TWI801834B - Composition analysis method of electrical and electronic machine parts scraps, method of processing electrical and electronic machine parts scraps, composition analysis device for electrical and electronic machine parts scraps, and processing device for electrical and electronic machine parts scraps - Google Patents

Abstract

The present invention provides a method for analyzing the composition of electrical and electronic equipment scraps and a method for processing electrical and electronic equipment scraps that can analyze the composition of electrical and electronic equipment scraps in a short period of time and efficiently regardless of personal experience or skills , Composition analysis device for electronic and electrical machine parts scraps and processing device for electronic and electrical machine parts scraps. The composition analysis method of electronic and electrical machine parts chips of the present invention is characterized in that it comprises: Extracting electrical and electronic equipment parts scraps from photographed images obtained by photographing a plurality of electronic and electrical equipment scraps including various types of parts; Assigning an identification frame to the extracted electronic and electrical machine parts scraps, the identification frame includes the electronic and electrical machine parts scraps and the background image around the electronic and electrical machine parts scraps; Based on the part type area ratio data, for each of the various types of parts, estimate the total area of the electronic and electrical machine parts scraps with the identification frame attached. information; and By multiplying the estimated total area by the assumed weight per unit area of each of the various types of parts, the weight ratio of electrical and electronic equipment scraps for each of the various types of parts is analyzed separately, and the electronic and electrical components in the captured image are analyzed. Composition of machine parts chips.

Description

Composition analysis method of electrical and electronic machine parts scraps, method of processing electrical and electronic machine parts scraps, composition analysis device for electrical and electronic machine parts scraps, and processing device for electrical and electronic machine parts scraps

The present invention relates to a composition analysis method of electronic and electrical machine parts scraps, a processing method of electronic and electrical machine parts scraps, a composition analysis device for electronic and electrical machine parts scraps and a processing device for electronic and electrical machine parts scraps.

In recent years, from the viewpoint of resource protection, the recovery of valuable metals from scraps of electrical and electronic equipment such as waste household appliances, PCs, and mobile phones has become increasingly popular. In addition, in recent years, the amount of electronic and electrical equipment parts scraps tends to increase, and efficient recycling methods have been studied and proposed.

For example, in JP-A-2015-123418 (Patent Document 1), it is described that electric and electronic equipment parts scraps containing copper are incinerated, crushed to a size below a predetermined size, and the pulverized electric and electronic equipment parts scraps are utilized Copper smelting furnace for processing.

However, due to the increase in the processing volume of electronic and electrical equipment parts scraps, substances that are not conducive to the treatment in the subsequent copper smelting process (smelting hindering substances) are added according to the types of substances contained in electrical and electronic equipment scraps. more amount. If the amount of such smelting hindering substances entering the copper smelting step increases, there will be a situation where it is necessary to limit the input amount of electrical and electronic equipment parts scraps.

For example, electronic and electrical equipment parts scraps include parts scraps of various shapes and types, and the raw material composition changes depending on the source of supply. In order to properly screen the raw materials input into the copper smelting process, at present, the raw material composition of electronic and electrical equipment parts chips is evaluated in advance by visual judgment or chemical analysis, and the evaluation results are reflected in the operation management and operation condition setting of the screening process.

However, in the method of visually determining the composition of raw materials, the evaluation results are uneven due to personal experience or skills, and quantitative evaluation cannot be performed. Chemical analysis or manual screening to specify the composition of raw materials also takes time. [Prior Art Literature] [Patent Document]

[Patent Document 1] Japanese Patent Laid-Open No. 2015-123418

[Problem to be Solved by the Invention]

The present invention provides a method for analyzing the composition of electrical and electronic equipment scraps and a method for processing electrical and electronic equipment scraps that can analyze the composition of electrical and electronic equipment scraps in a short period of time and efficiently regardless of personal experience or skills , Composition analysis device for electronic and electrical machine parts scraps and processing device for electronic and electrical machine parts scraps. [Technical means to solve the problem]

The method for analyzing the composition of electronic and electrical machine parts scraps according to the embodiment of the present invention is the following method for analyzing the composition of electronic and electrical machine parts scraps, which includes: Extracting electrical and electronic equipment parts scraps for each of the multiple types of parts from a photographed image obtained by photographing a plurality of electronic and electrical equipment scraps including various types of parts; Assigning an identification frame to the extracted electronic and electrical machine parts scraps, the identification frame includes the electronic and electrical machine parts scraps and the background image around the electronic and electrical machine parts scraps; Based on the area ratio data of the part types, for each of the various types of parts, estimate the total area of the electronic and electrical machine parts scraps with the identification frame attached. the information of By multiplying the estimated total area by the assumed weight per unit area of each of the various types of parts, the weight ratio of electrical and electronic equipment scraps for each of the various types of parts is analyzed separately, and the electronic and electrical components in the captured image are analyzed. Composition of machine parts chips.

In one embodiment, the method for processing electronic and electrical equipment parts scraps according to the embodiment of the present invention is the following processing method for electronic and electrical equipment parts scraps, which includes a screening step, and the screening step is based on the composition of the above-mentioned electronic and electrical equipment scraps Analyze the results and filter specific part types from various part types.

In one embodiment, the composition analysis device for electronic and electrical machine parts scraps according to the embodiment of the present invention is the following composition analysis device for electronic and electrical machine parts scraps, which includes: Extraction means: extracting electrical and electronic equipment parts scraps from photographed images obtained by photographing a plurality of electronic and electrical equipment scraps including various types of parts; Identification frame imparting means: assigning an identification frame to the extracted electronic and electrical machine parts scraps, the identification frame including the electronic and electrical machine parts scraps and the background image around the electronic and electrical machine parts scraps; Area estimation method: based on the area ratio data of the part type, for each of the various types of parts, estimate the total area of the electronic and electrical machine parts scraps with the identification frame attached. information on the area ratio; and Analysis method: By multiplying the estimated total area by the assumed weight per unit area of each of the various types of parts, the weight ratio of the scraps of electrical and electronic equipment for each of the various types of parts is analyzed separately, and the captured image is analyzed Composition of electronic and electrical machine parts scraps.

The processing device for scraps of electronic and electrical equipment parts according to the embodiment of the present invention provides the following processing device for scraps of electrical and electronic equipment, which includes: Shooting method: Shooting multiple electronic and electrical machine parts scraps containing various types of parts; Composition analysis device: equipped with extraction means, recognition frame assignment means, area estimation means, and analysis means, the extraction means extracts electronic and electrical equipment parts scraps from photographed images; the identification frame assignment means extracts electronic and electrical equipment parts scraps Assign an identification frame, the identification frame includes electrical and electronic equipment parts scraps and the background image around the electrical and electronic equipment scraps; the area estimation means is based on the area ratio data of the type of parts, and for each of the various types of parts, it is estimated that the identification frame is added For the total area of the above-mentioned electronic and electrical machine parts scraps, the data on the area ratio of the electronic and electrical machine parts has information on the area ratio of the electronic and electrical machine parts scraps relative to the identification frame; Multiply the assumed weight per unit area to analyze the weight ratio of electronic and electrical equipment parts scraps for each of the various types of parts, and analyze the composition of electronic and electrical equipment scraps in the captured image; and Screening machine: Based on the composition analysis results analyzed by the composition analysis device, specific parts scraps are screened from electronic and electrical machine parts scraps. [Effect of Invention]

According to the present invention, it is possible to provide a method for analyzing the composition of electrical and electronic equipment scraps, and an electrical and electronic equipment component that can efficiently analyze the composition of electrical and electronic equipment scraps in a short period of time regardless of personal experience or skills. The processing method of shavings, the composition analysis device of electronic and electrical machine parts shavings, and the processing device of electronic and electrical machine parts shavings.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. The embodiments shown below are examples of devices or methods for realizing the technical idea of the present invention, and the technical idea of the present invention does not specify the structure, arrangement, etc. of the constituent parts as follows.

As shown in Fig. 1, the processing device of electronic and electrical machine parts scraps according to the embodiment of the present invention has: Photographing device 12: photographing electronic and electrical machine parts scraps; Composition analysis device 10: equipped with an analysis means for analyzing the composition of electrical and electronic equipment scraps; and Screening machine 13 : based on the composition analysis result analyzed by the composition analysis device 10 , selects specific scraps of parts from the scraps of electrical and electronic equipment.

The so-called "electronic and electrical equipment parts shavings" in this embodiment refers to the shavings of electronic and electrical equipment such as waste household appliances, PCs, and mobile phones, which are recovered and shredded into appropriate sizes. In this embodiment, the crushing to form electrical and electronic equipment parts scraps can be carried out by the processor himself, but it is also possible to purchase crushed ones in the market.

As a crushing method, it is not limited to a specific device, and it can be a shearing method or an impact method, but it is ideal to crush without damaging the shape of the parts as much as possible. Therefore, devices belonging to the category of pulverizers for finer pulverization are not included.

Electronic and electrical equipment parts scraps include plastics (synthetic resins), metal sheets, copper wire scraps, capacitors, IC chips, and others used in substrates and housings, and can be classified in more detail according to the processing purpose. In this embodiment, it is preferable to process electronic and electrical equipment parts chips crushed to a particle size of 50 mm or less, but it is not limited thereto. The lower limit of the particle size is not particularly limited, but is 5 mm or more, more typically 10 mm or more, further 15 mm or more.

The composition analysis device 10 may include a control unit (control device) 100 for controlling composition analysis processing, a memory device 110 for storing information required for various controls, an input device 120 , and a display device 130 . The control unit 100 may include extraction means 101 , recognition frame assignment means 102 , area estimation means 103 , analysis means 104 , operation condition formation means 105 , position information output means 106 , learning means 107 and updating means 108 .

The memory device 110 may include extracted data memory means 111 , part area ratio memory means 112 , analysis information memory means 113 , and additional information memory means 114 . The analysis means 104 can input and output the analysis result of the analysis means 104 to a screening machine 14 different from the screening machine 13 connected via the server 15 or the network 11 via the network 11 .

Extracted data memory means 111 memorizes extracted data, and the extracted data is used to classify and extract images of electronic and electrical machine parts scraps according to each of various types of parts . For example, the extraction data memory means 111 has the ability to extract basic information. The extracted basic information is used to classify various types of parts from the image information of electronic and electrical machine parts scraps, namely substrates, plastics, metal sheets, copper wire scraps, capacitors, and IC chips. , and others (connectors, film-like component scraps, coated wire scraps, etc.), at least two, preferably seven or more, and furthermore ten or more. The conditions for sorting and extracting electronic and electrical equipment parts scraps according to each of the various types of parts can be preset by the operator according to various conditions such as the purpose of subsequent screening and processing.

Extracted data for extraction processing may include, for example, shape information for extracting geometric shapes such as contours of electrical and electronic equipment scraps, color information for extracting the color of electrical and electronic equipment scraps, and information for extracting electrical and electronic equipment scraps. The color of the background image around parts chips, the background information of background information such as shadows formed by bumps, etc., the rotating image of electronic and electrical machine parts chips, etc. The extracted data is stored in the extracted data memory means 111 . The extracting means 101 extracts electronic and electrical equipment parts scraps for each type of parts based on the extracted data stored in the extracted data storage means 111 , and stores the extraction results in the extracted data storage means 111 .

The recognition frame assigning means 102 assigns a recognition frame including the electrical and electronic equipment scraps and a background image around the electrical and electronic equipment scraps to the electrical and electronic equipment scraps extracted by the extraction means. The recognition frame assigning means 102 can easily recognize the outline of electronic and electrical equipment parts chips by assigning a recognition frame including a background image.

The identification frame assigning means 102 preferably assigns a circumscribed and circumscribed figure to the contour of the electrical and electronic machine parts chip as the identification frame. The shape of the circumscribed figure may have any shape such as a circumscribed rectangle, circumscribed circle, or circumscribed polygon. The identification frame imparting means 102 ideally assigns identification frames with different characteristics (color, line shade, line type (thickness, dotted line/solid line, etc.)) for each type of part, so that the operator can easily distinguish between multiple parts. Parts crumbs. FIG. 2( a ) is a photograph showing an example of a situation in which a substrate is extracted from a photographed image as electronic and electrical equipment component scraps. The upper part of the paper in Fig. 2(b) shows the substrate, and the lower part of the paper shows an example of a plastic extract.

The area estimating means 103 uses the part type area ratio data stored in the part area ratio memory means 112 to estimate the total area of electronic and electrical equipment parts scraps with identification frames for each of the various part types. The part type area ratio data is at least Information on the area ratio of electronic and electrical machine parts scraps relative to the identification frame. As part type area rate data, it can include the shape information of the outline of electronic and electrical machine parts, the area of the identification frame, the area occupied by electronic and electrical machine parts in the identification frame and the background area, and the relative identification of electronic and electrical machine parts. Various information such as information on the area ratio of the frame, position information, etc., are learning materials that can be updated at any point in time by the learning means 107 described below.

The analysis means 104 multiplies the estimation result of the total area of electrical and electronic equipment scraps for each type of parts by the predetermined weight per unit area of each of the various types of parts, and the electronic and electrical equipment parts included in the various types of parts Analyze the weight of scraps, so as to analyze the weight ratio of various parts types, and then analyze the composition of electronic and electrical machine parts scraps in the captured images.

The assumed weight per unit area of various types of parts can be set in advance by the operator through the input device 120 etc. according to the operation result. For example, when classifying scraps of electronic and electrical equipment parts into three types: substrates, plastics, and other parts, the assumed weight of substrate scraps can be set to 2.0 g/cm ² , and the assumed weight of plastics can be set to 1.5 g/cm2. cm ² and other parts are set to 1.0 g/cm ² , but it is not limited thereto.

Moreover, in addition to the area information described above, the analysis means 104 can also analyze other physical characteristics and output them to the display device 130, etc., such other physical characteristics are the components of each extracted part type. The number (pieces) of parts of each type, the average particle size calculated based on the above-mentioned area estimation results and the number of parts, the weight ratio of elements constituting each type of part, etc.

The operating condition forming means 105 forms information on the operating conditions of the screening machine for screening the various types of parts based on the analysis results of the weight ratios of the various types of parts obtained by the analyzing means 104 . As the screening machine, there are various screening machines such as a sorting device, a color sorter, a metal sorter, an eddy current screener, a wind screener, and a screener. For example, according to the analysis result of the analyzing means 104, the operating condition forming means 105, for example, forms the operating conditions of a color sorter for screening substrates and plastics, and stores the formed operating conditions in the additional information memory means 114. The operating conditions stored in the additional information memory means 114 are output to the screening machines 13 and 14, and the screening machines 13 and 14 can perform screening processing according to the output operating conditions.

The location information output means 106 acquires the location information of each of the various types of parts classified by the extraction means 101 from the images of electronic and electrical machine parts scraps, and stores the location information in the additional information memory means 114 . Furthermore, the location information is output to specific screening machines 13, 14, and these specific screening machines 13, 14 are used to extract the location of a specific part type from a plurality of parts types and to filter it out. For example, substrates and metal sheets cannot be separated by specific screening machines 13, 14 such as metal sorters, but if position information is obtained individually by using image information, they can be separated by screening machines 13, 14 with a selection function. filter.

The learning means 107 creates learning data necessary for extraction processing and estimation processing by machine learning. For example, the learning means 107 learns the characteristics of each type of various parts such as substrates, plastics, metal sheets, and copper wire scraps. Information such as the relationship between rates is learned based on the input of hundreds to tens of thousands of data, and the purpose is to improve the accuracy of extraction processing and estimation processing.

Furthermore, the learning means 107 further learns the characteristics of the misrecognition or extraction omission of the electronic and electrical equipment part scraps when the misidentification or extraction omission of the extraction means 101 occurs when the misidentification of the electronic and electrical equipment parts scraps occurs. . For example, the learning means 107 creates a new learning model by machine learning, etc., and the machine learning corresponds to the input of various information, for example, the contour information of electronic and electrical equipment parts chips not extracted by the extraction means 101, including information not extracted by the extraction process. Information on the new identification frame of the background image of the electronic and electrical machine parts scraps, information on the area ratio of the electronic and electrical machine parts scraps to the identification frame, etc.

The update means 108 can update the extraction means 101 to extract the extraction data of the part type and the area ratio data of the part type based on the learning result of the learning means 107 . The updated data can also be sent to the screening machine 14 or server 15 connected via the network 11.

Using the flow chart of FIG. 3 , an example of the electrical and electronic equipment parts waste processing method using the electrical and electronic equipment parts waste processing apparatus shown in FIG. 1 will be described. In step S100, a captured image is obtained. The captured image may be a captured image input through the input device 120 or the network 11 , or a captured image captured by the capturing device 12 may be used. In step S101, the extraction means 101 in FIG. 1, based on the extracted data stored in the extracted data storage means 111, sorts the electrical and electronic equipment parts scraps existing in the image captured by the imaging device 12 according to each type of parts (for example, 7 types of substrates, plastics, metal sheets, copper wire scraps, capacitors, IC chips, and other parts) classification.

The classification result of the extraction means 101 can be displayed by the display device 130 and the like. In order to make it easy for the operator to confirm, the classification results can be marked on the image displayed on the display device 130 with identification frames of different colors according to each part type, for example, a red frame is marked on the substrate, a blue frame is marked on the plastic, etc. At this time, the location information output means in FIG. 1 can store the location information based on the extraction result of the extraction means 101 in the additional information storage means 114 .

For example, when classified into seven types of substrates, plastics, metal sheets, copper wire scraps, capacitors, IC chips, and other parts, the substrates, copper wire scraps, capacitors, and IC chips are regarded as valuables, and metal Chips (aluminum or SUS) and plastics are regarded as smelting hindering substances and screened to make the screening conditions appropriate, so that the separation efficiency, loss rate, and operation performance of electronic and electrical machine parts scraps can be quantified and managed.

In step S102 , the recognition frame assigning means 102 assigns a recognition frame including a background image around the electronic and electrical equipment scraps to each of the plurality of types of electronic and electrical equipment parts scraps extracted by the extraction means 101 . In step S103, the area estimating means 103 estimates the area (total area) of the scraps of electrical and electronic equipment with identification frames for each of the plurality of types of parts based on the area ratio data of the type of parts. Information on the area ratio of electrical machine parts scraps relative to the identification frame. In step S103, the analyzing means 104 multiplies the area estimation result obtained by the area estimating means 103 by the assumed weight per unit area of various types of parts and analyzes the weight ratios of the various types of parts respectively, thereby analyzing electrons in the captured image. Composition of electrical machine parts scraps. For example, if the total area of each part type in the image is multiplied by the weight per unit area, the total weight of part chips can be roughly calculated. By comparing the total weight of the scraps of each type of parts, the composition of the scraps of electronic and electrical equipment contained in the captured image can be analyzed. The analysis result is output in step S104.

According to the composition analysis method and composition analysis device of electronic and electrical machine parts scraps according to the embodiment of the present invention, a recognition frame including electronic and electrical machine parts scraps and their surrounding background images is given to the captured image, preferably a recognition frame with a rectangular shape, Using the information on the area ratio of electronic and electrical equipment parts to the recognition frame, the weight of each electronic and electrical equipment parts is analyzed, and image analysis can be used to find out the electrical and electronic equipment that exists in the captured image The weight ratio of each part type to part scrap. Thereby, the composition of raw materials can be estimated rapidly regardless of personal experience or skills. As a result, the operator can judge the purchase conditions of raw materials or the screening method of raw materials earlier, so the entire factory can be used more efficiently.

The background image around the electrical and electronic equipment scraps may vary depending on the conditions of the shooting location, and depending on the situation, the extraction means 101 may not be able to properly extract the electrical and electronic equipment scraps. In this embodiment, a more flexible composition analysis device corresponding to various conditions in the captured image can be obtained by recreating the learning data used for the extraction and processing of electronic and electrical machine parts scraps by the learning means 107. The learning data includes Background information and new identification frame information that is synthesized by combining images obtained by combining border images of electrical and electronic equipment parts scraps.

Fig. 4 is a table showing an example of comparing the estimated results of the areas with the actual measured values by extracting substrates and plastics from photographed images as electronic and electrical equipment parts chips according to the analysis method of the embodiment of the present invention. As shown in Figure 4, according to the composition analysis method of electronic and electrical equipment parts chips according to the embodiment of the present invention, the substrate can be properly evaluated with a measurement error of less than 5.0%, and the plastic can be evaluated with a measurement error of less than 10%. Proper evaluation can achieve a recognition rate of more than 90% when two parts are included. Therefore, this method can obtain a sufficient effect in that the composition of the raw material can be roughly grasped numerically.

Although the present invention has been described by the above-mentioned embodiments, it should not be understood that the statements and drawings forming a part of this disclosure limit the present invention. That is, the present invention is not limited to the respective embodiments, and the constituent elements may be modified and embodied within a range not departing from the gist. In addition, various inventions can be formed by appropriately combining a plurality of constituent elements disclosed in each embodiment. For example, some constituent elements may be deleted from all the constituent elements shown in the embodiment. Furthermore, components of different embodiments may be appropriately combined.

For example, with the analysis means 104, the average area, number, average particle size, weight ratio, etc. of each of various types of parts can be quantified and analyzed from the captured images. Compared with the raw material composition of electrical equipment parts chips, the composition of the raw material can be numerically grasped more quickly.

Furthermore, based on the raw material analysis results analyzed by the analysis means 104, information on the operating conditions of the screening machine for screening a specific type of parts from various types of parts is determined, for example, the selection and screening of a screening machine for screening raw materials Conditions, filter order and other operating conditions, based on the operating conditions for filtering processing.

For example, by wind-screening electronic and electrical machine parts scraps into lightweight and heavy objects, treatment can be performed to increase the weight ratio of substrates and plastics in the processed products after screening. In this case, in the processing by the screening machines 13 and 14, based on the raw material analysis results analyzed by the analysis means 104, the air volume of the air screening machine can be adjusted according to the average particle diameter of various parts types. The air volume can be set at, for example, 5 to 20 m/s, more preferably 5 to 12 m/s, and furthermore about 5 to 10 m/s. Wind screening can be repeated more than 2 times according to the raw material analysis results analyzed by the analysis means 104 .

Alternatively, before performing the above-mentioned wind-force screening, a sorting process using a sorting device may be performed to perform a sorting process for removing massive copper wire scraps. During the sorting process, the position information of the copper wire scraps stored in the additional information memory means 114 is output to the sorting device as the sorting machine 13, and the sorting device can remove the copper wire scraps according to the output result. This copper wire scrap can be sent, for example, to a valuable metal recovery step.

In the case of repeated wind screening for more than two times, the screening process using the screening machine can be carried out between the first wind screening and the second wind screening. In this case, as the screening machine 13, a screening machine can be used, and based on the raw material analysis results analyzed by the analysis means 104, that is, the average particle size of various types of parts, the sieve of the screening machine for screening a specific type of parts can be changed. mesh size.

In addition to the methods described above, the screening machine 13 used in the magnetic screening step, the eddy current screening step, and the optical screening step of optical screening of metal objects and non-metal objects can also be used in the embodiment of the present invention. The composition analysis result of the composition analysis device continuously takes pictures of the electrical and electronic equipment parts scraps being transported, and at the same time analyzes the image data in real time, thereby analyzing the composition of the raw materials.

In the past, the raw material composition of electrical and electronic equipment parts was evaluated by visual judgment or chemical analysis, and the evaluation results were reflected in the operation management and operation condition setting of the screening process. This method cannot be dealt with promptly.

According to the embodiment of the present invention, based on the image analysis and the prescribed classification data, the composition of the electronic and electrical equipment parts scraps is separated from the electronic and electrical equipment parts scraps whose composition changes every moment, so that it can be judged instantaneously and digitized, so it is possible to More suitable conditions to quickly screen a large number of electronic and electrical machine parts scraps.

Furthermore, by image analysis of the raw material composition of the scraps before and after processing by the sorters 13, 14, the sorting efficiency (score) of the sorters 13, 14 can be evaluated based on the amount of change in scrap. Identify the raw material composition of electronic and electrical machine parts scraps and extract their position information, and make it linked with the sorting device or color sorter, metal sorter and other screening machines 13, 14, so as to easily separate the parts types individually. In addition, by marking the analysis results in boxes of different colors for each type of raw material and displaying them on the display device 130 , it is easy for the operator to identify, and therefore it is also easy to identify false detections that constitute the analysis device.

10: Composition analysis device 11: Network 12: Shooting device 13,14: Screening machine 15:Server 100: Control Department 101: Extraction means 102: Identification frame endowment means 103: Area estimation means 104: Analytical means 105: Formation means of operating conditions 106: Location information output means 107: Learning Means 108: Update means 110: memory device 111: Means of extracting data and memory 112: Part area ratio memory means 113: Analyzing Information Memory Means 114:Additional information memory means 120: input device 130: display device S100: Acquiring a captured image S101: assign a recognition frame S102: Estimated area S103: Analyze composition S104: output

[ Fig. 1 ] is a block diagram showing an apparatus for processing scraps of electronic and electrical equipment parts according to an embodiment of the present invention. [Fig. 2] (a) is a photograph showing an example of an image with a recognition frame attached to electronic and electrical equipment parts scraps (substrates) existing in the captured image, and Fig. 2(b) is a photo showing an electronic and electrical device with a recognition frame attached to it. Photo of an example of machine parts shavings arranged by each part type (substrate, plastic). [ Fig. 3 ] is a flow chart showing an example of image analysis processing of electrical and electronic equipment parts chips. [Fig. 4] is a graph showing the comparison between the actual measured value and the estimated value of the total area of the substrate and plastic.

10: Composition analysis device

11: Network

12: Shooting device

13,14: Screening machine

15:Server

100: Control Department

101: Extraction means

102: Identification frame endowment means

103: Area estimation means

104: Analytical means

105: Formation means of operating conditions

106: Location information output means

107: Learning Means

108: Update means

110: memory device

111: Means of extracting data and memory

112: Part area ratio memory means

113: Analyzing Information Memory Means

114:Additional information memory means

120: input device

130: display device

Claims (7)

A method for analyzing the composition of electronic and electrical machine parts scraps, comprising: Extracting the electrical and electronic equipment parts scraps according to each of the multiple types of parts from the photographed images obtained by photographing a plurality of electrical and electronic equipment scraps containing multiple types of parts; Assigning an identification frame to the extracted electronic and electrical machine parts scraps, the identification frame including the electronic and electrical machine parts scraps and the background image around the electronic and electrical machine parts scraps; For each of the multiple types of parts, estimate the total area of the electronic and electrical machine parts scraps with the identification frame based on the area ratio data of the part types. Information on the area ratio of the identification frame; The shot is analyzed by multiplying the estimation result of the total area by the assumed weight per unit area of each of the plurality of parts types, and separately analyzing the weight ratio of the electrical and electronic equipment scraps for each of the plurality of parts types The composition of the electronic and electrical machine parts scraps in the image. The method for analyzing the composition of electronic and electrical equipment parts chips according to claim 1, which further includes: obtaining the contour information of the electronic and electrical equipment parts chips in the captured image that has not been extracted by the extraction process, including the information that has not been extracted by the extraction process Based on the acquisition As a result, the extraction processing and estimation processing are performed. According to claim 1, the composition analysis method of electrical and electronic equipment scraps, wherein the multiple types of parts at least include substrates and plastics. The method for analyzing the composition of electronic and electrical machine parts scraps according to claim 1 or 2, which further includes: forming a screening method for selecting a specific part type from the plurality of parts types based on the analysis result of the composition of the electronic and electrical machine parts scraps Information on the operating conditions of the machine. A method for processing electronic and electrical machine parts scraps, comprising a screening step of screening specific parts from the various types of parts based on the analysis results of the composition of the electronic and electrical machine parts scraps in any one of Claims 1 to 4 Type of part. A device for analyzing the composition of electronic and electrical machine parts scraps, comprising: Extraction means: extracting the electrical and electronic equipment parts scraps from the photographed images obtained by photographing a plurality of electronic and electrical equipment scraps including various types of parts; Identification frame imparting means: assigning an identification frame to the extracted electronic and electrical machine parts scraps, the identification frame including the electronic and electrical machine parts scraps and the background image around the electronic and electrical machine parts scraps; Area estimation means: Based on the area ratio data of the part type, for each of the various types of parts, estimate the total area of the electronic and electrical equipment part scraps with the identification frame attached. Information on the area ratio relative to the identification frame; and Analytical means: by multiplying the estimated total area by the assumed weight per unit area of each of the plurality of parts types, respectively analyzing the weight ratio of the electronic and electrical machine parts scraps for each of the plurality of parts types, and analyzing Composition of the electronic and electrical machine parts scraps in the captured image. A device for processing scraps of electronic and electrical machine parts, which includes: Shooting method: Shooting multiple electronic and electrical machine parts scraps containing various types of parts; Composition analysis device: equipped with extraction means, recognition frame assignment means, area estimation means, and analysis means, the extraction means extracts the electronic and electrical equipment parts scraps from the photographed images; the identification frame assignment means extracts the extracted electrical and electronic equipment Part scraps are assigned an identification frame, which includes the electronic and electrical machine parts scraps and the background image around the electronic and electrical machine parts scraps; the area estimation means is based on the area ratio data of the types of parts, and for each of the various types of parts, it is estimated The total area of the electrical and electronic equipment parts with the identification frame added, the area ratio data of the type of parts has the information of the area ratio of the electronic and electrical equipment parts to the identification frame; the analysis method is based on the total area The estimated result is multiplied by the assumed weight per unit area of each of the various types of parts, and the weight ratio of the electronic and electrical equipment scraps for each of the various types of parts is analyzed separately, and the electronic and electrical equipment in the captured image is analyzed. Composition of machine parts shavings; and Screening machine: Based on the composition analysis results analyzed by the composition analysis device, specific parts scraps are screened from the electronic and electrical machine parts scraps.

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