A method and system for rheological detection of the viscosity of an enema liquid

Abstract

The present application relates to the technical field of drug detection, and in particular to a rheological detection method and system for the viscosity of enema liquid medicine, which solves the technical problem of the influence of interference on the measurement accuracy of experimental instruments. The method comprises: acquiring a liquid surface image of the enema liquid medicine in the flow process in a capillary viscometer through an image acquisition device; performing morphological feature analysis on the liquid surface image to obtain image features of the enema liquid medicine, and evaluating a pollution degree value of the capillary viscometer based on the image features; the image features include at least one of curvature features, symmetry features and smoothness features; and determining the viscosity measurement reliability of the capillary viscometer according to the pollution degree value.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of drug detection, and in particular to a rheological detection method and system for the viscosity of an enema liquid. BACKGROUND

[0002] As a drug preparation directly acting on the intestinal tract, the viscosity of an enema liquid is a key physical parameter affecting the flowability and distribution uniformity of the drug in the intestinal tract. The flowability and distribution uniformity directly determine the adhesion area and absorption efficiency of the drug on the intestinal mucosa, and thus affect the clinical treatment effect. Therefore, in the production quality control, product inspection and research and development process of the enema liquid, accurate measurement of the viscosity is an important technical link for ensuring that the product quality meets the pharmaceutical standards and guaranteeing the stability of the clinical treatment effect.

[0003] At present, the mainstream method for measuring the viscosity of an enema liquid in the industry mainly relies on experimental instruments such as a capillary viscometer. The capillary viscometer is based on the Hagen-Poiseuille law and calculates the viscosity by measuring the flow time of the liquid in the capillary. However, experimental instruments usually have strict detection requirements for the internal structure. During use, the experimental instruments may have residual fine particles, internal wear and tear, etc., thereby changing the normal flow state or mechanical response characteristics of the liquid in the instrument, resulting in deviation of the viscosity measurement results, seriously affecting the accuracy and repeatability of the detection data, and failing to provide a reliable basis for the quality control of the enema liquid. SUMMARY

[0004] In order to solve the technical problem that the experimental instrument is disturbed to affect the measurement accuracy, the purpose of the present application is to provide a rheological detection method for the viscosity of an enema liquid, and the technical scheme adopted is as follows:

[0005] An image acquisition device is used to obtain a liquid surface image of the enema liquid during flow in the capillary viscometer;

[0006] Morphological feature analysis is performed on the liquid surface image to obtain image features of the enema liquid, and a pollution degree value of the capillary viscometer is evaluated based on the image features; the image features include at least one of a curvature feature, a symmetry feature and a smoothness feature;

[0007] The viscosity measurement reliability of the capillary viscometer is determined according to the pollution degree value.

[0008] In one possible implementation, the liquid surface image includes a first liquid surface image of a uniform inner diameter region of the enema liquid in the capillary viscometer and / or a second liquid surface image of a non-uniform inner diameter region of the enema liquid in the capillary viscometer.

[0009] In one possible implementation, the method includes:

[0010] performing morphological feature analysis on the first liquid surface image to obtain first image features of the enema liquid in the uniform inner diameter region, and evaluating a regional pollution degree value of the uniform inner diameter region based on the first image features; the first image features include a curvature standard deviation size mean value, a symmetry index mean value, and a smoothness index mean value;

[0011] performing morphological feature analysis on the second liquid surface image to obtain second image features of the enema liquid in the non-uniform inner diameter region, and evaluating a regional pollution degree value of the non-uniform inner diameter region based on the second image features; the second image features include a correlation coefficient of a curvature change rate and a pipe diameter change rate;

[0012] determining the pollution degree value of the capillary viscometer based on the regional pollution degree value of the uniform inner diameter region and the regional pollution degree value of the non-uniform inner diameter region.

[0013] In a possible implementation, the method comprises:

[0014] based on the first liquid surface image, dividing the uniform inner diameter region into a plurality of sub-regions, and extracting first image feature data of the enema liquid on each sub-region; the first image feature data includes a curvature radius of the liquid surface of the enema liquid on the sub-region, an offset distance, and an edge fitting error; the curvature radius is the radius of a fitting circle obtained by fitting the liquid surface of the enema liquid on the sub-region; the offset distance is the distance between the center of the fitting circle and the center of the uniform inner diameter region; the edge fitting error is used to represent the deviation between the points on the edge of the liquid surface of the enema liquid on the sub-region and the corresponding points on the edge of the fitting circle;

[0015] determining the first image features of the enema liquid corresponding to each sub-region of the uniform inner diameter region according to the first image feature data on each sub-region;

[0016] evaluating the regional pollution degree value of the uniform inner diameter region based on the first image features corresponding to each sub-region.

[0017] In a possible implementation, the method comprises:

[0018] for each sub-region of the uniform inner diameter region, determining the curvature according to the curvature radius of the liquid surface of the enema liquid on the sub-region, and determining the curvature standard deviation size mean value according to the curvature corresponding to the sub-region;

[0019] for each sub-region of the uniform inner diameter region, calculating the symmetry index corresponding to the sub-region according to the offset distance of the liquid surface of the enema liquid on the sub-region, and determining the symmetry index mean value according to the symmetry index corresponding to the sub-region;

[0020] for each sub-region of the uniform inner diameter region, calculating the smoothness index corresponding to the sub-region according to the edge fitting error of the liquid surface of the enema liquid on the sub-region, and determining the smoothness index mean value according to the smoothness index corresponding to the sub-region.

[0021] In a possible implementation, the method comprises:

[0022] The regional pollution degree value of the uniform inner diameter region is determined according to the mean value of the curvature standard deviation, the mean value of the symmetry index, and the mean value of the smoothness index; the mean value of the curvature standard deviation is positively correlated with the regional pollution degree value of the uniform inner diameter region; the mean value of the symmetry index and the mean value of the smoothness index are negatively correlated with the regional pollution degree value of the uniform inner diameter region, respectively.

[0023] In a possible implementation, the method comprises:

[0024] Based on the second liquid surface image, second image feature data of the enema medicinal liquid at a plurality of positions in the non-uniform inner diameter region is extracted; the second image feature data includes a change rate of the tube diameter of the capillary viscometer at the corresponding position and a change rate of the curvature of the liquid surface of the enema medicinal liquid at the corresponding position;

[0025] Second image features of the enema medicinal liquid in the non-uniform inner diameter region are determined according to the second image feature data at the plurality of positions.

[0026] Based on the second image features, a regional pollution degree value of the non-uniform inner diameter region is evaluated.

[0027] In a possible implementation, the method comprises:

[0028] Correlation analysis is performed according to the change rate of the tube diameter of the capillary viscometer and the change rate of the curvature of the liquid surface of the enema medicinal liquid at the plurality of positions, to determine a correlation coefficient of the change rate of the curvature and the change rate of the tube diameter.

[0029] In a possible implementation, the method comprises:

[0030] The regional pollution degree value of the non-uniform inner diameter region is determined according to an absolute value of the correlation coefficient of the change rate of the curvature and the change rate of the tube diameter; the absolute value of the correlation coefficient is negatively correlated with the regional pollution degree value of the uniform inner diameter region.

[0031] The present application provides a rheological detection system for the viscosity of enema medicinal liquid, comprising a capillary viscometer, an image acquisition device, and an electronic device.

[0032] The capillary viscometer is used to measure the viscosity of the enema medicinal liquid.

[0033] The image acquisition device is used to acquire liquid surface images of the enema medicinal liquid during the flow process in the capillary viscometer.

[0034] The electronic device is used to acquire a liquid surface image of the enema medicinal liquid in the flow process in the capillary viscometer through an image acquisition device; a morphological feature analysis is performed on the liquid surface image to obtain an image feature of the enema medicinal liquid, and a pollution degree value of the capillary viscometer is evaluated based on the image feature; the image feature includes at least one of a curvature feature, a symmetry feature and a smoothness feature; and the viscosity measurement reliability of the capillary viscometer is determined according to the pollution degree value.

[0035] The present application has the following beneficial effects:

[0036] Based on the above technical solution, the present application acquires the liquid surface image of the enema medicinal liquid in the flow process in the capillary viscometer through the image acquisition device, avoids the subjective error of manual observation of capillary pollution, then performs feature analysis on the acquired liquid surface image, and evaluates the pollution degree according to the extracted image features such as curvature, symmetry and smoothness, so as to accurately capture the subtle pollution that is difficult to distinguish with the naked eye. In this way, the present application can determine the measurement reliability based on the pollution degree, effectively screen the reliable detection data, avoid the viscosity measurement deviation caused by equipment pollution, and significantly improve the accuracy and repeatability of the enema medicinal liquid viscosity detection. BRIEF DESCRIPTION OF DRAWINGS

[0037] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, a brief introduction will be given below to the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can also obtain other drawings according to these drawings without any creative effort.

[0038] Figure 1 A system architecture diagram of a rheological detection system for enema medicinal liquid viscosity provided by an embodiment of the present application;

[0039] Figure 2 A structural schematic diagram of a capillary viscometer provided by an embodiment of the present application;

[0040] Figure 3 A flowchart of a rheological detection method for enema medicinal liquid viscosity provided by an embodiment of the present application;

[0041] Figure 4 A shape diagram of a liquid surface in a capillary viscometer for enema medicinal liquid provided by an embodiment of the present application;

[0042] Figure 5 A region diagram of a non-uniform inner diameter region and a uniform inner diameter region in a capillary viscometer provided by an embodiment of the present application;

[0043] Figure 6Another flowchart of a rheological detection method for viscosity of an enema liquid provided by one embodiment of the present application is shown in FIG. 2.

[0044] Figure 7 Another flowchart of a rheological detection method for viscosity of an enema liquid provided by one embodiment of the present application is shown in FIG. 2.

[0045] Figure 8 Another flowchart of a rheological detection method for viscosity of an enema liquid provided by one embodiment of the present application is shown in FIG. 2. DETAILED DESCRIPTION

[0046] In order to further illustrate the technical means and effects taken by the present application to achieve the predetermined purposes, the specific embodiments, structures, features and effects of a rheological detection method and system for viscosity of an enema liquid according to the present application are described in detail as follows in combination with the drawings and preferred embodiments. 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.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0048] In view of the technical problem that the experimental instrument is disturbed to affect the measurement accuracy, the present application provides a rheological detection method and system for viscosity of an enema liquid, which acquires liquid surface images of the enema liquid in the flow process in the capillary viscometer through an image acquisition device, avoids subjective errors of manual observation of capillary pollution, and then performs feature analysis on the acquired liquid surface images and evaluates the pollution degree according to the extracted image features such as curvature, symmetry and smoothness, so as to accurately capture subtle pollution that is difficult to distinguish with the naked eye. In this way, the present application can determine the measurement reliability based on the pollution degree, effectively screen reliable detection data, avoid viscosity measurement deviation caused by equipment pollution, and significantly improve the accuracy and repeatability of enema liquid viscosity detection.

[0049] The specific scheme of the rheological detection method and system for viscosity of an enema liquid provided by the present application is described in detail below in combination with the drawings.

[0050] Figure 1 An architectural diagram of the rheological detection system for viscosity of an enema liquid provided by the present application is shown in FIG. 1. Figure 1 As shown in the figure, the rheological detection system for viscosity of an enema liquid includes a capillary viscometer 101, an image acquisition device 102 and an electronic device 103.

[0051] The capillary viscometer 101 is used to measure the viscosity of the enema liquid. For example, as shown in FIG. 1, the capillary viscometer 101 can be a U-shaped capillary viscometer made of transparent glass material, the inner diameter of which is calibrated in advance and the surface of which is smooth. To eliminate the influence of temperature on the viscosity of the liquid, the capillary viscometer 101 can be matched with a constant temperature water bath (with a temperature control accuracy of at least ±0.1℃), and the capillary tube of the capillary viscometer 101 is immersed in the water bath during use. Figure 2

[0052] The image acquisition device 102 is used to acquire the liquid surface image of the enema liquid flowing in the capillary viscometer. For example, the image acquisition device 102 can be composed of a complementary metal oxide semiconductor (CMOS) camera, a macro lens, and an illumination module.

[0053] The CMOS camera is selected to have high resolution and high frame rate to ensure that the subtle morphological changes of the liquid surface (usually in the shape of a crescent, so it is also called meniscus) can be captured. The macro lens is used to enlarge the image and clearly capture the details of the meniscus in the capillary. The illumination module uses a diffuse light-emitting diode (LED) cold light source to provide uniform illumination from the side or back of the capillary, avoiding profile blurring caused by mirror reflection.

[0054] In some embodiments, the image acquisition device 102 can be fixed on a support, and the lens is directed to the liquid surface area of the capillary (including the uniform inner diameter area and the non-uniform inner diameter area), ensuring stable acquisition angle.

[0055] The electronic device 103 is used to acquire the liquid surface image of the enema liquid flowing in the capillary viscometer through the image acquisition device, analyze the morphological features of the liquid surface image, obtain the image features of the enema liquid, and evaluate the pollution degree value of the capillary viscometer based on the image features.

[0056] The image features include at least one of the curvature feature, the symmetry feature, and the smoothness feature; and the viscosity measurement reliability of the capillary viscometer is determined according to the pollution degree value.

[0057] For example, the electronic device 103 can be a computer, an industrial control machine, or other devices with data processing and storage functions, which is connected to the image acquisition device through a data line or a wireless link.

[0058] ​The rheological detection system for enema solution viscosity provided in this embodiment achieves automation and precision in enema solution viscosity detection through the coordinated operation of a capillary viscometer 101, an image acquisition device 102, and an electronic device 103. The capillary viscometer 101 provides a stable measurement medium, the image acquisition device 102 ensures the clarity and integrity of the liquid surface image, providing high-quality data for subsequent analysis, and the electronic device 103 integrates image analysis, contamination assessment, and reliability judgment, avoiding human error. The entire system has a simple structure and is easy to operate, meeting the needs of pharmaceutical companies, quality inspection agencies, and R&D units for rapid, accurate, and repeatable detection of enema solution viscosity, and is particularly suitable for quality control processes with high cleanliness requirements.

[0059] It should be noted that the various embodiments of this application can be referenced or learned from each other. For example, the same or similar steps, method embodiments, system embodiments and device embodiments can be referenced from each other without limitation.

[0060] Please see Figure 3 The diagram illustrates a rheological method for detecting the viscosity of an enema solution according to an embodiment of the present invention. The method includes the following steps:

[0061] Step 301: Acquire images of the liquid surface of the enema solution during its flow in a capillary viscometer using an image acquisition device.

[0062] When the viscosity of the enema solution is measured using a capillary viscometer, the liquid surface of the enema solution appears as a crescent-shaped meniscus. For example, such as... Figure 4 As shown, a meniscus is a convex-concave liquid surface formed by the combined effects of surface tension and the wettability of the solid tube wall within a liquid, such as in a capillary tube. Its specific shape is determined by the contact angle between the liquid and the tube wall material, and is the result of mechanical equilibrium at the solid-liquid-gas three-phase interface.

[0063] For example, the image acquisition device can acquire images of the liquid surface of the enema solution during its flow in the capillary viscometer in real time at preset time intervals, thereby obtaining morphological image information of the liquid surface of the enema solution at various positions in the capillary viscometer for subsequent analysis.

[0064] Step 302: Perform morphological feature analysis on the liquid surface image to obtain the image features of the enema solution, and evaluate the contamination level of the capillary viscometer based on the image features.

[0065] The image features include at least one of curvature features, symmetry features, and smoothness features.

[0066] It should be noted that the curvature of the liquid level of the enema liquid is directly related to the interfacial tension and pressure difference. In an ideal clean capillary tube, the meniscus should present a stable, symmetrical and smooth geometric shape. Any pollution will destroy the original mechanical balance, leading to changes in contact angle, curvature distortion or profile asymmetry. Therefore, the present application can collect the liquid level image during the flow of the enema liquid in the capillary viscometer, analyze the liquid level shape, and extract the curvature feature, symmetry feature and smoothness feature, so as to realize the objective and quantitative evaluation of the liquid level state.

[0067] The curvature feature is used to quantify the bending degree of the liquid level, which essentially reflects the bending state of the liquid level formed by the interaction of surface tension and pipe wall. When the capillary tube is polluted, the interfacial tension balance between the liquid and the pipe wall will change, leading to abnormal fluctuations in the bending degree of the liquid level. The more obvious the fluctuations, the more serious the pollution.

[0068] The symmetry feature is used to characterize the symmetry degree of the liquid level profile relative to the center axis of the capillary tube, which is a key parameter for measuring the regularity of the liquid level shape. If the capillary tube wall is clean, the liquid level will present a regular shape with the center axis of the capillary tube as the symmetry line under the action of uniform interfacial tension. When the pipe wall is polluted, the local interfacial tension imbalance will destroy this symmetry, and the lower the symmetry degree, the higher the pollution degree.

[0069] The smoothness feature refers to the flatness and continuity of the liquid level edge profile, which is used to characterize the regularity of the liquid level shape. In a clean capillary tube, the interaction between the liquid and the pipe wall is uniform, and the liquid level edge will form a continuous and flat profile. If the pipe wall has pollution residues or attached impurities, it will cause uneven force on the liquid level, resulting in irregular protrusions, depressions or breaks in the edge profile. The more uneven the profile, the worse the smoothness, and the more serious the pollution.

[0070] The present application can quantify the pollution degree value of the capillary viscometer based on at least one of the above image features.

[0071] Step 303, determining the viscosity measurement reliability of the capillary viscometer according to the pollution degree value.

[0072] It should be noted that pollution will introduce systematic errors, causing the measured value to deviate from the true value. The present application converts the abstract pollution quantity into a specific reliability index by establishing a quantitative decay model between the pollution degree value and the viscosity measurement reliability, so as to objectively and quantitatively classify the measurement results according to the pre-set threshold, and control the risk, ensuring the reliability of the output data. The viscosity measurement reliability is negatively correlated with the pollution degree value.

[0073] For example, the viscosity measurement reliability satisfies the following formula:

[0074]

[0075] wherein, viscosity measurement reliability of the capillary viscometer, pollution degree value of the capillary viscometer, is an attenuation coefficient, which is an empirical constant and can be calibrated by experiment.

[0076] In some embodiments, the viscosity measurement reliability level can be divided by a threshold value, for example, if the viscosity measurement reliability is greater than or equal to 0.9, it indicates that the measurement reliability is high and the data can be directly used; if 0.7≤viscosity measurement reliability<0.9, it indicates that the measurement reliability is moderate and needs to be comprehensively judged in combination with other detection results; if the viscosity measurement reliability is less than 0.7, it indicates that the measurement reliability is insufficient and needs to be re-detected after cleaning the capillary.

[0077] Based on the above technical solutions, the present application obtains the liquid surface image of the enema liquid flowing in the capillary viscometer through the image acquisition device, avoiding the subjective error of manual observation of capillary pollution. Then, the obtained liquid surface image is analyzed for features, and the pollution degree is evaluated according to the extracted image features such as curvature, symmetry and smoothness, so as to accurately capture the subtle pollution that is difficult to distinguish with the naked eye. In this way, the present application can determine the measurement reliability based on the pollution degree, effectively screen the reliable detection data, avoid the viscosity measurement deviation caused by equipment pollution, and significantly improve the accuracy and repeatability of enema liquid viscosity detection.

[0078] Further, due to the complexity of the structure of the capillary viscometer, the morphological characteristics of the liquid surface in the pipe wall of different shapes and structures are different, therefore, the present application can divide the capillary viscometer according to the shape and structure, respectively analyze the features and quantify the pollution, so as to obtain the final pollution degree value of the capillary viscometer.

[0079] As a possible embodiment of the present application, the liquid surface image includes a first liquid surface image of the enema liquid in a uniform inner diameter region of the capillary viscometer and / or a second liquid surface image of the enema liquid in a non-uniform inner diameter region of the capillary viscometer.

[0080] Wherein, the inner diameter of the pipe wall in the uniform inner diameter region of the capillary viscometer remains unchanged along the axial direction; the inner diameter of the pipe wall in the non-uniform inner diameter region of the capillary viscometer changes along the axial direction.

[0081] It should be noted that the capillary viscosity plan in the embodiments of the present application can be divided into one or more non-uniform inner diameter regions and one or more uniform inner diameter regions. The first liquid surface image includes a plurality of liquid surface images collected during the flow of the enema liquid in each non-uniform inner diameter region, and the second liquid surface image includes a plurality of liquid surface images collected during the flow of the enema liquid in each uniform inner diameter region. For example, the image acquisition device can acquire images at a preset acquisition frequency (e.g., 10 frames per second), and the enema liquid surface in the acquired images located in the non-uniform inner diameter region is divided into the first liquid surface image, and the enema liquid surface in the acquired images located in the uniform inner diameter region is divided into the second liquid surface image.

[0082] For example, as shown in FIG. 1, the capillary viscometer usually has a measuring ball and a liquid storage ball, and the part of the region belongs to the non-uniform inner diameter region, and the curvature changes, thereby changing the uniformity of the capillary inner diameter, and the other part of the region belongs to the uniform inner diameter region. Figure 5

[0083] The subjective error of the naked eye in judging the uniformity of the capillary inner diameter of the measuring region is large, and therefore, the present application can realize the objectivity and quantification of the division of the measuring region based on the image processing technology, and avoid the error of manual judgment.

[0084] For example, the present application can first acquire images of the blank capillary viscometer (without injecting the liquid medicine) to obtain a high-resolution gray image (in the axial direction of the capillary), extract the capillary inner wall edge by an edge detection operator (such as a Canny operator) to obtain a binary capillary edge image . For example, the actual physical width satisfies the following formula:

[0085]

[0086]

[0087] is the actual physical width of the capillary viscometer at the coordinate , is the conversion coefficient of the pixel distance and the actual distance, and is the pixel width of the capillary viscometer at the coordinate .

[0088] ​​​​​​​Thus, a function mapping relationship between the inner diameter of the capillary of the capillary viscometer and the axial direction position is obtained . A first derivative of the function is calculated If , it indicates that the inner diameter of the tube wall at the current position remains unchanged along the axial direction, i.e., the current position belongs to the uniform inner diameter region. If , it indicates that the inner diameter of the tube wall at the current position changes along the axial direction, i.e., the current position belongs to the non-uniform inner diameter region, so that the capillary viscosity plan can be divided into various uniform inner diameter regions and non-uniform inner diameter regions.

[0089] As a possible embodiment of the present application, in combination with Figure 3 , the step 302 can be implemented by the following steps, as shown in Figure 6 .

[0090] The step 601 performs morphological feature analysis on the first liquid surface image to obtain a first image feature of the enema liquid in the uniform inner diameter region, and evaluates a regional pollution degree value of the uniform inner diameter region based on the first image feature.

[0091] The first image feature includes a curvature standard deviation size average value, a symmetry index average value, and a smoothness index average value.

[0092] The curvature standard deviation size average value is an average quantitative index of the fluctuation degree of the liquid surface curvature in the plurality of first liquid surface images, and reflects the stability of the curvature change over time or position. When the capillary is polluted, the uneven force on the liquid surface will cause frequent fluctuations in the curvature. The greater the average value, the more serious the pollution.

[0093] The symmetry index average value is an average value of the symmetry degree of the liquid surface relative to the center axis of the capillary in the plurality of first liquid surface images, and is a comprehensive parameter for measuring the regularity of the liquid surface morphology. When the tube wall is clean, the symmetry of the liquid surface is stable, and the pollution is less severe. After pollution, the local interfacial tension is unbalanced, the symmetry degree decreases, and the smaller the average value, the more serious the pollution.

[0094] The smoothness index average value is an average value of the smoothness degree of the liquid surface edge in the plurality of first liquid surface images, and represents the overall level of the regularity of the edge morphology. When the tube wall is clean, the edge forms a smooth profile under the action of uniform force, and the pollution is less severe. Pollution residues will cause irregular protrusions or depressions on the edge, and the smaller the average value, the more serious the pollution.

[0095] It should be noted that in the uniform inner diameter area of the capillary viscometer, the curvature, symmetry and smoothness of the liquid surface are a direct manifestation of the balance of the solid-liquid-gas three-phase interfacial tension. A clean capillary viscometer environment will exhibit a highly stable, axisymmetric and smooth liquid surface, with a constant curvature radius and contact angle. Any contamination will non-uniformly change the local interfacial energy, destroy the original mechanical balance, cause the contact angle to change, the curvature to distort, the symmetry to be lost, or the profile to fluctuate.

[0096] Therefore, the present application can quantitatively extract the first image feature of the enema liquid in the uniform inner diameter area by image processing technology, and convert the abstract pollution phenomenon into a quantifiable feature parameter.

[0097] Step 602, morphological feature analysis is performed on the second liquid surface image to obtain a second image feature of the enema liquid in the non-uniform inner diameter area, and a regional pollution degree value of the non-uniform inner diameter area is evaluated based on the second image feature.

[0098] The second image feature includes a correlation coefficient of the curvature change rate and the pipe diameter change rate.

[0099] The pipe diameter change rate refers to the speed of the change of the pipe diameter with the axial position of the capillary in the non-uniform inner diameter area, reflecting the change trend of the pipe diameter distribution in this area. The pipe diameter of the non-uniform inner diameter area (such as the measuring ball) naturally changes, and the change trend is stable in a clean state.

[0100] The curvature change rate refers to the speed of the change of the liquid surface curvature with the axial position of the capillary in the non-uniform inner diameter area, reflecting the response of the bending degree of the liquid surface to the change of the pipe diameter. In a clean state, the curvature change will be adjusted synchronously with the natural change of the pipe diameter.

[0101] The correlation coefficient refers to an index quantifying the degree of coordination between the pipe diameter change rate and the curvature change rate, with a value range of [-1, 1]. The more coordinated the changes of the two (i.e., the absolute value of the correlation coefficient is closer to 1), the more uniform the force of the pipe wall on the liquid surface, and the cleaner the capillary. Pollution will destroy this coordination, resulting in a decrease in the absolute value of the correlation coefficient and a more serious pollution.

[0102] It should be noted that in an ideal clean capillary viscometer, for the non-uniform inner diameter area, the change of the liquid surface curvature will follow the Young-Laplace equation, and the change rate will be highly coordinated with the change rate of the inner diameter of the pipe, i.e., the curvature will adaptively respond to the change of the geometric size. If the area is contaminated, the contaminants will non-uniformly change the local cross-sectional tension and contact angle, destroying this inherent mechanical balance and geometric correlation.

[0103] Therefore, this application can assess the degree of contamination by quantifying the correlation between the rate of change of liquid surface curvature and the rate of change of pipe diameter. The weaker the correlation, the more severe the interference of non-geometric factors (contamination) on the cross-sectional properties.

[0104] Step 603: Determine the contamination level of the capillary viscometer based on the regional contamination level values ​​of the uniform inner diameter region and the regional contamination level values ​​of the non-uniform inner diameter region.

[0105] For example, this application can calculate the overall contamination level of the capillary viscometer by weighted average or arithmetic average of the regional contamination level values ​​of the uniform inner diameter region and the regional contamination level values ​​of the non-uniform inner diameter region.

[0106] In one example, the contamination level of the capillary viscometer satisfies the following formula:

[0107]

[0108] in, This represents the contamination level value of the capillary viscometer. For a region with uniform inner diameter The regional pollution level value, Non-uniform inner diameter region The regional pollution level value.

[0109] Based on the above technical solution, this application further distinguishes between the uniform inner diameter region and the non-uniform inner diameter region of the capillary viscometer, and adopts differentiated image feature analysis methods for the structural characteristics of different regions: the uniform inner diameter region is quantified by the curvature fluctuation, symmetry, and smoothness mean of multiple frames of images, while the non-uniform inner diameter region is quantified by the synergy between the pipe diameter and curvature changes. This avoids the interference of structural differences between different regions on the contamination assessment, making the contamination degree calculation more accurate. At the same time, the overall contamination value is obtained by combining the contamination degree of the two regions, which further improves the objectivity of the measurement reliability judgment and provides a more comprehensive guarantee for the credibility of subsequent viscosity detection data.

[0110] As one possible embodiment of this application, combined with Figure 6 ,like Figure 7 As shown, step 601 above can be achieved through the following steps:

[0111] Step 701: Based on the first liquid surface image, divide the uniform inner diameter region into multiple partitions and extract the first image feature data of the enema solution on each partition.

[0112] The first image feature data includes a curvature radius of the liquid level of the enema liquid on the partition, a offset distance, and an edge fitting error. The curvature radius is a radius of a fitting circle obtained by fitting the liquid level of the enema liquid on the partition. The offset distance is a distance between a center of the fitting circle and a center of the uniform inner diameter region. The edge fitting error is used to represent a deviation between a point on an edge of the liquid level of the enema liquid on the partition and a corresponding point on an edge of the fitting circle.

[0113] For example, the application can divide the uniform inner diameter region into a plurality of partitions with the same length (e.g., 1 mm) along the axial direction. For each partition, a plurality of liquid level images are collected, and the first image feature data of each partition is extracted. That is, the application can extract a plurality of groups of first image feature data from the plurality of liquid level images collected for one partition, and then determine the image feature corresponding to each partition by calculating the mean value, thereby improving the data stability.

[0114] The curvature radius can be obtained by circular fitting of the meniscus edge of each partition, thereby obtaining the radius of the fitting circle (i.e., the curvature radius), which is the basic data for calculating the curvature.

[0115] The offset distance is measured from the center axis of the uniform inner diameter region to the center of the meniscus fitting circle (i.e., the offset distance), which is the basic data for evaluating the symmetry.

[0116] The edge fitting error is obtained by uniformly extracting a plurality of feature points on the meniscus edge of each partition, calculating the distance from each feature point to the fitting circle, and calculating the edge fitting error according to the distance from each feature point to the fitting circle. The edge fitting error is the basic data for evaluating the smoothness.

[0117] For example, with 20 feature points, the edge fitting error of the liquid level of the enema liquid on the partition satisfies the following formula:

[0118]

[0119] wherein, is the edge fitting error of the liquid level of the enema liquid on the partition, is the distance from the feature point to the fitting circle

[0120] Step 702, determining the first image feature corresponding to each partition of the enema liquid on the uniform inner diameter region according to the first image feature data on each partition.

[0121] In some embodiments, the application can calculate the image features of the corresponding dimensions based on the above-mentioned first image feature data.

[0122] For the curvature, the application can determine the curvature of each subzone of the uniform inner diameter area according to the radius of curvature of the liquid level of the enema liquid on the subzone, and determine the curvature standard deviation size mean value according to the curvature corresponding to the subzone.

[0123] For example, the curvature corresponding to each subzone satisfies the following formula:

[0124]

[0125] wherein, is the curvature corresponding to the subzone, is the radius of curvature of the liquid level on the corresponding subzone.

[0126] It should be noted that one subzone can correspond to multiple curvatures. For example, the application can collect multiple first liquid level images of the liquid level in the subzone, thereby obtaining multiple curvatures corresponding to the subzone, and determining the curvature standard deviation size mean value according to the multiple curvatures to ensure data stability.

[0127] For symmetry, the application can calculate the symmetry index corresponding to each subzone of the uniform inner diameter area according to the offset distance of the liquid level of the enema liquid on the subzone, and determine the symmetry index mean value according to the symmetry index corresponding to the subzone.

[0128] For example, the symmetry index corresponding to each subzone satisfies the following formula:

[0129]

[0130] wherein, is the symmetry index corresponding to the subzone, is the offset distance of the liquid level of the enema liquid on the subzone, is the radius of curvature of the liquid level on the corresponding subzone. It should be understood that when the calculation result of S is less than a preset minimum positive number, S is limited to the preset minimum positive number to avoid S being 0 or negative. The value of the preset minimum positive number is obtained by experience, such as 0.0001.

[0131] Similarly, the application can collect multiple first liquid level images of the liquid level in the subzone, thereby obtaining multiple symmetry indices corresponding to the subzone, and determining the symmetry index mean value according to the multiple symmetry indices.

[0132] For smoothness, the application can calculate the smoothness index corresponding to each subzone of the uniform inner diameter area according to the edge fitting error of the liquid level of the enema liquid on the subzone, and determine the smoothness index mean value according to the smoothness index corresponding to the subzone.

[0133] For example, the smoothness index corresponding to each subzone satisfies the following formula:

[0134]

[0135] wherein, is the smoothness index corresponding to the partition, is the edge fitting error of the liquid surface of the enema liquid on the partition.

[0136] Similarly, the application can collect a plurality of first liquid surface images of the liquid surface in the partition, thereby obtaining a plurality of smoothness indexes corresponding to the partition, and thereby determining the smoothness index mean value according to the plurality of smoothness indexes.

[0137] Step 703, determining the regional pollution degree value of the uniform inner diameter region based on the first image feature corresponding to each partition.

[0138] In one possible implementation, the application determines the regional pollution degree value of the uniform inner diameter region according to the curvature standard deviation mean value, the symmetry index mean value, and the smoothness index mean value.

[0139] wherein the curvature standard deviation mean value is positively correlated with the regional pollution degree value of the uniform inner diameter region, and the symmetry index mean value and the smoothness index mean value are negatively correlated with the regional pollution degree value of the uniform inner diameter region, respectively.

[0140] For example, the application can first determine the partition pollution degree value of the corresponding partition through the curvature standard deviation mean value, the symmetry index mean value, and the smoothness index mean value corresponding to each partition, and then determine the regional pollution degree value of the uniform inner diameter region according to the partition pollution degree value of each partition.

[0141] In one example, the partition pollution degree value of the partition satisfies the following formula:

[0142]

[0143] wherein, is the partition pollution degree value, is the curvature standard deviation mean value corresponding to the partition , is the symmetry index mean value corresponding to the partition , is the smoothness index mean value corresponding to the partition . The in the embodiment indicates a normalization function, such as a maximum-minimum normalization method.

[0144] The regional pollution degree value of the uniform inner diameter region satisfies the following formula:

[0145]

[0146] wherein, is the regional pollution degree value of the uniform inner diameter region is the regional pollution degree value of the uniform inner diameter region is the regional pollution degree value of the uniform inner diameter region is the regional pollution degree value of the uniform inner diameter region is the regional pollution degree value of the uniform inner diameter region is the regional pollution degree value of the uniform inner diameter region

[0147] Based on the above technical scheme, the present application avoids the one-sidedness of single position analysis by analyzing the uniform inner diameter region in a partitioned manner. Meanwhile, by extracting the first image feature data such as the radius of curvature, the offset distance, the edge fitting error, and calculating the first image features (the mean value of the curvature standard deviation size, the symmetry index mean value, and the smoothness index mean value) based on the first image feature data, each step of the pollution degree evaluation has clear data support, reducing subjective errors. In addition, by quantifying the correlation between each feature and the pollution degree, the regional pollution degree value of the uniform inner diameter region can accurately reflect the pollution condition of the uniform inner diameter region, providing accurate basic data for subsequent comprehensive pollution degree calculation and measurement reliability judgment.

[0148] As a possible embodiment of the present application, in combination with Figure 6 as shown in Figure 8 , the above step 602 can be implemented by the following steps:

[0149] Step 801, based on the second liquid level image, extracting second image feature data of the enema liquid at multiple positions in the non-uniform inner diameter region.

[0150] Wherein, the second image feature data includes the capillary viscometer tube diameter change rate at the corresponding position and the curvature change rate of the liquid level of the enema liquid at the corresponding position. The tube diameter change rate is used to represent the change of the tube diameter at the corresponding position during the flow of the enema liquid in the non-uniform inner diameter region of the capillary viscometer. The curvature change rate is used to represent the curvature change of the liquid level at the corresponding position during the flow of the enema liquid in the non-uniform inner diameter region of the capillary viscometer.

[0151] In an ideal clean capillary, for the non-uniform inner diameter region, the change of liquid surface curvature is usually highly coordinated with the tube diameter change rate, that is, the curvature adaptively responds to the change of geometric size. If the region is contaminated, the pollutants will non-uniformly change the local cross-sectional tension and contact angle, destroying this inherent mechanical balance and geometric correlation.

[0152] Therefore, the present application can evaluate the pollution degree of the non-uniform inner diameter region by quantifying the correlation between the liquid surface curvature change rate and the tube diameter change rate. The weaker the correlation, the more serious the interference of non-geometric factors (pollution) on the cross-sectional properties.

[0153] Exemplarily, the application can select multiple sampling positions (e.g., 20 positions) along the axial direction for the non-uniform inner diameter region (e.g., the measuring ball region of the capillary), and extract second image feature data based on the second liquid surface image of each position.

[0154] For the pipe diameter change rate, the application can determine the function relationship between the actual physical width corresponding to each position and the axial coordinate, and derive the pipe diameter change rate, which can be referred to the above embodiments and will not be described here.

[0155] Similarly, for the curvature change rate data, the application can perform edge extraction and circular fitting on the liquid surface image of each sampling position to obtain the curvature of the position, and calculate the change rate of the curvature with the axial position as the basic data of the curvature change rate.

[0156] Step 802, determining the second image feature of the enema liquid in the non-uniform inner diameter region according to the second image feature data at multiple positions.

[0157] In a possible implementation, the application can perform correlation analysis on the pipe diameter change rate of the capillary viscometer and the curvature change rate of the liquid surface of the enema liquid at multiple positions to determine the correlation coefficient of the curvature change rate and the pipe diameter change rate.

[0158] Exemplarily, the application can evaluate the correlation coefficient of the curvature change rate and the pipe diameter change rate through covariance, for example, the correlation coefficient of the curvature change rate and the pipe diameter change rate satisfies the following formula:

[0159]

[0160] wherein, is the correlation coefficient of the curvature change rate and the pipe diameter change rate, is the pipe diameter change rate, is the curvature change rate, is the Pearson correlation coefficient calculation function. The value range of is , The closer to 1, the greater the correlation.

[0161] Step 803, evaluating the regional pollution degree value of the non-uniform inner diameter region based on the second image feature.

[0162] In a possible implementation, the regional pollution degree value of the non-uniform inner diameter region is determined according to the absolute value of the correlation coefficient of the curvature change rate and the pipe diameter change rate.

[0163] Wherein, the absolute value of the correlation coefficient is negatively correlated with the regional pollution degree value of the uniform inner diameter region.

[0164] For example, the regional contamination level of a non-uniform inner diameter region satisfies the following formula:

[0165]

[0166] in, Non-uniform inner diameter region The regional pollution level value, This is the absolute value of the correlation coefficient between the rate of curvature change and the rate of pipe diameter change.

[0167] Based on the above technical solution, this application addresses the characteristics of pipe diameter changes in non-uniform inner diameter regions by quantifying the degree of contamination through the correlation coefficient between the pipe diameter change rate and the curvature change rate. Under clean conditions, the two changes are highly synergistic and correlated; after contamination, the synergy is disrupted and the correlation decreases. This assessment method is consistent with the physical characteristics of non-uniform regions, making the assessment method more targeted and further improving the accuracy of contamination assessment in non-uniform inner diameter regions.

[0168] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0169] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A rheological method for detecting the viscosity of an enema solution, characterized in that, The method includes: Images of the liquid level of the enema solution during its flow in a capillary viscometer were acquired using an image acquisition device. The liquid surface image is subjected to morphological feature analysis to obtain the image features of the enema solution, and the degree of contamination of the capillary viscometer is evaluated based on the image features; the image features include at least one of curvature features, symmetry features, and smoothness features; The reliability of the viscosity measurement of the capillary viscometer is determined based on the pollution level value. The liquid level image includes a first liquid level image of the enema solution in a uniform inner diameter region of the capillary viscometer and / or a second liquid level image of the enema solution in a non-uniform inner diameter region of the capillary viscometer. The step of performing morphological feature analysis on the liquid surface image to obtain the image features of the enema solution, and evaluating the contamination level of the capillary viscometer based on the image features, includes: Morphological feature analysis is performed on the first liquid surface image to obtain the first image features of the enema solution in the uniform inner diameter region, and the regional contamination degree value of the uniform inner diameter region is evaluated based on the first image features; the first image features include the mean value of the standard deviation of curvature, the mean value of the symmetry index, and the mean value of the smoothness index. Morphological feature analysis is performed on the second liquid surface image to obtain the second image features of the enema solution in the non-uniform inner diameter region, and the regional contamination degree value of the non-uniform inner diameter region is evaluated based on the second image features; the second image features include the correlation coefficient between the rate of curvature change and the rate of pipe diameter change; The contamination level of the capillary viscometer is determined based on the regional contamination level values ​​of the uniform inner diameter region and the regional contamination level values ​​of the non-uniform inner diameter region.

2. The rheological method for detecting the viscosity of the enema solution according to claim 1, characterized in that, The step of performing morphological feature analysis on the first liquid surface image to obtain the first image features of the enema solution in a uniform inner diameter region, and evaluating the regional contamination degree value of the uniform inner diameter region based on the first image features, includes: Based on the first liquid surface image, the uniform inner diameter region is divided into multiple partitions, and the first image feature data of the enema solution on each partition is extracted. The first image feature data includes the radius of curvature, offset distance, and edge fitting error of the liquid surface of the enema solution on the partition. The radius of curvature is the radius of the fitted circle obtained by fitting the liquid surface of the enema solution on the partition. The offset distance is the distance between the center of the fitted circle and the center of the uniform inner diameter region. The edge fitting error is used to characterize the deviation between a point on the edge of the liquid surface of the enema solution on the partition and a point on the corresponding edge of the fitted circle. The first image features of the enema solution in each partition of the uniform inner diameter region are determined based on the first image feature data of each partition. The degree of regional contamination in the uniform inner diameter region is evaluated based on the first image features corresponding to each partition.

3. The rheological method for detecting the viscosity of the enema solution according to claim 2, characterized in that, The step of determining the first image features of the enema solution corresponding to each partition in the uniform inner diameter region based on the first image feature data of each partition includes: For each partition of the uniform inner diameter region, the curvature is determined based on the radius of curvature of the enema solution on the partition, and the mean value of the standard deviation of the curvature is determined based on the curvature corresponding to the partition. For each partition of the uniform inner diameter region, the symmetry index corresponding to the partition is calculated based on the offset distance of the enema solution on the partition, and the mean value of the symmetry index is determined based on the symmetry index corresponding to the partition. For each partition of the uniform inner diameter region, the smoothness index corresponding to the partition is calculated based on the edge fitting error of the enema solution on the partition, and the mean value of the smoothness index is determined based on the smoothness index corresponding to the partition.

4. The rheological method for detecting the viscosity of the enema solution according to claim 2, characterized in that, The step of evaluating the regional contamination level of the uniform inner diameter region based on the first image features corresponding to each partition includes: The regional contamination level of the uniform inner diameter region is determined based on the mean of the standard deviation of curvature, the mean of the symmetry index, and the mean of the smoothness index; the mean of the standard deviation of curvature is positively correlated with the regional contamination level of the uniform inner diameter region; the mean of the symmetry index and the mean of the smoothness index are negatively correlated with the regional contamination level of the uniform inner diameter region, respectively.

5. The rheological method for detecting the viscosity of the enema solution according to claim 1, characterized in that, The step of performing morphological feature analysis on the second liquid surface image to obtain the second image features of the enema solution in the non-uniform inner diameter region, and evaluating the regional contamination degree value of the non-uniform inner diameter region based on the second image features, includes: Based on the second liquid surface image, second image feature data of the enema solution at multiple locations in the non-uniform inner diameter region are extracted; the second image feature data includes the rate of change of the capillary viscometer diameter at the corresponding location and the rate of change of the curvature of the enema solution surface at the corresponding location. The second image features of the enema solution in the non-uniform inner diameter region are determined based on the second image feature data at the multiple locations; The degree of regional contamination in the non-uniform inner diameter region is evaluated based on the second image features.

6. The rheological method for detecting the viscosity of the enema solution according to claim 5, characterized in that, Determining the second image features of the enema solution in a non-uniform inner diameter region based on the second image feature data at the multiple locations includes: Correlation analysis was performed on the rate of change of the capillary viscometer diameter at the multiple locations and the rate of change of the curvature of the enema solution surface to determine the correlation coefficient between the rate of change of curvature and the rate of change of the capillary diameter.

7. The rheological method for detecting the viscosity of the enema solution according to claim 5, characterized in that, The evaluation of the regional contamination level of the non-uniform inner diameter region based on the second image features includes: The regional contamination level of the non-uniform inner diameter region is determined based on the absolute value of the correlation coefficient between the rate of curvature change and the rate of pipe diameter change; the absolute value of the correlation coefficient is negatively correlated with the regional contamination level of the uniform inner diameter region.

8. A rheological detection system for the viscosity of an enema solution, characterized in that, The rheological detection system is used to implement the rheological detection method according to any one of claims 1-7, and the rheological detection system includes a capillary viscometer, an image acquisition device, and an electronic device; The capillary viscometer is used to measure the viscosity of the enema solution; The image acquisition device is used to acquire images of the liquid level of the enema solution during its flow in the capillary viscometer; The electronic device is used to acquire images of the liquid surface of the enema solution during its flow in the capillary viscometer via the image acquisition device; to perform morphological feature analysis on the liquid surface image to obtain image features of the enema solution, and to evaluate the degree of contamination of the capillary viscometer based on the image features; the image features include at least one of curvature features, symmetry features, and smoothness features; and to determine the viscosity measurement reliability of the capillary viscometer based on the degree of contamination value.

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