Assembly and adjustment method of spliced ​​detector based on active support structure and gradient descent method

Abstract

The present invention relates to a method for assembling and adjusting a spliced ​​detector based on an active support structure and a gradient descent method, belonging to the field of optical assembly and adjustment technology, and comprising the steps of: obtaining initial point cloud data of each detector spliced ​​together in a matrix; calculating the initial flatness of each detector; establishing a pin adjustment model, and determining a rotation matrix according to the pin adjustment model; setting an optimization objective function and constraint conditions for the overall flatness of the spliced ​​detector; iteratively solving the optimization objective function using a gradient descent method to obtain a final optimization result, the final optimization result including the optimal rotation angle of each pin of each detector; and performing in-situ correction and assembly of each detector according to the final optimization result obtained to obtain a spliced ​​detector with optimal flatness. The present invention is based on an active support structure and introduces a gradient descent method, and can achieve the purpose of achieving the optimal flatness of the spliced ​​detector by adjusting the pin rotation angle once, with higher assembly and adjustment efficiency and precision.

Description

Technical Field

[0001] The invention relates to the technical field of optical assembly and adjustment, and in particular to a splicing detector assembly and adjustment method based on an active support structure and a gradient descent method. Background Art

[0002] With the continuous progress of astronomy and science and technology, large-aperture, large-field-of-view, and wide-band astronomical optical telescopes have gradually become important tools for solving scientific problems. In order to detect farther and fainter celestial bodies, the aperture of astronomical optical systems has continued to increase; at the same time, in order to achieve observations of wider areas of the sky, the field of view of these systems has also continued to expand. These two developments have jointly promoted the continuous growth of focal plane sizes in the future. Large-size focal planes can not only capture more photons and improve image resolution, but also cover a larger area of ​​the sky in a single observation, improving observation efficiency. These advances have enabled astronomers to explore the mysteries of the universe more deeply and reveal more unknown celestial bodies and phenomena.

[0003] As a survey-type sky survey tool, the aperture, field of view and focal length of a large-aperture and large-field telescope determine the huge size of the imaging target surface. This size far exceeds the manufacturing capacity of a single existing detector, so this type of telescope usually uses detector splicing to cover such a large imaging area.

[0004] For a large field of view telescope system, the flatness of the detector used in the system is also an important indicator. Especially for large-surface spliced ​​detectors, the overall flatness of the detector array after splicing must be less than half of the focal depth of the system to ensure imaging quality. In the process of integrating and assembling spliced ​​detectors, it is necessary to measure the flatness multiple times, and after measuring the data, multiple fine-tuning is required to achieve the flatness requirements of the spliced ​​target surface.

[0005] According to the analysis of existing literature, the adjustment scheme mainly relies on calculating the root mean square error (RMS) and peak-to-valley error (PV) values ​​of the point cloud data collected through each scan during the mechanical design and adjustment process, and on this basis, the thickness of the gasket is continuously adjusted in a cycle based on experience until the requirements are met. However, this adjustment scheme relies too much on experience, lacks theoretical guidance, and requires a lot of measurement and debugging, and it is highly likely that the optimal flatness cannot be achieved to improve the imaging effect. Summary of the invention

[0006] In order to solve the problems that the existing splicing detector assembly and adjustment schemes are too dependent on experience, lack theoretical guidance, require a lot of measurement and debugging, and cannot achieve optimal flatness through a single assembly and adjustment, the present invention provides a splicing detector assembly and adjustment method based on an active support structure and a gradient descent method. The method can achieve the purpose of achieving the optimal flatness of the splicing detector by a one-time adjustment of the ejector pin rotation angle, and the assembly efficiency and accuracy are higher.

[0007] To solve the above problems, the present invention adopts the following technical solutions:

[0008] A method for assembling and adjusting a spliced ​​detector based on an active support structure and a gradient descent method, wherein an active support structure including three ejector pins is arranged at the bottom of the base of each detector to be spliced, the three ejector pins form an equilateral triangle layout, and the ejector pins are in tangential contact with the installation station at the bottom of the detector base, and the pitch angle and yaw angle of the detector are changed by adjusting the rotation angle of the ejector pins; the method comprises the following steps:

[0009] Step 1: Obtain the initial point cloud data of each detector spliced ​​together in a matrix;

[0010] Step 2: Calculate the initial flatness of each detector based on the acquired initial point cloud data, and determine whether the calculated initial flatness is all less than the single flatness threshold. If so, execute step 3; otherwise, adjust the pitch angle and / or yaw angle of the detector whose initial flatness is greater than the single flatness threshold by the ejector, and return to step 1;

[0011] Step 3: Establish an ejector adjustment model to obtain a rotation matrix for rotating the point cloud data;

[0012] Step 4: Set the optimization objective function and constraint conditions for the overall flatness of the spliced ​​detector, where the optimization objective function is:

[0013] ;

[0014] The constraints are:

[0015] ;

[0016] in, represents the rotation angle of the kth pin of the detector in the i-th row and j-th column, Represents the overall point cloud data matrix of the spliced ​​detector, Represents the overall point cloud data matrix Calculate the Z-axis standard deviation, represents the overall flatness threshold of the spliced ​​detector, ;

[0017] Step 5: Use the gradient descent method to iteratively solve the optimization objective function to obtain the final optimization result, which includes the optimal rotation angle of each ejector pin of each detector;

[0018] Step 6: Based on the final optimization result obtained in step 5, each detector is corrected and adjusted in situ to obtain a spliced ​​detector with optimal flatness.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] Compared with the shim structure, the ejector pin, i.e. the active support structure, can provide higher precision and control because the movement of the ejector pin can be precisely managed by the mechanical system. This makes it very suitable for applications that require precise positioning. The thickness of the shim is fixed, so when adjusting the height, it is necessary to replace or add shims of different thicknesses, which has relatively low precision and a cumbersome adjustment process.

[0021] The ejector pin can be adjusted quickly in height, usually only by adjusting the parameters of the control system, without disassembling the mechanical parts, so the adjustment speed is fast. The shim structure needs to be replaced or added manually, and the adjustment process is relatively time-consuming, which is not as flexible as the ejector pin structure.

[0022] Because the ejector pin can precisely control its contact point and support strength, it can distribute force more evenly, reduce local stress concentration, and extend the life of the equipment. Due to its fixed thickness, the force transmission of the gasket may not be as uniform as the ejector pin structure, which can easily lead to stress concentration and equipment wear.

[0023] The ejector pin can be approximated as a point contact due to its small contact area, which facilitates mathematical modeling, while the gasket structure is more difficult.

[0024] The invention provides theoretical guidance for the assembly and adjustment of spliced ​​detectors, eliminating a large number of repetitive tests and assembly and adjustment processes. During the detector assembly and adjustment process, the traditional manual adjustment method relies on the operator's experience and repeated trial and error. This method is not only time-consuming and labor-intensive, but also difficult to ensure accuracy and stability. By introducing an assembly and adjustment strategy guided by an optimization algorithm, the assembly and adjustment efficiency and accuracy are significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a flow chart of the method for assembling and adjusting a spliced ​​detector based on an active support structure and a gradient descent method according to an embodiment of the present invention;

[0026] Figure 2 Schematic diagram of the mechanical structure of the single detector and active support structure.

[0027] Explanation of the reference numerals: 1. Splicing substrate; 2. Micro groove; 3. Fixing screw; 4. Fixing nut; 5. Ball head structure; 6. Detector base. DETAILED DESCRIPTION

[0028] The technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0029] The purpose of the present invention is to establish a mathematical model of a spliced ​​detector based on an active support structure, and to design an algorithm based on a gradient descent method using the mathematical model as an analysis object, so as to calculate the ejector pins and the rotation angles required to achieve the target flatness. The spliced ​​detector assembly method proposed by the present invention mainly includes the following steps:

[0030] Step 1: Detector point cloud data acquisition: obtain the initial point cloud data of each detector to be spliced;

[0031] Step 2, flatness calculation: calculate the initial flatness of each detector to ensure that its initial flatness is within a reasonable range;

[0032] Step 3, establish the rotation matrix: establish the ejector adjustment model, determine the rotation matrix according to the ejector adjustment model, and use the rotation matrix to realize the rotation transformation of the point cloud data;

[0033] Step 4, flatness optimization: set the optimization objective function and constraint conditions for the overall flatness of the spliced ​​detector;

[0034] Step 5, iterative solution: adjust the ejector rotation angle through the numerical optimization algorithm, gradually optimize the angle combination of each detector, and obtain the final optimization result;

[0035] Step 6: In-situ correction and adjustment: Perform in-situ correction and adjustment on each detector according to the final optimization result to obtain a spliced ​​detector with optimal flatness.

[0036] Furthermore, the method further comprises the following steps:

[0037] Step 7, result verification: Measure and verify the overall flatness of the spliced ​​detector obtained in step 6 to ensure that the overall flatness of the spliced ​​detector is less than the target requirement.

[0038] Combine the following Figure 1 and Figure 2 Each of the above steps is described in detail.

[0039] Step 1: Detector point cloud data acquisition.

[0040] This step requires obtaining the initial point cloud data of multiple detectors to be spliced, which are spliced ​​together in a matrix arrangement. The number of detectors to be spliced, the side length, and the spacing between adjacent detectors can be set according to actual needs. For example, the initial point cloud data of 16 detectors are obtained. These detectors are arranged in a 4×4 matrix, the side length of each detector is 6 cm, and the spacing between adjacent detectors is 50 mm. The point cloud data of each detector can be obtained in advance through experiments, and it is ensured that the flatness of each detector is less than the set threshold to facilitate subsequent adjustments and optimizations.

[0041] Step 2: Flatness calculation.

[0042] After obtaining the initial point cloud data of each detector, this step calculates the initial flatness of each detector. The initial flatness is represented by the Z-axis standard deviation of the initial point cloud data. The calculation formula of the Z-axis standard deviation is as follows:

[0043] ;

[0044] in, is the Z-axis standard deviation, i.e. the initial flatness of the detector, is the number of points in the initial point cloud data, It is The Z coordinate of the point, is the average value of the Z coordinates of all points. By calculating the initial flatness, the plane error of the single detector before splicing can be calculated to provide a benchmark for subsequent optimization, and the flatness of the single detector should meet the design requirements. If the flatness of the single detector is too large, it will affect the overall splicing effect and make it impossible to achieve the target splicing flatness. Therefore, after calculating the initial flatness of each detector, it is necessary to determine whether the calculated initial flatness is less than the single flatness threshold. If all the initial flatnesses are less than the single flatness threshold, execute step 3; if there is any detector whose initial flatness is greater than or equal to the single flatness threshold, adjust the pitch angle and / or yaw angle of the detector through the ejector, and then return to step 1, re-acquire the initial point cloud data and calculate the flatness until the initial flatness of all detectors is less than the single flatness threshold.

[0045] Step 3: Create the rotation matrix.

[0046] In order to optimize the overall flatness of the detector after splicing, an active support structure including three ejector pins is provided at the bottom of each detector substrate 6, and the three ejector pins form an equilateral triangle layout, such as Figure 2As shown, each active support structure includes a splicing substrate 1 and three ejectors, wherein each ejector includes a microgroove 2, a fixed screw 3 and a fixed nut 4. The microgroove 2 is used to cooperate with the installation station set at the bottom of the detector base 6 to form a point contact, and the microgroove 2 is fixed to the top of the fixed screw 3. After the fixed screw 3 passes through the splicing substrate 1, the other end is threadedly matched with the fixed nut 4. The splicing substrate 1 provides support for the fixed screw 3. By screwing the fixed nut 4, the microgroove 2 at the top of the fixed screw 3 is raised or lowered, thereby adjusting the pitch angle and / or yaw angle of the detector. The installation station at the bottom of the detector base 6 adopts a semi-kinematic support structure, namely a ball head structure 5, which cooperates with the microgroove 2 to achieve stable support for the detector while reducing contact friction.

[0047] Since the ejector pin and the detector are in tangential contact, they can be approximately considered as point contact. Based on this condition, the mathematical model of the ejector pin adjustment model is established. By adjusting the rotation angle of the ejector pin, the pitch angle and yaw angle of the detector can be changed.

[0048] Specifically, the adjustment of the ejector rotation angle is achieved through the rotation matrix, which rotates around the x, y, and z axes respectively. The rotation matrix formula is as follows:

[0049] ;

[0050] ;

[0051] ;

[0052] in, , , Point cloud data are axis, axis, The rotation matrix used for coordinate transformation when the axis rotates, , , They are axis, axis, The axis corresponds to the rotation angle of the ejector pin.

[0053] pass , and The point cloud data is rotated to achieve coordinate fusion and adjust the detector angle. The formula for rotating the point cloud data is as follows:

[0054] ;

[0055] in, is the point cloud data matrix, It is the point cloud data matrix after rotation transformation.

[0056] Step 4: Planarity optimization.

[0057] This step sets the optimization objective function and constraints for the overall flatness of the spliced ​​detector.

[0058] The optimization objective function is:

[0059] ;

[0060] The constraints are:

[0061] ;

[0062] in, Indicates Row, No. The detector of the The rotation angle of the ejector pin, ; Represents the overall point cloud data matrix of the spliced ​​detector; Represents the function of obtaining the Z-axis standard deviation of the point cloud data. Represents the overall point cloud data matrix Calculate the Z-axis standard deviation; It represents the minimum target requirement for the flatness of the spliced ​​detector system, that is, the overall flatness threshold of the spliced ​​detector, in microns.

[0063] After setting the optimization objective function and constraint conditions for the overall flatness, in the next step 5, the rotation angle of the ejector pin is adjusted by the numerical optimization algorithm, and the angle combination of each detector is gradually optimized to ensure that the overall flatness after splicing is less than Micrometer.

[0064] Step 5: Iterate the solution.

[0065] This step uses the gradient descent method to iteratively solve the optimization objective function to obtain the final optimization result. The iterative solution process includes: making a small range adjustment to the ejector pin rotation angle of each detector (such as adjusting 0.001 radians each time); calculating the overall flatness after adjustment, and measuring it by the Z-axis standard deviation of the point cloud data; if the adjusted flatness is better than the previous flatness, save the current ejector pin rotation angle and proceed to the next step of adjustment; repeat this process until the maximum number of iterations is reached or the overall flatness meets the requirements (less than Micrometers). This step uses the gradient descent method for iterative solution. The gradient descent method is a commonly used optimization algorithm that calculates the gradient of the objective function and adjusts the variables along the direction of gradient descent so that the objective function gradually approaches the optimal solution.

[0066] Step 5.1: Randomly initialize the rotation angle of each detector's pin , set the learning rate and the maximum number of iterations max_iter; where the learning rate Can be set to 0.001;

[0067] Step 5.2: Rotate the pins of each detector by an angle , calculate the optimization objective function for the rotation angle The partial derivative of , the calculation formula is as follows:

[0068] ;

[0069] Step 5.3: Update the corresponding ejector rotation angle according to the gradient calculated in step 5.2. The update formula is as follows:

[0070] ;

[0071] The left side of the equal sign The updated ejector rotation angle, on the right side of the equal sign The rotation angle of the ejector pin before updating;

[0072] Step 5.4: Determine whether the current number of iterations has reached the maximum number of iterations or whether the flatness has converged to a value less than the target value under the current number of iterations ( micrometers) means that the optimization objective function is less than the overall flatness threshold of the detector after splicing. , if the maximum number of iterations is reached or the optimization objective function is less than , it is considered converged and the iteration is stopped. At this time, the rotation angle of each ejector pin of each detector is the optimal rotation angle, and the optimal rotation angle of each ejector pin of each detector is output as the final optimization result; if the maximum number of iterations is not reached and the optimization objective function is not less than , then adjust the rotation angle of the ejector pin and return to step 5.2, recalculate the gradient, and execute step 5.3 to update the rotation angle of the ejector pin until convergence and then stop the iteration.

[0073] The optimization algorithm used in the present invention establishes a mathematical model to accurately control the rotation angle of the ejector pin of each detector, reducing the number of trial and error and achieving rapid convergence. Compared with manual adjustment, optimization algorithms such as the gradient descent method can find the global optimal solution in a shorter time to ensure that the overall flatness meets the requirements. Compared with traditional methods, the optimization algorithm not only improves the adjustment efficiency, but also significantly improves the flatness accuracy and consistency of the final adjustment.

[0074] This algorithm-guided assembly and adjustment strategy greatly reduces the burden on operators and improves the level of automation in production and debugging. It not only improves the overall performance and reliability of the detector, but also significantly improves the repeatability and predictability of the assembly and adjustment process.

[0075] Specifically, the application of the gradient descent method in the present invention shows its advantages in the following aspects:

[0076] Improve installation efficiency: The algorithm can quickly converge to the global optimal solution, reducing the installation time;

[0077] Improve precision: Through accurate calculation of mathematical models, high-precision flatness control can be achieved;

[0078] Reduce human errors: The automated adjustment process reduces changes in manual operations and improves the consistency and reliability of installation and adjustment;

[0079] Optimize resource allocation: reduce the cost and time of trial and error, and improve production efficiency.

[0080] In short, the introduction of the gradient descent method for detector assembly and adjustment not only optimizes the assembly and adjustment process, but also significantly improves the quality and performance of the final product.

[0081] Step 6: Correct and adjust in situ.

[0082] According to the optimal rotation angle of each ejector pin of each detector obtained in step 5, each detector is corrected and adjusted in situ, and finally a spliced ​​detector with optimal flatness is obtained.

[0083] Step 7: Verify the results.

[0084] Use a measuring mechanism such as a non-contact profilometer to measure the overall flatness of the spliced ​​detector obtained in step 6 to verify whether the measured flatness meets the target requirements, that is, whether it is less than the overall flatness threshold of the spliced ​​detector. .

[0085] From the structural point of view, the present invention has the following beneficial effects:

[0086] Compared with the shim structure, the active support structure can provide higher precision and control because the movement of the ejector pin can be precisely managed by the mechanical system, which makes it very suitable for applications that require precise positioning. However, the thickness of the shim is fixed, so when adjusting the height, it is necessary to replace or add shims of different thicknesses, which has relatively low precision and a cumbersome adjustment process.

[0087] The ejector pin can be adjusted in height quickly, usually only by adjusting the parameters of the control system, without disassembling the mechanical parts, so the adjustment speed is fast, while the shim structure needs to be replaced or added manually, and the adjustment process is relatively time-consuming, which is not as flexible as the ejector pin structure;

[0088] Because the ejector pin can precisely control its contact point and support strength, it can distribute force more evenly, reduce local stress concentration, and extend the life of the equipment. However, due to its fixed thickness, the force transmission of the gasket may not be as uniform as that of the ejector pin structure, which can easily lead to stress concentration and equipment wear.

[0089] The ejector pin can be approximated as a point contact due to its small contact area, which facilitates mathematical modeling, while the gasket structure is more difficult.

[0090] From the perspective of efficiency, the present invention has the following beneficial effects:

[0091] The invention provides theoretical guidance for the assembly and adjustment of spliced ​​detectors, eliminating a large number of repetitive tests and assembly and adjustment processes. In the detector assembly and adjustment process, the traditional manual adjustment method relies on the operator's experience and repeated trial and error, which is not only time-consuming and labor-intensive, but also difficult to ensure accuracy and stability. By introducing an assembly and adjustment strategy guided by an optimization algorithm, the assembly and adjustment efficiency and accuracy are significantly improved.

[0092] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described 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.

[0093] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for assembling and adjusting a spliced ​​detector based on an active support structure and a gradient descent method, characterized in that: An active support structure including three ejector pins is arranged at the bottom of the base of each detector to be spliced. The three ejector pins form an equilateral triangle layout. The ejector pins are in tangential contact with the installation station at the bottom of the detector base. The pitch angle and yaw angle of the detector are changed by adjusting the rotation angle of the ejector pins. The method comprises the following steps: Step 1: Obtain the initial point cloud data of each detector spliced ​​together in a matrix; Step 2: Calculate the initial flatness of each detector based on the acquired initial point cloud data, and determine whether the calculated initial flatness is all less than the single flatness threshold. If so, execute step 3; otherwise, adjust the pitch angle and / or yaw angle of the detector whose initial flatness is greater than the single flatness threshold by the ejector, and return to step 1; Step 3: Establish an ejector adjustment model to obtain a rotation matrix for rotating the point cloud data; Step 4: Set the optimization objective function and constraint conditions for the overall flatness of the spliced ​​detector, where the optimization objective function is: ； The constraints are: ； in, Indicates Row, No. The detector of the The rotation angle of the ejector pin, Represents the overall point cloud data matrix of the spliced ​​detector, Represents the overall point cloud data matrix Calculate the Z-axis standard deviation, represents the overall flatness threshold of the spliced ​​detector, ; Step 5: Use the gradient descent method to iteratively solve the optimization objective function to obtain the final optimization result, which includes the optimal rotation angle of each ejector pin of each detector; Step 6: Based on the final optimization result obtained in step 5, each detector is corrected and adjusted in situ to obtain a spliced ​​detector with optimal flatness.

2. The method for assembling and adjusting a spliced ​​detector based on an active support structure and a gradient descent method according to claim 1, characterized in that: The following steps are also included: Step 7: Use a measuring mechanism to measure the overall flatness of the spliced ​​detector obtained in step 6 to verify whether the measured flatness is less than the overall flatness threshold of the spliced ​​detector.

3. The method for assembling and adjusting a spliced ​​detector based on an active support structure and a gradient descent method according to claim 1 or 2, characterized in that: Step 5 includes the following steps: Step 5.1: Randomly initialize the rotation angle of each pin of each detector And set the learning rate and maximum number of iterations; Step 5.2: Calculate the optimization objective function for the rotation angle The partial derivative is the gradient, and the calculation formula is as follows: ； Step 5.3: Update the corresponding pin rotation angle according to the gradient calculated in step 5.2: ； in, is the learning rate; Step 5.4: Determine whether the maximum number of iterations has been reached or the optimization objective function at the current number of iterations is less than the overall flatness threshold of the spliced ​​detector. If so, stop the iteration and output the rotation angle of each ejector pin of each detector as the final optimization result. Otherwise, adjust the rotation angle of the ejector pin and return to step 5.2 to recalculate the gradient.

4. The method for assembling and adjusting a spliced ​​detector based on an active support structure and a gradient descent method according to claim 3, characterized in that: Learning Rate Set to 0.

001.

5. The method for assembling and adjusting a spliced ​​detector based on an active support structure and a gradient descent method according to claim 1 or 2, characterized in that: In step 2, the initial flatness of the detector uses the Z-axis standard deviation of the initial point cloud data, and the calculation formula is as follows: ； in, is the initial flatness, is the number of points in the initial point cloud data, It is The Z coordinate of the point, is the average Z coordinate of all points.

6. The method for assembling and adjusting a spliced ​​detector based on an active support structure and a gradient descent method according to claim 1 or 2, characterized in that: The formula for the rotation matrix is ​​as follows: ； ； ； in, , , Point cloud data are axis, axis, The rotation matrix used for coordinate transformation when the axis rotates, , , They are axis, axis, The axis corresponds to the rotation angle of the ejector pin.

7. The method for assembling and adjusting a spliced ​​detector based on an active support structure and a gradient descent method according to claim 1 or 2, characterized in that: The number of detectors is 16, and all detectors are arranged in a 4×4 matrix, with a spacing of 50 mm between adjacent detectors.

8. The method for assembling and adjusting a spliced ​​detector based on an active support structure and a gradient descent method according to claim 1 or 2, characterized in that: The monomer planarity threshold is 10 microns.

9. The method for assembling and adjusting a spliced ​​detector based on an active support structure and a gradient descent method according to claim 1 or 2, characterized in that: Each active support structure comprises a splicing substrate (1) and three ejector pins, each ejector pin comprises a microgroove (2), a fixing screw (3) and a fixing nut (4), the microgroove matched with the installation station is fixed on the top of the fixing screw, and the other end of the fixing screw is matched with the fixing nut thread after passing through the splicing substrate.

10. The method for assembling and adjusting a spliced ​​detector based on an active support structure and a gradient descent method according to claim 9, characterized in that: The mounting station at the bottom of the detector base adopts a ball head structure (5).

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