CN110717533A - Water body purification method based on image recognition pipeline device - Google Patents
Water body purification method based on image recognition pipeline device Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F3/00—Biological treatment of water, waste water, or sewage
- C02F3/02—Aerobic processes
- C02F3/12—Activated sludge processes
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
- Y02W10/00—Technologies for wastewater treatment
- Y02W10/10—Biological treatment of water, waste water, or sewage
Abstract
The invention provides a water body purification method based on an image recognition pipeline device, which comprises the following steps: the image sensor generates a first mixed liquid image by shooting the mixed liquid in the groove and sends the first mixed liquid image to the control module; the control module receives a first mixed liquid image sent by the image sensor and identifies the first mixed liquid image; the control module counts the microbial scores in the mixed liquid based on a preset microbial weighted value; the control module screens out the microorganisms with the grades in the top n on the basis of the mixed liquor microorganism grades; the control module generates real-time optimal water body environmental conditions; the control module generates an adjusting signal based on the real-time optimal water environment condition and sends the adjusting signal to the water environment adjusting module. The method identifies the change of the number of microorganisms in the water body by means of visual identification, and utilizes the water body adjusting module to adjust the water body environment to the optimum water body environment condition of specific microorganisms, so that the microorganisms are rapidly propagated, and the sewage purification speed is accelerated.
Description
Technical Field
The invention relates to the field of pipeline monitoring, in particular to a water body purification method based on an image recognition pipeline device.
Background
The activated sludge process is a biological treatment technique for wastewater, which is a main biological treatment method for wastewater mainly comprising activated sludge, and comprises mixing and stirring wastewater and activated sludge (microorganisms) and aerating to decompose organic pollutants in the wastewater, separating biosolids from the treated wastewater, and returning part of the biosolids to an aeration tank as required.
For sewage of different water qualities, its main pollutant is different, and is corresponding, the microorganism kind that the pollutant corresponds is different, and is specific, if can the pertinence increase the microorganism quantity that main pollutant corresponds in the sewage, have good effect to accelerating sewage purification.
Disclosure of Invention
In order to accelerate the sewage purification speed, the invention provides a water body purification method based on an image recognition pipeline device, because the specific types of microorganisms in the mixed liquid are increased due to functional substances (pollutants), the flora scale is enlarged, the change of the number of the microorganisms in the water body is recognized by means of visual recognition, so that the microorganisms which are most effective in purifying the mixed liquid under the real-time condition are judged, and the water body environment in a sewage treatment pool is regulated to the optimum water body environment condition of the microorganisms by a water body regulation module, so that the microorganisms are rapidly propagated, the sewage purification speed is accelerated, and the water body purification method has good practicability.
Correspondingly, the invention provides a water body purification method based on an image recognition pipeline device, wherein the image recognition pipeline device comprises a sewage treatment pool, a water pump, a pipeline main body with a groove on the inner wall, an image sensor arranged above the groove, a control module and a water body environment adjusting module; the input end of the water suction pump is communicated with the sewage treatment tank, the output end of the water suction pump is communicated with the sewage treatment device through the pipeline main body, and the control module is respectively in signal connection with the image sensor and the water body environment adjusting module;
the sewage purification method comprises the following steps:
the control module sends a water pumping signal to the water pumping pump, the water pumping signal enables the water pumping pump to be started for a certain time, the mixed liquid in the sewage treatment pool flows back to the sewage treatment pool through the pipeline main body, and part of the mixed liquid flowing through the pipeline main body falls into the groove;
the image sensor generates a first mixed liquid image by shooting the mixed liquid in the groove and sends the first mixed liquid image to the control module;
the control module receives a first mixed liquid image sent by the image sensor, identifies the first mixed liquid image, and identifies the type and the corresponding number of microorganisms in the first mixed liquid image;
the control module counts the microorganism scores in the mixed liquor based on a preset microorganism weighted value to generate a mixed liquor microorganism score table;
the control module screens out the microorganisms with the grades in the top n on the basis of the mixed liquid microorganism grading table, and extracts the most suitable water body environmental conditions of any one of the microorganisms with the grades in the top n from a database, wherein n is a positive integer;
the control module synthesizes the optimum water environmental conditions of the first n microorganisms to generate real-time optimum water environmental conditions;
the control module generates an adjusting signal based on the real-time optimal water environment condition and sends the adjusting signal to the water environment adjusting module, and the adjusting signal enables the water environment adjusting module to control the water environment of the sewage treatment tank to change towards the real-time optimal water environment condition.
In an alternative implementation manner, the method for purifying a water body based on an image recognition pipeline device according to claim 1, wherein the controlling module receives a first mixed liquid image sent by the image sensor and recognizes the first mixed liquid image, and the recognizing the types of microorganisms and the corresponding numbers of microorganisms in the first mixed liquid image includes:
the control module is used for preprocessing the first mixed liquid image to generate a second mixed liquid image;
the control module performs image segmentation on the second mixed liquid image by taking a single microorganism as a target to form a plurality of third mixed liquid images;
the control module extracts a microorganism pattern in the third mixed liquid image;
the control module extracts a microorganism feature from the microorganism pattern and extracts a microorganism name from the database based on the microorganism feature;
and the control module counts the types and the quantity of the microorganisms in the second mixed liquid image.
In an optional embodiment, the preprocessing the first mixed image by the control module to generate the second mixed image includes:
and sequentially carrying out illumination compensation processing, image graying processing, filtering denoising processing and normalization processing on the first mixed liquid image to generate a second mixed liquid image.
In an optional embodiment, the extracting, by the control module, the microorganism pattern in the third mixed liquor image includes:
and extracting the microorganism pattern in the third mixed liquid image based on a Haar-Like algorithm.
In an optional embodiment, the extracting the microorganism pattern in the third mixture image based on the Haar-Like algorithm includes:
calculating Haar-Like wavelet characteristics in the third mixed liquid image, and transmitting the Haar-Like wavelet characteristics to a multilayer cascade AdaBoost classifier trained offline; and if the detected microorganism pattern does not pass, taking the third mixed liquid image as a sample to train a classifier, and automatically updating the classifier on line.
In alternative embodiments, the microbial signature includes a profile of the microorganism, a size of the microorganism, and an aggregate density of the microorganism.
In an alternative embodiment, the database stores a data table of the corresponding relationship between the name of the microorganism and the contour and shape of the microorganism, the size of the microorganism, and the aggregation density characteristics of the microorganism.
In an alternative embodiment, the optimal water body environment condition corresponding to the microorganism comprises an optimal temperature interval and an optimal dissolved oxygen content interval;
the real-time optimal water body environmental conditions comprise real-time optimal water body temperature and real-time optimal water body dissolved oxygen content;
the real-time optimal water body temperature is the intersection or average value of the optimal temperature intervals of the first n microorganisms;
the real-time optimal water body dissolved oxygen content is the intersection or average value of the optimal dissolved oxygen content intervals of the first n microorganisms.
In an optional embodiment, the water body environment adjusting module comprises a temperature adjusting module and a dissolved oxygen content adjusting module;
the adjusting signal makes the temperature adjusting module control the water temperature of sewage treatment pond court real-time best water temperature changes, just the adjusting signal is so that dissolved oxygen content adjusting module control the water dissolved oxygen content court of sewage treatment pond real-time best water dissolved oxygen content changes.
The invention provides a water body purification method based on an image recognition pipeline device, which is characterized in that the change of the number of microorganisms in a water body is recognized by means of visual recognition, so that the microorganisms which are most effective in purifying mixed liquid under the real-time condition are judged, and the water body environment in a sewage treatment pool is regulated to the optimum water body environment condition of the microorganisms by utilizing a water body regulation module, so that the microorganisms are rapidly propagated, the sewage purification speed is accelerated, and the water body purification method has good practicability.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of an image recognition pipeline apparatus according to an embodiment of the present invention;
FIG. 2 shows a schematic structural view of a pipe body according to an embodiment of the invention;
FIG. 3 is a flow chart of a water purification method based on an image recognition pipeline device according to an embodiment of the invention;
FIG. 4 is a flow chart showing a method for counting microorganisms according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic structural diagram of an image recognition pipeline device according to an embodiment of the present invention, in which a dotted line indicates signal transmission, a dotted line indicates pipeline transmission (liquid transmission), and some parts are shown in block diagram form because they are common structures.
The image recognition pipeline device comprises a sewage treatment tank, a water suction pump, a pipeline main body with a groove on the inner wall, an image sensor arranged above the groove, a control module and a water body environment adjusting module; the suction pump input with sewage treatment pond intercommunication, the suction pump output warp pipeline main part with sewage treatment ware intercommunication, control module respectively with image sensor with water environment regulation module signal connection.
Fig. 2 is a schematic structural diagram of a pipeline body according to an embodiment of the present invention, where the pipeline body is composed of a first body 101 and a second body 102 that are screwed together based on flanges, and specifically, the first body 101 and the second body 102 are symmetrical about a plane.
The inner side of the first main body 101 is provided with an annular groove 103, and the annular groove 103 of the first main body 101 and the annular groove of the second main body 102 are combined to form a groove of the pipeline main body for accommodating a small amount of mixed liquid flowing through the pipeline main body. A bracket 105 is arranged in the groove along the radial direction, two ends of the bracket 105 are matched on the wall of the groove based on rollers 106, and the size of the bracket 105 (including the rollers 106) in the axial direction is matched with the inner diameter of the groove; an image sensor 105 is fixed to the middle of the bracket in a direction toward the groove. In the concrete implementation, when the pipeline main part is in different position when setting up, under the action of gravity, can keep image sensor orientation directly under all the time, the direction of storing the mixed liquid in the recess promptly. In addition, the first body 101 is further provided with a fluid hole communicated with the ring shape.
Specifically, the water environment affecting the propagation of the microorganisms is mainly the water temperature and the dissolved oxygen content of the water, and therefore the water environment adjusting device provided by the embodiment of the invention comprises a heating element, a heating controller and an air pump, wherein the heating controller controls the heating element to heat the mixed liquid, and the air pump is used for introducing gas containing oxygen into the mixed liquid.
According to the image recognition pipeline device, the mixed liquid is circulated through the pipeline main body through the water suction pump, the groove of the pipeline main body stores part of the mixed liquid flowing through the pipeline main body, the image of the mixed liquid is obtained through the image sensor and is processed through the control module, water body environment conditions which are most beneficial to purification of the mixed liquid are generated, and the water body environment in the sewage treatment pool is adjusted through the water body environment adjusting module, so that the water body environment is beneficial to breeding of specific microorganisms, the speed of sewage purification is improved, and the image recognition pipeline device has good practicability.
Fig. 3 shows a flowchart of a water purifying method based on an image recognition pipeline device according to an embodiment of the present invention, and accordingly, an embodiment of the present invention further provides a water purifying method based on an image recognition pipeline device, where the water purifying method based on an image recognition pipeline device includes the following steps:
s101: the control module sends a pumping signal to the water pump;
the water pumping signal enables the water pumping pump to be started for a certain time, the mixed liquor in the sewage treatment tank flows back to the sewage treatment tank through the pipeline main body, and part of the mixed liquor flowing through the pipeline main body falls into the groove; in specific implementation, a proper light source can be arranged at the bottom of the groove so as to improve the quality of pictures acquired by the image sensor.
S102: the image sensor generates a first mixed liquid image by shooting the mixed liquid in the groove and sends the first mixed liquid image to the control module;
first mixed liquid image is the mixed liquid image in the recess that image sensor shot, and is concrete, and the resolution ratio of first mixed liquid image needs to reach the degree that can show microorganism in the mixed liquid, need set up the magnification of image sensor eyepiece according to the demand in the concrete implementation.
S103: the control module receives a first mixed liquid image sent by the image sensor, identifies the first mixed liquid image, and identifies the type and the corresponding number of microorganisms in the first mixed liquid image;
FIG. 4 is a flow chart showing a method for counting microorganisms according to an embodiment of the present invention. Specifically, the identifying the type of the microorganism and the number of corresponding microorganisms in the first mixed liquid image according to the embodiment of the present invention includes the following steps:
s201: preprocessing the first mixed liquid image to generate a second mixed liquid image;
specifically, after illumination compensation processing, image graying processing, filtering denoising processing and normalization processing are sequentially performed on the first mixed liquid image, a second mixed liquid image is generated.
S202: carrying out image segmentation on the second mixed liquid image by taking a single microorganism as a target to form a plurality of third mixed liquid images;
specifically, patterns which may be microorganisms are detected and located from the second mixed liquid image, the second mixture is segmented based on the patterns of the microorganisms by using an image segmentation technology, and a plurality of third mixed liquid images are generated, wherein each third mixed liquid image comprises at least one microorganism pattern.
S203: extracting a microorganism pattern in the third mixed liquid image based on a Haar-Like algorithm;
calculating Haar-Like wavelet characteristics in the third mixed liquid image, and transmitting the Haar-Like wavelet characteristics to a multilayer cascade AdaBoost classifier trained offline; and if the detected microorganism pattern does not pass, taking the third mixed liquid image as a sample to train a classifier, and automatically updating the classifier on line.
The Haar-like is a very classical feature extraction algorithm, and particularly has good effect on face detection when being used in combination with AdaBoost; OpenCV also packages the cascade face detection composed of AdaBoost and Haar-like, so that Haar-like is generally referred to, and generally appears together with AdaBoost, a cascade classifier, face detection, an integral graph and the like. However, the Haar-like is essentially only a feature extraction algorithm, and since the basic logic adopted is the extraction of the basic features, compared with the complex human face detection, the feature extraction of the microorganisms is simpler, for example, the appearance features of the microorganisms mainly have shapes such as a long straight type, a cluster type, a beam type, a single-wheel non-spiral type, a secondary wheel type and the like, after the image is subjected to gray level processing, the appearance contour of the microorganisms is highlighted due to the influence of light, and the feature extraction is performed through the Haar-like algorithm, so that the appearance features of the microorganisms can be well extracted. Specifically, for some third mixed liquid images which are not matched in the classifier, the microorganism patterns need to be extracted separately after training.
Specifically, the offline training process of the multilayer cascade AdaBoost classifier comprises the following steps:
training samples are divided into a microorganism pattern set and a non-microorganism pattern set, and in the preprocessing stage, the samples are subjected to gray processing so as to calculate the Haar-Like wavelet characteristics of the samples; each Haar-Like wavelet feature forms a weak classifier, an optimal weak classifier is selected through AdaBoost iterative training, the weight is updated, the weak classifiers are combined into a strong classifier, and then a multi-classifier cascade structure from simple to complex and from coarse to fine is adopted; filtering the non-microbial pattern set by using the classifier which is trained offline at present to remove samples which can be classified correctly, and continuing to train a new strong classifier by using continuous AdaBoost if the non-microbial pattern set is not empty; and circulating the steps until all the non-microbial pattern sets are used up.
By the embodiment, the microbial patterns of the existing template can be effectively extracted, and the unknown microbial patterns can be reasonably identified and judged.
S204: performing feature extraction on the microorganism pattern in the third mixed liquid image;
specifically, the step is to characterize the microorganism pattern, and express the microorganism pattern by using specific features.
Specifically, based on step S203, the third mixed liquid image may be subjected to microorganism pattern extraction by using a Haar-like algorithm, and specifically, it is necessary to start species determination on the microorganism pattern.
Specifically, after extracting the microbial pattern, the plane contour information of the microbial pattern can be obtained, specifically, firstly, the shape contour types of the microbial pattern, such as long straight type, cluster type, bundle type, single-wheel non-spiral type, secondary rotation and the like, are determined; then, the size of the microbial pattern is confirmed; the density of the aggregation of the microorganism pattern was then analyzed (continuous aggregation density, not referring to the density in the second mixed liquor image).
Optionally, the features of the microbiological pattern of the embodiments of the invention include profile shape, size, and concentration density.
In specific implementation, more contents can be selected for feature extraction of the microorganism patterns, so that the identification precision is improved. However, because the flora in the activated sludge is limited in variety and can be identified without particularly many features, the embodiment of the invention selects three more prominent features as the features of the microorganism pattern for extraction.
S205: obtaining a microorganism species from the database based on the characteristic;
specifically, the database of the control module stores a data table related to the correspondence between the names of the microorganisms and the characteristics of the microorganisms, and the types of the microorganisms corresponding to the patterns of the microorganisms can be identified by using the characteristics of the patterns of the microorganisms obtained in step S204.
S206: and counting the types and the number of the microorganisms in the second mixed liquid image.
And repeatedly executing the steps, and traversing and calculating the microbial species and the corresponding number of different microbes in the second mixed liquid image.
S104, the control module counts the microorganism scores in the mixed liquor based on a preset microorganism weighted value to generate a mixed liquor microorganism score table;
specifically, since the number of different microorganisms has different meanings, and the number of microorganisms does not match the actual sewage purification effect, in the specific implementation, different microorganism weights are usually set for different microorganisms, the product of the microorganism weights and the microorganism weights is a microorganism score, and the microorganism type which can exert the maximum effect or a larger effect in the water purification can be determined by comparing the microorganism scores of different microorganisms.
S105, screening out the microorganisms with the scores of the top n by the control module based on the mixed liquid microorganism score table, and extracting the most suitable water body environmental conditions of any one of the microorganisms with the scores of the top n from a database, wherein n is a positive integer;
specifically, in step S104, a mixed liquor microorganism score table of microorganism scores of different microorganisms is obtained, and in order to take account of purification speeds of different pollutants, the microorganisms with the microorganism scores ranked in the previous n items are generally taken as targets, and the optimal water environment conditions of any one microorganism of the previous n items are extracted from the database.
S106, the control module synthesizes the optimum water body environmental conditions of the first n microorganisms to generate real-time optimum water body environmental conditions;
specifically, the optimum water environmental conditions of the embodiment of the present invention mainly include temperature and dissolved oxygen content, and therefore, in the optimum water environmental conditions of any one of the first n microorganisms, the optimum propagation temperatures of different microorganisms may have an intersection, and thus it can be obtained that the temperature of the optimum water environmental conditions is within the intersection range; the temperature of the optimal water environmental condition is the mean of the optimal propagation temperatures of the different microorganisms if there may be no intersection of the optimal propagation temperatures of the different microorganisms. Similarly, in connection with the identification of dissolved oxygen content, the dissolved oxygen content for optimal water environmental conditions is the intersection range of the optimal dissolved oxygen content or the mean of the optimal dissolved oxygen content for the different microorganisms.
And S107, the control module generates an adjusting signal based on the real-time optimal water body environment condition and sends the adjusting signal to the water body environment adjusting module, and the adjusting signal enables the water body environment adjusting module to control the water body environment of the sewage treatment tank to change towards the real-time optimal water body environment condition.
Specifically, the most suitable water environment conditions according to the embodiment of the present invention mainly include temperature and dissolved oxygen content, and correspondingly, the water environment adjusting module includes a temperature adjusting module and a dissolved oxygen content adjusting module.
Specifically, the temperature adjusting module controls the temperature of the mixed liquid in the sewage treatment tank through the heating element, and the dissolved oxygen content adjusting module adjusts the dissolved oxygen content in the sewage treatment tank.
The invention provides a water body purification method based on an image recognition pipeline device, which enlarges the scale of flora due to the increase of functional substances (pollutants) of specific types of microorganisms in mixed liquid, recognizes the change of the number of the microorganisms in the water body by means of visual recognition, thereby judging the microorganisms which are most effective in purifying the mixed liquid under the real-time condition, and utilizes a water body adjusting module to adjust the water body environment in a sewage treatment pool to the most suitable water body environment condition of the microorganisms, so that the microorganisms are rapidly propagated, the sewage purification speed is accelerated, and the water body purification method has good practicability.
The water purifying method based on the image recognition pipeline device provided by the embodiment of the invention is described in detail, a specific example is applied in the method to explain the principle and the implementation mode of the invention, and the description of the embodiment is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (9)
1. A water body purification method based on an image recognition pipeline device is characterized in that the image recognition pipeline device comprises a sewage treatment pool, a water pump, a pipeline main body with a groove in the inner wall, an image sensor arranged above the groove, a control module and a water body environment adjusting module; the input end of the water suction pump is communicated with the sewage treatment tank, the output end of the water suction pump is communicated with the sewage treatment device through the pipeline main body, and the control module is respectively in signal connection with the image sensor and the water body environment adjusting module;
the sewage purification method comprises the following steps:
the control module sends a water pumping signal to the water pumping pump, the water pumping signal enables the water pumping pump to be started for a certain time, the mixed liquid in the sewage treatment pool flows back to the sewage treatment pool through the pipeline main body, and part of the mixed liquid flowing through the pipeline main body falls into the groove;
the image sensor generates a first mixed liquid image by shooting the mixed liquid in the groove and sends the first mixed liquid image to the control module;
the control module receives a first mixed liquid image sent by the image sensor, identifies the first mixed liquid image, and identifies the type and the corresponding number of microorganisms in the first mixed liquid image;
the control module counts the microorganism scores in the mixed liquor based on a preset microorganism weighted value to generate a mixed liquor microorganism score table;
the control module screens out the microorganisms with the grades in the top n on the basis of the mixed liquid microorganism grading table, and extracts the most suitable water body environmental conditions of any one of the microorganisms with the grades in the top n from a database, wherein n is a positive integer;
the control module synthesizes the optimum water environmental conditions of the first n microorganisms to generate real-time optimum water environmental conditions;
the control module generates an adjusting signal based on the real-time optimal water environment condition and sends the adjusting signal to the water environment adjusting module, and the adjusting signal enables the water environment adjusting module to control the water environment of the sewage treatment tank to change towards the real-time optimal water environment condition.
2. The water purification method based on image recognition pipeline device according to claim 1, wherein the control module receives a first mixed liquid image sent by the image sensor and recognizes the first mixed liquid image, and the recognizing of the type and the corresponding number of the microorganisms in the first mixed liquid image comprises:
the control module is used for preprocessing the first mixed liquid image to generate a second mixed liquid image;
the control module performs image segmentation on the second mixed liquid image by taking a single microorganism as a target to form a plurality of third mixed liquid images;
the control module extracts a microorganism pattern in the third mixed liquid image;
the control module extracts a microorganism feature from the microorganism pattern and extracts a microorganism name from the database based on the microorganism feature;
and the control module counts the types and the quantity of the microorganisms in the second mixed liquid image.
3. The image-recognition-pipeline-apparatus-based water purification method of claim 2, wherein the control module preprocesses the first mixed liquid image and generates the second mixed liquid image comprises:
and sequentially carrying out illumination compensation processing, image graying processing, filtering denoising processing and normalization processing on the first mixed liquid image to generate a second mixed liquid image.
4. The image-recognition-pipeline-apparatus-based water purification method of claim 2, wherein the extracting of the microorganism pattern in the third mixed liquid image by the control module comprises:
and extracting the microorganism pattern in the third mixed liquid image based on a Haar-Like algorithm.
5. The image-recognition-pipeline-apparatus-based water purification method of claim 3, wherein the extraction of the microorganism pattern in the third mixed liquid image based on the Haar-Like algorithm comprises:
calculating Haar-Like wavelet characteristics in the third mixed liquid image, and transmitting the Haar-Like wavelet characteristics to a multilayer cascade AdaBoost classifier trained offline; and if the detected microorganism pattern does not pass, taking the third mixed liquid image as a sample to train a classifier, and automatically updating the classifier on line.
6. The water purifying method based on image recognition pipeline device as claimed in claim 2, wherein the microorganism characteristics comprise contour shape of microorganism, size of microorganism and concentration density of microorganism.
7. The water purifying method based on image recognition pipeline device as claimed in claim 6, wherein the database stores a data table of the corresponding relationship between the microorganism name and the contour and shape of the microorganism, the size of the microorganism, and the aggregation density of the microorganism.
8. The water purifying method based on the image recognition pipeline device as claimed in claim 1, wherein the optimal water environment condition corresponding to the microorganism comprises an optimal temperature interval and an optimal dissolved oxygen content interval;
the real-time optimal water body environmental conditions comprise real-time optimal water body temperature and real-time optimal water body dissolved oxygen content;
the real-time optimal water body temperature is the intersection or average value of the optimal temperature intervals of the first n microorganisms;
the real-time optimal water body dissolved oxygen content is the intersection or average value of the optimal dissolved oxygen content intervals of the first n microorganisms.
9. The water body purification method based on the image recognition pipeline device as claimed in claim 8, wherein the water body environment adjusting module comprises a temperature adjusting module and a dissolved oxygen content adjusting module;
the adjusting signal makes the temperature adjusting module control the water temperature of sewage treatment pond court real-time best water temperature changes, just the adjusting signal is so that dissolved oxygen content adjusting module control the water dissolved oxygen content court of sewage treatment pond real-time best water dissolved oxygen content changes.
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| CN113485484A (en) * | 2021-07-26 | 2021-10-08 | 利晟（杭州）科技有限公司 | Adaptive temperature control system suitable for biological degradation sewage treatment |
| CN117171675A (en) * | 2023-11-02 | 2023-12-05 | 北京建工环境修复股份有限公司 | Water environment microorganism detection method, system and medium based on multi-source data |
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| CN117171675B (en) * | 2023-11-02 | 2024-01-12 | 北京建工环境修复股份有限公司 | Water environment microorganism detection method, system and medium based on multi-source data |
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