Gaussian light spot real-time detection system and method based on line scanning

Abstract

The invention discloses a Gaussian light spot real-time detection system and method based on line scanning. The Gaussian light spot real-time detection system comprises an electric displacement table, a light source assembly, a semi-transparent and semi-reflecting mirror, a photoelectric conversion module, a data interface module and a signal processing module. Wherein a mask plate is mounted on the electric displacement table, and multi-slope lines are arranged on the mask plate; the light source assembly is used for providing Gaussian beams. The electric displacement table is configured to be used for driving the mask plate to move according to a preset path, so that the Gaussian light spots are irradiated on the multi-slope lines one by one, and corresponding Gaussian light spots are formed; the semi-transparent and semi-reflective mirror is used for reflecting reflected light generated by the Gaussian light spots on the multi-slope lines to the photoelectric conversion module; the photoelectric conversion module is used for receiving the reflected light signals and converting the reflected light signals into pulse signals; the data interface module is used for collecting pulse signals and transmitting the pulse signals to the signal processing module; the signal processing module is used for measuring the size and shape of the Gaussian light spot based on the pulse signal. The method can be used for accurately measuring the size of the Gaussian light spot.

Description

Technical Field

[0001] The present invention relates to the technical field of optical measurement and laser beam quality analysis. In particular, it relates to a real-time detection system and method for Gaussian spots based on line scanning. Background Art

[0002] The parameter measurement of Gaussian spots is one of the key technologies in the field of laser applications. Its size, shape, and intensity distribution directly affect the performance and processing quality of laser systems. Currently, common Gaussian spot measurement methods mainly include the knife-edge method, slit scanning method, CCD imaging method, and wavefront sensing method, etc.

[0003] The knife-edge method is one of the earliest applied spot measurement methods. Its technical principle is to use a knife-edge (usually a sharp metal edge) to sweep across the beam transversely in a plane perpendicular to the optical axis, while using a photodetector to record the change in the total optical power transmitted through the knife-edge. When the knife-edge moves from the outside of the beam towards the center, the blocked optical power gradually increases. The curve of the optical power versus the knife-edge position obtained thereby is called the knife-edge curve. The derivative of this curve represents the intensity distribution, and the spot diameter can be determined by the distance between the 10% to 90% power points. The main equipment of the traditional knife-edge method includes a precision displacement platform, a knife-edge holder, a photodetector, and a data acquisition system.

[0004] The slit scanning method is an improved version of the knife-edge method, using a slit with a width much smaller than the spot diameter instead of the knife-edge. The slit sweeps across the beam transversely in a plane perpendicular to the optical axis, and the detector records the change in the optical power transmitted through the slit with position. Different from the knife-edge method, the power-position curve obtained by the slit scanning method directly represents the intensity distribution in this direction, without the need for differential calculation of the data. A typical slit scanning device consists of a precision linear displacement platform, a slit with a width of 10 - 50 μm, a photodetector, and a signal processing system.

[0005] The CCD imaging method is the most widely used spot measurement method currently, using a CCD or CMOS sensor to directly image the beam intensity distribution. This method usually requires a light attenuation system to reduce the beam intensity to within the dynamic range of the sensor, and at the same time uses a lens system to magnify or reduce the beam to a size suitable for the sensor. A typical system includes a CCD / CMOS camera, an optical attenuator, an imaging lens group, and image processing software. The advantage of the CCD imaging method is that it can obtain a complete two-dimensional intensity distribution at one time, and the measurement is relatively intuitive.

[0006] Wavefront sensing method is an advanced beam parameter measurement technology developed in recent years. Representative methods include Shack-Hartmann wavefront sensor and coherent diffraction method. The Shack-Hartmann wavefront sensor uses a microlens array to decompose the incident wavefront into multiple sub-beams, and reconstructs the wavefront shape by measuring the focal position offset of each sub-beam, and then derives the beam parameters. A typical system consists of a microlens array (the diameter of the microlens is usually 100 - 500μm), a CCD / CMOS detector, and a wavefront reconstruction algorithm. The coherent diffraction method reconstructs the light field information using the diffraction pattern of the beam. The advantage of the wavefront sensing method is that it can simultaneously obtain the intensity and phase information of the beam, and is suitable for the characterization of complex light fields.

[0007] Although the knife-edge method has a simple principle and low cost, it has disadvantages such as slow measurement speed, difficulty in realizing real-time monitoring, and only being able to obtain information on a single-direction cross-section. Moreover, the knife-edge method is sensitive to environmental vibration and requires a high-precision mechanical displacement system, which increases the complexity of the system.

[0008] The slit scanning method improves the signal-to-noise ratio of the knife-edge method, but still faces the limitations of slow measurement speed and only being able to obtain single-direction information. To obtain full-direction information, it is necessary to rotate the slit or the beam, which greatly increases the measurement time and system complexity.

[0009] The CCD imaging method has the following disadvantages: 1. The spatial resolution of the CCD / CMOS sensor is limited by the pixel size (usually 3 - 10μm), making it difficult to accurately measure small-sized light spots; 2. The dynamic range of the sensor is limited (the typical value is 60 - 70dB), making it difficult to accurately characterize high-contrast beams; 3. The frame rate of the sensor is limited (usually 30 - 120fps), making it difficult to realize high-speed real-time monitoring; 4. The sensor is easily damaged by the thermal effect of the beam and requires a complex attenuation system, which may introduce additional beam distortion.

[0010] The wavefront sensing method also has many limitations: the system structure is complex, the cost is high, the requirements for the optical path layout are strict, and the beam must pass through the wavefront sensor, making it impossible to achieve true non-invasive measurement. In addition, the spatial resolution of the microlens array is limited, making it difficult to accurately characterize small-sized light spots or beams with complex structures. Summary of the Invention

[0011] In view of this, the first object of the present invention is to provide a real-time detection system for Gaussian light spots based on line scanning, which can be used to accurately measure the size of Gaussian light spots.

[0012] To solve the above technical problems, the technical solution of the present invention is: A real-time detection system for Gaussian light spots based on line scanning, including an electric displacement stage, a light source assembly, a semi-transparent and semi-reflective mirror, a photoelectric conversion module, a data interface module, and a signal processing module; wherein, An electric displacement stage, on which a reticle is mounted, and multi-slope lines are arranged on the reticle. The multi-slope lines are composed of multiple groups of lines with different slopes, and each line intersects at the same point; The light source assembly is used to provide a Gaussian beam; the electric displacement stage is configured to drive the reticle to move along a predetermined path, so that the Gaussian beam irradiates the multi-slope lines one by one and forms corresponding Gaussian spots; The semi-transmissive and semi-reflective mirror is located directly above the reticle and is used to reflect the reflected light generated by the Gaussian spot on the multi-slope lines to the photoelectric conversion module; The photoelectric conversion module is used to receive the reflected light signal and convert it into a pulse signal; The data interface module is used to collect the pulse signal and transmit it to the signal processing module; The signal processing module is used to measure the size and shape of the Gaussian spot based on the pulse signal;

[0013] Preferably, the multi-slope lines specifically include 0° lines, ±15° lines, ±30° lines, ±45° lines, ±60° lines, ±75° lines and ±85° lines.

[0014] Preferably, the photoelectric conversion module is composed of a PMT sensor.

[0015] Preferably, a signal preprocessing module is further provided between the photoelectric conversion module and the data acquisition module, and the signal preprocessing module is used to filter and amplify the pulse signal output by the PMT.

[0016] Preferably, the data acquisition module uses a multi-channel synchronous data acquisition card.

[0017] The second object of the present invention is to provide a real-time detection method for Gaussian spots based on line scanning. Based on the above detection system, the size of the Gaussian spot can be measured more accurately.

[0018] In order to solve the above technical problems, the technical solution of the present invention is: A real-time detection method for Gaussian spots based on line scanning, the method includes: S1. According to the pulse time width t and the scanning speed v of the Gaussian spot, calculate its scanning distance D: D = v * t; S2. Based on the angle θ and the line width w of the line, calculate the spot size S in the direction of the spot on the line: S = D * cosθ - w; S3. Judge whether it is a regular Gaussian spot according to the spot size S measured by the Gaussian spot on the lines with each slope; If so, calculate the waist diameter parameter w0 of the Gaussian spot according to the ratio of the optical power P1 under the current measurement conditions to the total optical power P0 of the light source: and continue to calculate the full width at half maximum FWHM1 of the Gaussian spot based on this: ; If not, first calculate the angle of the line connecting the centers of the main peak and the secondary peak of the pulse of the Gaussian spot, then find the pulse signal corresponding to the direction approximately perpendicular to this connection angle; judge the relative position relationship between the main peak and the secondary peak according to the rate of change of the rise and fall of the pulse gray value; calculate the specific distance value S1 from the center of the main peak to the edge according to the distance from the faster rising or falling side edge of the pulse signal to the highest point; calculate the waist diameter parameter w1 of the main peak according to the ratio of the optical power P2 of the main peak to the total optical power P0 under the current measurement conditions: ; and continue to calculate the full width at half maximum FWHM2 of the Gaussian spot based on this: FWHM2≈0.5887×w1; based on the principle of multi-peak Gaussian distribution superposition, combine the relative position relationship between the main peak and the secondary peak, the waist size of the main peak and the overall spot size, and fit the complete fitting spot through an iterative optimization algorithm.

[0019] Preferably, the calculation of the angle of the line connecting the centers of the main peak and the secondary peak of the pulse of the Gaussian spot includes: By comparing the pulse peak values generated by lines at different angles, identify the pulses corresponding to the two angles with the highest peaks; if there is a significant difference in the two peak values, perform weighted calculation according to the relative ratio of the peaks to obtain the angle of the line connecting the centers of the main peak and the secondary peak of the pulse of the Gaussian spot.

[0020] The technical effects of the present invention are mainly reflected in the following aspects: It can identify and characterize irregular Gaussian spots with various complex shapes in real time and effectively, breaking through the limitation that traditional spot measurement methods can only process beams with ideal Gaussian distributions, greatly expanding the application range of spot detection technology, and is particularly suitable for complex optical field analysis in high-precision optical systems and laser processing fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is a schematic structural diagram of a real-time detection system; Figure 2 is a schematic diagram of a scanned Gaussian spot; Figure 3 is a schematic diagram of multi-slope lines; Figure 4 is a schematic diagram of the process of the spot scanning lines; Figure 5 is a schematic diagram of the matlab simulation of the pmt signal output; Figure 6 is a schematic diagram of fitting the spot according to the output signal.

[0022] Reference numerals: 1, reticle; 2, multi-slope lines; 3, Gaussian spot; 4, reflected light; 5, PMT sensor; 6, host computer; 7, semi-transparent and semi-reflective mirror; 8, 0° lines; 9, 15° lines; 10, 30° lines; 11, 45° lines; 12, 60° lines; 13, 75° lines; 14, 85° lines; 15, -15° lines; 16, -30° lines; 17, -45° lines; 18, -60° lines; 19, -75° lines; 20, -85° lines; 21, spot scanning direction; 22, PMT output signal; 23, fitted spot. Detailed implementation manners

[0023] The following further details the specific implementation manners of the present invention in conjunction with the accompanying drawings, so that the technical solutions of the present invention are easier to understand and master.

[0024] Refer to Figure 1 , this embodiment provides a real-time detection system for Gaussian spot 3 based on line scanning, including an electric displacement stage (not shown), a light source assembly, a semi-transparent and semi-reflective mirror 7, a photoelectric conversion module, a data interface module, a signal preprocessing module, and a signal processing module.

[0025] The light source assembly is used to provide a Gaussian beam. Generally, the light source assembly is the light source of a lithography machine.

[0026] A reticle is installed on the electric displacement stage, and multi-slope lines 2 are arranged on the reticle. The multi-slope lines 2 are composed of multiple groups of lines with different slopes, and each line intersects at the same point; in this embodiment, the multi-slope lines 2 specifically include 0° lines 8, ±15° lines 9, ±30° lines 108, ±45° lines 11, ±60° lines 128, ±75° lines 13, and ±85° lines 14, as specifically shown in Figure 3 shown.

[0027] The Gaussian beam is projected onto the reticle to form a Gaussian spot 3.

[0028] The electric displacement stage is configured to drive the reticle to move and scan along a predetermined path, so that the Gaussian spot 3 irradiates the multi-slope lines 2 one by one. The semi-transparent and semi-reflective mirror 7 is located directly above the reticle. After the Gaussian spot 3 penetrates the semi-transparent and semi-reflective mirror 7 from top to bottom, reflected light 4 is generated on the multi-slope lines 2, and the reflected light 4 is reflected by the semi-transparent and semi-reflective mirror 7 to the photoelectric conversion module.

[0029] The photoelectric conversion module is composed of a PMT sensor 5, the housing is provided with an electromagnetic shielding layer, and an anti-environmental light interference filter is provided in front of the PMT sensor 5 to effectively eliminate external noise interference. The photoelectric conversion module is used to receive the reflected light 4 signal and convert it into a pulse signal.

[0030] When the Gaussian spot 3 scans along a specific direction (refer to the mark 21 in Figure 4 ), it will pass through the edges of lines with different slopes in sequence, causing the pulse signals output by the PMT sensor 5 to exhibit different time and gray-scale distribution characteristics. By analyzing these characteristics, the two-dimensional shape information of the Gaussian spot 3 can be deduced. Specifically, when the Gaussian spot 3 sweeps across the line edge, the rise or fall time of the pulse signal is directly related to the width of the Gaussian spot 3 and the slope of the line edge, so the spot size can be accurately calculated through a mathematical model. For specific details, please refer to the algorithm flow provided later.

[0031] The data interface module is used to collect pulse signals and transfer them to the signal processing module. It uses a multi-channel synchronous data acquisition card and selects an appropriate sampling frequency to ensure the capture of high-frequency detail information of the edge transition of the Gaussian spot 3.

[0032] The signal preprocessing module is located between the photoelectric conversion module and the data acquisition module and is used to filter and amplify the pulse signals output by the PMT sensor 5. This module includes an adjustable amplifier based on dynamic gain control, which can automatically adjust the gain according to the incident light intensity to ensure the best signal-to-noise ratio under different light intensity conditions.

[0033] The signal processing module includes a host computer 6. The host computer 6 uses processing tools such as MATLAB to analyze and process the pulse signals, and then measures the size and shape of the Gaussian spot 3. As Figure 5 shown in the PMT output signal 22 simulated by MATLAB. The Gaussian spot 3 used in the simulation is as Figure 2 shown.

[0034] After obtaining the pulse signals (time-domain parameters and gray scale), the following specific algorithm flow is used to accurately fit the size and shape of the Gaussian spot: First, adjust the light intensity of the light source component to the optimal state where the gray scale is just not saturated, so as to ensure the acquisition of signal information with the largest dynamic range. At this time, record the pulse time parameters generated by all line patterns at different angles, providing basic data for subsequent calculations.

[0035] For each line at a specific angle, calculate the size based on the pulse time, scanning speed, and geometric characteristics of the line pattern: 1. Measure the time width t of the pulse; 2. According to the known scanning speed v, calculate the scanning distance: D = v * t; 3. Considering the line pattern angle θ and line width w, calculate the size of the actual spot in this direction: S = D * cosθ - w.

[0036] First, determine whether it is a regular Gaussian spot. The specific judgment criteria are as follows: Calculate the spot size measured when the Gaussian spot sweeps across the lines at various angles (0°, ±15°, ±30°, ±45°, ±60°, ±75°, ±85°). If the deviation of the spot size measured in each direction is within the preset threshold range (usually ±5%), it is considered a regular Gaussian spot.

[0037] For the case confirmed as a regular Gaussian spot, perform the following calculations: 1. Record the ratio of the optical power P1 under the current measurement conditions to the total optical power P0 of the light source; 2. According to the energy distribution theory of the Gaussian spot, the relationship between the optical power ratio and the spot measurement size S (waist diameter w0) satisfies: ; 3. Solve the waist diameter parameter w0 through the above relationship; 4. Calculate the full width at half maximum FWHM1 of the Gaussian spot .

[0038] When the deviation of the spot size measured in each direction is not within the preset threshold range, it is determined as an irregular Gaussian spot, and the following steps are used for analysis: For the detection of irregular Gaussian spots, first determine the angle of the line connecting the centers of the main peak and the secondary peak of the pulse signal. By comparing the pulse peak magnitudes of the pulse signals generated by the Gaussian spot on the lines at different angles, identify the pulses corresponding to the two angles with the highest peaks. For example, if the pulse peaks in the 15° and 30° directions are the largest and their values are close, it is determined that the angle of the line connecting the centers of the main peak and the secondary peak is approximately 27°. If there is a significant difference in the magnitudes of the two peaks, a weighted calculation will be performed based on the relative ratio of the peaks to obtain a more accurate connection angle. This method can adapt to irregular spots of different shapes and ensure the accuracy of angle judgment.

[0039] After determining the angle of the line connecting the centers of the main peak and the secondary peak, further search for the pulse signal corresponding to the direction approximately perpendicular to this line. For example, when the angle of the line connecting the main peak and the secondary peak is 27°, select the pulse in the approximately -60° direction for analysis. By comparing the rate of change of the gray value increase and decrease of the pulse signal in this direction, the relative position relationship between the main peak and the secondary peak can be judged. If the rate of change of the rising edge is greater than that of the falling edge, it indicates that the main peak is located in the front section of the scan in this direction; otherwise, the main peak is located in the rear section of the scan in this direction. In addition, the specific distance value S1 from the center of the main peak to the edge can also be calculated based on the distance from the edge of the side with a faster rising or falling pulse signal to the highest point.

[0040] Based on the above measurement results, the waist w1 and full width at half maximum FWHM of the main peak are calculated. Specifically, the ratio of the optical power P2 of the main peak to the total optical power P0 under the current measurement conditions is recorded, and according to the formula w1: The waist diameter parameter w1 of the main peak is calculated. The full width at half maximum FWHM2 is obtained by the formula FWHM2≈0.5887×w1. These parameters lay the foundation for the accurate fitting of the subsequent spot shape.

[0041] Finally, a complete irregular Gaussian spot model is established. This model is based on the principle of superposition of multi-peak Gaussian distributions, combines the relative position relationship between the main peak and the secondary peak, the waist size of the main peak and the overall spot size, and fits the complete two-dimensional light intensity distribution through an iterative optimization algorithm to generate a fitted spot (22) as shown in Figure 6 Figure. Such a fitting result not only accurately reflects the actual shape of the Gaussian spot, but also can quantitatively describe the key parameters of the Gaussian spot, providing a reliable basis for the precise adjustment and performance evaluation of the optical system.

[0042] Of course, the above are only typical examples of the present invention. In addition, the present invention may have many other specific implementation manners. Any technical solutions formed by equivalent replacement or equivalent transformation fall within the scope of protection required by the present invention.

Claims

1. A Gaussian spot real-time detection system based on line scanning, characterized in that: It comprises an electric displacement stage, a light source assembly, a semi-transparent and semi-reflective mirror (7), a photoelectric conversion module, a data interface module and a signal processing module; wherein: An electric displacement stage, on which a mask plate is mounted, on which multi-slope lines (2) are arranged, the multi-slope lines (2) being composed of a plurality of groups of lines with different slopes, and each line intersects at the same point; The light source assembly is used to provide a Gaussian light beam; the electric translation stage is configured to drive the mask to move along a predetermined path so that the Gaussian light beam is irradiated onto the multi-slope lines (2) one by one and forms corresponding Gaussian light spots (3); The semi-transparent and semi-reflective mirror (7) is located directly above the mask plate and is used to reflect the reflected light (4) generated by the Gaussian light spot on the multi-slope line (2) to the photoelectric conversion module; The photoelectric conversion module is used to receive the reflected light (4) signal and convert it into a pulse signal; The data interface module is used to collect the pulse signal and transmit it to the signal processing module; The signal processing module is used to measure the size and shape of the Gaussian spot based on the pulse signal.

2. A Gaussian spot real-time detection system based on line scanning as claimed in claim 1, characterized in that: The multi-slope lines (2) specifically include a 0° line (8), a ±15° line (9), a ±30° line (10)(8), a ±45° line (11), a ±60° line (12)(8), a ±75° line (13) and a ±85° line (14).

3. The Gaussian spot real-time detection system based on line scanning as claimed in claim 1, characterized in that: The photoelectric conversion module is composed of a PMT sensor (5).

4. The Gaussian spot real-time detection system based on line scanning as claimed in claim 1, characterized in that: A signal preprocessing module is also provided between the photoelectric conversion module and the data acquisition module, and the signal preprocessing module is used to filter and amplify the pulse signal output by the PMT sensor (5).

5. The Gaussian spot real-time detection system based on line scanning as claimed in claim 1, characterized in that: The data acquisition module adopts a multi-channel synchronous data acquisition card.

6. A Gaussian spot real-time detection method based on line scanning, implemented based on the detection system of claim 1, characterized in that: The method includes: S1. Calculate the scanning distance D according to the pulse time width t and scanning speed v of the Gaussian spot: D=v*t; S2. Based on the angle θ and line width w of the line, calculate the spot size S in the direction of the line: S=D*cosθ-w; S3, judging whether it is a regular Gaussian spot according to the spot size S measured on the lines of each slope of the Gaussian spot; If so, the beam waist diameter parameter w0 of the Gaussian spot is calculated based on the total ratio of the optical power P1 under the current measurement conditions to the total optical power P0 of the light source: , and then continue to calculate the half-height full width FWHM1 of the Gaussian spot: ; If not, first calculate the angle of the main peak and the secondary peak center of the Gaussian spot pulse, and then find the pulse signal corresponding to the direction approximately perpendicular to the angle of the line; judge the relative position relationship between the main peak and the secondary peak according to the change in the rate of increase and decrease of the pulse gray value; calculate the specific distance value S1 from the center of the main peak to the edge according to the distance from the edge of the side with a faster rise or decrease to the highest point of the pulse signal; calculate the beam waist diameter parameter w1 of the main peak according to the ratio of the main peak optical power P2 to the total optical power P0 under the current measurement conditions: ; and continue to calculate the half-height full width FWHM2 of the Gaussian spot: FWHM2≈0.5887×w1; based on the principle of multi-peak Gaussian distribution superposition, combined with the relative position relationship between the main peak and the secondary peak, the waist size of the main peak and the overall spot size, and through the iterative optimization algorithm, the complete fitting spot is fitted.

7. A Gaussian spot real-time detection method based on line scanning as claimed in claim 6, characterized in that: The calculation of the angle of the center line between the main peak and the secondary peak of the pulse of the Gaussian spot includes: By comparing the pulse peak sizes generated by lines at different angles, the pulses corresponding to the two angles with the highest peak values ​​are identified; if there is a significant difference in the sizes of the two peaks, a weighted calculation will be performed based on the relative proportion of the peaks to obtain the angle of the line connecting the centers of the main peak and secondary peak of the Gaussian spot pulse.

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