CN203148531U - Water level and water quality monitoring terminal based on machine vision - Google Patents

Water level and water quality monitoring terminal based on machine vision Download PDF

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CN203148531U
CN203148531U CN 201320121849 CN201320121849U CN203148531U CN 203148531 U CN203148531 U CN 203148531U CN 201320121849 CN201320121849 CN 201320121849 CN 201320121849 U CN201320121849 U CN 201320121849U CN 203148531 U CN203148531 U CN 203148531U
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water
camera
water level
float
water quality
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张学武
周卓贇
孙浩
张卓
李敏
范新南
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Hohai University HHU
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Abstract

本实用新型涉及一种基于机器视觉的水位和水质监测终端,包括:浮子,位于浮子的正上方设有适于拍摄浮子影像的第一摄像头,位于水面上方设有适于拍摄水面影像的第二摄像头,第一、第二摄像头输出的相应视频信号输入至视频采集模块,与视频采集模块相连的处理器,该处理器适于计算出浮子影像的面积像素以得到第一摄像头与浮子的间距,摄像装置的安装高度减去所述间距以获得水位值,并对水面影像进行灰度处理以得出水质情况。本实用新型利用了视觉图像处理技术,将图像视觉技术应用与水位、水质监测领域,通过图像视觉技术测量视频中的浮子影像面积,根据影像面积的大小换算成浮子与摄像头之间的距离以得到水位数值,并且得到水质信息。

The utility model relates to a water level and water quality monitoring terminal based on machine vision. Camera, the corresponding video signals output by the first and second cameras are input to the video acquisition module, and the processor connected to the video acquisition module is suitable for calculating the area pixels of the float image to obtain the distance between the first camera and the float, The distance is subtracted from the installation height of the camera device to obtain the water level value, and the water surface image is grayscale processed to obtain the water quality. The utility model utilizes the visual image processing technology, applies the image visual technology to the field of water level and water quality monitoring, measures the image area of the float in the video through the image visual technology, and converts the distance between the float and the camera according to the size of the image area to obtain Water level value, and get water quality information.

Description

A kind of water level and water quality monitoring terminal based on machine vision
Technical field
The utility model relates to a kind of electronic surveying field, relates in particular to a kind of image vision treatment technology and realizes water level and water monitoring device.
Background technology
In the water level measurement method of prior art, the application of float type level meter in water regime monitoring is the most general.Float is vertically hung on the pulley with line, and float is placed on the water surface, will produce displacement up and down along with the height of water level.By measuring the distance of float and specified point, again by certain calculating, just current water level can have been obtained.Float gauge needs special-purpose well logging, and its shortcoming is installed complicated exactly, and heavier if the while current contain silt, through operation after a while, the water inlet pipe of well logging will produce the phenomenon of alluvial, easily forms artifical water height.
Pressure type water level meter is according to the proportional hydrostatic force principle of pressure and the depth of water, use pressure-active element to make sensor, produce corresponding electric current and measure the height of equivalent water level at different depth of water induction different pressures, this mode has solved the shortcoming of float type level meter, but can't reach very high precision, and easily by environment temperature and liquid density variation influence.
The principle of aerosphere type or the wave reflection of liquid Jie formula ultrasonic type water level meter using ultrasound is measured water level.Ultrasound wave is propagated with certain speed in medium, and when running into the dielectric interface of different densities, ultrasound wave reflects immediately.Liquid Jie formula is that transducer is installed in the river bed, vertically to water surface emission ultrasound wave; Aerosphere type is that transducer is fixed on a certain eminence in the air, to water surface emission ultrasound wave.Two kinds of forms all need not built well logging.Liquid Jie formula is subject in water temperature, hydraulic pressure and the water floating outstanding particle concentration influence, and aerosphere type is subject to the temperature influence, and its advantage is not to be subjected to that pasture and water, silt etc. influence in the water.This method has its advance, but cost is higher.
And existing Level monitor often can only be independent sensed water level, can't detect water quality, need to adopt water monitoring device realize how realizing measuring simultaneously water level and water quality is the technical barrier of this area in addition.
The utility model content
The technical problems to be solved in the utility model provides a kind of water level and water quality monitoring terminal based on machine vision that is suitable for carrying out simultaneously water level and water quality measurement.
In order to solve the problems of the technologies described above, the utility model provides a kind of water level based on machine vision and water quality monitoring terminal, comprise: float, be positioned at described float directly over be provided with first camera that is suitable for taking the float image, be positioned at water surface top and be provided with second camera that is suitable for the filming surface image, the corresponding video signal of described first camera and the output of second camera inputs to video acquisition module, the processor that links to each other with described video acquisition module, this processor is suitable for calculating the area pixel of described float image to obtain the spacing of described first camera and float, the setting height(from bottom) of described camera head deducts described spacing with the acquisition water level value, and described water surface image is carried out gray scale handle to draw the water quality situation.
Further, for the ease of showing concrete water level and water quality data, perhaps can connect with computer and carry out data analysis, described water level and water quality monitoring terminal based on machine vision also comprises: the display module that is suitable for showing water level value and water quality situation, be suitable for the communication module with the computing machine communication, processor links to each other with communication module with described display module.
Further, for the light influence that prevents that ambient light from finding a view and producing camera lens, isolate visible light, the camera lens of described first camera, second camera is equipped with infrared filter.
Further, around the camera lens of described first camera, second camera, be distributed with the LED lighting device.
Further, described processor is FPGA module or DSP module.
Technique scheme of the present utility model has the following advantages compared to existing technology: the utility model has utilized the visual pattern treatment technology, with the application of image vision technology and water level, water quality monitoring field, by the float imagery coverage in the image vision commercial measurement video, be converted into distance between float and the camera to obtain water level numerical value according to the size of imagery coverage, and can obtain water quality information, need not expensive level sensor and loaded down with trivial details water quality monitoring, easy to use.
Description of drawings
Content of the present utility model is easier clearly to be understood in order to make, below the specific embodiment and by reference to the accompanying drawings of basis, the utility model is described in further detail, wherein
Fig. 1 is the structural representation of the water level based on machine vision of the present utility model and water quality monitoring terminal.Wherein, float 1, the water surface 2.
Embodiment
The present invention is described in detail below in conjunction with drawings and Examples:
See Fig. 1, a kind of water level and water quality monitoring terminal based on machine vision, comprise: float 1, be positioned at described float 1 directly over be provided with first camera that is suitable for taking float 1 image, be positioned at the water surface 2 tops and be provided with second camera that is suitable for the filming surface image, the corresponding video signal of described first camera and the output of second camera inputs to video acquisition module, the processor that links to each other with described video acquisition module, this processor is suitable for calculating the area pixel of described float image to obtain the spacing of described first camera and float 1, the setting height(from bottom) of described camera head deducts described spacing with the acquisition water level value, and described water surface image is carried out gray scale handle to draw the water quality situation.
Described water level and water quality monitoring terminal based on machine vision also comprises: be suitable for showing the display module of water level value and water quality situation, be suitable for the communication module with the computing machine communication, processor links to each other with communication module with described display module.
The camera lens of described first camera, second camera is equipped with infrared filter.
Around the camera lens of described first camera, second camera, be distributed with the LED lighting device.
Described processor is FPGA module or DSP module.
The level measuring ultimate principle is according to the image-forming principle of object in eye; That is, target is more far away, is seeing just more for a short time, for video, the picture of camera, camera, is like this equally.So, a float 1 is placed on the water surface 2, first camera is fixed on certain position, the water surface 2 tops takes float 1 vertically downward.Along with the variation up and down of water level, float 1 also can move up and down, and variation has also taken place the relative distance with first camera then, and this variation is presented as the variation of float 1 shared picture area size in the video image of clapping.Therefore, by the size of 1 area of float in the computed image, the relative distance of float 1 and first camera can be judged, owing to first camera position is fixed, thereby water level can be conversed.
The float image that the utility model adopts the MATLAB function that first camera is taken carries out the threshold value dividing processing, and its step is as follows:
I=imread (' image.jpg '); % opens pending picture
Imshow (I); % shows this picture
Inew=im2bw (I, x/255); % carries out image binaryzation according to threshold value x, divides target and background
Figure; Imshow (Inew); % shows the result after the binaryzation
Obtain the imagery coverage of float 1 by above-mentioned steps, establish this imagery coverage and be white, background is black.
In order to calculate the area of white portion, can call MATLAB built-in function bwarea.The Bwarea function is not the number of non-0 pixel of simple computation, and it also gives different authorities to different pixels, to compensate owing to represent the error that consecutive image is brought with discrete data.Than 50 long horizontal line lengths, therefore, 50 long horizontal line areas that the bwarea function returns are 50 as 50 long diagonal line, are 62.5 and 50 long diagonal line areas return.
The step that employing bwarea carries out area calculating is as follows:
Number=bwarea(Inew);
Number
Calculate the pixel of white portion, i.e. the area pixel of described float image, and compare with the pixel corresponding lists with the distance in being stored in processor, as shown in table 1:
Figure BDA00002932595600041
For example, if Number is 54116, i.e. 54116 elemental areas.This figure is that camera is taken during apart from water surface 19cm, thus 54116 elemental areas and 19cm this apart from producing mapping relations.
The distance of first camera and the water surface 2 is not linear with the imagery coverage of float, but a curve that is delayed by abrupt change, namely float is more near apart from camera, identical SEA LEVEL VARIATION, and the imagery coverage of float changes more greatly.Thereby the precision of this water level measurement method also is inconstant, measurement range hour ability guarantee a suitable precision, so be applicable to the little waters of SEA LEVEL VARIATION (lake little as flowability, highly limited cistern).
The utility model can also adopt Canny to detect operator to carry out edge extracting for gray component, and concrete steps are referring to patent of invention, application number 200910232679.6, and name is called " based on water level measurement system and the method for image vision ".
The utility model adopts the water quality detection principle, and to be each gray-scale value of utilizing different quality compare with the gray scale of the water surface to be detected, and namely processor stores each gray-scale value of different quality, and the water surface image that processor is taken second camera carries out the gray scale processing.
Adopt the MATLAB built-in function that described water surface image is carried out gray-scale value and handle, step is as follows:
I=imread (' image.jpg '); % opens pending picture (8 gray scales)
Imshow (I); % shows this picture
C=mean2 (I); The mean value of % computed image picture element matrix
By the calculating of mean2 function, just can obtain the gray-scale value of described water surface image, table 2 is average gray values of various water quality:
Figure BDA00002932595600051
According to general general knowledge, the water quality quality of these water samples can be arranged like this: pure water〉green tea water〉swimming-pool water〉river〉be mixed with the water of mud〉by the water of dye discoloration〉industrial waste water ≈ prepared Chinese ink water, when water body sampled images gray-scale value (brightness value) more hour, can think that its water quality is more poor, vice versa.Thereby when water quality detection, can also pass through more senior processing means such as sample extraction, neural network, pattern-recognition by to the corresponding water quality conclusion of calculating of water body overall gray level, accomplish to detect the more water-quality guideline of refinement such as turbidity.
For example the gray-scale value of detected water surface image is 85, and the water quality that then draws the water quality of this water surface 2 and river is suitable.
Obviously, above-described embodiment only is for the utility model example clearly is described, and is not to be restriction to embodiment of the present utility model.For those of ordinary skill in the field, can also make other changes in different forms on the basis of the above description.Here need not also can't give all embodiments exhaustive.And these belong to apparent variation or the change that spirit of the present utility model extended out and still are among the protection domain of the present utility model.

Claims (5)

1.一种基于机器视觉的水位和水质监测终端,包括:浮子,其特征在于包括:位于所述浮子的正上方设有适于拍摄浮子影像的第一摄像头,位于水面上方设有适于拍摄水面影像的第二摄像头,所述第一摄像头和第二摄像头输出的相应视频信号输入至视频采集模块,与所述视频采集模块相连的处理器。 1. A water level and water quality monitoring terminal based on machine vision, comprising: a float, characterized in that it includes: a first camera suitable for taking pictures of the float is positioned directly above the float, and a camera suitable for taking pictures is positioned above the water surface The second camera of the water surface image, the corresponding video signals output by the first camera and the second camera are input to the video acquisition module, and the processor connected to the video acquisition module. 2.根据权利要求1所述的基于机器视觉的水位和水质监测终端,其特征在于还包括:适于显示水位值和水质情况的显示模块,适于与计算机通讯的通信模块,处理器与所述显示模块和通信模块相连。 2. The water level and water quality monitoring terminal based on machine vision according to claim 1 is characterized in that it also includes: a display module suitable for displaying water level value and water quality situation, a communication module suitable for communicating with a computer, a processor and the The above display module is connected with the communication module. 3.根据权利要求2所述的基于机器视觉的水位和水质监测终端,其特征在于,所述第一摄像头、第二摄像头的镜头装有红外滤光镜。 3. The water level and water quality monitoring terminal based on machine vision according to claim 2, wherein the lenses of the first camera and the second camera are equipped with infrared filters. 4.根据权利要求3所述的基于机器视觉的水位和水质监测终端,其特征在于,在所述第一摄像头、第二摄像头的镜头周围分布有LED照明装置。 4. The water level and water quality monitoring terminal based on machine vision according to claim 3, characterized in that LED lighting devices are distributed around the lenses of the first camera and the second camera. 5.根据权利要求4所述的基于机器视觉的水位和水质监测终端,其特征在于,所述处理器为FPGA模块或者DSP模块。 5. The water level and water quality monitoring terminal based on machine vision according to claim 4, wherein the processor is an FPGA module or a DSP module.
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Cited By (10)

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CN104148300A (en) * 2014-01-24 2014-11-19 北京聚鑫跃锋科技发展有限公司 Garbage sorting method and system based on machine vision
CN104848917A (en) * 2015-04-20 2015-08-19 大连理工大学 Image measuring method for analyzing water level in glass water tank
CN104943830A (en) * 2015-06-30 2015-09-30 浙江海洋学院 Water gauge detection device based on fixed point camera shooting method
CN106382971A (en) * 2016-11-10 2017-02-08 中国矿业大学(北京) Multifunctional glimmering underground water level monitoring device and system
CN107894264A (en) * 2016-10-04 2018-04-10 恩德莱斯和豪瑟尔分析仪表两合公司 The method determined for material position
CN108252740A (en) * 2018-03-15 2018-07-06 中国矿业大学(北京) Swallet and sump moisture storage capacity monitoring system based on image
CN108457700A (en) * 2018-03-15 2018-08-28 中国矿业大学(北京) Mine sump monitoring and alarming system based on infrared image
CN109139116A (en) * 2018-10-19 2019-01-04 淮南矿业(集团)有限责任公司 A kind of underground emergency water level monitoring system and method
CN111999294A (en) * 2020-08-06 2020-11-27 浙江力聚热水机有限公司 Boiler water quality online detection device and method
CN112884731A (en) * 2021-02-05 2021-06-01 慧目(重庆)科技有限公司 Water level detection method and river channel monitoring method based on machine vision

Cited By (16)

* Cited by examiner, † Cited by third party
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CN104148300A (en) * 2014-01-24 2014-11-19 北京聚鑫跃锋科技发展有限公司 Garbage sorting method and system based on machine vision
CN104148300B (en) * 2014-01-24 2017-02-15 北京聚鑫跃锋科技发展有限公司 Garbage sorting method and system based on machine vision
CN104848917A (en) * 2015-04-20 2015-08-19 大连理工大学 Image measuring method for analyzing water level in glass water tank
CN104848917B (en) * 2015-04-20 2017-11-10 大连理工大学 A kind of image measuring method for water level analysis in glass flume
CN104943830A (en) * 2015-06-30 2015-09-30 浙江海洋学院 Water gauge detection device based on fixed point camera shooting method
CN107894264A (en) * 2016-10-04 2018-04-10 恩德莱斯和豪瑟尔分析仪表两合公司 The method determined for material position
CN106382971A (en) * 2016-11-10 2017-02-08 中国矿业大学(北京) Multifunctional glimmering underground water level monitoring device and system
CN108457700A (en) * 2018-03-15 2018-08-28 中国矿业大学(北京) Mine sump monitoring and alarming system based on infrared image
CN108252740A (en) * 2018-03-15 2018-07-06 中国矿业大学(北京) Swallet and sump moisture storage capacity monitoring system based on image
CN108252740B (en) * 2018-03-15 2023-04-18 中国矿业大学(北京) Image-based mine water burst and water sump water storage capacity monitoring system
CN108457700B (en) * 2018-03-15 2023-04-18 中国矿业大学(北京) Mine sump monitoring alarm system based on infrared image
CN109139116A (en) * 2018-10-19 2019-01-04 淮南矿业(集团)有限责任公司 A kind of underground emergency water level monitoring system and method
CN109139116B (en) * 2018-10-19 2025-02-11 淮南矿业(集团)有限责任公司 A kind of underground emergency water level monitoring system and method
CN111999294A (en) * 2020-08-06 2020-11-27 浙江力聚热水机有限公司 Boiler water quality online detection device and method
CN112884731A (en) * 2021-02-05 2021-06-01 慧目(重庆)科技有限公司 Water level detection method and river channel monitoring method based on machine vision
CN112884731B (en) * 2021-02-05 2022-03-29 慧目(重庆)科技有限公司 Water level detection method and river channel monitoring method based on machine vision

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