CN114589109A - High-precision recyclable intelligent identification system and identification method thereof - Google Patents
High-precision recyclable intelligent identification system and identification method thereof Download PDFInfo
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- CN114589109A CN114589109A CN202210187199.8A CN202210187199A CN114589109A CN 114589109 A CN114589109 A CN 114589109A CN 202210187199 A CN202210187199 A CN 202210187199A CN 114589109 A CN114589109 A CN 114589109A
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- 238000000034 method Methods 0.000 title claims abstract description 23
- 239000000463 material Substances 0.000 claims abstract description 113
- 238000001228 spectrum Methods 0.000 claims abstract description 47
- 238000006073 displacement reaction Methods 0.000 claims description 13
- 238000004458 analytical method Methods 0.000 claims description 7
- 238000001514 detection method Methods 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 6
- 230000003595 spectral effect Effects 0.000 claims description 6
- 238000011084 recovery Methods 0.000 claims description 4
- 238000004064 recycling Methods 0.000 description 4
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000004744 fabric Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
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- 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
- B07C5/02—Measures preceding sorting, e.g. arranging articles in a stream orientating
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- 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
- B07C5/342—Sorting according to other particular properties according to optical properties, e.g. colour
- B07C5/3422—Sorting according to other particular properties according to optical properties, e.g. colour using video scanning devices, e.g. TV-cameras
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- 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
- B07C5/36—Sorting apparatus characterised by the means used for distribution
- B07C5/361—Processing or control devices therefor, e.g. escort memory
- B07C5/362—Separating or distributor mechanisms
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- 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
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- 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
- B07C2501/0063—Using robots
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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
- Y02W30/00—Technologies for solid waste management
- Y02W30/50—Reuse, recycling or recovery technologies
- Y02W30/62—Plastics recycling; Rubber recycling
Abstract
The invention provides a high-precision recyclable intelligent identification system and an identification method thereof, wherein the system comprises an image acquisition unit, an image processing unit and a control unit which are electrically connected in sequence; the image acquisition unit comprises a camera unit and a spectrum unit which are sequentially arranged along the material conveying direction at intervals, and the camera unit and the spectrum unit are respectively and electrically connected with the image processing unit. The camera unit and the spectrum unit are matched, so that overlapped materials can be effectively identified, the material identification precision is improved, deviation of the materials in the transportation process is effectively avoided, and the material identification and grabbing precision is improved.
Description
Technical Field
The invention relates to the technical field of classified recovery of recyclable materials, in particular to a high-precision recyclable material intelligent identification system and an identification method thereof.
Background
The recyclable materials are discarded wastes which can be recycled in a recycling mode in the production and living processes of people, according to the latest specification of 'household garbage classification mark' (GB/T19095-.
The recyclable materials are generally classified and recycled, so that the recycling efficiency and the utilization rate of the recyclable materials can be effectively improved. But use more among the prior art at present is recycling thing classification system, changes manual classification into mechanical classification, utilizes artificial intelligence sorter to carry out mechanical sorting, realizes the appointed letter sorting of different kinds of materials through image identification collocation intelligent robot, has effectively improved letter sorting efficiency.
There are still some problems in the recyclables sorting and recycling system at present. Present but categorised recovery system of recovery object adopts single camera to carry out image acquisition and material identification, can't carry out effective discernment to the material that overlaps, so causes the material identification error to lead to follow-up robot to appear some material sorting when sorting can't or sort wrong condition. In addition, adopt single camera to transmit follow-up letter sorting robot to corresponding position information after the material discernment together, nevertheless transport the removal in-process at the material along with the conveyer belt, can produce material swing skew, the deviation appears when snatching in the letter sorting robot that leads to so lieing in the rear, leads to the material not to grab or snatch the mistake.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides a high-precision recyclable intelligent identification system and an identification method thereof.
In order to achieve the purpose, the invention adopts the following technical scheme:
a high-precision recyclable intelligent identification system comprises an image acquisition unit, an image processing unit and a control unit which are electrically connected in sequence; the image acquisition unit comprises a camera unit and a spectrum unit which are sequentially arranged along the material conveying direction at intervals, and the camera unit and the spectrum unit are respectively and electrically connected with the image processing unit.
The image acquisition unit is used for accurately acquiring material images, the camera unit is used for acquiring the material images positioned on the outermost surface, the spectrum unit is used for effectively identifying overlapped materials, and the material image acquisition is carried out on the materials moving for a certain distance again.
The image processing unit is used for processing the images collected by the camera unit and the images collected by the spectrum unit and acquiring the position information of the material.
The control unit is used for receiving the image information and the position information of the material output by the image processing unit and analyzing and processing the information.
Preferably, the control unit comprises a calculation module and an intelligent analysis module.
Preferably, a lighting unit is further arranged in the intelligent recognition system.
Preferably, the rear of the control unit is electrically connected with an intelligent execution unit.
A recognition method of a high-precision recyclable intelligent recognition system comprises the following steps:
s1: turning on the lighting unit, laying the mixed recyclable material flat on a conveyor belt and pre-sorting;
s2: conveying the pre-sorted object to be detected to an image acquisition unit along with a conveying belt and carrying out image acquisition;
s2-1: the camera unit firstly takes a picture of a detection object to finish primary image acquisition;
s2-2: the spectrum unit performs spectrum scanning on the detection object to complete secondary image acquisition; the distance between the camera unit and the spectral unit is L1;
s3: the image processing unit receives images respectively collected by the camera unit and the spectrum unit, identifies and positions materials, and uniformly transmits the processed material types and position information to the control unit;
s4: the control unit analyzes the material information collected by the camera unit and the spectrum unit, discriminates the overlapped materials, captures the overlapped materials, calculates the relative deviation displacement a of the same material after being transmitted to the spectrum unit from the camera unit, and finally calculates the deviation degree of the material;
s5: and the distance L2 from the spectrum measuring unit to the intelligent execution unit is measured, the control unit calculates the deviation displacement b when the material reaches the intelligent execution unit according to the deviation degree, the material is repositioned and an instruction is issued to the intelligent execution unit for material grabbing, and more accurate grabbing of the material is realized.
Preferably, the deviation ratio P is calculated by the formula: p = a/L1= b/L2, where L1 and L2 are known data, and a is data available after the camera unit is compared with the spectral unit image acquisition.
Compared with the prior art, the invention has the following beneficial effects: the spectrum unit is additionally arranged to be matched with the camera unit, so that overlapped materials are effectively identified, and the embarrassing situation that the materials are not completely fallen is effectively avoided; in addition, firstly, image acquisition and positioning are carried out for the first time through the camera unit, image acquisition and positioning are carried out for the second time through the spectrum unit after the camera unit is transported for a certain distance, image information acquired for the two times is compared, the position of the same material is compared, the deflection error of the material in the process of the distance from the camera unit to the spectrum unit is calculated through an algorithm, and then the grabbing positioning of the intelligent execution unit is calculated, so that the grabbing precision is guaranteed, and the deviation is effectively avoided.
Drawings
FIG. 1 is an overall flow chart of a high-precision recyclable intelligent identification system and an identification method thereof according to the present invention;
fig. 2 is a block diagram of a high-precision recyclable intelligent identification system according to the present invention.
Detailed Description
In order to further understand the objects, structures, features, and functions of the present invention, the following embodiments are described in detail.
Referring to fig. 1 and fig. 2, the present invention provides a high-precision recyclable intelligent identification system, which includes an image acquisition unit, an image processing unit and a control unit, which are electrically connected in sequence; the image acquisition unit comprises a camera unit and a spectrum unit which are sequentially arranged along the material conveying direction at intervals, and the camera unit and the spectrum unit are respectively electrically connected with the image processing unit.
The image acquisition unit is used for accurately acquiring material images, the camera unit is used for acquiring the material images positioned on the outermost surface, the spectrum unit is used for effectively identifying overlapped materials, and the material image acquisition is carried out on the materials moving for a certain distance again.
The image processing unit is used for processing the images collected by the camera unit and the images collected by the spectrum unit and acquiring the position information of the material.
The control unit is used for receiving the image information and the position information of the material output by the image processing unit and analyzing and processing the information.
Preferably, the control unit comprises a calculation module and an intelligent analysis module.
Preferably, a lighting unit is further arranged in the intelligent recognition system.
Preferably, the rear of the control unit is electrically connected with an intelligent execution unit.
In one embodiment, the camera unit adopts a color industrial camera, the spectrum unit adopts a spectrometer, and the intelligent execution unit adopts an intelligent grabbing robot.
According to the invention, the image acquisition unit is mainly improved, the spectrometer is additionally arranged, on one hand, overlapped materials are effectively identified, the omission of material identification is avoided, on the other hand, the secondary positioning is carried out by matching with the industrial camera, so that the deflection error of the materials in the distance process from the industrial camera to the spectrometer is calculated through the control unit, the deflection error rate of the materials in the transportation process is calculated, and the deflection error when the materials reach the intelligent grabbing robot is finally calculated, so that the specific grabbing position of the intelligent grabbing robot is adjusted, and the grabbing precision is improved.
In addition, a calculation module and a positive energy analysis module are additionally arranged in the control unit, the control unit is mainly used for calculating the position deviation of the industrial camera and the spectrometer after identifying and positioning the materials in real time, meanwhile, only the analysis module can calculate the deviation rate of the corresponding position according to a deviation rate calculation formula, and calculate the displacement deviation when the intelligent grabbing robot arrives, so that the mechanical arm of the intelligent grabbing robot can be grabbed and positioned again, the material grabbing precision is effectively improved, the sorting precision is improved, and the manual missing difficulty is further reduced.
It should be pointed out that different recoverable materials are in the transportation, and its material cheap position is unknown, and simultaneously, the adjacent range position of different materials is different, also can lead to the material cheap position different, consequently, need cooperate according to camera and spectrum appearance, gather in real time and the information of discernment calculate and analysis material deviation ratio, and then correspond and calculate the position deviation when arriving intelligent snatching robot, so can guarantee the accuracy that each material snatched.
A recognition method of a high-precision recyclable intelligent recognition system comprises the following steps:
s1: turning on the lighting unit, laying the mixed recyclable material flat on a conveyor belt and pre-sorting; mainly removes some materials which are not easy to grab and separate, such as large fabrics, wood boards and the like.
S2: the pre-sorted objects to be detected are conveyed to an image acquisition unit along with a conveyor belt and image acquisition is carried out; the method is used for identifying specific materials of which types and position information of the specific materials on one hand by collecting image information of the detection object.
S2-1: the camera unit firstly takes a picture of a detection object to finish primary image acquisition; the method mainly includes the steps that image information of the materials on the outermost surface is shot directly from the position right above a conveyor belt, and specific material type information and corresponding position information are obtained.
S2-2: the spectrum unit performs spectrum scanning on the detection object to complete secondary image acquisition; the distance between the camera unit and the spectral unit is L1; the overlapped materials are effectively identified through spectrum scanning, so that accurate statistics and identification positioning can be carried out on the materials; a distance L1 is arranged between the first image acquisition and the second image acquisition, so that the deflection error rate of the subsequent analysis material in the operation is convenient.
S3: the image processing unit receives images respectively collected by the camera unit and the spectrum unit, identifies and positions materials, and uniformly transmits the processed material types and position information to the control unit; the image processing unit is mainly used for processing and converting image information acquired by the camera unit and the spectrum unit into position information of corresponding materials respectively and outputting two material position information tables.
S4: the control unit analyzes the material information collected by the camera unit and the spectrum unit, discriminates the overlapped materials, captures the overlapped materials, calculates the relative deviation displacement a of the same material after being transmitted to the spectrum unit from the camera unit, and finally calculates the deviation degree of the material; the control unit compares the two material position information tables and calculates the position deviation of the same material to obtain the position deviation in the distance from the camera unit to the spectrum unit, thereby calculating the deviation rate.
S5: and the distance L2 from the spectrum measuring unit to the intelligent execution unit is measured, the control unit calculates the deviation displacement b when the material reaches the intelligent execution unit according to the deviation degree, the material is repositioned and an instruction is issued to the intelligent execution unit for material grabbing, and more accurate grabbing of the material is realized. The control unit calculates through a formula, and calculates the specific deviation displacement of the intelligent execution unit according to the distance and the deviation rate, so that the manipulator of the intelligent execution unit is accurately positioned according to the deviation displacement, and the grabbing precision is effectively improved.
Preferably, the deviation ratio P is calculated by the formula: p = a/L1= b/L2, where L1 and L2 are known data, and a is data available after the camera unit is compared with the spectral unit image acquisition.
The method comprises the steps of comparing images acquired by a camera unit and a spectrum unit, comparing the positions of the same material to obtain a deviation displacement a, dividing the deviation displacement a by the distance L1 between the camera unit and the spectrum unit to obtain a deviation rate P, multiplying the deviation rate P by the distance L2 between a spectrometer and an intelligent execution unit to obtain the deviation displacement in the displacement process from the spectrum unit to the intelligent grabbing unit, and finally determining the final grabbing position of a manipulator of the intelligent execution unit.
According to the high-precision recyclable intelligent identification system and the identification method thereof, the spectrum unit is additionally arranged to be matched with the camera unit, so that overlapped materials are effectively identified, and the embarrassing situation that the materials are not completely removed is effectively avoided; in addition, the camera unit is used for carrying out primary image acquisition and positioning, the spectrum unit is used for carrying out secondary image acquisition and positioning after the camera unit is transported for a certain distance, image information acquired twice is compared, the position of the same material is compared, and the intelligent execution unit is calculated through the deflection error of the material in the process of calculating the distance from the camera unit to the spectrum unit through an algorithm so as to guarantee the grabbing precision and effectively avoid deviation.
The present invention has been described in relation to the above embodiments, which are only exemplary of the implementation of the present invention. It should be noted that the disclosed embodiments do not limit the scope of the invention. Rather, it is intended that all such modifications and variations be included within the spirit and scope of this invention.
Claims (6)
1. The utility model provides a but high accuracy recovery thing intelligent recognition system which characterized in that: the system comprises an image acquisition unit, an image processing unit and a control unit which are electrically connected in sequence; the image acquisition unit comprises a camera unit and a spectrum unit which are arranged at intervals in sequence along the material conveying direction, and the camera unit and the spectrum unit are respectively electrically connected with the image processing unit;
the image acquisition unit is used for accurately acquiring material images, acquiring the material images positioned on the outermost surface by using the camera unit, effectively identifying overlapped materials by using the spectrum unit, and acquiring the material images of the materials moving for a certain distance again;
the image processing unit is used for processing the image acquired by the camera unit and the image acquired by the spectrum unit and acquiring the position information of the material;
the control unit is used for receiving the image information and the position information of the material output by the image processing unit and analyzing and processing the information.
2. The high-precision recyclables intelligent identification system of claim 1, wherein: the control unit comprises a calculation module and an intelligent analysis module.
3. The high-precision recyclables intelligent identification system of claim 1, wherein: and the intelligent identification system is also internally provided with a lighting unit.
4. The high-precision recyclables intelligent identification system of claim 1, wherein: the rear part of the control unit is electrically connected with an intelligent execution unit.
5. An identification method using the high-precision recyclable intelligent identification system as described in claim 1, characterized in that: the method comprises the following steps:
s1: turning on the lighting unit, laying the mixed recyclable material flat on a conveyor belt and pre-sorting;
s2: the pre-sorted objects to be detected are conveyed to an image acquisition unit along with a conveyor belt and image acquisition is carried out;
s2-1: the camera unit firstly takes a picture of a detection object to finish primary image acquisition;
s2-2: the spectrum unit performs spectrum scanning on the detection object to complete secondary image acquisition; the distance between the camera unit and the spectral unit is L1;
s3: the image processing unit receives images respectively collected by the camera unit and the spectrum unit, identifies and positions materials, and uniformly transmits the processed material types and position information to the control unit;
s4: the control unit analyzes the material information collected by the camera unit and the spectrum unit, discriminates the overlapped materials, captures the overlapped materials, calculates the relative deviation displacement a of the same material after being transmitted to the spectrum unit from the camera unit, and finally calculates the deviation degree of the material;
s5: and the distance L2 from the spectrum measuring unit to the intelligent execution unit is measured, the control unit calculates the deviation displacement b when the material reaches the intelligent execution unit according to the deviation degree, the material is repositioned and an instruction is issued to the intelligent execution unit for material grabbing, and more accurate grabbing of the material is realized.
6. The identification method of the high-precision recyclable intelligent identification system as claimed in claim 5, wherein: the calculation formula of the deviation ratio P is as follows: p = a/L1= b/L2, where L1 and L2 are known data, and a is data available after the camera unit is compared with the spectral unit image acquisition.
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