A method for detecting an abnormality of a water guide laser nozzle

Abstract

This invention belongs to the field of water-guided laser processing technology and relates to a method for detecting anomalies in water-guided laser nozzles. The method includes: step one, image acquisition; step two, image cropping for noise reduction; step three, image filtering and binarization; step four, anomaly detection; and step five, issuing anomaly warnings. This invention captures images of the processing waterline of the water-guided laser nozzle using a camera, and then performs cropping, noise reduction, filtering, and binarization on the captured images before anomaly detection. By subtracting the preceding and following frames of the processed image and calculating the difference, the method ultimately determines whether the water-guided laser nozzle is abnormal. This invention effectively reduces manual observation time, avoids damage to other parts in the coupling cavity caused by the laser when processing continues after the nozzle has burned out, improves processing efficiency, and frees up operators.

Description

Technical Field

[0001] This invention belongs to the field of water-guided laser processing technology and relates to a method for detecting abnormalities in water-guided laser nozzles. Background Technology

[0002] Water-guided laser processing technology is a novel technique that uses a water jet to guide a laser beam for cutting the workpiece. The principle involves focusing the laser beam through a glass window, adjusting the nozzle so that the laser enters the center of the nozzle, and then causing total internal reflection within the water flow. This creates a high-energy water flow that acts as a propagation mechanism, allowing processing to be performed throughout the stable water flow. Compared to traditional laser processing, this offers a longer working distance, and the water flow also washes away processing debris, reducing the heat impact of processing. The key step in coupling the laser and water is aligning the laser with the center of the nozzle. Current coupling alignment primarily involves using a CCD camera to image the laser spot and nozzle, positioning them, and then adjusting the X and Y axes of the coupling device to move the nozzle center to the laser spot center. Fine-tuning is then performed using CCD imaging and coupled power. While this method can achieve high coupling power, human eye error, operational errors, and external influences mean that the adjusted laser spot may not entirely enter the nozzle. Processing under these conditions can easily burn out the nozzle, cause water flow instability, prevent water-laser coupling, and hinder normal processing. It may also damage other components within the coupling cavity.

[0003] However, in existing technologies, the commonly used method for nozzle anomaly detection involves operators manually observing the waterline length and brightness in real time, and then comprehensively judging whether the nozzle is damaged by considering processing sounds, waterline length, and nozzle usage time. This method is extremely demanding on the operator's energy and eyesight, especially when dealing with ultra-hard or ultra-deep materials that require long processing times. The operator must constantly monitor the nozzle for burnout to ensure timely replacement, reduce processing time, and prevent damage to other components within the coupling cavity caused by a burnt-out nozzle, which could seriously affect the operator's health. This method is time-consuming, labor-intensive, and inefficient.

[0004] Therefore, a more reliable and effective method for detecting nozzle anomalies that reduces the burden on manpower is needed to solve the above problems. Summary of the Invention

[0005] The technical solution adopted by this invention to solve the technical problem is: a method for detecting abnormalities in a water-guided laser nozzle, comprising the following steps:

[0006] Step 1: Image Acquisition; Use a camera to capture real-time images of the processing waterline of the water-guided laser nozzle, and adjust parameters such as exposure time to obtain an image of the processing waterline, generating Image 1;

[0007] Step 2: Cut the image obtained in Step 1 so that only the high-energy waterline portion of the image is retained, and generate Image 2: Remove irrelevant image information to achieve noise reduction;

[0008] Step 3: Perform image processing on Image 2 obtained in Step 2, making the processed waterline area of ​​Image 2 white and the background black, generating Image 3:

[0009] Step 4: Anomaly detection; Starting from the second frame, for the image 3 after image processing in Step 3, subtract each frame from the previous frame and calculate the sum of the differences. If the sum of the differences exceeds threshold 1, calculate the proportion of the white water line portion to the entire image for the current image. If the calculated proportion is less than threshold 2, determine that there is no laser undergoing total internal reflection in the current processing water line, that is, determine that the water-guided laser nozzle is abnormal.

[0010] Step 5: Send the abnormal signal of the water-guided laser nozzle to the processing control system, stop processing, and issue a warning to remind the operator to replace the water-guided laser nozzle.

[0011] Preferably, in step three, when processing image two, image two is first processed into a single-channel grayscale image, then the grayscale image is filtered, and finally the filtered grayscale image is binarized using an adaptive thresholding method.

[0012] More preferably, the grayscale image is filtered in the following ways: median filtering and mean filtering.

[0013] More preferably, in step three, when processing image two, the white part represents the processed water flow with a pixel value of 1, and the black part represents the background with a pixel value of 0.

[0014] Preferably, in step four, when performing difference comparison on adjacent frame images,

[0015]

[0016] In equation (1), This represents the pixel value in the i-th row and j-th column of the n-th frame image, and abs() represents taking the absolute value;

[0017] If f > 0.5f0, where f represents the sum of the number of pixel value changes between the current frame and the previous frame. The sum of the pixel values ​​in the first frame represents the initial waterline length, indicating a significant change in the waterline portion of the current image compared to the previous one. If the sum of the pixel values ​​in the first frame of the image indicates a significant change in the waterline area of ​​the current image processing compared to the previous frame, then... If the sum of the pixel values ​​in the current image is much smaller than the sum of the pixel values ​​in the first image, it indicates that the processing waterline has become significantly shorter or disappeared, which can be used to determine that the water-guided laser nozzle is abnormal.

[0018] Preferably, the camera used in step one is an industrial camera; industrial cameras have better stability, better imaging effect, and higher clarity and pixels.

[0019] More preferably, the camera remains relatively stationary with respect to the water-guided laser nozzle during shooting; this relative stationary position can be achieved by fixing the camera and the water-guided laser nozzle to the coupling cavity respectively, thus eliminating the mutual interference between the camera and the water-guided laser nozzle during shooting and reducing the detection accuracy of abnormalities in the water-guided laser nozzle.

[0020] Preferably, in step four, threshold one is 0.45 to 0.55 times the sum of pixel values ​​of the first image, and threshold two is 0.35 to 0.44 times the sum of pixel values ​​of the first image.

[0021] More preferably, in step four, threshold one is 0.5 times the sum of pixel values ​​of the first image, and threshold two is 0.4 times the sum of pixel values ​​of the first image.

[0022] The beneficial effects of this invention are:

[0023] This invention captures images of the processing waterline of a water-guided laser nozzle using a camera, and then performs image cropping, noise reduction, filtering, binarization, and anomaly detection on the captured images. By subtracting the preceding and following frames of the processed image and calculating the difference, the invention ultimately determines whether the water-guided laser nozzle is abnormal. This invention effectively reduces manual observation time, avoids damage to other parts in the coupling cavity caused by the laser when processing continues after the nozzle has burned out, improves processing efficiency, and frees up operators. Attached Figure Description

[0024] Figure 1 This is a system schematic diagram of a method for detecting anomalies in a water-guided laser nozzle;

[0025] Figure 2 This is a schematic diagram of the detection device;

[0026] Figure 3 This is a schematic diagram of a waterline section with high energy.

[0027] Figure 4 This is a schematic diagram of a binarized grayscale image.

[0028] Among them, 1. focusing lens; 2. coupling cavity; 3. camera; 4. processing platform. Detailed Implementation

[0029] The related technologies of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0030] refer to Figures 1-4 A method for detecting anomalies in a water-guided laser nozzle, comprising:

[0031] Step 1: Image Acquisition; Use a camera to capture real-time images of the processing waterline of the water-guided laser nozzle, and adjust parameters such as exposure time to obtain an image of the processing waterline, generating Image 1;

[0032] Step 2: Cut the image obtained in Step 1 so that only the high-energy waterline portion of the image is retained, and generate Image 2: Remove irrelevant image information to achieve noise reduction;

[0033] Step 3: Perform image processing on Image 2 obtained in Step 2, making the processed waterline area of ​​Image 2 white and the background black, generating Image 3:

[0034] Step 4: Anomaly Detection; Starting from the second frame, for the image 3 after image processing in Step 3, subtract each frame from the previous frame and calculate the sum of the differences. If the sum of the differences exceeds threshold 1, which is 0.5 times the sum of the pixel values ​​of the first image, then calculate the proportion of the white waterline portion to the entire image for the current image. If the calculated proportion is less than threshold 2, which is 0.4 times the sum of the pixel values ​​of the first image, then it is determined that there is no laser undergoing total internal reflection in the current processing waterline, i.e., the water-guided laser nozzle is abnormal.

[0035] Step 5: Send the abnormal signal of the water-guided laser nozzle to the processing control system, stop processing, and issue a warning to remind the operator to replace the water-guided laser nozzle.

[0036] Furthermore, in step three, when processing image two, image two is first processed into a single-channel grayscale image, then the grayscale image is filtered, and finally the filtered grayscale image is binarized using an adaptive thresholding method.

[0037] Furthermore, the grayscale image is filtered in the following ways: median filtering and mean filtering.

[0038] Furthermore, in step three, when processing image two, the white portion represents the processed water flow with a pixel value of 1, and the black portion represents the background with a partial pixel value of 0.

[0039] Preferably, in step four, when performing difference comparison on adjacent frame images,

[0040]

[0041] In equation (1), This represents the pixel value in the i-th row and j-th column of the n-th frame image, and abs() represents taking the absolute value;

[0042] If f > 0.5f0, where If the sum of the pixel values ​​in the first frame of the image indicates a significant change in the waterline area of ​​the current image processing compared to the previous frame, then... If the sum of the pixel values ​​in the current image is much smaller than the sum of the pixel values ​​in the first image, it indicates that the processing waterline has become significantly shorter or disappeared, which can be used to determine that the water-guided laser nozzle is abnormal.

[0043] Furthermore, the camera used in step one is an industrial camera; industrial cameras have better stability, better imaging effect, and higher clarity and pixels.

[0044] Furthermore, the camera remains relatively stationary with respect to the water-guided laser nozzle during shooting. This relative stationary position can be achieved by fixing the camera and the water-guided laser nozzle to the coupling cavity respectively, thus eliminating the mutual interference between the camera and the water-guided laser nozzle during shooting and reducing the detection accuracy of abnormalities in the water-guided laser nozzle.

[0045] Example

[0046] In this embodiment, the water-guided laser processing uses a focusing lens 1 to focus the laser beam into the coupling cavity 2, and a camera 3 is positioned directly above the processing water jet of the water-guided laser. Below the processing water jet is the processing platform 4.

[0047] The abnormal detection method for the water-guided laser nozzle in this embodiment is as follows:

[0048] Water flow patterns are captured and processed using a camera, such as Figure 2 As shown, the area above the processed water flow in the captured image is darker because the laser undergoes total internal reflection in the water, resulting in less energy dissipation, while the brighter area below is due to some laser energy escaping into the water flow. Figure 3 As shown;

[0049] By selecting an appropriate local threshold, the image is binarized, as shown below, where the white portion represents the processed water flow with a pixel value of 1, and the background portion has a pixel value of 0; Figure 4 As shown;

[0050] Perform a difference comparison on adjacent frames. in Let f represent the pixel value in the i-th row and j-th column of the n-th frame image, and abs() represents taking the absolute value. If f > 0.5f0, where If the sum of the pixel values ​​in the first frame of the image indicates a significant change in the waterline area of ​​the current image processing compared to the previous frame, then... If the sum of the pixel values ​​in the current image is much smaller than the sum of the pixel values ​​in the first image, it indicates that the processing waterline has become significantly shorter or disappeared. This can be determined to be caused by a nozzle malfunction. The signal is then transmitted to the processing control system to stop processing and issue a warning, reminding the operator to replace the water-guided laser nozzle.

[0051] In summary, this invention captures images of the processing waterline of a water-guided laser nozzle using a camera, and then performs image cropping, noise reduction, filtering, binarization, and anomaly detection on the captured images. By subtracting consecutive frames of the processed image and calculating the difference, the invention ultimately determines whether the water-guided laser nozzle is abnormal. This invention effectively reduces manual observation time, avoids damage to other parts in the coupling cavity caused by the laser when processing continues after the nozzle has burned out, improves processing efficiency, and frees up operators. Therefore, this invention has broad application prospects.

[0052] It should be emphasized that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any way. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention shall still fall within the scope of the technical solution of the present invention.

Claims

1. A water guided laser nozzle anomaly detection method, characterized by, The method comprises the following steps: Step 1: image acquisition; using a camera to take a real-time image of the processing water line part of the water guide laser nozzle, obtaining the image of the processing water line, and generating image 1; Step 2: cutting the image 1 obtained in step 1 so that the image 1 only retains the image of the water line part with high energy, generating image 2: Step 3: performing image processing on the image 2 obtained in step 2 so that the processing water line part of the image 2 is white and the background is black, generating image 3: Step 4: anomaly detection; for the image 3 after image processing in step 3, starting from the second frame, each frame is subtracted from the previous frame image and the difference is calculated, and if the difference exceeds a threshold value 1, it is determined that the current water line changes significantly, and the proportion of the white water line part in the entire image is calculated for the current image, if the result of the calculation is less than a threshold value 2, it is determined that there is no stable total reflection of laser in the current processing water line, that is, the water guide laser nozzle is abnormal; Step 5: sending a signal of the water guide laser nozzle abnormality to the processing control system, stopping processing, and issuing a warning to remind the operator to replace the water guide laser nozzle.

2. The method of claim 1, wherein, In step 3, when performing image processing on image 2, first process image 2 into a single-channel grayscale image, then filter the grayscale image, and finally use an adaptive threshold method to binarize the filtered grayscale image.

3. The method of claim 2, wherein the method further comprises: The filtering method of the grayscale image includes median filtering and mean filtering.

4. The method of claim 2, wherein the method further comprises: In step 3, when performing image processing on image 2, the white part represents the processing water flow, and the pixel value is 1, and the black part represents the background, and the pixel value is 0.

5. The method of claim 1, wherein, In step 4, when comparing the difference between adjacent frame images, In formula (1), represents the pixel value of the i-th row and j-th column in the n-th frame of image, and abs() represents taking the absolute value. If f > 0.5f0, where f represents the sum of the pixel value change points of the current frame image and the previous frame image, is the first frame image pixel value sum, and represents the initial waterline length, then it represents that the current image processing waterline part has changed significantly compared to before, and then if that is, the current image pixel value sum is much smaller than the first frame image pixel value sum, which means that the processing waterline has obviously shortened or disappeared, and the water guide laser nozzle can be determined to be abnormal.

6. The method of claim 1, wherein, The camera used in step 1 is an industrial camera.

7. The method of claim 6, wherein the method further comprises: The camera remains relatively stationary when taking pictures with the water guide laser nozzle.

8. The method of claim 1, wherein the method further comprises: In step 4, the threshold value 1 is 0.45 to 0.55 times the sum of the pixel values of the first image, and the threshold value 2 is 0.35 to 0.44 times the sum of the pixel values of the first image.

9. The method of claim 8, wherein the method further comprises: In step 4, the threshold value 1 is 0.5 times the sum of the pixel values of the first image, and the threshold value 2 is 0.4 times the sum of the pixel values of the first image.

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