CN111027639A - Cloud-based garbage sorting system and method, information processing terminal and storage medium - Google Patents

Cloud-based garbage sorting system and method, information processing terminal and storage medium Download PDF

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CN111027639A
CN111027639A CN201911352074.0A CN201911352074A CN111027639A CN 111027639 A CN111027639 A CN 111027639A CN 201911352074 A CN201911352074 A CN 201911352074A CN 111027639 A CN111027639 A CN 111027639A
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garbage
module
image
main control
cloud
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白岩
田阳
金文海
王艳丽
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Beihua University
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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
    • G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B03—SEPARATION OF SOLID MATERIALS USING LIQUIDS OR USING PNEUMATIC TABLES OR JIGS; MAGNETIC OR ELECTROSTATIC SEPARATION OF SOLID MATERIALS FROM SOLID MATERIALS OR FLUIDS; SEPARATION BY HIGH-VOLTAGE ELECTRIC FIELDS
    • B03C—MAGNETIC OR ELECTROSTATIC SEPARATION OF SOLID MATERIALS FROM SOLID MATERIALS OR FLUIDS; SEPARATION BY HIGH-VOLTAGE ELECTRIC FIELDS
    • B03C1/00—Magnetic separation
    • B03C1/02—Magnetic separation acting directly on the substance being separated
    • B03C1/30—Combinations with other devices, not otherwise provided for
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
    • B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
    • B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
    • B07C5/34—Sorting according to other particular properties
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
    • F23G—CREMATION FURNACES; CONSUMING WASTE PRODUCTS BY COMBUSTION
    • F23G5/00—Incineration of waste; Incinerator constructions; Details, accessories or control therefor
    • F23G5/02—Incineration of waste; Incinerator constructions; Details, accessories or control therefor with pretreatment
    • F23G5/04—Incineration of waste; Incinerator constructions; Details, accessories or control therefor with pretreatment drying
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
    • F23G—CREMATION FURNACES; CONSUMING WASTE PRODUCTS BY COMBUSTION
    • F23G5/00—Incineration of waste; Incinerator constructions; Details, accessories or control therefor
    • F23G5/44—Details; Accessories
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
    • F23G—CREMATION FURNACES; CONSUMING WASTE PRODUCTS BY COMBUSTION
    • F23G5/00—Incineration of waste; Incinerator constructions; Details, accessories or control therefor
    • F23G5/44—Details; Accessories
    • F23G5/46—Recuperation of heat
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/25—Fusion techniques
    • G06F18/251—Fusion techniques of input or preprocessed data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/25—Determination of region of interest [ROI] or a volume of interest [VOI]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
    • G06V10/267—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion by performing operations on regions, e.g. growing, shrinking or watersheds
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
    • B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
    • B07C2501/00—Sorting according to a characteristic or feature of the articles or material to be sorted
    • B07C2501/0054—Sorting of waste or refuse

Abstract

The invention belongs to the technical field of garbage sorting, and discloses a cloud-based garbage sorting system, a cloud-based garbage sorting method, an information processing terminal and a storage medium, wherein the cloud-based garbage sorting system comprises a garbage image acquisition module, a main control module, an image analysis module, a filtering module, a separation module, a rotation module, a garbage processing module, a garbage recycling module and a display module; the garbage image acquisition module acquires garbage image data; the main control module controls each module to work normally; the image analysis module analyzes the collected garbage image; the separation module is used for separating and classifying the garbage. According to the invention, the complex oil-gas separation system in the traditional garbage pyrolysis process is omitted through the garbage treatment module, and the garbage treatment method is simple, low in cost and easy to operate; the garbage recycling module improves the garbage disposal and recycling efficiency, reduces the resource waste, reduces the difficulty of garbage innocent treatment, and weakens the influence on the environment.

Description

Cloud-based garbage sorting system and method, information processing terminal and storage medium
Technical Field
The invention belongs to the technical field of garbage sorting, and particularly relates to a cloud-based garbage sorting system and method, an information processing terminal and a storage medium.
Background
The garbage is a waste product which loses use value and cannot be utilized, and is an important link of material circulation. Is a solid, fluid substance that is not needed or useful. In densely populated large cities, waste disposal is a headache problem. It is common practice to collect and send the waste to a landfill for landfill treatment or incinerate the waste with an incinerator. Both create environmental protection issues and termination of overconsumption can further mitigate landfill saturation. Disposal of waste in landfill sites not only contaminates ground water and gives off odors, but also makes less and less area available for landfill in many cities. Incineration inevitably produces toxic gases, which harm different independent species. Most cities are researching ways to reduce the production of garbage and encouraging resource reclamation. The garbage classification is a necessary choice for realizing reduction, quality improvement and efficiency improvement, and is an important measure for improving human living environment, promoting fine management of cities and guaranteeing sustainable development. Can not classify garbage and directly reflect the ecological literacy and civilization degree of one person or even one city. However, the existing garbage treatment operation is complex, and sewage is generated; meanwhile, the recovery efficiency of the garbage is low.
Prior art 1
A household garbage sorting method based on machine vision comprises the following steps: the method comprises the following steps: carrying out constant volume treatment on garbage to be sorted;
step two: the conveyor belt conveys the garbage subjected to constant volume treatment forwards, the magnetic metal garbage sorting device sorts the magnetic metal garbage out of the conveyor belt and places the magnetic metal garbage into the magnetic garbage collecting device by using the mechanical arm;
step three: continuously shooting garbage advancing at a constant speed by using a high-definition CCD lens, sending a shot garbage image into a database, and comparing and analyzing the shot garbage image with an inherent image in the database so as to judge whether the garbage is non-fruit and vegetable garbage;
step four: obtaining contour images of the target garbage by adopting an image contour comparison algorithm, calculating a weighted average value of geometric positions of all contour pixels of each contour image of the target garbage to obtain position coordinates of the target garbage on a conveyor belt, and transmitting the position information to a control system;
step five: the control system outputs a control signal according to the position coordinate of the target garbage fed back by the data analysis device, and the mechanical arm sorting device automatically sorts the target garbage according to the control signal and sorts the target garbage to the material collection device.
Prior art 2
An intelligent rubbish sorting device and control system includes:
an image analysis module: the image analysis module consists of a camera and is used for reading garbage information and recording garbage images;
a control module: the control module consists of a memory, a processor and a controller, the memory is used for storing images of the garbage, the processor compares the information of the garbage transmitted by the image analysis module to determine the classification of the garbage, and the controller is used for signaling the rotary driving module and the garbage pushing module;
a rotation driving module: the rotary driving module consists of a rotator which receives a signal sent by the control module and then rotates the track to a specific position;
the garbage pushing module: the garbage pushing module receives a signal sent by the control module and then pushes the garbage into the garbage sorting box;
the image analysis module is connected with the control module, the rotation driving module is connected with the control module, and the garbage pushing module is connected with the control module.
In summary, the problems of the prior art are as follows:
the garbage sorting systems in the first and second prior art have complex garbage treatment operation and generate sewage; meanwhile, the existing garbage sorting system has low garbage recovery efficiency.
In the intelligent processing, the prior art does not really carry out intelligent control, the automatic classification effect of rubbish is poor, and convenient to use flexibility is low.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a cloud-based garbage sorting system method, an information processing terminal and a storage medium.
The invention is realized in such a way that a cloud-based garbage sorting method comprises the following steps:
the method comprises the following steps of firstly, analyzing the collected garbage image:
(1.1) extracting the quantity of different independent types of the collected garbage images, reducing the dimension, and obtaining a feature number k after dimension reduction; the mapping matrix is
Figure BDA0002333744440000031
Wherein the column vector fi∈RM×NAnd if i is 1, k, the characteristic data of different independent types of the shapes after the dimensionality reduction is
Figure BDA0002333744440000032
Forming matrix psi ═ psi1，...，ψn]；
(1.2) Peak degree
Figure BDA0002333744440000033
Measuring the characteristic data psi of different independent types of shapes after dimension reductioniN, and obtains the distinguishing feature of the maximum kurtosis { f ═ 11 T，...，fn T}；
(1.3) obtaining a mapping matrix F and the dimensionality reduced valueCharacteristic data of the same independent kind
Figure BDA0002333744440000034
(1.4) subtracting the mean value from the feature data D of different independent types to obtain the centralized feature data of different independent types:
Figure BDA0002333744440000035
(1.5) centering on different independent kinds of feature data D1Calculating D1C ═ D, of the covariance matrix1D1 TWherein D is1 TIs a matrix D1The covariance matrix C is subjected to eigenvalue decomposition, where C ═ U Λ UTWherein
Figure BDA0002333744440000036
A diagonal matrix formed of eigenvalues of C, U ═ U1，...，uM×N]A feature vector of C;
(1.6) centering on different independent kinds of feature data D1Whitening to obtain whitened matrix
Figure BDA0002333744440000037
Wherein W ═ inv (sqrt (Λ)) UTThe variance on each characteristic dimension is 1, and different characteristic dimensions are not related;
(1.7) carrying out pixel level image fusion on the image processed in the steps (1.1) to (1.6) based on wavelet transformation;
(1.8) carrying out region-of-interest segmentation and main feature extraction on the image after pixel-level image fusion to obtain different independent types of main image information;
(1.9) extracting an interested region from the image processed in the step (1.8), removing background and non-useful information, and segmenting and matching the gray value of a pixel, the contours of different independent types, the color, the reflection characteristics and the texture to obtain an accurate graph of the segmented independent type;
and secondly, performing separation and classification operation on the garbage according to an analysis result:
(2.1) selecting a standard image of classified garbage as a calibration sample,
(2.2) extracting garbage components to be classified from the analysis result obtained in the first step to obtain different independent types of feature data D1The eigenvalues are A1, A2, L and Ah from big to small; the eigenvector corresponding to the maximum eigenvalue lambda 1 is a first principal axis a1, and the eigenvector corresponding to the second eigenvalue lambda 2 is a second principal axis a2, so that the first and second garbage components to be classified t1 and t2 are obtained; the h-th garbage component th to be classified can be obtained by analogy in sequence;
and (2.3) establishing a component classification table for the acquired garbage component data to be classified, transmitting the information of the component classification table to the main control module, and executing classification operation.
Further, the cloud-based garbage sorting method specifically comprises:
acquiring garbage image data by a garbage image acquisition module through a camera assembly;
secondly, the main control module analyzes the garbage image acquired by the image analysis program through the image analysis module;
step three, filtering the garbage by a filtering module by using a filtering device;
step four, separating and classifying the garbage by using a separating device through a separating module according to the analysis result;
fifthly, the separated garbage is rotated to a corresponding storage box through a rotating module by utilizing a rotating storage box to be stored;
step six, the separated garbage is treated by a garbage treatment module through a garbage treatment device; recycling the separated garbage by using recycling equipment through a garbage recycling module;
and step seven, the display module displays the acquired garbage image and the analysis result by using a display.
Further, the first step specifically comprises: 1) utilizing a camera shooting component to scan images of the garbage according to a certain resolution ratio;
2) when corresponding garbage is scanned, converting the image gray scale of the garbage into a voltage value corresponding to the gray scale, and outputting the voltage value; converting the voltage value into a video signal and outputting the video signal;
3) in the process of voltage value transmission, the voltage value is processed through a filter network to prevent signal distortion;
further, the first step specifically comprises: in the sixth step, the garbage disposal module treatment method comprises the following steps:
(1) performing primary dehydration on garbage to be treated: putting the garbage to be treated into a retting pool for retting; carrying out filter pressing on the retted garbage;
(2) drying the garbage after preliminary dehydration;
(3) tamping the dried garbage;
(4) baking the garbage retort furnace to enable the temperature in a carbonization chamber of the garbage retort furnace to reach a set temperature;
the garbage retort is characterized in that a furnace door is arranged on a furnace body of the garbage retort, the retort chamber is arranged in the furnace body, and the retort chamber is formed by enclosing a partition wall arranged in the furnace body and the furnace door; a combustion chamber is formed in a space between the furnace body and the dry distillation chamber; the plurality of the dry distillation chambers and the combustion chambers are arranged at intervals;
(5) introducing the tamped garbage into a dry distillation chamber of a garbage dry distillation furnace, and performing dry distillation on the garbage to obtain dry distillation gas;
(6) introducing the dry distillation gas obtained in the step (5) into a combustion chamber of the garbage dry distillation furnace through a dry distillation gas guide outlet to burn so as to provide heat for garbage dry distillation; the dry distillation gas outlet is arranged at the upper part of the partition wall;
(7) and (4) introducing the combustion waste gas generated in the step (6) for combustion into a heat exchange chamber for heat exchange.
Further, in the sixth step, the garbage recycling module recycling method includes:
i) acquiring physical attribute information of the junk articles; the physical attribute information is information representing physical characteristics of the junk articles;
ii) determining the garbage type of the garbage article according to the physical attribute information of the garbage article, so that a user can recycle the garbage article according to the garbage type of the garbage article.
Further, the acquiring physical attribute information of the junk item in step i) includes: acquiring physical attribute information of the garbage articles through infrared ray or X-ray scanning;
the physical attribute information includes at least one or a combination of the following information: volume, shape, color, composition, density, hardness, thermal conductivity, electrical conductivity, magnetism, or transparency;
in step ii), before determining the trash type to which the trash item belongs, the method further includes:
presetting a corresponding relation between the garbage type and the physical attribute information;
the determining the garbage type to which the garbage article belongs according to the physical attribute information of the garbage article specifically includes:
determining the garbage type of the garbage article according to the physical attribute information of the garbage article and the corresponding relation;
after the determining the garbage type to which the garbage item belongs, the method further includes:
determining at least two first garbage recycling points matched with the garbage types according to the garbage types of the garbage articles;
respectively calculating the distances between the at least two first garbage collection points and the positions of the garbage articles;
taking the first garbage recycling point corresponding to the minimum distance in the distances as a second garbage recycling point matched with the garbage type;
after the determining the garbage type to which the garbage item belongs, the method further includes:
if the safety level of the garbage type is lower than a preset safety level threshold value, sending alarm information to a user;
after the determining the garbage type to which the garbage item belongs, the method further includes:
storing the corresponding relation between the garbage items and the garbage types to which the garbage items belong;
the garbage type comprises at least one of the following types: heavy metal type, plastic type, glass type, waste paper type, toxic and harmful substance containing type, or electronic waste type.
Another object of the present invention is to provide an information data processing terminal for implementing the cloud-based garbage sorting method.
It is another object of the present invention to provide a computer-readable storage medium comprising instructions which, when run on a computer, cause the computer to perform the cloud-based garbage sorting method.
Another object of the present invention is to provide a cloud-based garbage sorting system, comprising:
the garbage image acquisition module is connected with the main control module and used for acquiring garbage image data through the camera assembly;
the main control module is connected with the garbage image acquisition module, the image analysis module, the filtering module, the separation module, the rotation module, the garbage treatment module, the garbage recovery module and the display module and is used for controlling each module to normally work through the main control computer;
the image analysis module is connected with the main control module and is used for analyzing the garbage image collected by the image analysis program;
the filtering module is connected with the main control module and is used for filtering the garbage through the filtering device;
the separation module is connected with the main control module and is used for performing separation and classification operation on the garbage according to the analysis result through the separation device;
the rotating module is connected with the main control module and used for rotating the separated garbage to the corresponding storage box through the rotating storage box to store the separated garbage;
the garbage treatment module is connected with the main control module and is used for treating the separated garbage through the garbage treatment equipment;
the garbage recycling module is connected with the main control module and used for recycling the separated garbage through recycling equipment;
and the display module is connected with the main control module and used for displaying the acquired garbage image and the analysis result through the display.
Further, the image analysis module includes:
the image processing module is used for denoising, increasing the contrast, carrying out gray level processing and carrying out image color processing on the acquired image;
extracting image features, retrieving the processed image, and extracting corresponding feature description or feature vectors;
and image feature analysis, namely analyzing by using a neural network according to the extracted feature information.
The master control module comprises:
the input module is used for receiving the image information acquired by the garbage image acquisition module, coding the acquired image information into a form which can be analyzed by the system;
the storage module is used for compressing and storing the coded information;
the processing module is used for judging and analyzing according to the acquired information and carrying out comprehensive analysis;
the action command output module is used for providing a corresponding control command for an external execution mechanism;
the wireless signal transmission module transmits the processed information to the cloud server through a wireless signal transceiving module in the main control module;
the separation module includes:
the manual screening module is used for manually screening larger garbage according to the analysis result displayed by the display;
the electromagnetic screening module is used for controlling the electromagnet to be electrified according to the system analysis result so as to carry out refining on the iron garbage in the garbage;
the garbage crushing module is used for crushing the residual garbage by using a crusher; meanwhile, the garbage is conveyed into the drum screen by using a conveying belt.
The roller screening module is used for switching on a rotating motor in the roller screen to be powered on and screening the garbage by utilizing the rolling of the roller;
the airflow separation module is used for respectively conveying the screened garbage and the garbage retained in the roller to different separation pools, and screening out the light garbage by utilizing airflow;
the garbage recycling module is provided with a compression module, and the compression module pushes the classified garbage into a compression cavity by a hydraulic cylinder pushing baffle plate by utilizing pressure energy provided by a hydraulic power station; the main control module controls the clamping device to clamp the garbage, and the clamping force on the garbage is constantly detected by using the pressure sensor in the garbage clamping process; after the garbage is extruded into a block shape, the garbage is pushed out of the compression cavity by the electric push plate.
The invention has the advantages and positive effects that:
according to the invention, the garbage is tamped after being dehydrated and dried by the garbage treatment module, the tamped garbage can further dehydrate the dried garbage, and the bulk density of the garbage can be increased by more than two times after being tamped, so that the dry distillation efficiency of the garbage is improved. In the garbage treatment process, dry distillation gas generated by dry distillation of the garbage is used as fuel to provide energy for self dry distillation, and heat carried by combustion waste gas generated after combustion can be used for drying the garbage, so that the energy utilization rate in the garbage treatment process is improved, and the garbage treatment method is more environment-friendly; the dry distillation gas is completely used as fuel, a complex oil-gas separation system in the traditional garbage pyrolysis process is omitted, and the garbage treatment method is simple, low in cost and easy to operate; meanwhile, the garbage recycling module firstly acquires the physical attribute information of the garbage articles, and then determines the garbage types of the garbage articles according to the physical attribute information of the garbage articles, so that a user can recycle the garbage articles according to the garbage types of the garbage articles, and can effectively classify the garbage articles, so that the garbage articles can be further classified and recycled, the garbage disposal and recycling efficiency is improved, the resource waste is reduced, the garbage harmless disposal difficulty is reduced, and the influence on the environment is weakened.
The method comprises the steps of analyzing collected garbage images, extracting the quantity of different independent types from the collected garbage images, reducing dimensions, carrying out region-of-interest segmentation and main feature extraction on images obtained after pixel-level image fusion, and obtaining main image information of different independent types so as to obtain accurate graphs of the independent types after segmentation; and performing separation and classification operation on the garbage according to the analysis result. The intelligent classification of rubbish is realized.
Drawings
Fig. 1 is a flowchart of a cloud-based garbage sorting method according to an embodiment of the present invention.
Fig. 2 is a block diagram of a cloud-based garbage sorting system according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a main control module according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of a separation module according to an embodiment of the present invention.
In the figure: 1. a garbage image acquisition module; 2. a main control module; 3. an image analysis module; 4. a filtration module; 5. a separation module; 6. a rotation module; 7. a garbage disposal module; 8. a garbage recycling module; 9. a display module; 10. an input module; 11. a storage module; 12. a processing module; 13. an action command output module; 14. a wireless signal transmission module; 15. a manual screening module; 16. an electromagnetic screening module; 17. a garbage crushing module; 18. a roller screening module; 19. and a gas flow separation module.
Fig. 5 is a flowchart of a garbage disposal module processing method according to an embodiment of the present invention.
Fig. 6 is a flowchart of a garbage collection module collection method according to an embodiment of the present invention.
Detailed Description
In order to further understand the contents, features and effects of the present invention, the following embodiments are exemplified and included in the detailed description with reference to the accompanying drawings.
The structure of the present invention will be described in detail below with reference to the accompanying drawings.
The cloud-based garbage sorting method provided by the embodiment of the invention comprises the following steps:
the method comprises the following steps of firstly, analyzing the collected garbage image:
and (1.1) extracting the quantity of different independent types of the collected garbage images, reducing the dimension, and obtaining a feature number k after dimension reduction. The mapping matrix is
Figure BDA0002333744440000101
Wherein the column vector fi∈RM×NAnd if i is 1, k, the characteristic data of different independent types of the shapes after the dimensionality reduction is
Figure BDA0002333744440000102
Forming matrix psi ═ psi1，...，ψn]。
(1.2) Peak degree
Figure BDA0002333744440000103
Measuring the characteristic data psi of different independent types of shapes after dimension reductioniN, and obtains the distinguishing feature of the maximum kurtosis { f ═ 11 T，...，fn T}。
(1.3) obtaining a mapping matrix F and the characteristic data of different independent types after dimension reduction
Figure BDA0002333744440000104
(1.4) subtracting the mean value from the feature data D of different independent types to obtain the centralized feature data of different independent types:
Figure BDA0002333744440000105
(1.5) centering on different independent kinds of feature data D1Calculating D1C ═ D, of the covariance matrix1D1 TWherein D is1 TIs a matrix D1The covariance matrix C is subjected to eigenvalue decomposition, where C ═ U Λ UTWherein
Figure BDA0002333744440000106
A diagonal matrix formed of eigenvalues of C, U ═ U1，...，uM×N]Is the feature vector of C.
(1.6) centering on different independent kinds of feature data D1Whitening to obtain whitened matrix
Figure BDA0002333744440000107
Wherein W ═ inv (sqrt (Λ)) UTThe variance in each feature dimension is 1, and there is no correlation between different feature dimensions.
And (1.7) carrying out pixel-level image fusion on the image processed in the steps (1.1) to (1.6) based on wavelet transformation.
And (1.8) carrying out region-of-interest segmentation and main feature extraction on the image after pixel-level image fusion to obtain different independent types of main image information.
And (1.9) extracting an interested area from the image processed in the step (1.8), removing background and non-useful information, and segmenting and matching the gray value of the pixel, the contour of different independent types, the color, the reflection characteristic and the texture to obtain an accurate graph of the segmented independent type.
And secondly, performing separation and classification operation on the garbage according to an analysis result:
(2.1) selecting a standard image of classified garbage as a calibration sample,
(2.2) extracting garbage components to be classified from the analysis result obtained in the first step to obtain different independent types of feature data D1The eigenvalues of (a) are A1, A2, L and Ah in the order from large to small. The eigenvector corresponding to the maximum eigenvalue λ 1 is the first principal axis a1, and the eigenvector corresponding to the second eigenvalue λ 2 is the second principal axis a2, thereby obtaining the first and second garbage components to be classified t1 and t 2. And the h-th garbage component th to be classified can be obtained by analogy in turn.
And (2.3) establishing a component classification table for the acquired garbage component data to be classified, transmitting the information of the component classification table to the main control module, and executing classification operation.
As shown in fig. 1, the cloud-based garbage sorting method provided by the present invention includes the following steps:
and S101, acquiring garbage image data by utilizing a camera shooting assembly through a garbage image acquisition module.
And S102, the main control module analyzes the garbage image acquired by the image analysis program through the image analysis module.
And S103, filtering the garbage by using a filtering device through a filtering module.
And S104, performing separation and classification operation on the garbage according to the analysis result by using the separation device through the separation module.
And S105, rotating the separated garbage to a corresponding storage box by using the rotating storage box through the rotating module for storage.
S106, the separated garbage is processed by a garbage processing device through a garbage processing module; and recycling the separated garbage by using recycling equipment through a garbage recycling module.
And S107, the display module displays the acquired garbage image and the analysis result by using a display.
As shown in fig. 2, the cloud-based garbage sorting system provided by the embodiment of the present invention includes: the garbage image processing system comprises a garbage image acquisition module 1, a main control module 2, an image analysis module 3, a filtering module 4, a separation module 5, a rotation module 6, a garbage processing module 7, a garbage recycling module 8 and a display module 9.
And the garbage image acquisition module 1 is connected with the main control module 2 and is used for acquiring garbage image data through the camera shooting assembly.
The main control module 2 is connected with the garbage image acquisition module 1, the image analysis module 3, the filtering module 4, the separation module 5, the rotation module 6, the garbage disposal module 7, the garbage recovery module 8 and the display module 9, and is used for controlling each module to normally work through the main control computer.
And the image analysis module 3 is connected with the main control module 2 and is used for analyzing the garbage images collected by the image analysis program.
And the filtering module 4 is connected with the main control module 2 and is used for filtering the garbage through the filtering device.
And the separation module 5 is connected with the main control module 2 and is used for performing separation and classification operation on the garbage according to the analysis result through the separation device.
And the rotating module 6 is connected with the main control module 2 and used for rotating the separated garbage to the corresponding storage box for storage through rotating the storage box.
And the garbage treatment module 7 is connected with the main control module 2 and is used for treating the separated garbage through garbage treatment equipment.
And the garbage recycling module 8 is connected with the main control module 2 and is used for recycling the separated garbage through recycling equipment.
And the display module 9 is connected with the main control module 2 and used for displaying the acquired garbage image and the analysis result through a display.
The process for collecting the garbage image data through the camera shooting assembly in the garbage image acquisition module 1 comprises the following steps:
the garbage sparing system is provided with the camera shooting assembly, and the image scanning is carried out on garbage according to a certain resolution ratio by the camera shooting assembly.
When the corresponding garbage is scanned, the image gray scale of the garbage is converted into a voltage value corresponding to the gray scale, and the voltage value is output. And converting the voltage value into a video signal for output.
In the process of voltage value transmission, the voltage value is processed through a filter network, so that signal distortion is prevented.
The image analysis module 3 for analyzing the garbage image collected by the image analysis program includes:
and the image processing module is used for denoising the acquired image, increasing the contrast, carrying out gray level processing and carrying out image color processing.
And extracting image features, retrieving the processed image, and extracting corresponding feature description or feature vectors.
And image feature analysis, namely analyzing by using a neural network according to the extracted feature information.
As shown in fig. 3, the main control module 2 includes:
and the input module 10 is used for receiving the image information acquired by the garbage image acquisition module, coding the acquired image information into a form which can be analyzed by the system.
And the storage module 11 compresses and stores the coded information.
And the processing module 12 is used for judging and analyzing according to the acquired information and carrying out comprehensive analysis.
And the action command output module 13 provides a corresponding control command for an external execution mechanism.
The wireless signal transmission module 14 transmits the processed information to the cloud server through a wireless signal transceiver module in the main control module.
As shown in fig. 4, the separation module 5 includes:
and the manual screening module 15 is used for manually screening larger garbage according to the analysis result displayed by the display.
And the electromagnetic screening module 16 controls the electromagnet to be electrified according to the system analysis result, and divides and smelts the iron garbage in the garbage.
The garbage crushing module 17 crushes the remaining garbage with a crusher. Meanwhile, the garbage is conveyed into the drum screen by using a conveying belt.
And the roller screening module 18 is used for switching on a rotating motor in the roller screen to be powered on and screening the garbage by utilizing the rolling of the roller.
And an air flow separation module 19 for conveying the sorted garbage and the garbage accumulated in the drum to different separation tanks, respectively, and sorting out the light garbage by air flow.
In the embodiment of the invention, the garbage recycling module 8 for recycling the separated garbage through recycling equipment is provided with a compression module, and the compression module pushes the classified garbage into a compression cavity by a hydraulic cylinder pushing a baffle plate by utilizing pressure energy provided by a hydraulic power station; the control system controls the clamping device to clamp the garbage, and the clamping force on the garbage is detected by utilizing the pressure sensor constantly in the garbage clamping process; after the garbage is extruded into a block shape, the garbage is pushed out of the compression cavity by the electric push plate.
As shown in fig. 5, the processing method of the garbage disposal module 7 provided by the present invention includes:
s201, performing primary dehydration on the garbage to be treated: putting the garbage to be treated into a retting pool for retting; and carrying out filter pressing on the retted garbage.
And S202, drying the garbage after primary dehydration.
And S203, tamping the dried garbage.
S204, performing oven drying treatment on the garbage retort to enable the temperature in a retort chamber of the garbage retort to reach a set temperature. The garbage dry distillation furnace is characterized in that a furnace door is arranged on a furnace body of the garbage dry distillation furnace, the dry distillation chamber is arranged in the furnace body, and the dry distillation chamber is formed by enclosing a partition wall arranged in the furnace body and the furnace door; a combustion chamber is formed in a space between the furnace body and the dry distillation chamber; the plurality of dry distillation chambers and the combustion chamber are arranged at intervals.
And S205, introducing the tamped garbage into a dry distillation chamber of a garbage dry distillation furnace, and performing dry distillation on the garbage to obtain dry distillation gas.
S206, introducing the dry distillation gas obtained in the step S205 into a combustion chamber of the garbage dry distillation furnace through a dry distillation gas outlet to burn so as to provide heat for garbage dry distillation; the dry distillation gas outlet is arranged at the upper part of the partition wall.
And S207, introducing the combustion waste gas generated in the step S206 for combustion into a heat exchange chamber for heat exchange.
As shown in fig. 6, the recycling method of the garbage recycling module 8 provided by the present invention includes:
s301, acquiring physical attribute information of the junk articles; the physical attribute information is information representing physical characteristics of the junk item.
S302, determining the garbage type of the garbage article according to the physical attribute information of the garbage article, so that a user can recycle the garbage article according to the garbage type of the garbage article.
The invention provides a method for acquiring physical attribute information of junk articles, which comprises the following steps: and acquiring the physical attribute information of the garbage articles through infrared ray or X-ray scanning.
Before determining the garbage type to which the garbage item belongs, the method further comprises the following steps:
the corresponding relation between the garbage types and the physical attribute information is preset.
The determining the garbage type to which the garbage article belongs according to the physical attribute information of the garbage article specifically includes:
and determining the garbage type of the garbage article according to the physical attribute information of the garbage article and the corresponding relation.
After determining the garbage type to which the garbage item belongs, the method further comprises the following steps:
and determining at least two first garbage recycling points matched with the garbage types according to the garbage types of the garbage articles.
And respectively calculating the distances between the at least two first garbage collection points and the positions of the garbage articles.
And taking the first garbage recycling point corresponding to the minimum distance in the distances as a second garbage recycling point matched with the garbage type.
After determining the garbage type to which the garbage item belongs, the method further comprises the following steps:
and if the safety level of the garbage type is lower than a preset safety level threshold value, sending alarm information to a user.
After determining the garbage type to which the garbage item belongs, the method further comprises the following steps:
and storing the corresponding relation between the garbage items and the garbage types to which the garbage items belong.
The garbage types provided by the invention comprise at least one of the following types: heavy metal type, plastic type, glass type, waste paper type, toxic and harmful substance containing type, or electronic waste type.
The physical attribute information provided by the invention comprises at least one or more of the following information: volume, shape, color, composition, density, hardness, thermal conductivity, electrical conductivity, magnetism, or transparency.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and all simple modifications, equivalent changes and modifications made to the above embodiment according to the technical spirit of the present invention are within the scope of the technical solution of the present invention.

Claims (10)

1. A cloud-based garbage sorting method is characterized by comprising the following steps:
the method comprises the following steps of firstly, analyzing the collected garbage image:
(1.1) extracting the quantity of different independent types of the collected garbage images, reducing the dimension, and obtaining a feature number k after dimension reduction; the mapping matrix is
Figure FDA0002333744430000011
Wherein, the column directionQuantity fi∈RM×NAnd if i is 1, k, the characteristic data of different independent types of the shapes after the dimensionality reduction is
Figure FDA0002333744430000012
Forming matrix psi ═ psi1，...，ψn]；
(1.2) Peak degree
Figure FDA0002333744430000013
Measuring the characteristic data psi of different independent types of shapes after dimension reductioniN, and obtains the distinguishing feature of the maximum kurtosis { f ═ 11 T，...，fn T}；
(1.3) obtaining a mapping matrix F and the characteristic data of different independent types after dimension reduction
Figure FDA0002333744430000014
(1.4) subtracting the mean value from the feature data D of different independent types to obtain the centralized feature data of different independent types:
Figure FDA0002333744430000015
(1.5) centering on different independent kinds of feature data D1Calculating D1C ═ D, of the covariance matrix1D1 TWherein D is1 TIs a matrix D1The covariance matrix C is subjected to eigenvalue decomposition, where C ═ U Λ UTWherein
Figure FDA0002333744430000016
A diagonal matrix formed of eigenvalues of C, U ═ U1，...，uM×N]A feature vector of C;
(1.6) centering on different independent kinds of feature data D1Whitening to obtain whitened matrix
Figure FDA0002333744430000017
Wherein W ═ inv (sqrt (Λ)) UTThe variance on each characteristic dimension is 1, and different characteristic dimensions are not related;
(1.7) carrying out pixel level image fusion on the image processed in the steps (1.1) to (1.6) based on wavelet transformation;
(1.8) carrying out region-of-interest segmentation and main feature extraction on the image after pixel-level image fusion to obtain different independent types of main image information;
(1.9) extracting an interested region from the image processed in the step (1.8), removing background and non-useful information, and segmenting and matching the gray value of a pixel, the contours of different independent types, the color, the reflection characteristics and the texture to obtain an accurate graph of the segmented independent type;
and secondly, performing separation and classification operation on the garbage according to an analysis result:
(2.1) selecting a standard image of classified garbage as a calibration sample,
(2.2) extracting garbage components to be classified from the analysis result obtained in the first step to obtain different independent types of feature data D1The eigenvalues are A1, A2, L and Ah from big to small; the eigenvector corresponding to the maximum eigenvalue lambda 1 is a first principal axis a1, and the eigenvector corresponding to the second eigenvalue lambda 2 is a second principal axis a2, so that the first and second garbage components to be classified t1 and t2 are obtained; obtaining the h-th component th of the garbage to be classified by analogy in sequence;
and (2.3) establishing a component classification table for the acquired garbage component data to be classified, transmitting the information of the component classification table to the main control module, and executing classification operation.
2. The cloud-based garbage sorting method according to claim 1, wherein the cloud-based garbage sorting method specifically comprises:
acquiring garbage image data by a garbage image acquisition module through a camera assembly;
secondly, the main control module analyzes the garbage image acquired by the image analysis program through the image analysis module;
step three, filtering the garbage by a filtering module by using a filtering device;
step four, separating and classifying the garbage by using a separating device through a separating module according to the analysis result;
fifthly, the separated garbage is rotated to a corresponding storage box through a rotating module by utilizing a rotating storage box to be stored;
step six, the separated garbage is treated by a garbage treatment module through a garbage treatment device; recycling the separated garbage by using recycling equipment through a garbage recycling module;
and step seven, the display module displays the acquired garbage image and the analysis result by using a display.
3. The cloud-based garbage sorting method according to claim 2, wherein the first step specifically comprises: 1) utilizing a camera shooting component to scan images of the garbage according to a certain resolution ratio;
2) when corresponding garbage is scanned, converting the image gray scale of the garbage into a voltage value corresponding to the gray scale, and outputting the voltage value; converting the voltage value into a video signal and outputting the video signal;
3) in the process of voltage value transmission, the voltage value is processed through a filter network, so that signal distortion is prevented.
4. The cloud-based garbage sorting method according to claim 2, wherein the first step specifically comprises: in the sixth step, the garbage disposal module treatment method comprises the following steps:
(1) performing primary dehydration on garbage to be treated: putting the garbage to be treated into a retting pool for retting; carrying out filter pressing on the retted garbage;
(2) drying the garbage after preliminary dehydration;
(3) tamping the dried garbage;
(4) baking the garbage retort furnace to enable the temperature in a carbonization chamber of the garbage retort furnace to reach a set temperature;
the garbage retort is characterized in that a furnace door is arranged on a furnace body of the garbage retort, the retort chamber is arranged in the furnace body, and the retort chamber is formed by enclosing a partition wall arranged in the furnace body and the furnace door; a combustion chamber is formed in a space between the furnace body and the dry distillation chamber; the plurality of the dry distillation chambers and the combustion chambers are arranged at intervals;
(5) introducing the tamped garbage into a dry distillation chamber of a garbage dry distillation furnace, and performing dry distillation on the garbage to obtain dry distillation gas;
(6) introducing the dry distillation gas obtained in the step (5) into a combustion chamber of the garbage dry distillation furnace through a dry distillation gas guide outlet to burn so as to provide heat for garbage dry distillation; the dry distillation gas outlet is arranged at the upper part of the partition wall;
(7) and (4) introducing the combustion waste gas generated in the step (6) for combustion into a heat exchange chamber for heat exchange.
5. The cloud-based garbage sorting method according to claim 2, wherein in step six, the garbage recycling module recycling method comprises:
i) acquiring physical attribute information of the junk articles; the physical attribute information is information representing physical characteristics of the junk articles;
ii) determining the garbage type of the garbage article according to the physical attribute information of the garbage article, so that a user can recycle the garbage article according to the garbage type of the garbage article.
6. The cloud-based spam sorting method of claim 5, wherein said obtaining physical attribute information of spam items in step i) comprises: acquiring physical attribute information of the garbage articles through infrared ray or X-ray scanning;
the physical attribute information includes at least one or a combination of the following information: volume, shape, color, composition, density, hardness, thermal conductivity, electrical conductivity, magnetism, or transparency;
in step ii), before determining the trash type to which the trash item belongs, the method further includes:
presetting a corresponding relation between the garbage type and the physical attribute information;
the determining the garbage type to which the garbage article belongs according to the physical attribute information of the garbage article specifically includes:
determining the garbage type of the garbage article according to the physical attribute information of the garbage article and the corresponding relation;
after the determining the garbage type to which the garbage item belongs, the method further includes:
determining at least two first garbage recycling points matched with the garbage types according to the garbage types of the garbage articles;
respectively calculating the distances between the at least two first garbage collection points and the positions of the garbage articles;
taking the first garbage recycling point corresponding to the minimum distance in the distances as a second garbage recycling point matched with the garbage type;
after the determining the garbage type to which the garbage item belongs, the method further includes:
if the safety level of the garbage type is lower than a preset safety level threshold value, sending alarm information to a user;
after the determining the garbage type to which the garbage item belongs, the method further includes:
storing the corresponding relation between the garbage items and the garbage types to which the garbage items belong;
the garbage type comprises at least one of the following types: heavy metal type, plastic type, glass type, waste paper type, toxic and harmful substance containing type, or electronic waste type.
7. An information data processing terminal for implementing the cloud-based garbage sorting method according to any one of claims 1 to 6.
8. A computer-readable storage medium comprising instructions that, when executed on a computer, cause the computer to perform the cloud-based garbage sorting method of any of claims 1-6.
9. A cloud-based garbage sorting system, comprising:
the garbage image acquisition module is connected with the main control module and used for acquiring garbage image data through the camera assembly;
the main control module is connected with the garbage image acquisition module, the image analysis module, the filtering module, the separation module, the rotation module, the garbage treatment module, the garbage recovery module and the display module and is used for controlling each module to normally work through the main control computer;
the image analysis module is connected with the main control module and is used for analyzing the garbage image collected by the image analysis program;
the filtering module is connected with the main control module and is used for filtering the garbage through the filtering device;
the separation module is connected with the main control module and is used for performing separation and classification operation on the garbage according to the analysis result through the separation device;
the rotating module is connected with the main control module and used for rotating the separated garbage to the corresponding storage box through the rotating storage box to store the separated garbage;
the garbage treatment module is connected with the main control module and is used for treating the separated garbage through the garbage treatment equipment;
the garbage recycling module is connected with the main control module and used for recycling the separated garbage through recycling equipment;
and the display module is connected with the main control module and used for displaying the acquired garbage image and the analysis result through the display.
10. The cloud-based spam sorting system of claim 9, wherein the image analysis module comprises:
the image processing module is used for denoising, increasing the contrast, carrying out gray level processing and carrying out image color processing on the acquired image;
extracting image features, retrieving the processed image, and extracting corresponding feature description or feature vectors;
and image feature analysis, namely analyzing by using a neural network according to the extracted feature information.
The master control module comprises:
the input module is used for receiving the image information acquired by the garbage image acquisition module, coding the acquired image information into a form which can be analyzed by the system;
the storage module is used for compressing and storing the coded information;
the processing module is used for judging and analyzing according to the acquired information and carrying out comprehensive analysis;
the action command output module is used for providing a corresponding control command for an external execution mechanism;
the wireless signal transmission module transmits the processed information to the cloud server through a wireless signal transceiving module in the main control module;
the separation module includes:
the manual screening module is used for manually screening larger garbage according to the analysis result displayed by the display;
the electromagnetic screening module is used for controlling the electromagnet to be electrified according to the system analysis result so as to carry out refining on the iron garbage in the garbage;
the garbage crushing module is used for crushing the residual garbage by using a crusher; meanwhile, the garbage is conveyed into the drum screen by using a conveying belt.
The roller screening module is used for switching on a rotating motor in the roller screen to be powered on and screening the garbage by utilizing the rolling of the roller;
the airflow separation module is used for respectively conveying the screened garbage and the garbage retained in the roller to different separation pools, and screening out the light garbage by utilizing airflow;
the garbage recycling module is provided with a compression module, and the compression module pushes the classified garbage into a compression cavity by a hydraulic cylinder pushing baffle plate by utilizing pressure energy provided by a hydraulic power station; the main control module controls the clamping device to clamp the garbage, and the clamping force on the garbage is constantly detected by using the pressure sensor in the garbage clamping process; after the garbage is extruded into a block shape, the garbage is pushed out of the compression cavity by the electric push plate.
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