An optical fiber F-P cavity sensor autocollimation system and an autocollimation packaging method thereof

Abstract

The application discloses a kind of optical fiber F-P cavity sensor autocollimation system and its autocollimation packaging method, belong to MEMS sensor technical field, the optical fiber F-P cavity sensor autocollimation system includes MCU and three step motors, three The step motor is used to control collimator in X axis, Y axis and Z axis three direction movement;PID control module is inlayed and arranged in MCU, and PID control module is controlled between three step motors by PWM.This optical fiber F-P cavity sensor autocollimation system in the application compares the idea of the real-time light intensity and the theoretical light intensity by collection, the most value algorithm provides accurate theoretical light intensity, PID control system accurate positioning, accurate displacement prevents the appearance of steady-state error and overshoot, and when not satisfying maximum light intensity condition, it can be repeated operation and comparison, ensure the accuracy and precision of collimator on light alignment, so as to accurately realize MEMS sensor collimator self-alignment.

Description

Technical Field

[0001] This invention relates to the field of MEMS sensor technology, and in particular to a self-collimation system for an optical fiber FP cavity sensor and its self-collimation packaging method. Background Technology

[0002] Fiber optic collimators are mainly composed of optical fibers and collimating lenses. They can transform the divergent beam emitted from the end face of ordinary quartz optical fibers into a parallel beam, increase the working distance of the back-end optical components, thereby isolating the back-end optical components from the high-temperature region. Combined with a high-temperature resistant sensitive structure, measurements can be performed in high-temperature environments.

[0003] Optical MEMS sensors typically require collimators and sensing chips to be aligned for light exposure. When setting up an experimental setup to align the collimator with the light source, the law of reflection is primarily utilized. First, ensure the collimator's emitted light spot hits the exact center of the sensing chip. At this point, the sensor's sensitivity is highest, and the impact of diaphragm deformation due to pressure on the reflected light is minimal. Then, adjustments are made based on the position of the light returned from the sensing chip. The position of the returned light spot is observed against a single white background. When the returned light deviates from the center of the collimator lens, modulation is achieved using an adjustment mechanism.

[0004] There are also methods that measure the intensity of the returned light to subsequently modulate the collimator's position. After initially determining the relative positions of the components using visible light, a sensor is connected to the detection optical path, and precise adjustments are made by observing the returned light power and spectrum. During adjustment, the returned light power is measured using a power meter, and the signal is optimal when the returned light power is at its maximum. However, these methods generally require manual collimator alignment, and the calibration device is relatively cumbersome to operate. Further research is needed on collimator self-alignment techniques and methods. Summary of the Invention

[0005] To address the aforementioned problems, this invention aims to provide a self-collimating system for fiber optic FP cavity sensors and its self-collimating packaging method, thereby solving the problem that existing optical MEMS sensors rely on manual collimation, which fails to meet the requirements for fast and accurate sensor performance and production.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A fiber optic FP cavity sensor self-collimation system includes an MCU and an execution unit, characterized in that: the execution unit includes three stepper motors, which are respectively used to control the movement of the collimator in the X-axis, Y-axis and Z-axis directions; the MCU is embedded with a PID control module, which communicates with the three stepper motors via PWM control;

[0008] The self-collimation system further includes a power supply, and the MCU and the three stepper motors are all connected to the power supply.

[0009] Furthermore, the peripheral circuit of the MCU includes a reset circuit, a clock circuit, and a 3.3V power supply circuit.

[0010] Furthermore, a self-collimation packaging method for a fiber optic F-P cavity sensor self-collimation system, comprising the following steps:

[0011] S1: Predetermine the light intensity value P after collimation by the collimator, store it in the MCU, and set it as the initial parameter of the PID control module;

[0012] S2: Collect in real time the light intensity values traversed along the X-axis under PWM control, obtain the maximum light intensity value C0 along the traversed X-axis and the corresponding PID control parameters, and send them into the PID control module by the MCU;

[0013] S3: Control the stepper motor corresponding to the X-axis by the PID control module to make the collimator backscan the X-axis from the C0 value to obtain the point P1 with the strongest light intensity, and complete the alignment of the maximum value point of the X-axis collimated light intensity;

[0014] S4: Collect in real time the light intensity values traversed along the Y-axis under PWM control, obtain the maximum light intensity value C1 along the traversed Y-axis and the corresponding PID control parameters, and send them into the PID control module by the MCU;

[0015] S5: Control the stepper motor corresponding to the Y-axis by the PID control module to make the collimator backscan the Y-axis from the C1 value to obtain the point P2 with the strongest light intensity, and complete the alignment of the maximum value point of the Y-axis collimated light intensity;

[0016] S6: Judge the magnitude relationship between P2 and P. If P2≥P, drive the collimator to be packaged with the sensitive chip by the stepper motor corresponding to the Z-axis; if P2<P, repeat steps S2-S5 to update the displacement threshold C and the maximum light intensity value C1 until the collimator moves to the center of the sensor packaging support column, i.e., the place with the maximum light intensity value, and the self-alignment is completed.

[0017] Furthermore, in step S2, the maximum light intensity value C0 along the traversed X-axis is obtained by the differential interpolation method in the numerical maximum value algorithm. The specific operations include the following steps:

[0018] S201a: Set the initial positions x0, y0 of the light intensity calculation at the initial point, the iteration flag h, and the number of points N;

[0019] S202a: Given the increment flag as n and the maximum value point flag as k, and assign n as 1;

[0020] S203a: Assign x1 = x0 + h, assign y p = y0 + hf(x0,y0), yc =y0+hf(x1,y p The differential function y1 = (y) is obtained through iterative fitting. p +y c ) / 2;

[0021] S204a: Substitute the newly obtained values ​​of y1 and x1 back into step S203a as the initial values ​​of x0 and y0, and repeat step S203a N times to obtain the N-fold iterative linear fitting differential formula.

[0022] S205a: The extreme value flag is decremented by 1 with each iteration, resulting in k=0. Substituting this into the differential equation after N iterations yields the maximum light intensity value C0.

[0023] Furthermore, in step S2, the maximum light intensity value C0 on the X-axis after traversal can also be obtained using the bubble sort algorithm in numerical optimization. The specific operation includes the following steps:

[0024] S201b: Input the real-time acquired light intensity value array [Arr], and set the loop flag i to the maximum number of array elements;

[0025] S202b: Assign bit search flag j to 1;

[0026] S203b: Determine the size of the first and second values ​​in the array [Arr]. If the first value is smaller than the second value, swap the two values ​​and increment the bitwise search flag j+1. Continue this process until the size relationship between the j-th and j+1-th values ​​is determined, then end the loop and increment the loop flag i-1.

[0027] S204b: Reassign j to 1, perform the second sorting, and repeat steps S202b~S203b N times.

[0028] S205b: After the Nth iteration, i = 0. At this time, the highest digit in the array is the maximum value of the array after bubble sort. Let the Nth digit of the array [Arr] be the maximum value C0, and output it to the PID control module.

[0029] Furthermore, in step S2, the maximum light intensity value C0 on the X-axis after traversal can be obtained using the hill-climbing method combined with the cuckoo search algorithm. The specific operation includes the following steps:

[0030] S201c: First, initialize the population size N, i.e., the number of single-axis light intensity sampling points, the solution space dimension D, the iteration number flag K, the discovery probability pa, and the transformation parameter ps;

[0031] S202c: Flight via Lévy, where the single-axis dimension is 1-dimensional random alternating long and short flight. The Lévy flight calculation formula is as follows. u follows N(0, σ) uThe normal distribution v follows N(0, σ) v Normal distribution, where, σ v =1;

[0032] S203c: Position light intensity X obtained randomly through Levi's flight. i Move to the neighborhood of that point and use the hill-climbing algorithm to find a local optimum. Input the number of iterations k = 1 and the flags i and j = 1.

[0033] S204c: Determine the current light intensity X i Value and light intensity X i+1 Value size, when X i+1 The value is less than X i The value, the local optimal solution is C i This is the point of local optimal light intensity;

[0034] S205c: The local optimal solution C i Send N j The flag bit j+1 is used to store the address of each local optimal solution. Updating the bird's nest position is equivalent to updating the local optimal solution flag bit i.

[0035] S206c: Determine if the current local optimum satisfies the transformation parameters. If it does, then C i If the global optimal solution cannot be found, the next random number C is searched again using the Levi's plane. i ;

[0036] S207c: Re-determine X i The neighborhood of the current marker is used to obtain the light intensity value X. i The local optimum data is searched again using the hill-climbing method. Simultaneously, the optimum is stored in parameter N using a flag j. It is then determined whether the transformation parameter is less than a random number between 0 and 1. If N is satisfied... j and N j+1 If the size relationship is determined, the current flag bit i is saved, and the address of the local optimal solution is replaced with the current point of maximum light intensity C. i If the condition cannot be met, the Levi aircraft will search for the next local optimum.

[0037] S208c: By iterating K times, the local optimal solution is continuously exchanged and updated, and finally the global optimal solution of the current axis is obtained, that is, the point C0 with the maximum light intensity.

[0038] Furthermore, the control parameters of the PID mentioned in step S2 are incremental PID, and the output formula of the incremental PID is u(t)=u(t-1)+Kp*[e(t)-e(t-1)]+Ki*e(t)+Kd[(e(t)-2*e(t-1)+e(t-2)); where Kp, Ki, and Kd are the proportional, integral, and derivative coefficients of the incremental PID control module, respectively.

[0039] Furthermore, the PID control parameters are tuned using the decay curve method, specifically including the following steps:

[0040] S2A: Set the integral time of the regulator to infinity and the derivative time to zero, i.e., Ti = ∞, Td = 0;

[0041] S2B: The regulating system is put into operation in pure proportional mode. After the system stabilizes, the proportional degree is gradually reduced, and the changes in the regulating process are observed.

[0042] S2C: Determine whether the change in the adjustment process has reached the specified ratio. If not, repeat step S2B. If the adjustment process has reached the specified ratio, obtain the δ value under the corresponding decay condition. s and decay operation period T S ;

[0043] S2D: Based on δ s and T s The regulator setting parameters are calculated using empirical formulas.

[0044] S2E: Gradually introduce values ​​slightly larger than the regulator tuning parameters obtained in step S2D into the system, observe the operation, and gradually adjust them to smaller values;

[0045] S2F: Observe whether the curve meets the tuning requirements. If it does not, repeat step S2E until the PID parameters that meet the curve requirements are found and the tuning is completed.

[0046] The beneficial effects of this invention are: compared with the prior art, the improvement of this invention lies in that...

[0047] The fiber optic FP cavity sensor self-collimation system in this invention compares the real-time light intensity with the theoretical light intensity. The maximum value algorithm provides accurate theoretical light intensity, the PID control system provides precise positioning, and the precise displacement prevents steady-state errors and overshoot. Furthermore, the system can repeat the operation and comparison even when the maximum light intensity condition is not met, ensuring the accuracy and precision of the collimator's light alignment. Thus, the self-alignment of the MEMS sensor collimator can be accurately achieved. Attached Figure Description

[0048] Figure 1 This is a diagram of the self-collimation system architecture of the fiber optic FP cavity sensor in this invention.

[0049] Figure 2 This is a schematic diagram of the self-collimation system of the fiber optic FP cavity sensor in this invention.

[0050] Figure 3 This is a flowchart of the self-collimation packaging method of the fiber optic FP cavity sensor self-collimation system in this invention.

[0051] Figure 4 This is a flowchart of the differential interpolation method in the numerical extremum algorithm of Embodiment 2 of the present invention.

[0052] Figure 5 This is a flowchart of the PID parameter decay curve method 4:1 tuning method in Embodiment 2 of the present invention.

[0053] Figure 6 This is a comparison chart of the actual output and the ideal output of the simulation experiment in Embodiment 2 of the present invention.

[0054] Figure 7 This is a flowchart of the numerical algorithm for the global optimal solution in Embodiment 3 of the present invention.

[0055] Figure 8 This is a flowchart of the bubble sort algorithm in the numerical maximum / minimum algorithm of Embodiment 4 of the present invention. Detailed Implementation

[0056] To enable those skilled in the art to better understand the technical solutions of the present invention, the technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0057] Example 1:

[0058] As attached Figure 1 and 2 As shown, a fiber optic FP cavity sensor self-collimation system includes an MCU and an execution unit. The execution unit includes three stepper motors, which are used to control the movement of the collimator in the X, Y, and Z axes, respectively. The MCU has an embedded PID control module, which communicates with the three stepper motors via PWM control.

[0059] The self-collimation system also includes a power supply, to which the MCU and the three stepper motors are connected.

[0060] The peripheral circuitry of the MCU includes a reset circuit, a clock circuit, and a 3.3V power supply circuit. This peripheral circuitry, together with the MCU, forms a minimum system that serves as the main controller for the self-collimation system of the fiber optic FP cavity sensor. The execution unit consists of relay-isolated stepper motors controlled by PWM. Three stepper motors form a three-axis system, controlling the X, Y, and Z directions of the system respectively. Both the MCU and the stepper motors are powered by a power supply; the three stepper motors are powered by a standard 12V supply, while the MCU is typically powered by 3.3V.

[0061] Example 2:

[0062] Example 2 provides a self-collimation packaging method for a fiber optic FP cavity sensor self-collimation system as described in Example 1. The specific operation process is shown in the attached figure. Figure 3 As shown, it includes the following steps:

[0063] S1: Pre-measure the light intensity value P after collimation by the collimator, store it in the MCU, and set it as the initial parameter of the PID control module;

[0064] Specifically, the fiber optic FP cavity sensor self-collimation system is first initialized by pre-measuring the initial light intensity data after collimation by the collimator, which is then stored in the MCU as the given light intensity value P for this self-collimation encapsulation method.

[0065] S2: Real-time acquisition of X-axis traversal light intensity values ​​under PWM control, obtaining the maximum light intensity value C0 of the X-axis after traversal, and the corresponding PID control parameters, which are then sent to the PID control module by the MCU.

[0066] Specifically, in this embodiment, the differential interpolation method in the numerical optimization algorithm is used to obtain the maximum light intensity value C0 on the X-axis after traversal. The specific operation process is shown in the attached figure. Figure 4 As shown, it includes the following steps:

[0067] S201a: Set the light intensity of the initial point, calculate the initial position x0, y0, iteration flag h, and number of points N;

[0068] S202a: Given an increasing flag n and an extreme value flag k, assign n the value 1;

[0069] S203a: Assign x1 = x0 + h, assign y p = y0 + hf(x0, y0), y c =y0+hf(x1,y p The differential function y1 = (y) is obtained through iterative fitting. p +y c ) / 2;

[0070] S204a: Substitute the newly obtained values ​​of y1 and x1 back into step S203a as the initial values ​​of x0 and y0, and repeat step S203a N times to obtain the N-fold iterative linear fitting differential formula.

[0071] S205a: The extreme value flag is decremented by 1 with each iteration, resulting in k=0. Substituting this into the differential equation after N iterations yields the maximum light intensity value C0.

[0072] In this embodiment, the entire subroutine flow is simulated using cubic differential interpolation iteration. Given a sampling frequency of 1 / 100 (i.e., x-step size of 0.01), and inputs y0 = 0.009999833, y1 = 0.01999867, and y2 = 0.02999550, after N = 3 iterations, the iterative differential polynomial w is obtained:

[0073] f'(x2)=[f(x0)-4f(x1)+3f(x2)] / 2h, the maximum value is approximately 0.99958265, thus completing the maximum value algorithm calculation.

[0074] Furthermore, the maximum light intensity C value obtained by the MCU needs to be coordinated with PID behavioral control so that the motor can drive the collimator to the collimator alignment position. The PID algorithm is an incremental PID, which has the advantages of low false triggering, easy and seamless manual / automatic switching, and no integral loss.

[0075] The incremental PID output formula is:

[0076] u(t)=u(t-1)+Kp*[e(t)-e(t-1)]+Ki*e(t)+Kd[(e(t)-2*e(t-1)+e(t-2));

[0077] In the formula, Kp, Ki, and Kd are the proportional, integral, and derivative coefficients of the incremental PID control module, respectively.

[0078] The PID control parameters are tuned using the decay curve method (4:1 or 10:1). This embodiment uses 4:1 as an example, as shown in the attached figure. Figure 5 The PID parameter decay curve method 4:1 tuning method specifically includes the following steps.

[0079] S2A: Set the integral time of the regulator to infinity and the derivative time to zero, i.e., Ti = ∞, Td = 0;

[0080] S2B: The regulating system is put into operation in pure proportional mode. After the system stabilizes, the proportional degree is gradually reduced, and the changes in the regulating process are observed.

[0081] S2C: Determine whether the change in the adjustment process reaches the specified ratio of 4:1. If not, repeat step S2B. In this embodiment, after repeating step S2B multiple times, the first peak appears at 1.76s when p=17.5, and the second peak appears at 3.266s. δ s The steady-state value is 1.976, and the decay operation period is T. S The value is 1.506. The amplitude at the second peak is 2.137, which differs from the steady state by 0.171; the peak value at the first peak is 2.738, which differs from the steady state by 0.722. The calculated interpolation ratios are close to 4:1, which satisfies the attenuation curve and allows for the next step.

[0082] S2D: Based on δ s and T s The regulator tuning parameters are calculated using empirical formulas, and the PID system parameters can be obtained from this step.

[0083] Kp = 0.8 * δs = 1.5808

[0084] Ki = 0.3 * TS = 0.4518

[0085] Ki = 0.3 * TS = 0.1506;

[0086] S2E: Gradually introduce values ​​slightly larger than the regulator tuning parameters obtained in step S2D into the system, observe the operation, and gradually adjust them to smaller values;

[0087] Substituting Kp = 1.6 here, we find no obvious oscillation in the system. Inputting Ki = 0.145 and Kd = 0.15 yields a better comparison chart of the actual and ideal outputs in the simulation, as shown in the attached figure. Figure 6 As shown, there is no steady-state error between the ideal output and the actual output, and the output recovers to stability with minimal overshoot.

[0088] S2F: Observe whether the curve meets the tuning requirements. If it does not, repeat step S2E until the PID parameters that meet the curve requirements are found and the tuning is completed.

[0089] In this embodiment, the curve meets the tuning requirements, that is, there is no obvious oscillation affecting the system stability, and the actual curve coincides with the ideal curve, that is, there is no obvious steady-state error.

[0090] This step completes the setting of PID control system parameters. The X-axis traversal light intensity value under PWM control will be collected in real time. The maximum light intensity value C0 of the X-axis after traversal will be obtained by numerical extremum algorithm, and the corresponding PID control parameters will be sent to the PID control by MCU.

[0091] Further, S3: The stepper motor corresponding to the X-axis is controlled by the PID control module to make the collimator sweep back the X-axis from the C0 value to obtain the point P1 with the strongest light intensity, completing the alignment of the maximum value point of the X-axis collimated light intensity;

[0092] The calculated theoretical maximum light intensity value C is sent into the MCU. At this time, the sensor returns the real-time light intensity value F to the MCU. The interpolation is obtained from Err = C - F by the PID behavior control. A PWM modulation wave is generated by setting the system parameters. The stepper motor is controlled to rotate through the relay isolation control signal to send the collimator to the theoretical maximum light intensity position. After reaching the specified position, the X-axis positioning is completed.

[0093] The specific operation process is as follows: A total of 1000 data points are scanned from 0 to 1. After step S2, it is calculated that the maximum light intensity point is at the 200th position. At this time, the stepper motor rotates in reverse from 1 to 0.2. The PID behavior control is to avoid overshooting to 0.15 or the occurrence of steady-state error, that is, it can only move to 0.18.

[0094] S4: The light intensity values traversed by the Y-axis under PWM control are collected in real time to obtain the maximum light intensity value C1 of the traversed Y-axis and the corresponding PID control parameters, and are sent into the PID control module by the MCU;

[0095] S5: The stepper motor corresponding to the Y-axis is controlled by the PID control module to make the collimator sweep back the Y-axis from the C1 value to obtain the point P2 with the strongest light intensity, completing the alignment of the maximum value point of the Y-axis collimated light intensity;

[0096] The operations of step S4 and step S5 are the same as those of step S2 and step S3, and the only difference is that the operation directions are the X-axis and the Y-axis.

[0097] Further, S6: Judge the size relationship between P2 and P. If P2 ≥ P, the collimator is driven by the stepper motor corresponding to the Z-axis to be packaged with the sensitive chip; if P2 < P, repeat steps S2 - S5 to update the displacement threshold C (a displacement threshold C will be obtained each time of traversal) and the maximum light intensity value C1 until the collimator moves to the center of the sensor packaging support column, that is, the position with the maximum light intensity, and the self-alignment is completed.

[0098] At this point, the X-axis and Y-axis positioning is complete. Because the collimator can transform the divergent beam emitted from the end face of a common quartz fiber into a parallel beam, increasing the working distance of the back-end optical components, the initial given value P is compared with the real-time acquired value P2 (the point of maximum light intensity on the X and Y axes). If it is less than P2, it is acceptable, and the fiber collimator is inserted via the z-axis drive. If it is greater than P2, it is unacceptable, and steps S2-S5 are repeated, continuously updating the displacement threshold C and the maximum light intensity value P2 using a numerical extremum algorithm until the fiber collimator moves to the center of the encapsulation pillar, i.e., the point of maximum light intensity. The entire system compares the acquired real-time light intensity with the theoretical light intensity. The extremum algorithm provides accurate theoretical light intensity, the PID control system provides precise positioning, and precise displacement prevents steady-state errors and overshoot. Furthermore, if the maximum light intensity condition is not met, the above steps can be repeated to ensure the accuracy and precision of the collimator's light alignment. Thus, the MEMS sensor collimator self-alignment method completes the system's self-alignment.

[0099] Example 3:

[0100] The difference between Example 3 and Example 2 lies only in the use of a hill-climbing method combined with a Cuckoo Search algorithm in step S2 to obtain the maximum light intensity value C0 on the X-axis after traversal. The specific operation process is shown in the attached figure. Figure 7 As shown, it includes the following steps:

[0101] S201c: First, initialize the population size N, i.e., the number of single-axis light intensity sampling points, the solution space dimension D, the iteration number flag K, the discovery probability pa, and the transformation parameter ps;

[0102] S202c: Flight via Lévy, where the single-axis dimension is 1-dimensional random alternating long and short flight. The Lévy flight calculation formula is as follows. u follows N(0, σ) u The normal distribution v follows N(0, σ) v Normal distribution, where, σ v =1;

[0103] S203c: Position light intensity X obtained randomly through Levi's flight. i Move to the neighborhood of that point and use the hill-climbing algorithm to find a local optimum. Input the number of iterations k = 1 and the flags i and j = 1.

[0104] S204c: Determine the current light intensity X i Value and light intensity X i+1 Value size, when X i+1 The value is less than X i The value, the local optimal solution is C i This is the point of local optimal light intensity;

[0105] S205c: The local optimal solution C i Send N j The flag bit j+1 is used to store the address of each local optimal solution. Updating the bird's nest position is equivalent to updating the local optimal solution flag bit i.

[0106] S206c: Determine if the current local optimum satisfies the transformation parameters. If it does, then C i If the global optimal solution cannot be found, the next random number C is searched again using the Levi's plane. i ;

[0107] S207c: Re-determine X i The neighborhood of the current marker is used to obtain the light intensity value X. i The local optimum data is searched again using the hill-climbing method. Simultaneously, the optimum is stored in parameter N using a flag j. It is then determined whether the transformation parameter is less than a random number between 0 and 1. If N is satisfied... j and N j+1 If the size relationship is determined, the current flag bit i is saved, and the address of the local optimal solution is replaced with the current point of maximum light intensity C. i If the condition cannot be met, the Levi aircraft will search for the next local optimum.

[0108] S208c: By iterating K times, the local optimal solution is continuously exchanged and updated, and finally the global optimal solution of the current axis is obtained, that is, the point C0 with the maximum light intensity.

[0109] Example 4:

[0110] The only difference between Example 4 and Example 2 is that in Example 4, the maximum light intensity value C0 on the X-axis after traversal is obtained by bubble sort. The specific operation process is shown in the attached figure. Figure 8 As shown, it includes the following steps:

[0111] S201b: Input the real-time acquired light intensity value array [Arr], and set the loop flag i to the maximum number of array elements;

[0112] S202b: Assign bit search flag j to 1;

[0113] S203b: Determine the size of the first and second values ​​in the array [Arr]. If the first value is smaller than the second value, swap the two values ​​and increment the bitwise search flag j+1. Continue this process until the size relationship between the j-th and j+1-th values ​​is determined, then end the loop and increment the loop flag i-1.

[0114] S204b: Reassign j to 1, perform the second sorting, and repeat steps S202b~S203b N times.

[0115] S205b: After the Nth iteration, i = 0. At this time, the highest digit in the array is the maximum value of the array after bubble sort. Let the Nth digit of the array [Arr] be the maximum value C0, and output it to the PID control module.

[0116] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A self-collimation packaging method for a fiber optic F-P cavity sensor self-collimation system. The fiber optic F-P cavity sensor self-collimation system includes an MCU and an execution unit. The execution unit includes three stepping motors, and the three stepping motors are respectively used to control the movement of the collimator in three directions of the X-axis, Y-axis, and Z-axis. The PID control module is embedded in the MCU, and the PID control module and the three stepping motors are controlled by PWM. The self-collimation system further includes a power supply, and the MCU and the three stepping motors are both connected to the power supply. The peripheral circuit of the MCU includes a reset circuit, a clock circuit, and a 3.3v power supply circuit. Its features are, The self-collimation packaging method includes the following steps. S1:预先测定准直器准直后的光强值P,存入MCU中,并设置为PID控制模块的初始参数; S1:预先 measure the light intensity value P after the collimator is collimated, store it in the MCU, and set it as the initial parameter of the PID control module; S2:实时采集在PWM控制下的X轴遍历光强值,得到遍历后X轴的最大光强值C0,和对应的PID的控制参数,并由MCU送入PID控制模块; S2: Real-time collect the light intensity values traversed along the X-axis under PWM control, obtain the maximum light intensity value C0 of the X-axis after traversal and the corresponding PID control parameters, and send them to the PID control module by the MCU; S3:由PID控制模块控制X轴对应的步进电机,使准直器由C0值回扫X轴得到最强光强处P1,完成X轴准光强最值点对准; S3: The PID control module controls the stepping motor corresponding to the X-axis, so that the collimator sweeps back along the X-axis from the C0 value to obtain the point P1 with the strongest light intensity, and completes the alignment of the maximum and minimum light intensity points of the X-axis collimation; 2. The self-collimation packaging method for a fiber optic FP cavity sensor self-collimation system according to claim 1, characterized in that, S4:实时采集在PWM控制下的Y轴遍历光强值,得到遍历后Y轴的最大光强值C1,和对应的PID的控制参数,并由MCU送入PID控制模块; S4: Real-time collect the light intensity values traversed along the Y-axis under PWM control, obtain the maximum light intensity value C1 of the Y-axis after traversal and the corresponding PID control parameters, and send them to the PID control module by the MCU; S5:由PID控制模块控制Y轴对应的步进电机,使准直器由C1值回扫Y轴得到最强光强处P2,完成Y轴准光强最值点对准; S203a: Assign x1 = x0 + h, assign y p = y0 + h*f(x0, y0), y c =y0+h*f(x1,y p The differential function y1 = (y) is obtained through iterative fitting. p +y c ) / 2; S5: The PID control module controls the stepping motor corresponding to the Y-axis, so that the collimator sweeps back along the Y-axis from the C1 value to obtain the point P2 with the strongest light intensity, and completes the alignment of the maximum and minimum light intensity points of the Y-axis collimation; S6:判断P2与P之间的大小关系,若P2≥P,则由Z轴对应的步进电机驱动准直器与敏感芯片进行封装;若P2<P,重复步骤S2-S5,更新位移阈值C和最大光强值C1,直至准直器移动到传感器封装支柱中心处即光强值最大处,自对准完成。 3. The self-collimation packaging method for a fiber optic FP cavity sensor self-collimation system according to claim 1, characterized in that, S6: Judge the size relationship between P2 and P. If P2≥P, the stepping motor corresponding to the Z-axis drives the collimator to package with the sensitive chip; if P2<P, repeat steps S2-S5, update the displacement threshold C and the maximum light intensity value C1 until the collimator moves to the center of the sensor packaging support column, that is, the place with the maximum light intensity value, and the self-alignment is completed. 步骤S2中由数值最值算法中的微分插值法得到遍历后X轴的最大光强值C0,具体操作包括以下步骤, In step S2, the maximum light intensity value C0 of the X-axis after traversal is obtained by the differential interpolation method in the numerical maximum and minimum value algorithm. The specific operations include the following steps. S201a:设定初始点位的光强计算初始位置x0,y0,迭代标志h,点数量N; S201a: Set the initial positions x0, y0 of the light intensity calculation at the initial point, the iteration flag h, and the number of points N; S202a:给定递增标志为n,最值点标志为k,并赋值n为1; S202a: Given the increment flag as n, the maximum and minimum point flag as k, and assign n as 1; S204a:将新得到的y1和x1的值作为初始x0和y0回带入步骤S203a中,重复N次步骤S203a,得到N次迭代线性拟合微分式; S204a: Substitute the newly obtained values of y1 and x1 as the initial x0 and y0 back into step S203a, and repeat step S203a N times to obtain N iterative linear fitting differential equations; S205a:最值标志位每经过一次迭代就会减1,可得到k=0,带入N次迭代拟合微分方程中获得最大光强值C0。 S205a: The maximum and minimum flag bit will be decremented by 1 every time an iteration is performed, and k = 0 can be obtained. Substitute it into the N iterative fitting differential equations to obtain the maximum light intensity value C0. 步骤S2中由数值最值算法中的冒泡排序法得到遍历后X轴的最大光强值C0,具体操作包括以下步骤, In step S2, the maximum light intensity value C0 of the X-axis after traversal is obtained by the bubble sort method in the numerical maximum and minimum value algorithm. The specific operations include the following steps. S201b:输入实时采集到的光强值数组[Arr],设置循环标志位i为数组数最大值; S201b: Input the light intensity value array [Arr] collected in real time, and set the loop flag bit i as the maximum value of the array number; S202b:赋值位寻标志j为1; S202b: Assign the bit search flag j as 1; S203b: Determine the size of the first and second values ​​in the array [Arr]. If the first value is smaller than the second value, swap the two values ​​and increment the bitwise search flag j+1. Continue this process until the size relationship between the j-th and j+1-th values ​​is determined, then end the loop and increment the loop flag i-1. S204b: Reassign j to 1, perform the second sorting, and repeat steps S202b~S203b N times. S205b: After the Nth iteration, i = 0. At this time, the highest digit in the array is the maximum value of the array after bubble sort. Let the Nth digit of the array [Arr] be the maximum value C0, and output it to the PID control module.

4. The self-collimation packaging method for a fiber optic FP cavity sensor self-collimation system according to claim 1, characterized in that, In step S2, the maximum light intensity value C0 on the X-axis after traversal is obtained using the hill-climbing method combined with the cuckoo search algorithm. The specific operation includes the following steps. S201c: First, initialize the population size N, i.e., the number of single-axis light intensity sampling points, the solution space dimension D, the iteration number flag K, the discovery probability pa, and the transformation parameter ps; S202c: Flight via Lévy, where the single-axis dimension is 1-dimensional random alternating long and short flight. The Lévy flight calculation formula is as follows. u follows N(0, σ) u The normal distribution v follows N(0, σ) v Normal distribution, where, σ v =1; S203c: Position light intensity X obtained randomly through Levi's flight. i Move to the neighborhood of Xi and find a local optimum using the hill-climbing algorithm. Input the number of iterations k = 1 and the flags i and j = 1. S204c: Determine the current light intensity X i Value and light intensity X i+1 Value size, when X i+1 The value is less than X i The value, the local optimal solution is C i This is the point of local optimum light intensity; S205c: The local optimal solution C i Send N j The flag bit j+1 is used to store the address of each local optimal solution. Updating the bird's nest position is equivalent to updating the local optimal solution flag bit i. S206c: Determine if the current local optimum satisfies the transformation parameters. If it does, then C i If the global optimal solution cannot be found, the next random number C is searched again using the Levi flight method. i ; S207c: Re-determine X i The neighborhood of the current marker is used to obtain the light intensity value X. i The local optimum data is searched again using the hill-climbing method. Simultaneously, the optimum is stored in parameter N using a flag j. It is then determined whether the transformation parameter is less than a random number between 0 and 1. If N is satisfied... j and N j+1 If the size relationship is determined, the current flag bit i is saved, and the address of the local optimal solution is replaced with the current point of maximum light intensity C. i If the condition cannot be met, then Levi's flight will restart to find the next local optimum. S208c: By iterating K times, the local optimal solution is continuously exchanged and updated, and finally the global optimal solution of the current axis is obtained, that is, the point C0 with the maximum light intensity.

5. A self-collimation packaging method for a fiber optic FP cavity sensor self-collimation system according to any one of claims 2-4, characterized in that: The control parameters of the PID mentioned in step S2 are incremental PID, and the output formula of incremental PID is u(t)=u(t-1)+Kp*[e(t)-e(t-1)]+Ki*e(t)+Kd[(e(t)-2*e(t-1)+e(t-2)); where Kp, Ki, and Kd are the proportional, integral, and derivative coefficients of the incremental PID control module, respectively.

6. The self-collimation packaging method for a fiber optic FP cavity sensor self-collimation system according to claim 5, characterized in that, The PID control parameters are tuned using the decay curve method, specifically... Includes the following steps, S2A: Set the integral time of the regulator to infinity and the derivative time to zero, i.e., Ti = ∞, Td = 0; S2B: The regulating system is put into operation in pure proportional mode. After the system stabilizes, the proportional degree is gradually reduced, and the changes in the regulating process are observed. S2C: Determine whether the change in the adjustment process has reached the specified ratio. If not, repeat step S2B. If the adjustment process has reached the specified ratio, obtain the δ value under the corresponding decay condition. s and decay operation period T S ; S2D: Based on δ s and T s The regulator setting parameters are calculated using empirical formulas. S2E: Gradually introduce values ​​slightly larger than the regulator tuning parameters obtained in step S2D into the system, observe the operation, and gradually adjust them to smaller values; S2F: Observe whether the curve meets the tuning requirements. If it does not, repeat step S2E until the PID parameters that meet the curve requirements are found and the tuning is completed.

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