Method for detecting chemical solution concentration after cleaning of chemical solution tank for printed circuit board

Abstract

This application relates to the technical field of concentration detection, specifically to a method for detecting the concentration of the chemical solution in a printed circuit board chemical solution tank after cleaning, including: obtaining the hyperspectral data of the chemical solution in the chemical solution tank; analyzing the differences between the absorption peaks of each hyperspectral data at each moment, and combining the distance relationship between each hyperspectral data point and the central hyperspectral data point to obtain the possibility of being interfered by debris for each hyperspectral data point at each moment; according to the distribution law of the hyperspectral data at each moment and the difference in the change trend of the absorption rate of each hyperspectral data at all moments, obtaining the interference degree of the support device for each hyperspectral data point at each moment, and then obtaining the spectral interference index of each hyperspectral data point at each moment to screen the hyperspectral data points, and combining the hyperspectral data of the chemical solution sample to detect the concentration of the chemical solution in the chemical solution tank. This application can improve the detection accuracy of the concentration of the chemical solution in the chemical solution tank after cleaning.

Description

Technical Field

[0001] This application relates to the technical field of concentration detection, and specifically relates to a method for detecting the concentration of the chemical solution after cleaning the chemical solution tank of a printed circuit board. Background Art

[0002] In the production of printed circuit boards (PCBs), the detection of the concentration of the chemical solution after cleaning the chemical solution tank has an important application background. The environment around the chemical solution tank is complex. If manual sampling is carried out, there are safety risks, and sampling at multiple tank positions takes a long time and is costly. Therefore, developing an efficient, accurate, and automated method for detecting the concentration of the chemical solution can not only improve production efficiency and product quality but also effectively reduce the impact on the environment and meet environmental protection requirements.

[0003] With the development of detection technologies, the means for detecting the concentration of the chemical solution in the chemical solution tank are gradually increasing. Currently, the absorbance photometry method is used to obtain optical signals and then convert them into electrical signals to detect the concentration of the chemical solution. However, since the absorbance photometry method is easily affected by the environment during the detection process and thus generates noise, how to efficiently remove the noise has become a research hotspot. There are still certain deficiencies in some current methods. There may be metal debris shed from the printed circuit board and materials for electroplating or soldering in the chemical solution tank used for cleaning the printed circuit board, which will interfere with the detection of the concentration of the chemical solution and affect the detection results. Summary of the Invention

[0004] In order to solve the above technical problems, this application provides a method for detecting the concentration of the chemical solution after cleaning the chemical solution tank of a printed circuit board to solve the existing problems.

[0005] The method for detecting the concentration of the chemical solution after cleaning the chemical solution tank of a printed circuit board in this application adopts the following technical solutions:

[0006] An embodiment of this application provides a method for detecting the concentration of the chemical solution after cleaning the chemical solution tank of a printed circuit board, including the following steps:

[0007] Obtain the hyperspectral data of the chemical solution in the chemical solution tank;

[0008] Analyze the peak value differences of the absorption peaks of each hyperspectral data at each moment and the differences between the wavelengths corresponding to the absorption peaks, and combine the distance relationship between each hyperspectral data point and the central hyperspectral data point at each moment to obtain the possibility of being interfered by debris for each hyperspectral data point at each moment;

[0009] According to the distribution law of the hyperspectral data at each moment and the difference in the change trend of the absorption rates of each hyperspectral data at all moments, obtain the interference degree of the support device for each hyperspectral data point at each moment, and combine the possibility of being interfered by debris to obtain the spectral interference index of each hyperspectral data point at each moment;

[0010] According to the spectral perturbation index, hyperspectral data points are screened, and combined with the hyperspectral data of the liquid medicine sample, the concentration of the liquid medicine in the liquid medicine tank is detected.

[0011] Preferably, the central hyperspectral data point is the hyperspectral data point corresponding to the center of the liquid medicine tank at a single moment.

[0012] Preferably, the calculation method of the possibility of debris interference for each hyperspectral data point at each moment is as follows:

[0013] ;

[0014] In the formula, is the possibility of debris interference of the th hyperspectral data point at the th moment, is the average value of the peak difference of the absorption peaks of the th hyperspectral data point at the th moment and its left and right adjacent moments, is the average value of the wavelength difference corresponding to the absorption peaks of the th hyperspectral data point at the th moment and its left and right adjacent moments, is the Euclidean distance between the th hyperspectral data point at the th moment and the central hyperspectral data point, is a constant to prevent the denominator from being 0.

[0015] Preferably, the calculation method of the interference degree of the support device for each hyperspectral data point at each moment is as follows:

[0016] ;

[0017] In the formula, is the interference degree of the support device of the th hyperspectral data point at the th moment, is the spectral regularity degree of the th hyperspectral data point at the th moment, is the difference in the trend intensity of the th hyperspectral data point, and the difference in the trend intensity of the absorption rate sequence of the remaining hyperspectral data points at the th moment.

[0018] Preferably, the acquisition of the spectral regularity degree further includes: clustering all hyperspectral data points at the th moment, and the Take the reciprocal of the variance of the Euclidean distances between all pairs of hyperspectral data points in the cluster where a hyperspectral data point is located as the spectral regularity degree of the hyperspectral data point at the

[0019] Preferably, the construction of the absorption rate sequence includes: arranging the absorption rates of the hyperspectral data points at all sampling times in the order of the sampling times to form an absorption rate sequence.

[0020] Preferably, the obtaining of the trend intensity difference degree is further the average value of the absolute value of the difference between the trend intensity of the absorption rate sequence of the hyperspectral data point at the time and the trend intensity of the absorption rate sequences of other hyperspectral data points at the

[0021] Preferably, the spectral disturbance index of each hyperspectral data point at each time is the sum value of the possibility of being disturbed by debris and the disturbance degree of the support device.

[0022] Preferably, the screening of the hyperspectral data points further includes:

[0023] Extract the segmentation threshold of the spectral disturbance indices of all hyperspectral data points, screen out the hyperspectral data points with spectral disturbance indices less than the segmentation threshold, and use them as the points to be analyzed.

[0024] Preferably, the detection of the potion concentration in the potion tank further includes:

[0025] Obtain the hyperspectral data of multiple potion samples and form a database, and combine the hyperspectral data of all points to be analyzed, and use the Lambert-Beer law to calculate the potion concentration in the current potion tank.

[0026] This application has at least the following beneficial effects:

[0027] By analyzing the disturbance situation of the potion in the printed circuit board potion tank, this application derives and constructs an evaluation index for judging potion disturbance, further screens the collected hyperspectral data of the potion by combining the evaluation index, and finally calculates the potion concentration in the potion tank by combining the database, solving the problem that when using the absorption photometry method to detect the potion concentration in the potion tank, only environmental noise can be removed and the interference of material debris and support devices in the potion tank on the hyperspectral data cannot be avoided, and further improving the accuracy of potion concentration detection. Description of the Drawings

[0028] To more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0029] Figure 1 This is a flowchart of the steps of the method for detecting the chemical solution concentration after cleaning a chemical solution tank for a printed circuit board provided by the present application. Specific embodiments

[0030] To further elaborate on the technical means and effects adopted by the present application to achieve the intended invention purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific embodiments, structures, features, and effects of the method for detecting the chemical solution concentration after cleaning a chemical solution tank for a printed circuit board proposed according to the present application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0031] Unless otherwise defined, terms such as "including", "comprising", or any other variant thereof are intended to cover non-exclusive inclusion, such that a circuit structure, article, or device including a series of elements not only includes those elements but also includes other elements not explicitly listed, or further includes elements inherent to such article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the presence of another identical element in the article or device including the said element. Additionally, the term "and / or" used herein includes any and all combinations of one or more of the related listed items. All technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present application belongs.

[0032] The following specifically describes the specific solution of the method for detecting the chemical solution concentration after cleaning a chemical solution tank for a printed circuit board provided by the present application in conjunction with the accompanying drawings.

[0033] The method for detecting the chemical solution concentration after cleaning a chemical solution tank for a printed circuit board provided by an embodiment of the present application. Specifically, please refer to Figure 1 , including the following steps:

[0034] Step 1: Obtain the hyperspectral data of the chemical solution in the chemical solution tank.

[0035] In this embodiment, a hyperspectral camera is set directly above the chemical solution tank. For the chemical solution in the chemical solution tank, after cleaning a printed circuit board once, hyperspectral data is collected every interval of time T, and the first derivative spectroscopy method and the quadratic polynomial fitting method are used to obtain the corresponding band length and absorption peak intensity of the absorption peak of the hyperspectral data at each hyperspectral data point. Among them, both the first derivative spectroscopy method and the quadratic polynomial fitting method are well-known technologies. Among them, in this embodiment, T = 10s.

[0036] Step 2: Analyze the peak value differences of the absorption peaks of each hyperspectral data at each moment and the differences between the wavelengths corresponding to the absorption peaks, and combine the distance relationships between each hyperspectral data point and the central hyperspectral data at each moment to obtain the possibility of being interfered by debris at each hyperspectral data point at each moment.

[0037] Before the printed circuit board is cleaned, it undergoes multiple production processes such as electroplating and soldering. Therefore, after cleaning, some material debris will enter the chemical solution tank and float in the chemical solution. During the process of collecting data using the hyperspectral camera, these material debris may cause light scattering, which in turn causes some light to deviate from the path, resulting in a decrease in the detected light intensity. Or it may be that some material debris absorbs light of a specific wavelength, thereby interfering with the absorption spectrum of the chemical solution components, resulting in absorption peak overlap, and thus causing the absorption peak intensity to be too high to distinguish the actual chemical solution concentration.

[0038] Since the chemical solution is not completely stationary in the chemical solution tank, the position of the material debris in the chemical solution tank will change over time. Therefore, for a single hyperspectral data point, there may be hyperspectral data of a mixture of material debris and chemical solution at different times, or there may only be hyperspectral data of the chemical solution components. Therefore, the absorption peak intensity and the band length corresponding to the absorption peak of the hyperspectral data at this hyperspectral data point will also change greatly over time. And since the cleaning of the printed circuit board is mainly carried out in the middle of the chemical solution tank during the cleaning process, the closer to the middle of the chemical solution tank, the more likely the hyperspectral data of the chemical solution is affected by the material debris.

[0039] Based on the above characteristics, the interference situation of each chemical solution hyperspectral data point is reflected by the following relational expression, and the possibility of being interfered by debris at each hyperspectral data point at each moment is constructed:

[0040] ;

[0041] In the formula, is the possibility of being interfered by debris at the th hyperspectral data point at the th moment, is the th hyperspectral data point at the The mean value of the difference between the peak values of the absorption peaks at each moment and the adjacent moments, is the mean value of the difference in the corresponding wavelength lengths of the absorption peaks of the th hyperspectral data points at the th moment and the adjacent moments, is the Euclidean distance between the th hyperspectral data points at the th moment and the central hyperspectral data point, where the central hyperspectral data point is the hyperspectral data point corresponding to the center of the liquid medicine tank at the th moment, .

[0042] It can be understood that: as time changes, the greater the degree of change in the peak values of the absorption peaks in the hyperspectral data points, and the greater the difference in the wavelength changes corresponding to each absorption peak, the more likely it is that there is floating of material debris in the hyperspectral data points, and the more likely the hyperspectral data is affected by interference.

[0043] Step 3: According to the distribution law of the hyperspectral data at each moment and the difference in the change trend of the absorption rates of each hyperspectral data at all moments, obtain the interference degree of the support device at each moment for each hyperspectral data point, and combine the possibility of being disturbed by debris to obtain the spectral interference index of each hyperspectral data point at each moment.

[0044] When cleaning the printed circuit board, a support device such as a nail bed fixing device or a floating frame is needed in the liquid medicine tank to fix the printed circuit board for more comprehensive cleaning. However, the support device will also have a certain impact on the hyperspectral data points of the liquid medicine in the liquid medicine tank. Since the support device is usually fixed in position and at a fixed interval, the interference of the hyperspectral data points at the position of the support device calculated by the above method is relatively small, resulting in a deviation when calculating the liquid medicine concentration using this data. Therefore, further analysis is required.

[0045] For the position where the support device is located, due to its fixed position and fixed interval, the interval of the hyperspectral data points at the position of the support device is more regular and the distribution is more concentrated. After the liquid medicine tank completes a round of cleaning of the printed circuit board, the floating situation of the liquid medicine in the liquid medicine tank is complex and the water surface will have a certain fluctuation. Therefore, there will still be a certain difference in the absorption rates of the hyperspectral data points corresponding to the position of the support device.

[0046] Therefore, further, in this embodiment, all hyperspectral data points collected at a single moment are clustered, taking all hyperspectral data points collected at a single moment as an example. Preferably, the DPC density clustering algorithm is used in this example, and the absolute value of the difference between the absorbances of the hyperspectral data is taken as the distance metric. In this embodiment, considering that for a single hyperspectral data point, there may be multiple absorption peaks caused by the mixture of material debris and the potion at different moments, the absorbance of a single hyperspectral data point at a single moment is the mean of the absorbances corresponding to all absorption peaks of the hyperspectral data at a single moment. In the clustering process, the cutoff distance is set to 3, and the clusters after clustering all the hyperspectral data at a single moment are output. The DPC density clustering algorithm is a well-known technique, and its process is not further described in this embodiment. At the same time, for each hyperspectral data point, the absorbances at all moments are arranged in the order of the sampling moments to construct an absorbance sequence for each hyperspectral data point, which is used to characterize the specific changes in the absorbance of the hyperspectral data point over time.

[0047] Based on the above analysis, the following relationship is used to express the The influence of the supporting device on the potion at each moment is used to construct the interference degree of the supporting device for each hyperspectral data point at each moment:

[0048] ;

[0049] Where, For the Hyperspectral data points in The interference degree of the supporting device at a certain moment, For the Hyperspectral data points in The spectral regularity at each moment, For the The trend intensity difference of the hyperspectral data point is compared with the rest of the hyperspectral data points in the The trend intensity difference of the absorption rate series at each moment.

[0050] Among them, for the The clusters obtained after clustering all the hyperspectral data points at the moment are The inverse of the variance of the Euclidean distance between any two hyperspectral data points in the cluster where the hyperspectral data point is located is taken as the first Hyperspectral data points in The spectral regularity at each moment. It should be noted that in order to avoid the denominator being zero in the process of taking the reciprocal, a constant can be added to the denominator to avoid the denominator being zero. In this embodiment, the value is 0.01;

[0051] The trend strength difference is further obtained as The average value of the absolute value of the difference between the trend intensity of the absorption rate sequence of a hyperspectral data point at the -th moment and the trend intensity of the absorption rate sequence of other hyperspectral data points at the -th moment is taken. It should be noted that the calculation method of the trend intensity is a prior art and will not be elaborated in this embodiment.

[0052] It can be understood that: when the difference fluctuation among the hyperspectral data points within the clustering cluster where the -th hyperspectral data point is located is smaller, that is, the spectral regularity degree is larger, the distribution is more regular, and the difference degree of the trend intensity is larger, it indicates that this hyperspectral data point is more likely to be the hyperspectral data point at the position of the support device and is more likely to be affected by the support device.

[0053] According to the interference degree of the support device and the possibility of being interfered by debris at each moment of each hyperspectral data point, the spectral interference index of each hyperspectral data point at each moment is obtained. The spectral interference index of each hyperspectral data point at each moment is the sum value of the possibility of being interfered by debris and the interference degree of the support device. For the convenience of understanding, the calculation formula in this embodiment is: ; where is the spectral interference index of the -th hyperspectral data point at the -th moment, is the possibility of being interfered by debris of the -th hyperspectral data point at the -th moment, is the interference degree of the support device of the -th hyperspectral data point at the -th moment.

[0054] It can be understood that: when the possibility that the -th hyperspectral data point is interfered by the material debris in the liquid medicine tank is greater and the degree of interference by the support device is greater, it indicates that the interference degree of the liquid medicine spectrum data in this hyperspectral data point is stronger, and the accuracy of detecting the liquid medicine concentration using this data is lower.

[0055] Step Four: According to the spectral interference index, screen the hyperspectral data points, and combine with the hyperspectral data of the liquid medicine sample to detect the concentration of the liquid medicine in the liquid medicine tank.

[0056] The spectral perturbation index that can be calculated using the above process is used as the input. By means of cross-validation, the output is the segmentation threshold of the spectral perturbation index. When the spectral perturbation index of a hyperspectral data point is greater than or equal to the segmentation threshold, it indicates that the interference degree of the hyperspectral data point is strong and it is not suitable as data support for potion concentration detection. On the contrary, when the spectral perturbation index of a hyperspectral data point is less than the segmentation threshold, it indicates that the perturbation degree of the hyperspectral data point is low and it can be used as data support for potion concentration detection, and such hyperspectral data points are used as points to be analyzed.

[0057] Finally, for the current sampling moment, the hyperspectral data of all points to be analyzed are extracted. Combining with the database constructed from the hyperspectral data of the potion samples, that is, obtaining the hyperspectral data of multiple potion samples and forming a database. It should be noted that the implementer of the potion sample selects it according to the actual situation in the actual application scenario, and this embodiment does not make special restrictions on this. Further, the concentration of the potion in the current potion tank is calculated using Lambert-Beer's law to complete the detection of the concentration of the potion in the potion tank.

[0058] It can be understood that referring to "one embodiment" or "some embodiments" etc. described in the specification of this application means that specific features, structures or characteristics described in connection with the embodiment are included in one or more embodiments of this application. Thus, if "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments" etc. appear in different places in this specification, they do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "comprising", "including", "having" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0059] It should be noted that the above sequence of the embodiments of this application is only for description and does not represent the superiority or inferiority of the embodiments. And the above specific embodiments of this specification have been described. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous. At the same time, the size of the serial numbers of the steps in the embodiments does not mean the sequence of execution. The execution sequence of each process should be determined by its function and internal logic and should not constitute any limitation to the implementation process of the embodiments in this specification.

[0060] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application, and should all be included within the protection scope of the present application.

Claims

1. A method for detecting the chemical solution concentration after cleaning a chemical solution tank of a printed circuit board, characterized in that, Including the following steps: Obtain the hyperspectral data of the potion in the potion tank; Analyze the peak value differences of the absorption peaks of each hyperspectral data at each moment and the differences between the wavelengths corresponding to the absorption peaks, and combine the distance relationship between each hyperspectral data point and the central hyperspectral data point at each moment to obtain the possibility of being interfered by debris for each hyperspectral data point at each moment; According to the distribution law of the hyperspectral data at each moment and the difference in the change trend of the absorption rates of each hyperspectral data at all moments, obtain the interference degree of the support device for each hyperspectral data point at each moment, and combine the possibility of being interfered by debris to obtain the spectral interference index of each hyperspectral data point at each moment; the absorption rate of a hyperspectral data point at a single moment is the average value of the absorption rates corresponding to all absorption peaks of the hyperspectral data point at a single moment; According to the spectral interference index, screen the hyperspectral data points, and combine the hyperspectral data of the potion sample to detect the concentration of the potion in the potion tank; The calculation method for the possibility of being interfered by debris for each hyperspectral data point at each moment is: ； Wherein, is the likelihood of the i-th hyperspectral data point being interfered by debris at the j-th moment, is the mean value of the peak difference of the absorption peaks of the i-th hyperspectral data point at the j-th moment from the left and right adjacent moments, is the mean value of the wavelength difference corresponding to the absorption peaks of the i-th hyperspectral data point at the j-th moment from the left and right adjacent moments, is the Euclidean distance between the i-th hyperspectral data point and the central hyperspectral data point at the j-th moment, is a constant to prevent the denominator from being zero; The calculation method for the interference degree of the support device for each hyperspectral data point at each moment is: ; where, is the interference degree of the support device for the i-th hyperspectral data point at the j-th moment, is the spectral regularity degree of the i-th hyperspectral data point at the j-th moment, is the trend intensity difference degree of the i-th hyperspectral data point at the j-th moment; the obtaining of the trend intensity difference degree is further the average value of the absolute value of the difference between the trend intensity of the absorption rate sequence of the i-th hyperspectral data point at the j-th moment and the trend intensity of the absorption rate sequence of other hyperspectral data points at the j-th moment; The obtaining of the spectral regularity further includes: clustering all hyperspectral data points at the j-th moment, and taking the reciprocal of the variance of the Euclidean distances between any two hyperspectral data points in the cluster where the i-th hyperspectral data point is located as the spectral regularity of the i-th hyperspectral data point at the j-th moment.

2. The method for detecting the chemical solution concentration after cleaning the chemical solution tank for printed circuit boards according to claim 1, wherein, The central hyperspectral data point is the hyperspectral data point corresponding to the center of the potion tank at a single moment.

3. The method for detecting the chemical solution concentration after cleaning the chemical solution tank for printed circuit boards according to claim 1, characterized in that, The construction of the absorption rate sequence includes: arranging the absorption rates of the hyperspectral data points at all sampling moments in the order of the sampling moments to form an absorption rate sequence.

4. The method for detecting the chemical solution concentration after cleaning the chemical solution tank for printed circuit boards according to claim 1, characterized in that, The spectral interference index of each hyperspectral data point at each moment is the sum value of the possibility of being interfered by debris and the interference degree of the support device.

5. The method for detecting the chemical solution concentration after cleaning a chemical solution tank for a printed circuit board according to claim 1, wherein, The screening of the hyperspectral data points further includes: Extract the segmentation threshold of the spectral interference index of all hyperspectral data points, screen out the hyperspectral data points with a spectral interference index less than the segmentation threshold, and use them as the points to be analyzed.

6. The method for detecting the chemical solution concentration after cleaning a chemical solution tank for a printed circuit board according to claim 5, characterized in that, The detection of the concentration of the potion in the potion tank further includes: Obtain the hyperspectral data of multiple potion samples and form a database, and combine the hyperspectral data of all points to be analyzed, and use the Lambert-Beer law to calculate the concentration of the potion in the current potion tank.

Images