Method and system for measuring effective depth of notch processed by femtosecond laser in rocket rupture membrane

Abstract

The present invention provides a method and system for measuring the effective depth of a rocket ruptured diaphragm femtosecond laser processing notch, which belongs to the field of length, thickness or similar linear dimension measurement technology, including the measurement of the diaphragm notch morphology, data processing and calculation of the effective depth. The present invention performs confocal microscopic measurement of the tiny trapezoidal notches of the ruptured diaphragm, performs data processing and statistical analysis based on the measured point cloud data, determines the height difference between the notch top and the notch bottom, and thus calculates the effective depth of the notch; it solves the problem of accurately measuring the effective notch depth of the ruptured diaphragm, can be used for accurate prediction of diaphragm performance, and has important engineering value.

Description

Technical Field

[0001] The present invention relates to the field of measurement technology of length, thickness or similar linear dimensions, and specifically, to a method and system for measuring the effective depth of notches of a ruptured diaphragm of a rocket by femtosecond laser processing, and more specifically, to a power valve of a booster delivery system of a launch vehicle, and specifically, to a method for measuring the effective depth of notches of a ruptured diaphragm of a rocket valve. Background Art

[0002] The rupture diaphragm is one of the key core components of the booster delivery system of the launch vehicle. It is mainly used in the booster pipeline to isolate the tank from the booster cylinder before the gas in the cylinder is pressurized. After the rocket engine is ignited, the pressure reducing valve opens, and the upstream booster gas enters the pipeline. The diaphragm is subjected to the pressure gradually rising to the target pressure until it ruptures, and the booster pipeline is connected. The accurate rupture of the diaphragm at the target pressure directly affects the normal operation of the rocket booster delivery system. The traditional rupture diaphragm is processed by stamping. The mechanical properties of the material at the notch position change due to strain strengthening, which has a strong uncertainty. Therefore, the diaphragm rupture pressure difference can only be measured by destructive testing, and there is a lack of accurate prediction methods for its performance. For the rupture diaphragm processed by femtosecond laser, due to the "cold processing" characteristics of the femtosecond laser, the mechanical properties parameters of the diaphragm material will not change due to processing. At this time, the effective depth of the diaphragm notch is the only factor affecting the diaphragm rupture pressure. Accurately measuring the effective notch depth of the rupture diaphragm can be used for accurate prediction of diaphragm performance, which has important engineering value.

[0003] Femtosecond laser processing is the use of extremely short pulse lasers to perform subtractive processing on materials. Due to its pulse properties, the material is removed piece by piece during the processing process. In addition, considering the energy distribution of the laser spot and the speed of the spot movement, the bottom of the trapezoidal notch of the diaphragm processed by the femtosecond laser is not an ideal plane, and there are many tiny pits, protrusions and other structures. At present, the measurement of notch depth mainly adopts contact measurement (such as patent document CN108195698A) and non-contact measurement (such as patent document CN116608774B). Limited by the size of the measuring head and the measurement method, the contact measurement can only obtain the depth of a limited position, the measurement is random, and the bottom morphology of the notch cannot be fully measured. In addition, analysis shows that the maximum depth of the notch cannot accurately predict the rupture pressure of the diaphragm, that is, the maximum depth of the notch cannot replace the effective depth. Non-contact measurement generally uses a confocal (coaxial) laser (displacement) sensor (such as patent: CN116608774B) to simultaneously measure the upper and lower surfaces of the diaphragm, and the laser spot diameter is generally about 30um. For the tiny trapezoidal cross-section notches on rocket diaphragms, the measurement is distorted due to the large spot diameter of the laser sensor. The cross-sectional shape measurement result is usually a V-shape with a circular bottom. The error when using the notch measurement depth to predict the diaphragm performance is large and cannot meet aerospace requirements. The range of a laser sensor with a small spot diameter is generally below 300um, which cannot meet the measurement requirements of rocket diaphragm notches (depth 500-900um). Therefore, a more effective method for measuring the effective depth of diaphragm notches is needed. Summary of the invention

[0004] In view of the defects in the prior art, the purpose of the present invention is to provide a method and system for measuring the effective depth of the incision processed by femtosecond laser on a rocket ruptured diaphragm.

[0005] According to the present invention, a method for measuring the effective depth of a rocket ruptured diaphragm femtosecond laser processing notch comprises:

[0006] Step S1: using a laser confocal microscope to measure the scratches on the ruptured film to obtain three-dimensional point cloud data of the scratches;

[0007] Step S2: performing plane fitting on the three-dimensional point cloud data of the notch to obtain a reference plane;

[0008] Step S3: using the reference plane to perform plane calibration on the three-dimensional point cloud data of the notch to obtain the three-dimensional point cloud data after plane calibration;

[0009] Step S4: performing statistical analysis on the height coordinate information of the calibrated three-dimensional point cloud data to obtain a bimodal distribution histogram of the data;

[0010] Step S5: using a statistical averaging method to calculate the average heights of the two wave peaks;

[0011] Step S6: Calculate the difference between the average values ​​of the double peak heights to obtain the effective depth of the trapezoidal notch of the membrane.

[0012] Preferably, in the process of measuring the score of the ruptured membrane using a laser confocal microscope, the measuring position is within a preset range of the intersection of the C-shaped score of the membrane and the symmetry axis of the membrane.

[0013] Preferably, the step S2 adopts: according to the x, y, z coordinates of the notch three-dimensional point cloud data, a least square method is used to perform plane fitting processing on the notch three-dimensional point cloud data.

[0014] Preferably, step S3 adopts: according to the x and y coordinates of the notched three-dimensional point cloud, using the reference plane equation, calculating the z coordinate of the (x, y) point on the reference plane, and using the z coordinate of the notched three-dimensional point cloud minus the z coordinate of the corresponding position on the reference plane to obtain the three-dimensional point cloud data after plane calibration.

[0015] Preferably, the step S4 comprises: determining the number and range of histogram columns according to the maximum value, minimum value and single column interval width of the point cloud z coordinate;

[0016] No. The interval corresponding to the root column is:

[0017]

[0018] in, Indicates the column interval width; Indicates taking the minimum value of the z coordinates of all point clouds;

[0019] Count the z coordinates that fall in each interval The number of point clouds in each interval is calculated, the average z coordinate of the point cloud in each interval is calculated, and a histogram is drawn;

[0020] The average z-coordinate in each interval is:

[0021]

[0022] in, represents the average z-coordinate in each interval; Indicates taking the average z coordinate of all point cloud data in the interval; Representation interval z coordinate of the inner point cloud; Representation interval ;

[0023] The data whose z coordinate in the histogram is less than the average depth of the notch is regarded as a smaller part of the data, and the distribution of the smaller part of the data is arranged in descending order to obtain a permutation list of the point cloud data of each interval from high to low; based on the current permutation list, the first n elements in the list are obtained, L1, L2, ..., Ln; based on L1, L2, ..., Ln, the bottom peak of the notch is constructed;

[0024] The data in the histogram whose z coordinate is greater than the average depth of the notch is regarded as the larger part of the data, and the distribution of the larger part of the data is arranged in descending order to obtain a list of point cloud data in each interval from high to low; based on the current arrangement list, the first n elements H1, H2, ..., Hn in the list are obtained; based on H1, H2, ..., Hn, the peak of the notch top is constructed.

[0025] Preferably, step S5 comprises:

[0026] After obtaining the average height of all point clouds in L1, use the average height as the effective height of the bottom plane of the notch; when the difference between the number of point clouds in L1 and L2 is less than the preset value, calculate the average height of all point cloud data in L1 and L2, and use the average height as the effective height of the bottom plane of the notch; when the difference between the number of point clouds in L1 and L2 is less than the preset value, and the difference between the number of point clouds in L2 and L3 is less than the preset value, calculate the average height of all point cloud data in L1, L2 and L3, and use the average height as the effective height of the bottom plane of the notch; and so on to Ln; where, ;

[0027] After obtaining the average height of all point clouds in H1, use this average as the effective height of the top plane of the notch; when the difference in the number of point clouds in H1 and H2 is less than the preset value, calculate the average height of all point cloud data in H1 and H2, and use this average as the effective height of the top plane of the notch. When the difference in the number of point clouds in H1 and H2 is less than the preset value, and the difference in the number of point clouds in H2 and H3 is less than the preset value, calculate the average height of all point cloud data in H1, H2 and H3, and use this average as the effective height of the top plane of the notch.

[0028] According to the present invention, a rocket rupture membrane femtosecond laser processing notch effective depth measurement system is provided, comprising:

[0029] Module M1: Use laser confocal microscopy to measure the scratches on the ruptured membrane to obtain the three-dimensional point cloud data of the scratches;

[0030] Module M2: plane fitting is performed on the three-dimensional point cloud data of the notch to obtain the reference plane;

[0031] Module M3: Use the reference plane to perform plane calibration on the three-dimensional point cloud data of the notch to obtain the three-dimensional point cloud data after plane calibration;

[0032] Module M4: Statistically analyze the height coordinate information of the calibrated 3D point cloud data to obtain a bimodal distribution histogram of the data;

[0033] Module M5: Calculate the average height of the two wave peaks using the statistical averaging method;

[0034] Module M6: Calculate the difference between the average values ​​of the double peak heights to obtain the effective depth of the trapezoidal notch of the diaphragm.

[0035] Preferably, in the process of measuring the score of the ruptured membrane using a laser confocal microscope, the measuring position is within a preset range of the intersection of the C-shaped score of the membrane and the symmetry axis of the membrane;

[0036] The module M2 adopts: according to the x, y, z coordinates of the notch three-dimensional point cloud data, the least square method is used to perform plane fitting processing on the notch three-dimensional point cloud data.

[0037] Preferably, the module M3 adopts: according to the x and y coordinates of the notched three-dimensional point cloud, using the reference plane equation, calculating the z coordinate of the (x, y) point on the reference plane, using the z coordinate of the notched three-dimensional point cloud minus the z coordinate of the corresponding position on the reference plane, to obtain the three-dimensional point cloud data after plane calibration;

[0038] The module M4 includes: determining the number and range of histogram columns according to the maximum and minimum values ​​of the point cloud z coordinates and the width of a single column interval;

[0039] No. The interval corresponding to the root column is:

[0040]

[0041] in, Indicates the column interval width; Indicates taking the minimum value of the z coordinates of all point clouds;

[0042] Count the z coordinates that fall in each interval The number of point clouds in each interval is calculated, the average z coordinate of the point cloud in each interval is calculated, and a histogram is drawn;

[0043] The average z-coordinate in each interval is:

[0044]

[0045] in, represents the average z-coordinate in each interval; Indicates taking the average z coordinate of all point cloud data in the interval; Representation interval z coordinate of the inner point cloud; Representation interval ;

[0046] The data whose z coordinate in the histogram is less than the average depth of the notch is regarded as a smaller part of the data, and the distribution of the smaller part of the data is arranged in descending order to obtain a permutation list of the point cloud data of each interval from high to low; based on the current permutation list, the first n elements in the list are obtained, L1, L2, ..., Ln; based on L1, L2, ..., Ln, the bottom peak of the notch is constructed;

[0047] The data in the histogram whose z coordinate is greater than the average depth of the notch is regarded as the larger part of the data, and the distribution of the larger part of the data is arranged in descending order to obtain a list of point cloud data in each interval from high to low; based on the current arrangement list, the first n elements H1, H2, ..., Hn in the list are obtained; based on H1, H2, ..., Hn, the peak of the notch top is constructed.

[0048] Preferably, the module M5 comprises:

[0049] After obtaining the average height of all point clouds in L1, use the average height as the effective height of the bottom plane of the notch; when the difference between the number of point clouds in L1 and L2 is less than the preset value, calculate the average height of all point cloud data in L1 and L2, and use the average height as the effective height of the bottom plane of the notch; when the difference between the number of point clouds in L1 and L2 is less than the preset value, and the difference between the number of point clouds in L2 and L3 is less than the preset value, calculate the average height of all point cloud data in L1, L2 and L3, and use the average height as the effective height of the bottom plane of the notch; and so on to Ln; where, ;

[0050] After obtaining the average height of all point clouds in H1, use this average as the effective height of the top plane of the notch; when the difference in the number of point clouds in H1 and H2 is less than the preset value, calculate the average height of all point cloud data in H1 and H2, and use this average as the effective height of the top plane of the notch. When the difference in the number of point clouds in H1 and H2 is less than the preset value, and the difference in the number of point clouds in H2 and H3 is less than the preset value, calculate the average height of all point cloud data in H1, H2 and H3, and use this average as the effective height of the top plane of the notch.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] 1. The present invention obtains millions of large-scale measurement point cloud data including the size of the diaphragm scratches and the surface morphology characteristics by high-precision confocal microscopy measurement of the key positions of the rocket ruptured diaphragm. By processing and analyzing the point cloud data, the effective depth characteristics of the scratches are extracted from the large-scale point cloud, realizing the accurate prediction of the diaphragm performance based on the effective depth of the scratches;

[0053] 2. The diaphragm notch depth determination method proposed in the present invention can accurately measure the diaphragm notch depth, solving the problem that the traditional measurement method cannot determine the accurate depth of the diaphragm, and the performance of the diaphragm can be accurately calculated based on the measurement results;

[0054] 3. The present invention uses a femtosecond laser to process the diaphragm notch. There is no processing internal stress and heat-affected zone at the notch position, and the mechanical properties of the substrate are not affected, so that the working performance of the diaphragm depends only on the material's own properties and the remaining thickness of the diaphragm. Through the selection of raw materials and the combination of reasonable processing parameters, notches of a specific depth can be processed, thereby achieving the rupture of the diaphragm near the set pressure value;

[0055] 4. The 1 mm aluminum alloy diaphragm processed by the method provided by the present invention can achieve a rupture pressure deviation of no more than ±0.01 MPa. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0057] Figure 1 This is the schematic diagram of femtosecond laser processing of diaphragm.

[0058] Figure 2 This is the overall top view of the diaphragm.

[0059] Figure 3 It is a schematic diagram of the partial cross-sectional structure of a trapezoidal cross-section notched rupture diaphragm.

[0060] Figure 4 This is a cross-sectional view of the diaphragm notch structure.

[0061] Figure 5 Schematic diagram of the statistical results of the confocal measurement point cloud data of the notch.

[0062] Figure 6 Statistical histogram of the point cloud data at the bottom of the notch.

[0063] Figure 7 Statistical histogram of the notch top point cloud data.

[0064] Figure 8 This is a graph showing the relationship between the effective notch depth of the diaphragm and the diaphragm rupture pressure difference.

[0065] Among them, 1-femtosecond laser beam; 2-X scanning galvanometer; 3-Y scanning galvanometer; 4-field mirror; 5-diaphragm; 6-notch; 7-negative pressure adsorption device; 8-rotating workbench; 9-measuring position; 10-ruptured diaphragm; 11-trapezoidal notch side wall; 12-notch bottom; 13-notch top; 14-notch bottom coordinate information; 15-notch top coordinate information. DETAILED DESCRIPTION

[0066] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0067] Example 1

[0068] According to the invention, a method for precisely machining a rocket rupture diaphragm at a constant pressure is provided, such as Figure 1 As shown, including:

[0069] Steps for measuring the overall thickness of the diaphragm: Use precision measuring instruments such as contact measuring instruments and lever micrometers to measure the original thickness of the diaphragm.

[0070] Clamping and positioning steps: Place the circular diaphragm raw material to be processed on a special negative pressure adsorption clamping fixture, use the laser axis bypass camera to identify the edge of the diaphragm and determine the center of the circle. Move the optical axis to make it concentric with the center of the diaphragm.

[0071] Laser processing steps: After the film is clamped and positioned, adjust the focus of the laser spot and focus on the film surface. Set the laser scanning path, laser power, number of scanning layers, feed amount per layer, angular velocity of the worktable and other parameters, and use femtosecond laser to complete the film scoring process.

[0072] Membrane scratch depth measurement steps: Use a confocal microscope to measure the membrane scratch and calculate the depth of the membrane scratch.

[0073] Diaphragm screening steps: Calculate the remaining thickness of the diaphragm based on the original thickness and the depth of the notch, remove diaphragms with surface scratches and excess remaining thickness, and retain diaphragms with remaining thickness within the required range.

[0074] In this embodiment, the femtosecond laser beam 1 reaches the center of the field lens 4 after passing through the X-scanning galvanometer 2 and the Y-scanning galvanometer 3, and reaches the surface of the diaphragm 5 to be processed after being focused by the field lens 4. The laser spot is focused on the upper surface of the diaphragm 5. During the processing, the X-scanning galvanometer 2 and the Y-scanning galvanometer 3 are controlled to realize a small reciprocating swing of the spot in the radial direction of the diaphragm to process a groove of a specific width. At the same time, the rotary table 8 is used to rotate to realize the circular motion of the diaphragm 5 relative to the laser spot. Through the effective cooperation of the X-scanning galvanometer 2, the Y-scanning galvanometer 3 and the rotary table 8, the processing of the complete C-shaped groove 6 is realized. During the processing, the laser beam always moves in the central area of ​​the field lens 4, the spatial distortion of the spot is small, and the processing shape control ability is strong. At the same time, the negative pressure adsorption device 7 is used to firmly adsorb the diaphragm 5 on the surface of the negative pressure adsorption device 7, which increases the flatness of the diaphragm 5, eliminates the deformation of traditional mechanical clamping, and further improves the processing accuracy.

[0075] The specific implementation is as follows:

[0076] The overall thickness measurement step of the diaphragm is as follows: the original thickness of the diaphragm is measured using a contact measuring instrument, a lever micrometer or other precision measuring instrument. The measuring positions are four positions evenly distributed on the circumference of the diaphragm notch, and the original thickness of the diaphragm is determined based on the average value of the four positions, and the thickness should meet 1.0±0.02mm.

[0077] The clamping and positioning steps are as follows: Place the circular diaphragm raw material to be processed on a special negative pressure adsorption clamping tool, use a laser axis bypass camera to identify the edge of the diaphragm, and determine the center of the circle. Move the optical axis so that it is concentric with the center of the diaphragm. The clamping device includes a rotating worktable at the bottom and a negative pressure adsorption device at the top, which are concentrically arranged and relatively fixed. There are bosses around the negative pressure adsorption device for horizontal positioning of the circular diaphragm. Place the diaphragm on the negative pressure adsorption device and identify the center of the circle, turn on the vacuum pump, and maintain the gauge pressure at -0.1MPa. Use negative pressure to adsorb and fix the diaphragm. Use a bypass camera to identify the outer circle of the negative pressure adsorption device and calculate the center of the circle, and move the laser spindle so that it is concentric with the diaphragm.

[0078] The laser processing steps are as follows: After the diaphragm is clamped and positioned, adjust the focus of the femtosecond laser spot and focus on the surface of the diaphragm. Set the pattern of the notch to be processed according to the notch design drawing, select a laser spot with a diameter of 30um, set the repetition frequency to 200kHz, set the laser power to 3.0-3.5W, and use a galvanometer to realize the radial swing scanning of the spot along the diaphragm to realize the notch width processing, and set the spot scanning speed to 270-400mm / s. Use the workbench rotation to realize the processing in the circumferential direction of the notch, and the workbench rotation speed is 200-280° / s. Set the number of scanning layers to 51-61 layers according to the original thickness of the diaphragm, and set the feed amount per layer to 13-15um. The spot scanning is coordinated with the workbench rotation to realize the complete C-shaped notch processing until the given number of processing layers is processed to complete the final processing of the diaphragm.

[0079] The diaphragm screening step is to check whether the diaphragm surface is scratched or not. If so, it is considered as an unqualified diaphragm and is discarded. Then, the original thickness of the diaphragm is measured minus the depth of the scratch to obtain the remaining thickness d of the diaphragm, such as Figure 4 As shown, the membranes with a residual thickness d between 196um and 214um are considered qualified, can be accurately ruptured, and have a small dispersion, and the rest are discarded.

[0080] Example 2

[0081] According to the present invention, a method for measuring the effective depth of a rocket ruptured diaphragm processed by femtosecond laser includes: Figure 2 As shown, the ruptured membrane involved has a C-shaped notch as a whole, and the cross-sectional shape of the notch is a trapezoid, such as Figure 3 and Figure 4 The diaphragm notch was measured using a Zeiss LSM900 laser confocal microscope to obtain the three-dimensional point cloud data of the notch. The measurement position 9 is near the intersection of the C-shaped notch of the diaphragm and the symmetry axis of the diaphragm, as shown in FIG. Figure 2 As shown. The reference plane of the point cloud data is obtained by plane fitting, and the reference plane is used to calibrate the point cloud data. The height coordinate information (the direction of the notch depth) of the calibrated point cloud data is statistically analyzed to obtain the data histogram, as shown in Figure 5 As shown, Figure 5 The horizontal coordinate of the histogram distribution is the height coordinate information of the point cloud data, and the vertical coordinate is the number of point clouds within this height range. The interval width of a single column of the histogram is 1-10um. The height averages of the two peak positions are calculated using the statistical average method; that is, according to the double peak positions of the histogram distribution, the top coordinate information 15 of the notch and the bottom coordinate information 14 of the notch are determined, such as Figure 6 and Figure 7 In this embodiment, for the histogram with lower values, the maximum value algorithm is used to find the column with the largest number of point clouds, which is recorded as L1, the second largest as L2, and so on to L5. The relevant processing algorithm is as follows:

[0082] 1) First, determine the number and range of histogram columns based on the maximum and minimum z-coordinate values ​​of the point cloud and the width of a single column. i The interval corresponding to the root column is as follows, which is a left-closed and right-open interval, where bin_width is the column interval width.

[0083] ;

[0084] in, Indicates the column interval width; Indicates taking the minimum value of the z coordinates of all point clouds.

[0085] 2) Count the z coordinates that fall in each interval S i The number of point clouds in each interval is calculated, the average z coordinate of the point cloud in each interval is calculated, and a histogram is drawn;

[0086] The average z-coordinate in each interval

[0087] ;

[0088] in, represents the average z-coordinate in each interval; Indicates taking the average z coordinate of all point cloud data in the interval; Representation interval z coordinate of the inner point cloud; Representation interval .

[0089] 3) Get the column with the most point clouds

[0090] According to the average depth of the scratch, such as about 300um, the histogram is divided into two parts. The z coordinate of the smaller part is less than -300um, and the z coordinate of the larger part is not less than -300um. The distribution of the smaller part is sorted in descending order to obtain a list R of the number of point clouds in each interval from high to low. L ;

[0091] Then L1 is R L The first element in the list, L2 is R L The second element in the list, and so on:

[0092] .

[0093] The average height of the point cloud in L1 is:

[0094] .

[0095] After obtaining the average height of all point clouds in L1, use this average as the effective height of the bottom 12 plane of the notch. When the difference in the number of point clouds in L1 and L2 is less than 3%, calculate the average height of all point cloud data in L1 and L2, and use this average as the effective height of the bottom plane of the notch. When the difference in the number of point clouds in L1 and L2 is less than 3%, and the difference in the number of point clouds in L2 and L3 is less than 3%, calculate the average height of all point cloud data in L1, L2 and L3, and use this average as the effective height of the bottom plane of the notch. And so on to L5. For the histogram with higher values, use the maximum value algorithm to find the column with the largest number of point clouds, record it as H1, the second largest as H2, and so on to H3. The specific processing method is the same as above, calculate the average height of all point clouds in H1, and use this average as the effective height of the top 13 plane of the notch. When the difference in the number of point clouds in H1 and H2 is less than 3%, calculate the average height of all point cloud data in H1 and H2, and use this average as the effective height of the top plane of the notch. When the difference between the number of point clouds in H1 and H2 is less than 3%, and the difference between the number of point clouds in H2 and H3 is less than 3%, the average height of all point cloud data in H1, H2 and H3 is calculated, and the average height is used as the effective height of the top plane of the notch. Finally, the effective height of the bottom plane is subtracted from the effective height of the top plane to obtain the effective depth h of the trapezoidal notch. Figure 8 The relationship between the effective depth of 11 diaphragms and the rupture pressure difference is given, and the correlation coefficient (absolute value) reaches 0.9991, which shows that the notch effective depth measurement method proposed in the present invention is reasonable and can reflect the change of the diaphragm rupture pressure difference.

[0096] The present invention also provides a system for measuring the effective depth of a rocket ruptured diaphragm femtosecond laser processing scratch. The system can be implemented by executing the process steps of the method for measuring the effective depth of a rocket ruptured diaphragm femtosecond laser processing scratch. That is, those skilled in the art can understand the method for measuring the effective depth of a rocket ruptured diaphragm femtosecond laser processing scratch as a preferred implementation of the system for measuring the effective depth of a rocket ruptured diaphragm femtosecond laser processing scratch.

[0097] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0098] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A method for measuring the effective depth of a rocket ruptured diaphragm femtosecond laser processing notch, characterized in that: include: Step S1: using a laser confocal microscope to measure the scratches on the ruptured film to obtain three-dimensional point cloud data of the scratches; Step S2: performing plane fitting on the three-dimensional point cloud data of the notch to obtain a reference plane; Step S3: using the reference plane to perform plane calibration on the three-dimensional point cloud data of the notch to obtain the three-dimensional point cloud data after plane calibration; Step S4: performing statistical analysis on the height coordinate information of the calibrated three-dimensional point cloud data to obtain a bimodal distribution histogram of the data; Step S5: using a statistical averaging method to calculate the average heights of the two wave peaks; Step S6: Calculate the difference between the average values ​​of the double peak heights to obtain the effective depth of the trapezoidal notch of the membrane; The step S5 comprises: The data whose z coordinate in the histogram is less than the average depth of the notch is regarded as a smaller part of the data, and the distribution of the smaller part of the data is arranged in descending order to obtain a permutation list of the point cloud data of each interval from high to low; based on the current permutation list, the first n elements in the list are obtained, L1, L2, ..., Ln; based on L1, L2, ..., Ln, the bottom peak of the notch is constructed; The data with z coordinates greater than the average depth of the notch in the histogram are regarded as the larger part of the data, and the distribution of the larger part of the data is arranged in descending order to obtain a list of point cloud data in each interval from high to low; based on the current arrangement list, the first n elements H1, H2, ..., Hn in the list are obtained; based on H1, H2, ..., Hn, the peak of the notch top is constructed; After obtaining the average height of all point clouds in L1, use the average height as the effective height of the bottom plane of the notch; when the difference between the number of point clouds in L1 and L2 is less than the preset value, calculate the average height of all point cloud data in L1 and L2, and use the average height as the effective height of the bottom plane of the notch; when the difference between the number of point clouds in L1 and L2 is less than the preset value, and the difference between the number of point clouds in L2 and L3 is less than the preset value, calculate the average height of all point cloud data in L1, L2 and L3, and use the average height as the effective height of the bottom plane of the notch; and so on to Ln; where, ; After obtaining the average height of all point clouds in H1, use the average height as the effective height of the top plane of the notch; when the difference in the number of point clouds in H1 and H2 is less than a preset value, calculate the average height of all point cloud data in H1 and H2, and use the average height as the effective height of the top plane of the notch; when the difference in the number of point clouds in H1 and H2 is less than a preset value, and the difference in the number of point clouds in H2 and H3 is less than a preset value, calculate the average height of all point cloud data in H1, H2 and H3, and use the average height as the effective height of the top plane of the notch.

2. The method for measuring the effective depth of a rocket rupture diaphragm femtosecond laser processing notch according to claim 1 is characterized in that: In the process of measuring the score of the ruptured membrane using a laser confocal microscope, the measuring position is within a preset range of the intersection of the C-shaped score of the membrane and the symmetry axis of the membrane.

3. The method for measuring the effective depth of a rocket rupture diaphragm femtosecond laser processing notch according to claim 1 is characterized in that: The step S2 adopts: according to the x, y, z coordinates of the notch three-dimensional point cloud data, the least square method is used to perform plane fitting processing on the notch three-dimensional point cloud data.

4. The method for measuring the effective depth of a rocket rupture diaphragm femtosecond laser processing notch according to claim 1 is characterized in that: The step S3 adopts: according to the x and y coordinates of the notched three-dimensional point cloud, using the reference plane equation, calculating the z coordinate of the (x, y) point on the reference plane, using the z coordinate of the notched three-dimensional point cloud minus the z coordinate of the corresponding position on the reference plane to obtain the three-dimensional point cloud data after plane calibration.

5. The method for measuring the effective depth of a rocket rupture diaphragm femtosecond laser processing notch according to claim 1 is characterized in that: The step S4 comprises: determining the number and range of histogram columns according to the maximum value, minimum value and single column interval width of the point cloud z coordinate; No. The interval corresponding to the root column is: in, Indicates the column interval width; Indicates taking the minimum value of the z coordinates of all point clouds; Count the z coordinates that fall in each interval The number of point clouds in each interval is calculated, the average z coordinate of the point cloud in each interval is calculated, and a histogram is drawn; The average z-coordinate in each interval is: in, represents the average z-coordinate in each interval; Indicates taking the average z coordinate of all point cloud data in the interval; Representation interval z coordinate of the inner point cloud; Representation interval .

6. A rocket rupture membrane femtosecond laser processing notch effective depth measurement system, characterized in that: include: Module M1: Use laser confocal microscopy to measure the scratches on the ruptured membrane to obtain the three-dimensional point cloud data of the scratches; Module M2: plane fitting is performed on the three-dimensional point cloud data of the notch to obtain the reference plane; Module M3: Use the reference plane to perform plane calibration on the three-dimensional point cloud data of the notch to obtain the three-dimensional point cloud data after plane calibration; Module M4: Statistically analyze the height coordinate information of the calibrated 3D point cloud data to obtain a bimodal distribution histogram of the data; Module M5: Calculate the average height of the two wave peaks using the statistical averaging method; Module M6: Calculate the difference between the average values ​​of the double peak heights to obtain the effective depth of the trapezoidal notch of the membrane; The module M5 comprises: The data whose z coordinate in the histogram is less than the average depth of the notch is regarded as a smaller part of the data, and the distribution of the smaller part of the data is arranged in descending order to obtain a permutation list of the point cloud data of each interval from high to low; based on the current permutation list, the first n elements in the list are obtained, L1, L2, ..., Ln; based on L1, L2, ..., Ln, the bottom peak of the notch is constructed; The data with z coordinates greater than the average depth of the notch in the histogram are regarded as the larger part of the data, and the distribution of the larger part of the data is arranged in descending order to obtain a list of point cloud data in each interval from high to low; based on the current arrangement list, the first n elements H1, H2, ..., Hn in the list are obtained; based on H1, H2, ..., Hn, the peak of the notch top is constructed; After obtaining the average height of all point clouds in L1, use the average height as the effective height of the bottom plane of the notch; when the difference between the number of point clouds in L1 and L2 is less than the preset value, calculate the average height of all point cloud data in L1 and L2, and use the average height as the effective height of the bottom plane of the notch; when the difference between the number of point clouds in L1 and L2 is less than the preset value, and the difference between the number of point clouds in L2 and L3 is less than the preset value, calculate the average height of all point cloud data in L1, L2 and L3, and use the average height as the effective height of the bottom plane of the notch; and so on to Ln; where, ; After obtaining the average height of all point clouds in H1, use the average height as the effective height of the top plane of the notch; when the difference in the number of point clouds in H1 and H2 is less than a preset value, calculate the average height of all point cloud data in H1 and H2, and use the average height as the effective height of the top plane of the notch; when the difference in the number of point clouds in H1 and H2 is less than a preset value, and the difference in the number of point clouds in H2 and H3 is less than a preset value, calculate the average height of all point cloud data in H1, H2 and H3, and use the average height as the effective height of the top plane of the notch.

7. The rocket rupture diaphragm femtosecond laser processing notch effective depth measurement system according to claim 6 is characterized in that: In the process of measuring the score of the ruptured membrane using a laser confocal microscope, the measurement position is within a preset range of the intersection of the C-shaped score of the membrane and the symmetry axis of the membrane; The module M2 adopts: according to the x, y, z coordinates of the notch three-dimensional point cloud data, the least square method is used to perform plane fitting processing on the notch three-dimensional point cloud data.

8. The rocket rupture diaphragm femtosecond laser processing notch effective depth measurement system according to claim 6 is characterized in that: The module M3 adopts: according to the x and y coordinates of the notched three-dimensional point cloud, using the reference plane equation, calculating the z coordinate of the (x, y) point on the reference plane, using the z coordinate of the notched three-dimensional point cloud minus the z coordinate of the corresponding position on the reference plane, to obtain the three-dimensional point cloud data after plane calibration; The module M4 includes: determining the number and range of histogram columns according to the maximum and minimum values ​​of the point cloud z coordinates and the width of a single column interval; No. The interval corresponding to the root column is: in, Indicates the column interval width; Indicates taking the minimum value of the z coordinates of all point clouds; Count the z coordinates that fall in each interval The number of point clouds in each interval is calculated, the average z coordinate of the point cloud in each interval is calculated, and a histogram is drawn; The average z-coordinate in each interval is: in, represents the average z-coordinate in each interval; Indicates taking the average z coordinate of all point cloud data in the interval; Representation interval z coordinate of the inner point cloud; Representation interval .

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