Hyperspectral camera semi-automatic focal plane adjustment method based on PI control

Abstract

The invention relates to the technical field of camera imaging, and particularly discloses a hyperspectral camera semi-automatic focal plane adjustment method based on PI control. In order to solve the problem that the pose relationship between a sensor and a focal plane has great influence on performance indexes during the adjustment of the hyperspectral camera, the method proposes to realize semi-automatic adjustment by using PI control software. By controlling imaging of the hyperspectral camera, displaying light and shadow on a software interface in real time, calculating indexes such as MTF and signal-to-noise ratio and combining feedback adjustment of a PI control algorithm, the optimal pose relation between the focal plane and the detector is rapidly and accurately obtained. According to the method, the installation and adjustment efficiency and precision are improved, the installation and adjustment period is shortened, the dependence on the experience of installation and adjustment personnel is reduced, and standardized focal plane installation and adjustment of the hyperspectral camera are realized. Reliable image support is provided for subsequent hyperspectral application, an effective solution thought is provided for similar engineering requirements, and the method has wide application prospects and value.

Description

Technical Field

[0001] This application belongs to the technical field of camera imaging, and discloses a semi-automatic focal plane alignment method for hyperspectral cameras based on PI control. Background Art

[0002] With the increasingly wide application of hyperspectral cameras, the market demand continues to grow. Building an efficient and stable hyperspectral camera alignment production line has become the key to improving output and quality. During the alignment process, the pose relationship between the sensor and the focal plane is crucial for the camera performance. However, the traditional method relies on senior alignment personnel for long-term manual adjustment, seriously affecting the production line efficiency and capacity expansion.

[0003] In the existing process, the alignment personnel need to repeatedly adjust the PI position to pursue the best imaging. This process takes a long time (usually one day), and due to the lack of quantitative standards and re-inspection mechanisms, it is difficult to ensure the consistency and reliability of the alignment results. Manual alignment highly depends on personal experience, resulting in fluctuating alignment effects and being difficult to meet the requirements of standardization and precision for efficient production lines.

[0004] Therefore, the current alignment process faces challenges such as low timeliness, lack of quantitative and standardized operation guidelines, and difficulty in supporting the construction of efficient production lines. There is an urgent need for a fast, accurate, and standardized alignment method to meet the market demand. Summary of the Invention

[0005] Aiming at the existing problems in the alignment of hyperspectral cameras, we propose an innovative semi-automatic focal plane alignment method for hyperspectral cameras based on PI control. This method uses software to achieve digital precise control of the PI adjustment steps, effectively avoiding the uncertainty of manual operation. The software can record and analyze the imaging effect after each adjustment in real time, and automatically optimize the PI position until the optimal configuration is reached. During this process, the changes in the imaging effect are quantified and digitally recorded, enhancing the controllability and re-inspection ability of the alignment process.

[0006] In addition, software control not only significantly shortens the alignment cycle, but also provides strong support for alignment optimization, quality control, and fault diagnosis by thoroughly recording the historical data of the PI pose and imaging effect. The application of digital means significantly improves the production efficiency and accuracy of the alignment process, while providing instant feedback to the alignment personnel to ensure that each alignment meets the expected effect and is convenient for subsequent traceability and analysis. The content of the present invention is as follows:

[0007] The present invention provides a semi-automatic focal plane alignment method for hyperspectral cameras based on PI control. The technical point is that it specifically includes the following steps:

[0008] Step 1: First, fix the hyperspectral detector on the PI platform and perform a rough adjustment on the PI platform through the optical alignment software to position the photosensitive surface of the detector at the theoretical position and facing the light emission direction, and record the initial pose.

[0009] Step 2: Detect the light and shadow imaging state through the optical alignment software. If no imaging occurs, continuously fine-tune the PI platform until imaging appears.

[0010] Step 3: Start the assembly and adjustment control software for fine adjustment. Perform multi-objective optimization by evaluating the MTF values at 9 imaging positions of the area array to make the MTF values at each point reach the optimal.

[0011] Step 4: Adjust the pose of the PI platform to make the focal plane parallel to the sensor, synchronously monitor the stability of the MTF values at 9 imaging points, and maintain the optimal MTF state through closed-loop control.

[0012] Step 5: Verify the matching relationship between the focal plane parallelism and the MTF value. When parameter conflicts occur, give priority to ensuring the parallelism index.

[0013] Step 6: Adjust the PI pose to achieve the centering control of the light and shadow field of view, and ensure that the imaging field of view is in the best focusing area.

[0014] Step 7: Perform a re-inspection of the focal plane assembly and adjustment, record the final PI pose parameters, and calculate the spectral resolution and central wavelength.

[0015] Step 8: After completing the parameter calibration, enter the application test stage.

[0016] Compared with the prior art, the beneficial effects of a semi-automatic focal plane assembly and adjustment method for a hyperspectral camera based on PI control of the present invention are as follows:

[0017] The present invention proposes a semi-automatic focal plane assembly and adjustment method for a hyperspectral camera based on PI control software, including controlling the imaging of the hyperspectral camera, displaying the light and shadow in real time in the software interface, calculating the MTF in real time, calculating indicators such as the signal-to-noise ratio, and then using PI control combined with the feedback of various real-time indicators to obtain the optimal pose relationship between the focal plane and the detector, realizing the fast and accurate standardized focal plane assembly and adjustment of the hyperspectral camera. It provides reliable images for subsequent hyperspectral applications and also provides a solution idea for subsequent projects with the same requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present invention, and constitute a part of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0019] Figure 1 It is a flowchart of a semi-automatic focal plane assembly and adjustment method for a hyperspectral camera based on PI control of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0020] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention.

[0021] The following will detail the technical solutions provided by each embodiment of the present invention in conjunction with the drawings.

[0022] A semi-automatic focal plane alignment method for a hyperspectral camera based on PI control software specifically includes the following steps:

[0023] Step 1: First, fix the hyperspectral detector on the PI platform to ensure the stability of the detector position. Then turn on the light source and dock the optical system for preliminary light source debugging. At this time, manually fine-tune the PI platform through the optical calibration software to ensure that the photosensitive surface of the detector is placed at the theoretical position and faces the light output direction, and record the pose P0 to prepare for subsequent fine adjustment.

[0024] Step 2: Use the optical calibration software to determine whether the light and shadow are displayed. After the preliminary adjustment, check whether the light and shadow can be seen. If the light and shadow are not seen, continue to fine-tune the PI platform until the light and shadow are displayed. The current pose is P1.

[0025] Step 3: When the light and shadow are displayed, enter the fine adjustment stage. Start the alignment control software and adjust the pose of the PI platform (P1 + ΔP < P, ΔP ≤ 0.01°) to make the MTF value of the hyperspectral camera imaging reach the optimal. During this process, the MTF needs to be evaluated at 9 positions respectively, and ensure that the MTF at each position reaches the expected optimal value. The current pose is P2.

[0026] Step 4: Continue to adjust the pose of the PI platform to make the focal plane as parallel as possible to the sensor and ensure uniform focusing in the entire imaging area. During this process, continuously monitor the MTF values of 9 points to ensure that the MTF remains in the optimal state. If the MTF value fluctuates, continue to adjust the PI pose until the MTF values of all 9 points are stable at the optimal solution. The current pose is P3.

[0027] Step 5: Once the focal plane is parallel to the sensor, start the verification of parallelism and check the MTF values of 9 points again. If the MTF value has reached the optimal and the parallelism meets the requirements, enter the next step; if not, repeat the previous steps until both the MTF and the focal plane parallelism reach the optimal solution.

[0028] Step 6: Continue to adjust the PI pose to ensure that the optical image field is centered. During this process, ensure that the field of view of the imaging area does not shift, and the optical image field always remains at the best focus position of the camera. The current pose is P4.

[0029] Step 7: After the optical image field is centered, conduct a re-inspection of the focal plane alignment to ensure that all adjustments have achieved the expected results. At this time, record the pose of the PI platform, and calculate the spectral resolution and the spectral center wavelength. Through the recorded data, subsequent re-inspections can be carried out to ensure consistent imaging quality of the hyperspectral camera in different batches of products.

[0030] Step 8: After all adjustments are completed, end the alignment process. At this time, all parameters have been adjusted to the optimal state, the detector has completed the fine adjustment of the focal plane pose, and enters the subsequent application test stage.

[0031] The above are only embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, various changes and modifications can be made to the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the scope of the claims of the present invention.

Claims

1. A semi-automatic focus adjustment method for a hyperspectral camera based on PI control, characterized in that: The following steps are involved: Step 1: First, fix the hyperspectral detector on the PI platform, and make a rough adjustment through the optical calibration software PI platform to position the detector's photosensitive surface at the theoretical position and toward the light emission direction, and record the initial position; Step 2: Use the optical calibration software to detect the light and shadow imaging status. If no imaging occurs, continue to fine-tune the PI platform until imaging occurs. Step 3, start the adjustment control software to make fine adjustments, and perform multi-objective optimization by evaluating the MTF values ​​of the 9 imaging positions of the array to optimize the MTF value of each point; Step 4: Adjust the PI platform posture so that the focal plane is parallel to the sensor, monitor the stability of the MTF values ​​of the nine imaging points simultaneously, and maintain the optimal MTF state through closed-loop control; Step 5, verify the matching relationship between the focal plane parallelism and the MTF value. When a parameter conflict occurs, the parallelism index is prioritized; Step 6: Adjust the PI posture to achieve centering control of the optical and visual field to ensure that the imaging field is in the optimal focus area; Step 7, perform focal plane adjustment and re-inspection, record the final PI pose parameters and calculate the spectral resolution and central wavelength; Step 8: After completing parameter calibration, enter the application testing phase.

2. The method for semi-automatic focus adjustment of a hyperspectral camera based on PI control according to claim 1, characterized in that: The single posture adjustment of the fine adjustment described in step 3 does not exceed 0.01°, and the cumulative adjustment range is constrained by the preset angle threshold.

3. The method for semi-automatic focus adjustment of a hyperspectral camera based on PI control according to claim 1, characterized in that: In step 3, the MTF satisfies the relationship: Where V max is the maximum value of DN area in the QuickView software, V min It is the minimum value of DN area in the QuickView software, and Dark is the mean value of dark signal in the current working condition.

4. The method for semi-automatic focus adjustment of a hyperspectral camera based on PI control according to claim 1, characterized in that: The parallelism adjustment described in step 4 adopts the three-point coplanarity method, and the spatial parallelism between the focal plane and the sensor is achieved by adjusting the pitch angle and yaw angle of the PI platform in a coordinated manner.

5. The method for semi-automatic focus adjustment of a hyperspectral camera based on PI control according to claim 1, characterized in that: In step 5, the parallelism verification uses a laser interferometer to measure the angle between the focal plane normal vector and the sensor reference plane. When the angle is ≤0.005°, it is judged to be parallel.

6. The method for semi-automatic focus adjustment of a hyperspectral camera based on PI control according to claim 1, characterized in that: In step 6, the field of view centering control is achieved through the image centroid algorithm, keeping the offset between the center point of the imaging area and the geometric center of the detector target surface ≤ 3 pixels.

7. The method for semi-automatic focus adjustment of a hyperspectral camera based on PI control according to claim 1, characterized in that: The re-testing process in step 7 includes: MTF value back-testing after temperature cycle test, posture parameter reproducibility verification after vibration test, and spectral center wavelength drift detection.

8. The method for semi-automatic focus adjustment of a hyperspectral camera based on PI control according to claim 1, characterized in that: The adjustment process of step 3 to step 6 adopts the fuzzy PID control algorithm to establish a nonlinear mapping relationship between the posture adjustment amount and the MTF change amount.

9. The method for semi-automatic focus adjustment of a hyperspectral camera based on PI control according to claim 1, characterized in that: The final recorded PI posture parameters include: six degrees of freedom coordinates (X, Y, Z, θ_x, θ_y, θ_z), ambient temperature value T, and adjustment timestamp t, forming a traceable installation parameter database.

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