short-wave, mid-wave, and long-wave infrared sub-light sources. The optical focusing module is symmetrically arranged on both sides of the light source module to converge the probe light emitted by the light source and the target reflected light. The target reflected light is the light reflected after the light shines on the target object 7. The interference suppression module is mainly for clutter filtering. It has built-in filters and polarizers to filter the target reflected light and probe light of the output target wavelength and send them to the multi-channel detection module. The multi-channel detection module contains several infrared detectors, each connected to a preamplifier to convert the spectral signal into an electrical signal, which is then sent to the signal processing module at the back end. The signal processing module performs noise reduction and feature parameter extraction on the electrical signal of each channel, and outputs the detection result through feature fusion calculation.

[0024] Specifically, the multi-band probe light emitted by the light source module converges into a focused optical path through symmetrically distributed optical focusing modules, enhancing the illumination intensity on the target object's surface. The target reflected light and probe light return along the same optical path, where filters in the interference suppression module select a preset wavelength, and polarizers eliminate incoherent stray light components. In the multi-channel detection module, each detector independently receives a specific wavelength of light signal, which is converted into an electrical signal by a preamplifier and then processed by the signal processing module for channel-specific noise reduction. Subsequently, the feature parameters extracted from each channel are correlated and calculated using a weighted fusion algorithm, ultimately outputting a comprehensive detection result. In this process, the symmetrical layout of the optical focusing modules ensures optical path stability, the composite filtering mechanism of the interference suppression module improves the signal-to-noise ratio, and the multi-channel architecture enables parallel processing of spectral data.

[0025] This application addresses the core challenges of traditional solutions through a technical approach combining multi-band collaborative detection, dual interference suppression, and lightweight data fusion. It achieves interference-resistant detection across a broad spectral range (400-900nm) and infrared (1.5-14µm) while maintaining low dark current, high response speed, and good scene adaptability. In complex detection scenarios, it significantly reduces the impact of ambient light interference on signal quality, improves target parameter recognition accuracy through multi-spectral feature fusion, and shortens system response time using a multi-channel parallel processing architecture. This enables the system to stably output high-precision detection results in dynamic scenarios such as high-speed industrial production line inspections and outdoor environmental monitoring.

[0026] In one possible implementation, the structural characteristics of each module can be designed as follows: 1. Light Source Module: Employs a multi-band infrared light source array containing at least three sub-light source units, such as outputting short-wave infrared (1.5-3μm), mid-wave infrared (3-5μm), and long-wave infrared (8-14μm) respectively. InGaAsP chips are used for short-wave infrared fabrication (e.g., InGaAsP chips for short-wave infrared and HgCdTe chips for long-wave infrared). A built-in pulse drive circuit (composed of MOSFETs, inductors, and capacitors) allows adjustment of output power (10-100mW) and pulse frequency (1-10kHz) via a control module. During fabrication, wavelength calibration of the light source array is required to ensure that the center wavelength deviation of at least three bands is ≤±5nm and power stability is ≤±2% / h.

[0027] 2. Optical Focusing Module: A composite focusing structure of "double parabolic mirrors + convex lens group" is adopted. The parabolic mirrors (made of aluminum coated glass with a reflectivity of ≥95%) are symmetrically arranged on both sides of the light source module to converge the probe light emitted by the light source. The convex lens group (composed of two achromatic lenses with a focal length of 20-50mm) is placed between the mirrors and the target object to converge the target reflected light and the probe light into the same optical path. During fabrication, the coaxiality of the optical path is calibrated using a laser interferometer to ensure that the diameter of the focused spot can be adjusted by the control module (0.5-2mm) and the spot uniformity is ≥90%.

[0028] 3. Interference Suppression Module: Composed of a "narrowband filter group + rotatable polarizer". The narrowband filter group contains 3 filters corresponding to the wavelength of the sub-light source (bandwidth ≤ 50nm, transmittance ≥ 85%), which are switched by an electric slide rail (composed of a stepper motor, guide rail, and position sensor). The slide rail positioning accuracy is ≤ ±0.1mm. The polarizer (made of polymer polarizing film, polarization degree ≥ 99%) is driven by a rotary motor, and the angle adjustment range is 0-90° with an adjustment accuracy of ≤ ±1°. During fabrication, wavelength matching tests are required on the filter group to ensure that the band deviation with the light source module is ≤ ±3nm. Figure 2 A schematic diagram of the interference suppression module is shown, where a represents the narrowband filter group and the electric slide rail, and b represents the rotatable polarizer and the rotary motor.

[0029] 4. Multi-channel detection module: Contains at least three independent infrared detectors (using HgCdTe detectors, with response wavelengths matching the respective bands of the aforementioned light source module: 1.5-3μm, 3-5μm, and 8-14μm, with response times ≤10ns). Each detector is connected to a preamplifier (composed of an operational amplifier, resistors, and capacitors, with an adjustable gain range of 10-1000 times and a noise figure ≤1.5dB). During fabrication, the detectors and amplifiers are integrated using a low-temperature bonding process (bonding temperature <150℃) to ensure a contact resistance ≤5×10-6Ω. cm², enabling synchronous acquisition of multi-band signals.

[0030] 5. Signal Processing Module: Built on an FPGA chip (Xilinx XC7K325T), it incorporates a "multispectral data fusion algorithm," the algorithm flow of which may include: ① A wavelet threshold denoising algorithm is used to denoise the original signals of the three channels, and the threshold is adaptively adjusted by the signal standard deviation; ② Extract the characteristic values ​​of each band (such as peak value, integral area, and rise time). ③ The target parameters are calculated using a weighted fusion formula (the weights are pre-calibrated by a standard calibrator); during preparation, the algorithm needs to be hardware-accelerated to ensure that the processing time is ≤1ms.

[0031] In addition, this system is equipped with a control module to assist in controlling the operation of the entire system.

[0032] 6. Control Module: Employs an STM32H743 microcontroller (480MHz main frequency), communicating with the light source module, interference suppression module, multi-channel detection module, and signal processing module via an SPI interface (10Mbps communication rate) to achieve coordinated control of "light source parameter adjustment, filter switching, detector gain control, and data fusion triggering"; the module integrates an SD card interface (supporting up to 128GB of storage) and an RS485 / Ethernet interface (100Mbps Ethernet rate) for data storage and external communication; electromagnetic compatibility (EMC) testing is required during fabrication to ensure radiated emissions ≤54dBuV / m in the 10-1000MHz frequency range.

[0033] In some possible implementations, the heat dissipation structure of the sub-light source unit in the light source module adopts a microchannel water-cooling design with a heat dissipation power ≥5W, ensuring that the light source operating temperature is stable at 25-35℃ and avoiding wavelength drift caused by temperature fluctuations. The lens surface of the optical focusing module is coated with an anti-reflection film (for the 1.5-14µm band) to reduce light reflection loss and improve light utilization. The detector package of the multi-channel detection module uses a metal shell with built-in desiccant to ensure that the internal humidity of the package is ≤30%RH, preventing moisture from affecting detection performance.

[0034] Furthermore, the FPGA chip of the signal processing module and the microcontroller of the control module transmit data via a DMA interface (Direct Memory Access) with a transmission rate ≥100MB / s, reducing data transmission latency. The control module supports remote control functionality, receiving commands from the host computer via Ethernet to configure parameters and read detection results.

[0035] Based on the above system, this application further proposes a multispectral infrared photoelectric detection method, such as... Figure 3 As shown, the method includes the following steps: S1. The control module selects preset parameters according to the detection scenario, drives the electric slide rail to switch the narrowband filter to the target band, and controls the rotary motor to adjust the polarizer to the target angle. S2. Place the target object in the detection optical path and trigger the light source module to emit multi-band detection light through the control module; the infrared light reflected by the target object and the detection light are converged by the optical focusing module, and then pass through the interference suppression module to filter stray light before entering the detector field of view of the multi-channel detection module. S3, the multi-channel detection module synchronously collects optical signals of different wavelengths through various detectors, converts them into electrical signals through a preamplifier, and sends them to the signal processing module; S4. The signal processing module calls up the acquired signal to perform noise reduction and feature extraction, combines the calibration coefficient to perform data fusion, and outputs the detection results.

[0036] The control module selects preset parameters based on ambient light intensity, target object material, or detection accuracy requirements. This selection, achieved through preset logic, chooses the corresponding filter band and polarizer angle, typically using a built-in preset parameter table in the microcontroller. This dynamically matches the light interference suppression needs of different detection scenarios. The motorized slide rail switching of the narrowband filter involves a stepper motor driving the filter assembly along a guide rail to bring the target band filter into the optical path. Precise positioning can be achieved using a position sensor to eliminate stray light interference from non-target bands. Adjusting the polarizer to the target angle involves changing the polarizer's direction using a rotary motor. This can be achieved using an angle encoder to control the polarizer's rotation angle, suppressing background noise in specific polarization directions. Optical path control within 50-200 mm involves adjusting the distance between the reflector and lens of the optical focusing module to keep the light signal transmission distance within a preset range. This can be achieved using a motorized displacement stage to adjust the optical path length, balancing signal strength with spatial layout constraints. Multi-channel synchronous acquisition refers to the parallel acquisition of optical signals from different bands by multiple detectors within the same time window. This can be implemented using an FPGA-triggered synchronous acquisition circuit to eliminate timing errors and improve dynamic response speed. Data fusion refers to the weighted calculation of feature parameters from multiple bands with calibration coefficients. This can be implemented using linear weighting algorithms or machine learning models to improve the comprehensive discrimination accuracy of multi-dimensional features.

[0037] Specifically, during the detection process, the control module first selects the appropriate filter and polarizer combination based on the ambient lighting conditions. For example, in a workshop environment with strong visible light interference, the infrared band filter with the greatest wavelength difference from the interfering light is preferentially selected, and the polarizer is rotated to an angle orthogonal to the polarization direction of the interfering light source. Subsequently, the light source module emits multi-band detection light containing short-wave, mid-wave, and long-wave infrared light, which is focused to form a superimposed light spot illuminating the target object. After the reflected light and detection light are filtered by the filter group, only the signal of the target band enters the detector. The optical path control module dynamically adjusts the optical path length according to the detector sensitivity, for example, shortening the optical path to the lower limit in a weak reflection scene to enhance the signal strength. Three infrared detectors simultaneously collect signals of different bands, which are amplified by a preamplifier and then transmitted to the signal processing module. The signal processing module performs digital filtering and noise reduction on the data of each channel, extracts feature parameters, calls the pre-stored calibration coefficients for fusion calculation, and finally outputs the detection result of the target object.

[0038] Compared to existing technologies, traditional methods using single-band light sources and single-channel detectors cannot distinguish between target signals and background interference. For example, when detecting metal cracks, the infrared absorption characteristics of the oxide layer and the crack are difficult to differentiate under a single band. This method, however, utilizes multi-band detection to simultaneously acquire the characteristic differences of the target in short-wave, mid-wave, and long-wave infrared light. Combined with polarizer angle adjustment, it effectively suppresses interference caused by specular reflection from the metal surface. Existing technologies use sequential filter switching to acquire multi-band data, resulting in time differences between signals in dynamic scenes, such as displacement errors in detecting moving objects on an assembly line. This method, through a multi-channel synchronous acquisition mechanism, ensures that signals from different bands originate from the same spatiotemporal location, eliminating detection bias caused by motion. Furthermore, existing technologies use single threshold judgment for signal processing, making them susceptible to environmental noise. This method, however, enhances anti-interference capabilities by fusing multi-dimensional features and utilizing the correlation between signals from different bands.

[0039] Through the above technical solutions, this application significantly reduces the false detection rate in complex environments. For example, under strong light interference, the stray light suppression rate can be increased to over 90% by jointly adjusting the filter and polarizer; in multi-target detection scenarios, the recognition accuracy of different materials can be increased to over 95% by multi-band feature fusion; in dynamic detection scenarios, the signal processing delay can be reduced to less than 2 milliseconds by multi-channel synchronous acquisition, meeting the real-time detection requirements of high-speed pipelines.

[0040] In some embodiments, before selecting preset parameters, an initialization calibration is also performed, including: The light source module outputs infrared light of various bands to illuminate the standard calibration piece; the multi-channel detection module synchronously acquires the calibration signals of infrared light of various bands, transmits them to the signal processing module for noise reduction and feature extraction, and calculates the calibration coefficient of each band.

[0041] Taking the output of infrared light in three bands (power and frequency preset according to the detection target) as an example, when the standard calibration piece is a steel test block with a known crack depth, the extracted feature parameter is the integral area of ​​the crack depth in each band, the calibration coefficient represents the linear coefficient between the crack depth and the signal peak value, and the detection result is the crack depth.

[0042] When the standard calibration component is a standard gas of known concentration (such as CO gas), the extracted characteristic parameter is the integral area of ​​the gas concentration in each band. The calibration coefficient represents the proportionality between the gas concentration and the signal integral area, and the detection result is the gas concentration. Detection results under n-band signal detection. The calculation is as follows:

[0043]

[0044] to This represents the feature parameters extracted from n bands. to This represents the calibration coefficients corresponding to n bands.

[0045] Figure 4 The flowchart of the multispectral data fusion algorithm is shown, which mainly includes initialization calibration, interference suppression settings, target detection, multi-channel signal acquisition, data fusion and result output.

[0046] During the initial calibration procedure, the standard calibration kit needs to be calibrated regularly (it is recommended to do so every 3 months) to ensure the accuracy of the calibration coefficients. If the detection target is changed (such as switching from metal crack detection to gas concentration monitoring), the initial calibration needs to be performed again, and the standard calibration kit corresponding to the target needs to be loaded.

[0047] The data fusion and result output process involves denoising the acquired signals (wavelet threshold denoising), feature extraction (e.g., extracting peak values ​​in the 1.5-3µm band and integral area in the 3-5µm band), and weighted fusion (using the weights calibrated in S1). The target parameters (e.g., crack depth, CO concentration) are calculated based on the calibration coefficients. The control module displays the calculation results in real-time on a screen (800×480 resolution) and transmits them to the host computer via RS485 / Ethernet, storing them on an SD card. The result output delay is ≤500ms. If the detection results exceed preset thresholds (e.g., crack depth > 0.2mm, CO concentration > 100ppm), the control module triggers an alarm function (audible and visual alarm, sound pressure level ≥ 85dB, alarm light brightness ≥ 500cd / m²), alerting staff to handle the situation promptly.

[0048] The infrared photoelectric detection achieved using the apparatus and method described above has the following advantages compared to existing single-band infrared detection schemes: 1. Significantly improved anti-interference capability: Through the dual suppression of "narrowband filter group (shielding non-target wavelength stray light) + rotatable polarizer (filtering polarization state interference light)" and combined with multispectral data fusion (counteracting the influence of residual stray light), the false detection rate caused by ambient light interference is reduced to below 5%, and it can be stably applied to strong light and complex electromagnetic environments. 2. High detection accuracy: Multi-band synchronous acquisition of infrared features of the target (such as the reflection peak of metal cracks in the 1.5-3um band and the absorption valley in the 3-5um band), avoiding the limitations of a single band. The detection error of metal cracks is ≤±0.01mm, and the detection error of gas concentration is ≤±2%FS, meeting the requirements of high-precision detection. 3. Strong real-time performance: Multi-channel detector synchronous acquisition (response time ≤10ns) + lightweight data fusion algorithm (processing time ≤1ms) + high-speed data transmission (DMA interface), the overall detection cycle is ≤2ms, which can meet the requirements of dynamic scenarios with pipeline speed ≤1m / s; 4. Good versatility: By switching narrowband filters (to adapt to the characteristic wavelengths of different targets), adjusting the light source parameters (power / frequency to match target characteristics), and loading the corresponding calibration coefficients, it can adapt to the detection needs of different targets such as metal defects, gases, and biological tissues without replacing the entire set of equipment, reducing the cost of use by more than 40%. 5. High stability: The microchannel water cooling of the light source module, the sealed moisture-proof packaging of the detector, and the EMC optimization of the control module ensure that the device can work stably in the temperature range of -10-50℃ and the humidity range of 10%-90%RH, with a performance fluctuation of ≤±3% after 72 hours of continuous operation.

[0049] Figure 5 This illustration shows a structural block diagram of a computer device provided in an exemplary embodiment of this application. The computer device can be a desktop computer, a laptop computer, a handheld computer, or a cloud server, etc. The computer device may include, but is not limited to, a processor and memory. The processor and memory can be connected via a bus or other means. The processor can be a Central Processing Unit (CPU). The processor can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, graphics processing units (GPUs), embedded neural network processing units (NPUs) or other dedicated deep learning coprocessors, discrete gate or transistor logic devices, discrete hardware components, or combinations of the above types of chips.

[0050] This application also discloses a computer-readable storage medium. Specifically, the computer-readable storage medium is used to store a computer program, which, when executed by a processor, implements the methods described in the above-described method embodiments. Those skilled in the art will understand that implementing all or part of the processes in the methods described in the above-described embodiments of this application can be accomplished by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium can also include combinations of the above types of memory.

[0051] This specific embodiment is merely an explanation of the present invention and is not intended to limit the invention. After reading this specification, those skilled in the art can make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they are within the scope of the claims of the present invention.

Claims

1. A multispectral infrared photodetector system, characterized by, The light source module, the optical focusing module, the interference suppression module, the multi-channel detection module and the signal processing module are cascaded; The optical focusing module is symmetrically arranged on both sides of the light source module, converges the detection light and the target reflection light emitted by the light source, the interference suppression module is internally provided with a filter and a polarizer, filters the target reflection light and the detection light of the target wavelength, and sends the target reflection light and the detection light into the multi-channel detection module; The multi-channel detection module comprises a plurality of infrared detectors, and each detector is connected with a preamplifier to convert the input light spectrum signal into an electric signal; The signal processing module reduces noise and extracts characteristic parameters of the electric signal of each channel, and calculates and outputs a detection result through characteristic fusion.

2. The multispectral infrared photodetector system of claim 1, wherein, The light source module is an infrared light source array, comprising at least three sub-light source units, respectively outputting 1.5-3 μm short-wave infrared, 3-5 μm medium-wave infrared and 8-14 μm long-wave infrared; InGaAsP chips are used for short-wave infrared preparation, HgCdTe chips are used for long-wave infrared preparation, an internal pulse driving circuit is provided, the output power and pulse frequency are adjusted by a control module, the output power is 10-100 mW, and the pulse frequency is 1-10 kHz; during preparation, the wavelength of the light source array is calibrated to ensure that the center wavelength deviation of the three wavebands is less than or equal to ±5 nm, and the power stability is less than or equal to ±2% / h.

3. The multispectral infrared photodetector system of claim 1, wherein, The optical focusing module comprises a double parabolic reflector and a convex lens group; the parabolic reflector is symmetrically arranged on both sides of the light source module, converges the detection light emitted by the light source, and the convex lens group is arranged between the reflector and the target object, converges the target reflection light and the detection light into the same light path; During preparation, the coaxiality of the light path is calibrated by a laser interferometer, the focusing spot diameter is adjusted by a control module, the adjusting range is 0.5-2 mm, and the light spot uniformity is greater than or equal to 90%.

4. The multispectral infrared photodetector system of claim 2, wherein, The interference suppression module comprises a narrow-band filter group and a rotatable polarizer, the narrow-band filter group comprises three filters corresponding to the wavelengths of the sub-light sources; the bandwidth of the filter is less than or equal to 50 nm, the transmittance is greater than or equal to 85%, and the filter is switched by an electric sliding rail; the electric sliding rail comprises a stepping motor, a guide rail and a position sensor, and the positioning accuracy is less than or equal to ±0.1 mm; The polarizer is driven by a rotating motor, the adjusting angle range is 0-90°; during preparation, the wavelength matching test of the filter group needs to be performed to ensure that the waveband deviation of the light source module is less than or equal to ±3 nm.

5. The multispectral infrared photodetector system of claim 3, wherein, The multi-channel detection module comprises three independent infrared detectors, and the response wavelengths are matched with 1.5-3 μm short-wave infrared, 3-5 μm medium-wave infrared and 8-14 μm long-wave infrared respectively. The infrared detector adopts a mercury cadmium telluride HgCdTe detector, each detector is connected with a preamplifier, the preamplifier is composed of an operational amplifier, a resistor and a capacitor, the gain is adjustable in the range of 10-1000 times, and the noise coefficient is less than or equal to 1.5 dB.

6. The multispectral infrared photodetector system of claim 2 or 3, wherein, The signal processing module is based on an FPGA chip and is used for fusion output of spectrum data. The control module is built with an STM32H743 microcontroller, and communicates with the light source module, interference suppression module, multi-channel detection module, and signal processing module through an SPI interface, to respectively control light source parameter adjustment, filter switching, detector gain control, and data fusion trigger control.

7. A multispectral infrared photodetection method, characterized in that, The method comprises: The control module selects preset parameters according to a detection scene, drives the electric sliding rail to switch the narrowband filter to a target waveband, and controls the rotating motor to adjust the polarizer to a target angle; The target object is placed in the detection light path, and the control module triggers the light source module to emit multi-waveband detection light; the infrared light reflected by the target object and the detection light are converged by the optical focusing module, pass through the interference suppression module to filter stray light in turn, and enter the field of view of the detector of the multi-channel detection module; The multi-channel detection module synchronously collects light signals of different wavebands through the detectors, converts and outputs electrical signals through the preamplifier, and sends the electrical signals to the signal processing module; The signal processing module retrieves the collected signals, performs noise reduction and feature extraction, combines the calibration coefficients to perform data fusion, and outputs the detection result.

8. The method of claim 7, wherein, Before the preset parameters are selected, initialization calibration is also performed, including: The light source module outputs infrared light of each waveband to irradiate a standard calibration piece; the multi-channel detection module synchronously collects calibration signals of each waveband of infrared light, and transmits the calibration signals to the signal processing module to perform noise reduction and feature extraction, and calculate calibration coefficients of each waveband.

9. The method of claim 8, wherein, When the standard calibration piece is a steel test block with a known crack depth, the extracted feature parameters are integral areas of crack depths of each waveband, the calibration coefficients represent linear coefficients of crack depths and signal peak values, and the detection result is the crack depth; When the standard calibration piece is a standard gas with a known concentration, the extracted feature parameters are integral areas of gas concentrations of each waveband, the calibration coefficients represent proportional coefficients of gas concentrations and signal integral areas, and the detection result is the gas concentration.

10. The method of claim 9, wherein, n-band signal detection under detection results The calculation is as follows: to denotes the feature parameters extracted from n wavebands, to denotes the calibration coefficients corresponding to n wavebands.

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