Method for detecting concentration of liquid medicine after cleaning of liquid medicine tank of printed circuit board

Abstract

The invention relates to the technical field of concentration detection, in particular to a method for detecting the concentration of liquid medicine after cleaning of a liquid medicine tank of a printed circuit board, which comprises the following steps: acquiring hyperspectral data of liquid medicine in the liquid medicine tank; analyzing the difference between the absorption peaks of the hyperspectral data at each moment, and combining the distance relationship between each hyperspectral data point and the central hyperspectral data point to obtain the probability of chipping interference of each hyperspectral data point at each moment; according to the distribution rule condition of the hyperspectral data at each moment and the variation trend difference of the absorptivity of each hyperspectral data at all moments, obtaining the support device interference degree of each hyperspectral data point at each moment, and further obtaining the spectral interference index of each hyperspectral data point at each moment, so as to screen the hyperspectral data points, and obtain the spectral interference index of each hyperspectral data point at each moment. And the concentration of the liquid medicine in the liquid medicine tank is detected by combining the hyperspectral data of the liquid medicine sample. The detection precision of the liquid medicine concentration after the liquid medicine tank is cleaned can be improved.

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 liquid medicine after cleaning the liquid medicine tank of a printed circuit board. Background Art

[0002] In the production of printed circuit boards (PCBs), the detection of the concentration of the liquid medicine after cleaning the liquid medicine tank has an important application background. The environment around the liquid medicine 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 liquid medicine 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 technology, the means for detecting the concentration of the liquid medicine in the liquid medicine tank are gradually increasing. Currently, the absorbance photometry method is used to obtain an optical signal and then convert it into an electrical signal to detect the concentration of the liquid medicine. 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. At present, there are still certain deficiencies in some methods. There may be metal debris detached from the circuit board and materials for electroplating or soldering in the liquid medicine tank for cleaning the printed circuit board, which will interfere with the detection of the concentration of the liquid medicine 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 liquid medicine after cleaning the liquid medicine tank of a printed circuit board to solve the existing problems.

[0005] The method for detecting the concentration of the liquid medicine after cleaning the liquid medicine tank of a printed circuit board in this application adopts the following technical solutions: An embodiment of this application provides a method for detecting the concentration of the liquid medicine after cleaning the liquid medicine tank of a printed circuit board, including the following steps: Obtain the hyperspectral data of the liquid medicine in the liquid medicine 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; According to the spectral interference index, screen the hyperspectral data points, and combine the hyperspectral data of the liquid medicine sample to detect the concentration of the liquid medicine in the liquid medicine tank.

[0006] Preferably, the central hyperspectral data point is the hyperspectral data point corresponding to the center of the liquid medicine tank at a single moment.

[0007] Preferably, the calculation method for the possibility of debris interference of each hyperspectral data point at each moment is as follows: ; 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 value differences 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 differences 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 moment's th hyperspectral data point and the central hyperspectral data point, is a constant to prevent the denominator from being 0.

[0008] Preferably, the calculation method for the interference degree of the support device of each hyperspectral data point at each moment is as follows: ; 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.

[0009] Preferably, the obtaining of the spectral regularity degree further includes: clustering all hyperspectral data points at the th moment, and taking the reciprocal of the variance of the Euclidean distances between any two hyperspectral data points in the cluster where the th hyperspectral data point is located as the spectral regularity degree of the th hyperspectral data point at the th moment.

[0010] 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.

[0011] Preferably, the obtaining of the trend intensity difference further is the average value of the absolute value of the difference between the trend intensity of the absorption rate sequence of the th hyperspectral data point at the th moment and the trend intensity of the absorption rate sequences of other hyperspectral data points at the th moment.

[0012] Preferably, the spectral disturbance index of each hyperspectral data point at each moment is the sum value of the possibility of being disturbed by debris and the disturbance degree of the support device.

[0013] Preferably, the screening of the hyperspectral data points further includes: extracting the segmentation threshold of the spectral disturbance index of all hyperspectral data points, screening out the hyperspectral data points with the spectral disturbance index less than the segmentation threshold, and taking them as the points to be analyzed.

[0014] Preferably, the detection of the potion concentration in the potion tank further includes: obtaining the hyperspectral data of multiple potion samples to form a database, and combining the hyperspectral data of all points to be analyzed, and using the Lambert-Beer law to calculate the potion concentration in the current potion tank.

[0015] This application has at least the following beneficial effects: By analyzing the disturbance situation of the potion in the printed circuit board potion tank, this application deduces 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 currently, only removing environmental noise cannot avoid the interference of material debris and support devices in the potion tank on the hyperspectral data, and further improving the accuracy of potion concentration detection. Description of the Drawings

[0016] In order 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 drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to these drawings.

[0017] Figure 1 It is the step flow chart of the potion concentration detection method for the printed circuit board potion tank after cleaning provided by this application. Detailed implementation manners

[0018] In order to further elaborate on the technical means and effects adopted by this application to achieve the intended invention purpose, the following, in combination with the accompanying drawings and preferred embodiments, details the specific implementation manners, structures, features, and effects of the method for detecting the chemical solution concentration after cleaning a chemical solution tank for a printed circuit board according to this 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.

[0019] 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 also includes elements inherent to such article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the article or device including the said element. Additionally, the term "and / or" used herein includes any and all combinations of any one of the one or more related listed items. All technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs.

[0020] 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 this application with reference to the accompanying drawings.

[0021] The method for detecting the chemical solution concentration after cleaning a chemical solution tank for a printed circuit board provided by one embodiment of this application. Specifically, please refer to Figure 1 , including the following steps: Step 1: Obtain the hyperspectral data of the chemical solution in the chemical solution tank.

[0022] In this embodiment, a hyperspectral camera is set directly above the chemical solution tank. For the chemical solution in the chemical solution tank, after completing the cleaning of a printed circuit board once, hyperspectral data is collected every interval of time T, and the method of first derivative spectroscopy and quadratic polynomial fitting is used to obtain the band length corresponding to the absorption peak and the absorption peak intensity of the hyperspectral data at each hyperspectral data point. The methods of first derivative spectroscopy and quadratic polynomial fitting are both well-known technologies. Among them, in this embodiment, T = 10s.

[0023] 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 relationship between each hyperspectral data point and the central hyperspectral data at each moment to obtain the possibility of each hyperspectral data point being interfered by debris at each moment.

[0024] Before the printed circuit board is cleaned, it goes through 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 data collection using a 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 the light of a specific wavelength absorbed by some material debris interferes with the absorption spectrum of the chemical solution components, resulting in overlapping absorption peaks, and thus the absorption peak intensity is too high to distinguish the actual chemical solution concentration.

[0025] Since the chemical solution is not completely static 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 the mixture of material debris and chemical solution at different times, or there may be only hyperspectral data of the chemical solution components. Therefore, the absorption peak intensity and the wavelength length corresponding to the absorption peak of the hyperspectral data of this hyperspectral data point will also change greatly over time. And because the printed circuit board cleaning process mainly occurs in the middle of the chemical solution tank, 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.

[0026] 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 moment of each hyperspectral data point is constructed: ; In the formula, is the possibility of being interfered by debris at the th hyperspectral data point at the th moment, is the average value of the difference in the peak values of the absorption peaks at the th hyperspectral data point at the th moment and the adjacent moments, is the average value of the difference in the wavelength lengths corresponding to the absorption peaks at the th hyperspectral data point at the th moment and the adjacent moments, is the Euclidean distance between the th hyperspectral data point 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 chemical solution tank at the th moment, is a constant to prevent the denominator from being 0, and its value range is from 0 to 0.1. In this embodiment, .

[0027] 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, it indicates that there is a greater possibility of floating of material debris in the hyperspectral data points, and the hyperspectral data is more likely to be affected by interference.

[0028] 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 the hyperspectral data at all moments, obtain the interference degree of the support device at 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.

[0029] When cleaning a printed circuit board, a support device such as a nail bed fixing device or a floating rack is needed in the chemical solution tank to fix the printed circuit board for more comprehensive cleaning. However, this support device will also have a certain impact on the hyperspectral data points of the chemical solution in the chemical solution. Since the support device is usually fixed in position and at fixed intervals, the interference of the hyperspectral data points at the position of the support device calculated by the above method is relatively small. Therefore, there is a deviation when using this data to calculate the chemical solution concentration, so further analysis is required.

[0030] 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 chemical solution tank completes a round of cleaning of the printed circuit board, the floating situation of the chemical solution in the chemical solution 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.

[0031] Therefore, further, in this embodiment, taking all the hyperspectral data points collected at a single moment as an example, cluster all the hyperspectral data collected at a single moment. Preferably, in this example, the DPC density clustering algorithm is used, and the absolute value of the difference between the absorption rates of the hyperspectral data is used as the metric distance. Among them, in this embodiment, considering that for a single hyperspectral data point, there may be multiple absorption peaks of material debris mixed with the chemical solution at different moments. Therefore, in this embodiment, the absorption rate of a single hyperspectral data at a single moment is the average value of the absorption rates corresponding to all the absorption peaks of the hyperspectral data at a single moment. During the clustering process, the cut-off distance is set to 3, and each cluster after clustering and partitioning of all the hyperspectral data at a single moment is output. The DPC density clustering algorithm is a well-known technology, and the process thereof will not be elaborated in this embodiment. At the same time, for each hyperspectral data point, arrange the absorption rates at all moments in the order of the sampling moments to construct the absorption rate sequence of each hyperspectral data point, which is used to characterize the specific situation of the change of the absorption rate of the hyperspectral data point over time.

[0032] Based on the above analysis, the influence of the liquid medicine in the liquid medicine tank by the support device at the th moment is represented by the following relational expression, and the interference degree of the support device for each hyperspectral data point at each moment is constructed: ; In the formula, is the interference degree of the support device for 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 degree of the trend intensity of the th hyperspectral data point, which is the difference in the trend intensity of the absorption rate sequence between the th moment and the absorption rate sequences of the remaining hyperspectral data points.

[0033] Among them, for each clustering cluster obtained by clustering all hyperspectral data points at the th moment, the reciprocal of the variance of the Euclidean distances between any two hyperspectral data points in the clustering cluster where the th hyperspectral data point is located is taken as the spectral regularity degree of the th hyperspectral data point at the th moment. It should be noted that in the process of taking the reciprocal, to avoid the case where the denominator is zero, a constant to avoid the denominator being zero can be added to the denominator. In this embodiment, the value is 0.01; The acquisition of the difference degree of the trend intensity is further the average value of the absolute value of the difference between the trend intensity of the absorption rate sequence of the th hyperspectral data point at the th moment and the trend intensity of the absorption rate sequences of other hyperspectral data points at the th moment. It should be noted that the calculation method of the trend intensity is a prior art and will not be elaborated in this embodiment.

[0034] It can be understood that: when the difference fluctuation between 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 the 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.

[0035] According to the interference degree of the support device and the possibility of being interfered by debris at each moment for 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: ; In the formula, 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.

[0036] It can be understood that: when the possibility of the th hyperspectral data point being 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 spectral data in this hyperspectral data point is stronger, and the accuracy of detecting the liquid medicine concentration using this data is lower.

[0037] 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.

[0038] Using the spectral interference index that can be calculated and obtained through the above process, taking all spectral interference indices as inputs, and using the cross-validation method, the output is the segmentation threshold of the spectral interference index. When the spectral interference index of a hyperspectral data point is greater than or equal to the segmentation threshold, it indicates that the interference degree of this hyperspectral data point is stronger and it is not suitable as data support for detecting the liquid medicine concentration. On the contrary, when the spectral interference index of a hyperspectral data point is less than the segmentation threshold, it indicates that the interference degree of this hyperspectral data point is lower and it can be used as data support for detecting the liquid medicine concentration, and such hyperspectral data points are used as points to be analyzed.

[0039] Finally, for the current sampling moment, extract the hyperspectral data of all points to be analyzed, and combine with the database constructed by the hyperspectral data of the liquid medicine sample, that is, obtain the hyperspectral data of multiple liquid medicine samples and form a database. It should be noted that the implementer of the liquid medicine sample selects it according to the actual situation in the actual application scenario, and this embodiment does not make special restrictions on this. Further, use Lambert-Beer's law to calculate the concentration of the liquid medicine in the current liquid medicine tank, and complete the detection of the concentration of the liquid medicine in the liquid medicine tank.

[0040] It should be understood that references to "one embodiment" or "some embodiments" etc. described in the specification of the present application mean that specific features, structures or characteristics described in connection with that embodiment are included in one or more embodiments of the present application. Thus, when "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments", etc. appear at different places in this specification, they do not necessarily 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.

[0041] It should be noted that the above sequence of embodiments of the present 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 magnitudes of the sequence numbers of the steps in the embodiments do not mean the sequence of execution is prior or subsequent. 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.

[0042] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; 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 concentration of a solution after cleaning a printed circuit board solution tank, characterized in that: The following steps are involved: Obtain the hyperspectral data of the medicine in the medicine tank; Analyze the peak difference of the absorption peak of each hyperspectral data at each time and the difference 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 time to obtain the possibility of debris interference for each hyperspectral data point at each time; 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, the interference degree of the support device of each hyperspectral data point at each moment is obtained, and combined with the possibility of interference by debris, the spectral interference index of each hyperspectral data point at each moment is obtained; According to the spectral disturbance index, the hyperspectral data points are screened, and the concentration of the medicine in the medicine tank is detected in combination with the hyperspectral data of the medicine sample.

2. The method for detecting the concentration of a chemical solution after cleaning a printed circuit board chemical solution tank according to claim 1, characterized in that: The central hyperspectral data point is a hyperspectral data point corresponding to the center of the medicine tank at a single moment.

3. The method for detecting the concentration of the chemical solution after cleaning the printed circuit board chemical solution tank according to claim 1, characterized in that: The calculation method of the possibility of each hyperspectral data point being disturbed by debris at each moment is: ； In the formula, For the The hyperspectral data points are The probability of being disturbed by debris at a given moment, For the The hyperspectral data points are The average of the difference between the absorption peak value at the moment and the left and right adjacent moments, For the The hyperspectral data points are The average value of the wavelength difference between the absorption peak at a moment and the left and right adjacent moments, For the Moment The Euclidean distance between the hyperspectral data points and the central hyperspectral data point, To prevent the denominator from being a constant of 0.

4. The method for detecting the concentration of a chemical solution after cleaning a printed circuit board chemical solution tank according to claim 1, characterized in that: The calculation method of the support device interference degree of each hyperspectral data point at each moment is: ； In the formula, For the The hyperspectral data points are The interference degree of the supporting device at a certain moment, For the The hyperspectral data points are The spectral regularity at each moment, For the The trend intensity difference between the hyperspectral data point in the The trend intensity difference of the absorption rate series at each moment.

5. The method for detecting the concentration of the chemical solution after cleaning the printed circuit board chemical solution tank according to claim 4, characterized in that: The acquisition of the spectral regularity further comprises: All the hyperspectral data points at the moment are clustered. 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 The hyperspectral data points are The spectral regularity at each moment.

6. The method for detecting the concentration of the chemical solution after cleaning the printed circuit board chemical solution tank according to claim 4, characterized in that: The construction of the absorbance sequence includes: arranging the absorbances of the hyperspectral data points at all sampling moments in the order of the sampling moments to form an absorbance sequence.

7. The method for detecting the concentration of the chemical solution after cleaning the printed circuit board chemical solution tank according to claim 4, characterized in that: The trend strength difference is further obtained as The hyperspectral data points are The trend strength of the absorbance series at the moment is consistent with that of other hyperspectral data points at the The difference in the trend strength of the absorption rate series at each moment is taken as the average of the absolute values.

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

9. The method for detecting the concentration of a chemical solution after cleaning a printed circuit board chemical solution tank according to claim 1, characterized in that: The screening of the hyperspectral data points further comprises: The segmentation threshold of the spectral disturbance index of all hyperspectral data points is extracted, and the hyperspectral data points whose spectral disturbance index is less than the segmentation threshold are screened out and used as the points to be analyzed.

10. The method for detecting the concentration of the chemical solution after cleaning the printed circuit board chemical solution tank according to claim 9, characterized in that: The detection of the concentration of the medicine in the medicine tank further comprises: The hyperspectral data of multiple medicine samples are obtained and formed into a database. The hyperspectral data of all points to be analyzed are combined, and the Lambert-Beer law is used to calculate the concentration of the medicine in the current medicine tank.

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