CN115235948A - Liquid viscosity measurement system based on computer vision identification - Google Patents
Liquid viscosity measurement system based on computer vision identification Download PDFInfo
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- G01N11/00—Investigating flow properties of materials, e.g. viscosity, plasticity; Analysing materials by determining flow properties
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Abstract
The invention relates to a liquid viscosity measurement system based on computer vision recognition, which belongs to the technical field of viscosity measurement under the detection and measurement technology, and designs and builds an image acquisition hardware structure, comprising the following steps: the system comprises a constant-temperature water tank, a surface light source, a cloud deck, an industrial camera, a stepping motor and a computer, wherein video images are collected and detected through the industrial camera, cross-platform computer vision library OpenCV image collection processing and computer vision technology are applied under a Windows operating system, after gray processing is carried out on collected images, identification of scale marks is achieved through a straight-line segment detection algorithm, and identification and detection of motion liquid levels are achieved through an improved ViBe motion target detection algorithm. Experiments show that the system is accurate and reliable in detection in a reliable environment and meets the requirement of on-line monitoring on real-time performance; the man-machine interaction performance is good, the intelligent degree and the detection efficiency of the viscometer are effectively improved, and the actual use value is high.
Description
Technical Field
The invention belongs to the technical field of viscosity measurement under the detection and metering technology, and particularly relates to a liquid viscosity measurement system based on the computer vision recognition technology.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The viscosity, i.e. the magnitude of the degree of viscosity, is an inherent property of a fluid and is used for representing the difficulty of fluid flow, the flow process of the fluid can be continuously deformed under the action of gravity or some external force, the interaction force of the liquid motion is represented as the viscosity of the liquid, and the magnitude of the interaction force between the molecules of the fluid is represented as the magnitude of the viscosity of the fluid. Different substances have different viscosities, and the viscosity of the same substance at different temperatures is also different. The viscosity measurement comprises two absolute viscosity measurement methods of dynamic viscosity and kinematic viscosity, the absolute measurement method requires the processing of a viscometer to be very accurate, the measurement operation process is complicated, and the measurement precision is low. The capillary viscometer measures the viscosity of fluid based on a capillary method, and is a measurement method which is applied more in a plurality of viscosity measurement methods. The capillary method is based on the principle of Poiseuille's law, i.e., the viscous fluid descends in a capillary tube under the action of its own gravity, and there is a corresponding relationship between the time taken for a certain volume of fluid to flow through the capillary tube and the viscosity of the fluid. The kinematic viscosity of the fluid is found by measuring the product of the time the fluid flows through the capillary and the instrument constant calibrated for the capillary. In use, due to different condition characteristics and different measurement objects, the structure of the viscometer is slightly different, and the major common viscometer is a black-type capillary viscometer and a Fin-type capillary viscometer.
When measuring liquid with high viscosity, the liquid descends slowly in the pipe for too long, and the measurement result needs to be calculated manually, which can seriously consume the energy and time of the operator. Therefore, viscosity measurement is gradually moving towards automated measurement.
Disclosure of Invention
In order to overcome the defects, the invention provides a proper viscosity measuring system based on a computer vision identification technology, an image acquisition, image acquisition processing and timing calculation system is designed, the detection and tracking of the motion liquid level are realized through a computer, whether the liquid level flows through the upper and lower scale lines of a viscometer timing ball or not is judged, the timing time is obtained, and then the calculation is carried out according to a formula v = C t through a relative method, wherein v represents the motion viscosity of the liquid; c represents a viscometer constant; t represents the time taken for a volume of liquid to flow through the capillary. The system can reduce the workload of experimenters, improve the verification precision and the detection efficiency, increase the economic benefit and has high innovation and practical significance.
To achieve the above object, one or more embodiments of the present invention provide the following technical solutions:
a liquid viscosity measurement system based on computer vision recognition, comprising: the device comprises a constant-temperature water tank, a surface light source, a holder, an industrial camera, a stepping motor and a computer, wherein the surface light source and the holder are respectively positioned on two opposite sides of the constant-temperature water tank; the industrial camera is slidably mounted on the cradle head through the movable support to form an image acquisition system, the lower part of the cradle head is provided with a stepping motor, the stepping motor drives the movable support to slide up and down, and the industrial camera moves left and right on the horizontal plane of the movable support; the capillary viscometer is fixed in a transparent circulating constant-temperature water tank through a measuring bracket, a frame image shot by an industrial camera is transmitted to a computer, an image acquisition processing and timing calculation control unit module is installed on the computer, and the computer receives the frame image shot by the industrial camera and judges scale lines and identifies a motion liquid level; when the liquid to be tested does free falling motion in the capillary viscometer and passes through the upper scale mark on the timing ball from top to bottom, the computer makes a judgment and starts timing; stopping timing when the liquid to be tested passes through the lower scale mark on the timing ball; and after the interval time is obtained through calculation, calculating the kinematic viscosity of the liquid to be tested according to a formula.
According to the further technical scheme, a computer obtains a frame image by establishing a camera, then converts the frame image into an image format recognizable by Open CV, converts a color image into a gray image, demarcates an interested area, performs edge detection on the image after gray processing in the interested area by using a Canny operator, and then performs detection of scale marks and detection of a moving liquid level.
According to the further technical scheme, for the identification and detection of the scale lines at the timing ball of the capillary viscometer, the used algorithm is a straight-line segment detection algorithm; for the detection and tracking of the moving liquid level in the capillary viscometer, the used algorithm is a modified ViBe moving target detection algorithm. The ViBe is Background modeling (Visual Background estimator) which is an algorithm for pixel-level video Background modeling or foreground detection, the detection effect of the ViBe is superior to that of mainstream detection algorithms such as an interframe difference method, and the ViBe occupies relatively little computer memory. However, when the moving speed of the moving object is relatively different, ghost images may occur, which may cause incomplete object detection. Therefore, it is suitably improved to reduce the occurrence of missing detection, erroneous detection, and the like.
According to the further technical scheme, firstly, an improved ViBe moving object detection algorithm is applied, a background model prototype of the ViBe algorithm is constructed by adopting a multi-frame image and an improved three-frame difference method, and adjacent element change values are added in the prototype. And adjusting the background model and the threshold value according to the difference value between the current frame image and the background model as an adjusting factor of the background complexity. And carrying out logical AND operation and post-processing operation on the detected result and an improved three-frame difference method to finish the detection of the motion liquid level in the viscometer.
Further technical scheme, surface light source and constant temperature water tank structure as an organic whole, the cloud platform when setting up not with the constant temperature water tank contact, the frame image that the industry camera was shot is transmitted to the computer by the giga net twine.
According to the further technical scheme, a Haikang industrial area-array camera is preferably used as the image acquisition equipment of the industrial camera, and the kinematic viscosity of the liquid to be tested is displayed on a display screen of a computer.
In a further embodiment, the capillary viscometer is a viscometer that has been certified and has a permanent identification.
The above one or more technical solutions have the following beneficial effects:
the technical scheme of the invention can finish timing work during viscosity measurement through a computer and can meet the index requirements in national metering regulations. Through the computer vision technology, the upper and lower scale lines of the capillary viscometer can be accurately identified and calibrated, and valuable reference is provided for the calibration process. And (3) detecting the time of the liquid level passing through the upper and lower timing lines of the capillary viscometer by identifying and tracking the motion liquid level, and obtaining a time interval so as to calculate the viscosity of the test liquid.
The detection environment and the detection method set up by the technical scheme have standard operation requirements, and an experimenter can fix the capillary viscometer containing the liquid to be tested in a constant-temperature water tank, and can start detection by adjusting the position of an industrial camera through a PC (personal computer) without operations such as readjustment of the environment and the like.
According to the technical scheme, an image acquisition processing part adopts an open source code computer vision class library OpenCV as a core part of the design, all codes of the library are optimized, the calculation efficiency is high, and the operation efficiency is high. The image acquisition processing technology meets the requirements of the design, and realizes the functions of image acquisition processing and computer vision.
The target detection algorithm of the technical scheme of the invention adopts an improved ViBe algorithm, which not only has the advantages of easy realization, high operation efficiency and the like of the original ViBe algorithm, but also can eliminate the problems of false targets (ghost), target and background fusion and the like.
The technical scheme of the invention has the advantages of simple measuring device, strong adaptability to the environment and few error influence factors, and can achieve higher measuring precision by means of advanced machine vision and image acquisition processing algorithms.
Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a schematic diagram of a capillary viscometer used in an embodiment of the invention;
FIG. 2 is a schematic structural diagram of a fluid viscosity measurement system according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an image area captured by an industrial camera according to an embodiment of the present invention;
FIG. 4 is a block diagram of an image acquisition process flow according to an embodiment of the present invention;
FIG. 5 is a block diagram of an improved ViBe moving object detection algorithm according to an embodiment of the present invention;
in the figure, 1 is a capillary viscometer, 2 is a constant temperature water tank, 3 is a surface light source, 4 is a holder, 5 is an industrial camera, 6 is a stepping motor, 7 is a computer, 8 is an upper scale mark, 9 is a lower scale mark, and 10 is a timing ball.
Detailed Description
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, 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 invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
As shown in fig. 1, a schematic diagram of a capillary viscometer used in an embodiment of the present invention, a capillary viscometer 1 is a viscometer that measures the viscosity of a fluid based on a capillary method, and is a viscometer that has been certified and has a permanent mark.
Fig. 2 is a schematic structural diagram of a liquid viscosity measurement system according to an embodiment of the present invention. A liquid viscosity measurement system based on computer vision recognition, comprising: constant temperature water tank 2, area source 3, cloud platform 4, industrial camera 5, step motor 6 and computer 7, area source 3 and cloud platform 4 are located the relative both sides of constant temperature water tank 2 respectively. Area source 3 and constant temperature water tank 2 structure as an organic whole, bottom panel is shared to the bottom, guarantees area source 3 and constant temperature water tank 2 stability in the test procedure, and area source 3 and constant temperature water tank 2 constitute the required environment of liquid viscosity measurement system, and the two of area source 3 and constant temperature water tank 2 can be dismantled and change alone to adapt to different environmental requirements.
The capillary viscometer 1 is fixed in a transparent circulating constant-temperature water tank 2 through a measuring bracket, a surface light source 3 with stable brightness provides proper background light, and an industrial camera 5 can be longitudinally and freely adjusted to adapt to different heights through the control of a stepping motor 6. The frame image shot by the industrial camera 5 is transmitted to the computer 7 through a gigabit network cable, and the computer 7 finishes the measurement, timing and calculation to obtain the viscosity of the liquid to be tested.
The computer 7 is provided with an image acquisition processing and timing calculation control unit module, and the computer 7 is used as an image acquisition processing and timing calculation control unit for receiving frame images shot by the industrial camera 5 and judging scale marks and identifying the motion liquid level. When the liquid to be tested makes free falling motion in the capillary viscometer 1 and passes through the upper scale mark 8 on the timing ball 10 from top to bottom, the computer 7 makes a judgment and starts timing; when the liquid to be tested passes through the lower scale mark 9 on the timing ball 10, stopping timing; and after the interval time is obtained through calculation, calculating the kinematic viscosity of the liquid to be tested according to a formula, and displaying the kinematic viscosity on a display screen of the computer 7.
Fig. 4 is a block diagram of an image acquisition process according to an embodiment of the present invention. The image acquisition processing and timing calculation unit is mainly realized in the Visual Studio 2019 through a C + + algorithm statement. The computer 7 obtains a frame image by establishing a camera, converts the frame image into an image format recognizable by Open CV, converts a color image into a gray image, delimits an interested Region (ROI), performs edge detection on the image after gray processing by using a Canny operator in the ROI, can accurately obtain the edge of a liquid level image, and then performs detection of a scale mark and detection of a moving liquid level.
For the identification and detection of the scale lines at the timing ball 10 of the capillary viscometer 1, the algorithm used is a Line Segment detection algorithm (LSD algorithm). The algorithm can obtain a straight line segment detection result with higher precision in a shorter time, has high detection speed, does not need parameter adjustment, and improves the accuracy of straight line detection by using an error control method.
For the detection and tracking of the moving liquid level in the capillary viscometer 1, an improved ViBe moving target detection algorithm is used, as shown in fig. 5, which is a block diagram of the improved ViBe moving target detection algorithm of the embodiment of the present invention. Based on the collected video sequence, a background model prototype of the ViBe algorithm is constructed by adopting a plurality of frames of images and using an improved three-frame difference method, and adjacent element change values are added in the prototype. Taking the difference value of the current frame image and the background model as an adjusting factor of the background complexity degree to adjust the background model and the threshold value, and carrying out median filtering; the improved three-frame difference method comprises the following steps: three-frame difference processing, expansion processing, logical OR operation and morphological filtering. Foreground detection is the process of identifying moving objects (foreground objects) and static parts in a sequence of video images, i.e. identifying a moving liquid level and a static background within a timing ball in a sequence of images. And performing logical AND operation and post-processing operation (morphological filtering) on the detected result and a three-frame difference method to finish the detection of the motion liquid level in the viscometer.
In the detection process, the method can be ensured in the aspect of experimental environment, and on the premise of less noise or no noise, the data operation amount is overlarge due to no excessive preprocessing, and errors are formed due to insufficient computer computing power.
Those skilled in the art will appreciate that the modules or steps of the present invention described above can be implemented using general purpose computer means, or alternatively, they can be implemented using program code that is executable by computing means, such that they are stored in memory means for execution by the computing means, or they are separately fabricated into individual integrated circuit modules, or multiple modules or steps of them are fabricated into a single integrated circuit module. The present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.
Claims (8)
1. The liquid viscosity measurement system based on computer vision discernment, characterized by, includes: the device comprises a constant-temperature water tank (2), a surface light source (3), a cradle head (4), an industrial camera (5), a stepping motor (6) and a computer (7), wherein the surface light source (3) and the cradle head (4) are respectively positioned on two opposite sides of the constant-temperature water tank (2); the industrial camera (5) is slidably mounted on the cradle head (4) through the movable support to form an image acquisition system, the stepping motor (6) is arranged at the lower part of the cradle head (4), the movable support is driven by the stepping motor (6) to slide up and down, and the industrial camera (5) moves left and right on the horizontal plane of the movable support; the capillary viscometer (1) is fixed in a transparent circulating constant-temperature water tank (2) through a measuring bracket, a frame image shot by an industrial camera (5) is transmitted to a computer (7), an image acquisition processing and timing calculation control unit module is installed on the computer (7), and the computer (7) receives the frame image shot by the industrial camera (5) and judges scale lines and identifies a motion liquid level; when the liquid to be tested does free falling motion in the capillary viscometer (1) and passes through an upper scale mark (8) on the timing ball (10) from top to bottom, the computer (7) makes a judgment and starts timing; when the liquid to be tested passes through the lower scale mark (9) on the timing ball (10), stopping timing; and after the interval time is obtained through calculation, calculating the kinematic viscosity of the liquid to be tested according to a formula.
2. The liquid viscosity measurement system based on computer vision recognition according to claim 1, wherein the computer (7) obtains a frame image by creating a camera, converts the frame image into an image format recognizable by Open CV, converts a color image into a gray scale image, delimits an area of interest, performs edge detection on the image after gray scale processing in the area of interest by using Canny operator, and then performs detection of scale marks and detection of moving liquid level.
3. The computer vision recognition-based liquid viscosity measurement system according to claim 2, characterized in that for the recognition detection of the scale lines at the timing ball (10) of the capillary viscometer (1), the algorithm used is a straight line segment detection algorithm; for the detection and tracking of the moving liquid level in the capillary viscometer (1), the adopted algorithm is an improved ViBe moving target detection algorithm; the ViBe, namely background modeling, is an algorithm for pixel-level video background modeling or foreground detection, and when the motion speed of a moving target is greatly different, ghost images can appear to cause incomplete target detection, so that the ViBe is improved to reduce the occurrence of missed detection and error detection.
4. The computer vision recognition-based liquid viscosity measurement system according to claim 3, wherein an improved ViBe moving object detection algorithm is applied, a background model prototype of the ViBe algorithm is constructed by using a multi-frame image and an improved three-frame difference method, and adjacent element change values are added to the prototype; taking the difference value of the current frame image and the background model as an adjusting factor of the background complexity degree to adjust the background model and the threshold value; and carrying out logical AND operation and post-processing operation on the detected result and an improved three-frame difference method to finish the detection of the motion liquid level in the viscometer.
5. The computer vision recognition-based liquid viscosity measurement system of claim 4, wherein the improved three-frame difference method comprises: three-frame difference processing, dilation processing, logical or operations, and morphological filtering.
6. The computer vision recognition-based liquid viscosity measurement system according to claim 1, wherein the surface light source (3) and the constant temperature water tank (2) are of an integral structure, the pan-tilt (4) is not in contact with the constant temperature water tank (2) when being set, and a frame image shot by the industrial camera (5) is transmitted to the computer (7) through a gigabit network.
7. The computer vision recognition based liquid viscosity measurement system according to claim 1, characterized in that an industrial camera (5), preferably a Haikang industrial area-array camera, is used as an image acquisition device, and the kinematic viscosity of the liquid to be tested is presented on a display screen of a computer (7).
8. The computer vision recognition based liquid viscosity measurement system according to claim 1, characterized in that the capillary viscometer (1) is a viscometer that has passed certification and has a permanent identification.
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| CN116474157A (en) * | 2023-04-28 | 2023-07-25 | 广州迅合医疗科技有限公司 | Preparation method and system of hard tissue biological adhesive for continuous adhesion in wet environment |
| CN116589652A (en) * | 2023-04-28 | 2023-08-15 | 广州迅合医疗科技有限公司 | Preparation method and system of soft tissue biological adhesive based on polyurethane |
| CN116474157B (en) * | 2023-04-28 | 2023-09-15 | 广州迅合医疗科技有限公司 | Preparation method and system of hard tissue biological adhesive for continuous adhesion in wet environment |
| CN116589652B (en) * | 2023-04-28 | 2023-10-27 | 广州迅合医疗科技有限公司 | Preparation method and system of soft tissue biological adhesive based on polyurethane |
| CN116908051A (en) * | 2023-06-21 | 2023-10-20 | 广州市嘉雁粘合剂有限公司 | Hot melt adhesive flow property detection method |
| CN116908051B (en) * | 2023-06-21 | 2023-12-29 | 广州市嘉雁粘合剂有限公司 | Hot melt adhesive flow property detection method |
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