CN115239790A - Grit composition screening analysis system based on image recognition - Google Patents
Grit composition screening analysis system based on image recognition Download PDFInfo
- Publication number
- CN115239790A CN115239790A CN202210889397.9A CN202210889397A CN115239790A CN 115239790 A CN115239790 A CN 115239790A CN 202210889397 A CN202210889397 A CN 202210889397A CN 115239790 A CN115239790 A CN 115239790A
- Authority
- CN
- China
- Prior art keywords
- sand
- terminal
- module
- sandstone
- drying
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000012106 screening analysis Methods 0.000 title claims description 5
- 239000004576 sand Substances 0.000 claims abstract description 160
- 238000004458 analytical method Methods 0.000 claims abstract description 56
- 239000000463 material Substances 0.000 claims abstract description 52
- 238000001035 drying Methods 0.000 claims abstract description 49
- 239000004575 stone Substances 0.000 claims abstract description 43
- 230000005540 biological transmission Effects 0.000 claims abstract description 36
- 238000004140 cleaning Methods 0.000 claims abstract description 32
- 238000000926 separation method Methods 0.000 claims abstract description 22
- 238000012216 screening Methods 0.000 claims abstract description 17
- 239000002689 soil Substances 0.000 claims description 47
- 239000002002 slurry Substances 0.000 claims description 45
- 239000011159 matrix material Substances 0.000 claims description 35
- 239000010865 sewage Substances 0.000 claims description 26
- 238000001914 filtration Methods 0.000 claims description 18
- 238000004364 calculation method Methods 0.000 claims description 17
- 238000000034 method Methods 0.000 claims description 10
- 239000012925 reference material Substances 0.000 claims description 9
- 238000005303 weighing Methods 0.000 claims description 8
- 238000012937 correction Methods 0.000 claims description 7
- 238000009826 distribution Methods 0.000 claims description 6
- 238000011156 evaluation Methods 0.000 claims description 4
- 238000003860 storage Methods 0.000 claims description 4
- 239000012535 impurity Substances 0.000 claims description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 3
- 230000003750 conditioning effect Effects 0.000 claims 1
- 239000002351 wastewater Substances 0.000 claims 1
- 238000010438 heat treatment Methods 0.000 description 13
- 238000007664 blowing Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 239000004566 building material Substances 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 239000004035 construction material Substances 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 239000011499 joint compound Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000013021 overheating Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
-
- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F11/00—Treatment of sludge; Devices therefor
-
- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F11/00—Treatment of sludge; Devices therefor
- C02F11/12—Treatment of sludge; Devices therefor by de-watering, drying or thickening
- C02F11/13—Treatment of sludge; Devices therefor by de-watering, drying or thickening by heating
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/06—Topological mapping of higher dimensional structures onto lower dimensional surfaces
- G06T3/067—Reshaping or unfolding 3D tree structures onto 2D planes
-
- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F2303/00—Specific treatment goals
- C02F2303/06—Sludge reduction, e.g. by lysis
-
- 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
- Y02W30/91—Use of waste materials as fillers for mortars or concrete
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Hydrology & Water Resources (AREA)
- Environmental & Geological Engineering (AREA)
- Water Supply & Treatment (AREA)
- Life Sciences & Earth Sciences (AREA)
- Organic Chemistry (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Mechanical Engineering (AREA)
- Geometry (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Sampling And Sample Adjustment (AREA)
- Analysing Materials By The Use Of Radiation (AREA)
Abstract
The invention provides a sand and stone component screening and analyzing system based on image recognition, which comprises a separation terminal, a cleaning terminal, a drying terminal, a transmission terminal, a scanning terminal and an analyzing terminal, wherein the separation terminal is used for separating sand and mud from sand and stone materials, the cleaning terminal is used for cleaning and collecting residual mud on the sand and stone, the drying terminal is used for drying sand and mud with moisture, the transmission terminal is used for transmitting the dried sand and stone, the scanning terminal is used for carrying out three-dimensional scanning shooting on the sand and stone on the transmission terminal, and the analyzing terminal is used for receiving and analyzing data information of the scanning terminal to generate analysis result information. The invention improves the efficiency and accuracy of the analysis system.
Description
Technical Field
The invention relates to the technical field of component analysis of building materials, in particular to a sand component screening and analyzing system based on image recognition.
Background
Image recognition, which is a technique for processing, analyzing and understanding images by using a computer to recognize various different patterns of targets and objects, is a practical application of applying a deep learning algorithm. Image recognition technology at present is generally divided into face recognition and commodity recognition, and the face recognition is mainly applied to security inspection, identity verification and mobile payment; the commodity identification is mainly applied to the commodity circulation process, in particular to the field of unmanned retail such as unmanned goods shelves and intelligent retail cabinets. The 3D camera is a digital camera that allows a user to enjoy stereoscopic images or moving pictures with the naked eye. And the three-dimensional data acquisition of images and videos can be realized. The combination of the two technologies can be used for component analysis of building materials, particularly for analyzing the sandstone materials, and is favorable for accurately analyzing the quality condition of the sandstone materials so as to improve the safety of building engineering.
A number of analysis systems or evaluation systems for construction materials have now been developed, and through our extensive search and reference, it has been found that the analysis systems of the prior art are disclosed in CN112528913A, CN210730115U, EP1070249A1, US3869110A, JP 2016166866A, which generally include: frame, unloading equipment, image acquisition equipment, light filling equipment, image processing equipment, display, slider, collection box, image processing equipment divides the step of handling to the grit image and includes: firstly, resNet based on a characteristic pyramid network (FPN) is used as a characteristic extraction network, secondly, a self-adaptive ROIAlign module is provided, each suggestion frame output by RPN is mapped to all characteristic levels of the FPN, a mode that multi-scale characteristics are fused by taking the maximum value through a parameter layer is adopted, and finally, ioU prediction branches are added to improve the positioning performance of the network. As the requirements of the construction industry on the quantity and the quality of the sandstone materials are continuously improved, a faster and more accurate analysis system is needed to analyze the sandstone materials continuously, but the analysis system has a lower analysis speed and a smaller quantity of sandstone which can be analyzed at each time, so that the defect that the analysis efficiency of the analysis system is reduced is caused.
Disclosure of Invention
The invention aims to provide a sand component screening and analyzing system based on image recognition, aiming at the defects of the analyzing system.
The invention adopts the following technical scheme:
a sand and stone component screening and analyzing system based on image recognition comprises a separation terminal, a cleaning terminal, a drying terminal, a transmission terminal, a scanning terminal and an analyzing terminal, wherein the separation terminal is used for performing sand and stone and mud separation on sand and stone materials, the cleaning terminal is used for cleaning and collecting residual mud on the sand and stone, the drying terminal is used for drying the sand and the mud with water, the transmission terminal is used for transmitting the dried sand and stone, the scanning terminal is used for performing three-dimensional scanning and shooting on the sand and stone on the transmission terminal, and the analyzing terminal is used for receiving and analyzing data information of the scanning terminal and generating analysis result information;
the separation terminal comprises a filtering module and a subpackaging module, the filtering module is used for filtering sand and stone and slurry, and the subpackaging module is used for subpackaging the separated sand and stone and slurry;
the cleaning terminal comprises a cleaning module and a collecting module, the cleaning module is used for cleaning sand, and the collecting module is used for collecting sewage generated when the sand is cleaned;
the drying terminal comprises a sand drying module and a slurry drying module, wherein the sand drying module is used for drying sand, and the slurry drying module is used for drying slurry and sewage;
the transmission terminal comprises a sand and stone transmission module and a soil transmission module, the sand and stone transmission module is used for transmitting sand and stone to a sand and stone collection weighing area, and the soil transmission module is used for transmitting soil to a soil collection weighing area;
the scanning terminal comprises a plurality of 3D cameras, and the 3D cameras are used for carrying out three-dimensional scanning shooting on the dry sand on the sand conveying module;
the analysis terminal comprises a receiving module and an analysis module, wherein the receiving module is used for receiving data information from the 3D camera, and the analysis module is used for analyzing the data information and generating analysis result information.
Optionally, the 3D camera scans and shoots the gravel with a fixed resolution when performing three-dimensional scanning on the gravel, and projects the three-dimensional data of each gravel into the two-dimensional matrix for storage, the three-dimensional data of one gravel corresponds to one two-dimensional matrix, the sizes of the two-dimensional matrices are the same, and the volume V of the gravel satisfies the following formula:
where n denotes the number of rows of the two-dimensional matrix, m denotes the number of columns of the two-dimensional matrix, H ij Representing the value of each matrix lattice in the two-dimensional matrix, wherein the value of each matrix lattice is the height of a corresponding point in the sand three-dimensional data, d area And representing the area of the corresponding matrix lattice in the two-dimensional matrix, wherein the area of the corresponding matrix lattice in the two-dimensional matrix corresponds to the area of the corresponding point in the sand three-dimensional data.
Optionally, when the analysis module analyzes the data information and generates analysis result information, the sand content index S and the soil content index H are calculated as the analysis result information, and the following formula is satisfied:
S n ＝Klog 2 | k aV con -V|*Q(x)*V
wherein S is n Representing the weight index of each sand, N representing the total number of sands in the sand material, K representing an adjustable weight factor, K a Indicating adjustable standard volume coefficients, K and K a Set or adjusted by the person skilled in the art according to experience or specific practice, V con Denotes the tunable standard volume value, log 2 |k a V con V | represents a weighting factor and Q (x) represents a filtering function for filtering smaller volumes of sand orImpurities, V represents the volume of the corresponding sand;
wherein, V k Represents the minimum volume of sand corresponding to the sand material;
wherein λ represents an adjustable weight coefficient, which can be set and adjusted by the skilled person based on experience and practice, and W s Denotes the weight of the soil after drying, W k Indicating the standard soil weight, W, of the corresponding sand material Z Representing the total weight of the sand material.
Optionally, the analysis module includes a first calculation sub-module, a second calculation sub-module, and a table generation sub-module, where the first calculation sub-module is configured to calculate a sandstone content index S, the second calculation sub-module is configured to calculate a soil content index Y, and the table generation sub-module is configured to count and sort out a sandstone volume distribution table;
the second calculation submodule comprises a record correction unit, an adjustment unit and an addition unit, wherein the record correction unit is used for recording and correcting the weight W of the filtered and dried soil 1 The adjusting unit is used for recording and adjusting the weight W of soil obtained after the sewage is dried 2 The addition unit is used for adding W 1 And W 2 Are added to obtain W s The recording and correcting unit, the adjusting unit and the adding unit meet the following expression when working:
W s ＝W 1 +W 2
wherein F (t) represents a calibration reference value,
a min represents a minimum calibration reference value, a max Represents the maximum calibration reference value, t represents the real-time air temperature, W A Represents the weight of the filtered slurry, W B Representing the weight of the filtered and dried soil before calibration;
wherein f (t) represents an adjustment reference value,
b min represents a minimum adjustment reference value, b max Denotes the maximum adjustment reference value, W D Denotes the weight of soil obtained after the sewage is dried before adjustment, W C Represents the sewage weight.
Optionally, the table generation sub-module satisfies the following equation when operating:
wherein Z is t Representing the sum of the numbers of sands of each volume interval in the evaluation table of the corresponding sand material, Z m The number of sands in the corresponding volume interval is shown, and M is the number of volume intervals in the table.
Optionally, the analysis module further includes a deviation degree calculation unit, where the deviation degree unit is configured to calculate a deviation degree P between the corresponding sand and the standard reference material, and the following equation is satisfied during calculation:
s represents the sandstone content index of the corresponding sandstone material and represents the X-axis coordinate of the corresponding sandstone material in a two-dimensional vector, H represents the soil content index of the corresponding sandstone material and represents the Y-axis coordinate of the corresponding sandstone material in the two-dimensional vector, S 'represents the X-axis coordinate of a standard reference material with the weight equal to that of the corresponding sandstone material in the two-dimensional vector, and H' represents the Y-axis coordinate of the standard reference material with the weight equal to that of the corresponding sandstone material in the two-dimensional vector.
An image recognition-based sand component screening and analyzing method is applied to the image recognition-based sand component screening and analyzing system, and the analyzing method comprises the following steps:
carrying out sand-stone and slurry separation on the sand-stone material;
cleaning and collecting slurry remained on the sandstone;
drying the sand and the slurry with water;
conveying the dried sand;
carrying out three-dimensional scanning shooting on the sandstone on the transmission terminal;
and receiving and analyzing the data information of the scanning terminal to generate analysis result information.
The beneficial effects obtained by the invention are as follows:
1. after the sandstone materials with known weight are placed into the separation terminal, the sandstone materials are sequentially subjected to separation, cleaning, drying, transmission, scanning and analysis, so that the sandstone materials can be rapidly analyzed, the analysis efficiency is greatly improved in a transmission and scanning mode, the scanned data information is directly analyzed by combining the analysis terminal, analysis result information is generated, and the analysis efficiency is further improved;
2. when the sand and the slurry are separated, the filtering module is utilized for direct filtering and separation, so that more sand and the slurry can be separated at one time, the sand and the slurry are cleaned through the cleaning module, sewage is collected through the collecting module, and the sand drying module and the slurry drying module can work simultaneously during drying, so that the drying time is shortened, and errors are reduced;
3. the sand and stone tiled on the transmission terminal are scanned and shot by the 3D camera, so that uninterrupted scanning and shooting are facilitated, the data acquisition efficiency is improved, and the analysis efficiency is further improved;
4. the three-dimensional data of each sand is projected into the two-dimensional matrix with the same size for storage, and then the volume of each sand is calculated, so that the volume of each sand in the sand material can be quickly and accurately obtained, and the analysis efficiency is improved;
5. the analysis module further calculates a sand content index, a soil content index and a deviation degree according to the sand volume, the sand material weight, the mud weight, the dried soil weight and other data, so that an analysis result is efficiently and accurately obtained;
6. when the soil content index is calculated, the weight of the filtered and dried soil is recorded and corrected, then the weight of the dried soil of the sewage is recorded and adjusted, and finally more accurate soil weight is obtained through addition, so that the analysis accuracy is further improved;
7. the heating unit is controlled based on the working state in the drying process, the real-time temperature detected by the working time and the temperature sensor is adjusted, and meanwhile, the correction algorithm of the wind sensor is utilized to correct, so that the whole drying process is efficient and stable, errors are reduced, and the accuracy of data is improved.
For a better understanding of the features and technical content of the present invention, reference should be made to the following detailed description of the invention and accompanying drawings, which are provided for purposes of illustration and description only and are not intended to limit the invention.
Drawings
FIG. 1 is a schematic view of the overall structure of the present invention;
FIG. 2 is a table schematic of a sand volume distribution table according to the present invention;
FIG. 3 is a schematic flow chart of a sand component screening and analyzing method based on image recognition according to the present invention;
fig. 4 is a schematic view of the overall structure of the slurry drying module according to the present invention.
Detailed Description
The following is a description of embodiments of the present invention with reference to specific embodiments, and those skilled in the art will understand the advantages and effects of the present invention from the disclosure of the present specification. The invention is capable of other and different embodiments and its several details are capable of modification in various other respects, all without departing from the spirit and scope of the present invention. The drawings of the present invention are for illustrative purposes only and are not drawn to scale. The following embodiments will further explain the technical matters related to the present invention in detail, but the disclosure is not intended to limit the scope of the present invention.
The first embodiment.
The embodiment provides a sand component screening and analyzing system based on image recognition. Referring to fig. 1, the sand and stone component screening and analyzing system based on image recognition comprises a separation terminal, a cleaning terminal, a drying terminal, a transmission terminal, a scanning terminal and an analyzing terminal, wherein the separation terminal is used for performing sand and stone separation on sand and stone materials, the cleaning terminal is used for cleaning and collecting residual slurry on the sand and stone, the drying terminal is used for drying the sand and the slurry with moisture, the transmission terminal is used for transmitting the dried sand and stone, the scanning terminal is used for performing three-dimensional scanning shooting on the sand and stone on the transmission terminal, and the analyzing terminal is used for receiving and analyzing data information of the scanning terminal to generate analysis result information;
the separation terminal comprises a filtering module and a subpackaging module, the filtering module is used for filtering sand and slurry, and the subpackaging module is used for subpackaging the separated sand and slurry;
the cleaning terminal comprises a cleaning module and a collecting module, the cleaning module is used for cleaning sand, and the collecting module is used for collecting sewage generated when the sand is cleaned;
the drying terminal comprises a sand drying module and a slurry drying module, the sand drying module is used for drying sand, and the slurry drying module is used for drying slurry and sewage;
the transmission terminal comprises a sandstone transmission module and a soil transmission module, the sandstone transmission module is used for transmitting sandstone to a sandstone collection weighing area, and the soil transmission module is used for transmitting soil to a soil collection weighing area;
the scanning terminal comprises a plurality of 3D cameras, and the 3D cameras are used for carrying out three-dimensional scanning shooting on the dry sand on the sand conveying module;
the analysis terminal comprises a receiving module and an analysis module, wherein the receiving module is used for receiving data information from the 3D camera, and the analysis module is used for carrying out image recognition and analysis on the data information and generating analysis result information.
Optionally, when the 3D camera performs three-dimensional scanning on sand, fixed resolution is adopted for scanning and shooting, and when image recognition is performed, three-dimensional data of each sand is projected into a two-dimensional matrix for storage, the three-dimensional data of one sand corresponds to one two-dimensional matrix, the sizes of the two-dimensional matrices are the same, the length and width of the three-dimensional data correspond to the length and width of the two-dimensional matrix, and the volume V of the sand satisfies the following formula:
the method comprises the following steps of obtaining sand three-dimensional data by using a sand three-dimensional data acquisition system, obtaining n and darea, wherein n represents the line number of a two-dimensional matrix, m represents the column number of the two-dimensional matrix, hij represents the numerical value of each matrix lattice in the two-dimensional matrix, the numerical value of each matrix lattice is the height of a corresponding point in the sand three-dimensional data, darea represents the area of the corresponding matrix lattice in the two-dimensional matrix, and the area of the corresponding matrix lattice in the two-dimensional matrix corresponds to the area of the corresponding point in the sand three-dimensional data.
Optionally, when the analysis module analyzes the data information and generates analysis result information, the sand content index S and the soil content index H are calculated as the analysis result information, and the following formula is satisfied:
S n ＝K log 2 |k a V con -V|*Q(x)*V
wherein S is n Weight index of each sand, N represents sandThe total number of sand in the material, K represents an adjustable weight coefficient, K a Indicating adjustable standard volume coefficients, K and K a Set or adjusted by the person skilled in the art according to experience or specific practice, V con Denotes the tunable standard volume value, log 2 |k a V con V | represents a weighting factor, log 2 |k a V con -V > 2, Q (x) representing a filtering function for filtering smaller volumes of sand or impurities, V representing the volume of the corresponding sand;
wherein, V k Representing the minimum volume of sand corresponding to the sand material for filtering volumes less than V k The impurities of (a);
wherein λ represents an adjustable weighting factor, which can be adjusted by the skilled person based on experience or specific practice, and W s Denotes the weight of the soil after drying, W k Indicating the standard soil weight, W, of the corresponding sand material Z Representing the total weight of the sand material.
Optionally, the analysis module includes a first calculation submodule, a second calculation submodule, and a table generation submodule, where the first calculation submodule is used to calculate a sand content index S, the second calculation submodule is used to calculate a soil content index Y, and the table generation submodule is used to count and sort out a sand volume distribution table, as shown in fig. 2;
the second calculation submodule comprises a record correction unit, an adjustment unit and an addition unit, wherein the record correction unit is used for recording and correcting the weight W of the filtered and dried soil 1 The adjusting unit is used for recording and adjusting the weight W of soil obtained after the sewage is dried 2 The addition unit is used for adding W 1 And W 2 Are added to obtain W s The recording and correcting unit, the adjusting unit and the adding unit meet the following expression when working:
W s ＝W 1 +W 2
wherein F (t) represents a calibration reference value,
a min represents a minimum calibration reference value, a max Represents the maximum calibration reference value, is set or adjusted by the skilled person according to experience or specific practical conditions, t represents the real-time air temperature, W A Denotes the weight of the filtered slurry, W B Representing the weight of the filtered and dried soil before calibration;
wherein f (t) represents an adjustment reference value,
b min represents a minimum adjustment reference value, b max Represents the maximum adjustment reference value, and is set or adjusted by the skilled person according to experience or specific practical conditions, W D Denotes the weight of soil obtained after the sewage is dried before adjustment, W C Represents the sewage weight.
Optionally, the table generation sub-module satisfies the following equation when operating:
wherein Z is t The sum of the number of sands, Z, of each volume interval in the evaluation chart representing the corresponding sand material m Representing sand in corresponding volume intervalsThe number, M, represents the number of volume intervals in the table.
Optionally, the analysis module further includes a deviation degree calculation unit, the deviation degree unit is configured to calculate a deviation degree P between the corresponding sandstone material and the standard reference material, and the following equation is satisfied during calculation:
s represents the sandstone content index of the corresponding sandstone material and represents the X-axis coordinate of the corresponding sandstone material in a two-dimensional vector, H represents the soil content index of the corresponding sandstone material and represents the Y-axis coordinate of the corresponding sandstone material in the two-dimensional vector, S 'represents the X-axis coordinate of a standard reference material with the weight equal to that of the corresponding sandstone material in the two-dimensional vector, and H' represents the Y-axis coordinate of the standard reference material with the weight equal to that of the corresponding sandstone material in the two-dimensional vector.
An image recognition-based sand component screening and analyzing method is applied to the image recognition-based sand component screening and analyzing system, and is shown in fig. 3, wherein the analyzing method comprises the following steps:
s1, carrying out sand-stone and mud separation on the sand-stone material.
Specifically, a known weight of sand material is poured into the separation terminal, the sand and slurry at the separation terminal are separated and discharged.
And S2, cleaning and collecting slurry remained on the sand.
Specifically, the separated sand and stone are added into a cleaning terminal, the sand and stone at the cleaning terminal are cleaned, and sewage generated during cleaning is collected, wherein the sewage contains residual slurry on the sand and stone.
And S3, drying the sand and the slurry with the moisture.
Specifically, the cleaned sand and stone are conveyed into a sand and stone drying module to be dried, and the slurry and the sewage are respectively added into the slurry drying module to be dried.
And S4, conveying the dried sand.
Specifically, the dried sand and stone are conveyed to a sand and stone weighing area for weighing.
And S5, carrying out three-dimensional scanning shooting on the sandstone on the transmission terminal.
Specifically, the 3D camera is controlled to conduct three-dimensional scanning shooting on the sand on the transmission terminal, and three-dimensional data information images of all the sand are generated. The sand on the transmission terminal is in a tiled state, so that the overlapping or piling of the sand is reduced, and the three-dimensional data information image is more accurate and clear.
And S6, receiving and analyzing the data information of the scanning terminal to generate analysis result information.
Specifically, a sand content index S, a soil content index H and a deviation degree P are calculated according to the three-dimensional data information image of each sand, a corresponding sand volume distribution table is generated, and the sand content index S, the soil content index H, the deviation degree P and the sand volume distribution table are used as analysis result information.
The second embodiment.
The embodiment contains the whole content of the first embodiment, provides a grit composition screening analysis system based on image recognition, and with reference to fig. 4, the mud stoving module includes heating submodule and wind power submodule, and the heating submodule is used for heating mud or sewage, and the wind power submodule is used for blowing mud or sewage. The heating submodule comprises a heating unit, a temperature sensor and a first control unit which are electrically connected with each other. Controlled by the first control unit, the heating unit works and heats the slurry or the sewage, and the temperature sensor is used for collecting the real-time temperature of the slurry or the sewage and feeding the real-time temperature back to the first control unit to form feedback control so as to control the heating temperature. Further, in order to reduce the occurrence of the overheating, the control performed by the first control unit based on the data of the temperature sensor satisfies the following equation:
wherein, WORK o Indicating the operation state of the heating unit, 0 indicating that the operation is not startedAnd J (W) represents entering a working state, no data represents that the temperature sensor has no data, and data represents that the temperature sensor has data. And J (W) satisfies the following formula:
J(W)＝β|sin 2t w *cost w |*L(off)
where β denotes an adjustable state coefficient, which can be adjusted by the person skilled in the art on the basis of experience or specific circumstances, t w The time of operation is indicated by the time of operation,
T w indicating the real-time temperature, T, of the slurry or sewage max Represents the upper limit value of heating when the temperature of the slurry or the sewage is less than T max When the temperature of the slurry or the sewage is more than T, the first control unit controls the heating unit to normally work max And when the heating unit stops working, the first control unit automatically controls the heating unit to stop working.
The wind power submodule comprises a blowing unit, a wind power sensor and a second control unit which are electrically connected with each other. The second control unit controls the wind power output of the blowing unit according to the feedback of the wind power sensor so as to reduce the occurrence of the condition of overlarge wind power. In order to improve the accuracy of control, when the second control unit performs control according to the wind sensor, the following formula is satisfied:
W new ＝W old *(1-Δ)+N n *Δ
wherein, W new Indicating the corrected detected value, W, of the wind sensor old Representing the last moment detected value of the wind sensor, delta representing an adjustable weight, adjusted by a person skilled in the art according to experience or specific practical conditions, N n The latest detected data representing the wind sensor uncorrected.
The disclosure is only a preferred embodiment of the invention, and is not intended to limit the scope of the invention, so that all equivalent technical changes made by using the contents of the specification and the drawings are included in the scope of the invention, and further, the elements thereof can be updated as the technology advances.
Claims (7)
1. The sandstone component screening and analyzing system based on image recognition is characterized by comprising a separation terminal, a cleaning terminal, a drying terminal, a transmission terminal, a scanning terminal and an analysis terminal, wherein the separation terminal is used for carrying out sandstone and slurry separation on sandstone materials, the cleaning terminal is used for cleaning and collecting residual slurry on sandstone, the drying terminal is used for drying sandstone and slurry with moisture, the transmission terminal is used for transmitting dried sandstone, the scanning terminal is used for carrying out three-dimensional scanning and shooting on sandstone on the transmission terminal, and the analysis terminal is used for receiving and analyzing data information of the scanning terminal to generate analysis result information;
the separation terminal comprises a filtering module and a subpackaging module, the filtering module is used for filtering sand and slurry, and the subpackaging module is used for subpackaging the separated sand and slurry;
the cleaning terminal comprises a cleaning module and a collecting module, the cleaning module is used for cleaning sand, and the collecting module is used for collecting sewage generated when the sand is cleaned;
the drying terminal comprises a sand drying module and a slurry drying module, the sand drying module is used for drying sand, and the slurry drying module is used for drying slurry and sewage;
the transmission terminal comprises a sand and stone transmission module and a soil transmission module, the sand and stone transmission module is used for transmitting sand and stone to a sand and stone collection weighing area, and the soil transmission module is used for transmitting soil to a soil collection weighing area;
the scanning terminal comprises a plurality of 3D cameras, and the 3D cameras are used for carrying out three-dimensional scanning shooting on the dry gravel on the gravel transmission module;
the analysis terminal comprises a receiving module and an analysis module, wherein the receiving module is used for receiving data information from the 3D camera, and the analysis module is used for analyzing the data information and generating analysis result information.
2. The sand component screening and analyzing system based on image recognition as claimed in claim 1, wherein the 3D camera scans and shoots sand with a fixed resolution when three-dimensionally scanning the sand, and projects three-dimensional data of each sand into a two-dimensional matrix for storage, the three-dimensional data of one sand corresponds to one two-dimensional matrix, the two-dimensional matrices have the same size, and the volume V of the sand satisfies the following equation:
where n denotes the number of rows of the two-dimensional matrix, m denotes the number of columns of the two-dimensional matrix, H ij Representing the numerical value of each matrix lattice in the two-dimensional matrix, wherein the numerical value of the matrix lattice is the height of a corresponding point in the sand three-dimensional data, d area And representing the area of the corresponding matrix lattice in the two-dimensional matrix, wherein the area of the corresponding matrix lattice in the two-dimensional matrix corresponds to the area of the corresponding point in the sand three-dimensional data.
3. The sand and stone component screening and analyzing system based on image recognition as claimed in claim 2, wherein when the analyzing module analyzes the data information and generates the analysis result information, the sand and stone content index S and the soil content index H are calculated as the analysis result information, and the following formula is satisfied:
S n ＝K log 2 |k a V con -V|*Q(x)*V
wherein S is n Representing the weight index of each sand, N representing the total number of sands in the sand material, K representing an adjustable weight factor, K a Indicating an adjustable standard volume factor, V con Denotes the tunable standard volume value, log 2 |k a V con -V represents a weighting factor, Q (x) represents a filtering function for filtering smaller volumes of sand or impurities, V represents the volume of the corresponding sand;
wherein, V k Represents the minimum volume of sand corresponding to the sand material;
wherein λ represents an adjustable weight coefficient, W s Denotes the weight of the soil after drying, W k Indicating the standard soil weight, W, of the corresponding sand material Z Representing the total weight of the sand material.
4. The sand component screening and analyzing system based on image recognition as claimed in claim 3, wherein the analyzing module comprises a first calculating submodule, a second calculating submodule and a table generating submodule, the first calculating submodule is used for calculating the sand content index S, the second calculating submodule is used for calculating the soil content index Y, and the table generating submodule is used for counting and sorting out a sand volume distribution table;
the second calculation submodule comprises a record correction unit, an adjustment unit and an addition unit, wherein the record correction unit is used for recording and correcting the weight W of the filtered and dried soil 1 The adjusting unit is used for recording and adjusting the weight W of soil obtained after the sewage is dried 2 The adding unit is used for adding W 1 And W 2 Are added to obtain W s And the recording and correcting unit, the adjusting unit and the adding unit satisfy the following expression when in operation:
W s ＝W 1 +W 2
wherein, F (t)It indicates the value of the calibration reference,
a min represents a minimum calibration reference value, a max Represents the maximum calibration reference value, t represents the real-time air temperature, W A Denotes the weight of the filtered slurry, W B Representing the weight of the filtered and dried soil before calibration;
wherein f (t) represents an adjustment reference value,
b min represents a minimum adjustment reference value, b max Denotes the maximum adjustment reference value, W D Represents the weight of soil obtained after the sewage is dried before conditioning, W C Indicating the weight of the wastewater.
5. An image recognition-based sand component screening analysis system as claimed in claim 4 wherein said table generation sub-module is operable to satisfy the following equation:
wherein Z is t Representing the sum of the numbers of sands of each volume interval in the evaluation table of the corresponding sand material, Z m The number of sands in the corresponding volume interval is shown, and M is the number of volume intervals in the table.
6. The image recognition-based sand component screening analysis system of claim 5, wherein the analysis module further comprises a degree of deviation calculation unit for calculating a degree of deviation P of the corresponding sand material from a standard reference material, the calculation satisfying the following equation:
s represents the sandstone content index of the corresponding sandstone material and represents the X-axis coordinate of the corresponding sandstone material in a two-dimensional vector, H represents the soil content index of the corresponding sandstone material and represents the Y-axis coordinate of the corresponding sandstone material in the two-dimensional vector, S 'represents the X-axis coordinate of a standard reference material with the weight equal to that of the corresponding sandstone material in the two-dimensional vector, and H' represents the Y-axis coordinate of the standard reference material with the weight equal to that of the corresponding sandstone material in the two-dimensional vector.
7. The sand component screening and analyzing method based on image recognition is applied to the sand component screening and analyzing system based on image recognition according to claim 6, and the analyzing method comprises the following steps:
carrying out sand-stone and slurry separation on the sand-stone material;
cleaning and collecting slurry remained on the sandstone;
drying the sandstone and the slurry with water;
conveying the dried sand;
carrying out three-dimensional scanning shooting on the sandstone on the transmission terminal;
and receiving and analyzing the data information of the scanning terminal to generate analysis result information.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210889397.9A CN115239790B (en) | 2022-07-27 | 2022-07-27 | Sand and stone component screening analysis system based on image recognition |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210889397.9A CN115239790B (en) | 2022-07-27 | 2022-07-27 | Sand and stone component screening analysis system based on image recognition |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115239790A true CN115239790A (en) | 2022-10-25 |
| CN115239790B CN115239790B (en) | 2023-06-13 |
Family
ID=83675745
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210889397.9A Active CN115239790B (en) | 2022-07-27 | 2022-07-27 | Sand and stone component screening analysis system based on image recognition |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115239790B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104853168A (en) * | 2015-05-25 | 2015-08-19 | 三峡大学 | Intelligent monitoring system for gravel aggregate quality |
| CN106053279A (en) * | 2016-05-24 | 2016-10-26 | 南京交通职业技术学院 | Method for detecting mud content of limestone |
| CN112528913A (en) * | 2020-12-18 | 2021-03-19 | 中山艾尚智同信息科技有限公司 | Grit particulate matter particle size detection analytic system based on image |
| CN112712519A (en) * | 2021-01-15 | 2021-04-27 | 清华大学 | Non-contact type machine-made sandstone powder content intelligent real-time detection method and device |
| CN114371106A (en) * | 2022-01-07 | 2022-04-19 | 苏州混凝土水泥制品研究院有限公司 | Method for testing and analyzing morphology parameters of machine-made sand |
| CN114472207A (en) * | 2022-01-07 | 2022-05-13 | 北京霍里思特科技有限公司 | Mineral sorting system and mineral sorting method |
-
2022
- 2022-07-27 CN CN202210889397.9A patent/CN115239790B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104853168A (en) * | 2015-05-25 | 2015-08-19 | 三峡大学 | Intelligent monitoring system for gravel aggregate quality |
| CN106053279A (en) * | 2016-05-24 | 2016-10-26 | 南京交通职业技术学院 | Method for detecting mud content of limestone |
| CN112528913A (en) * | 2020-12-18 | 2021-03-19 | 中山艾尚智同信息科技有限公司 | Grit particulate matter particle size detection analytic system based on image |
| CN112712519A (en) * | 2021-01-15 | 2021-04-27 | 清华大学 | Non-contact type machine-made sandstone powder content intelligent real-time detection method and device |
| CN114371106A (en) * | 2022-01-07 | 2022-04-19 | 苏州混凝土水泥制品研究院有限公司 | Method for testing and analyzing morphology parameters of machine-made sand |
| CN114472207A (en) * | 2022-01-07 | 2022-05-13 | 北京霍里思特科技有限公司 | Mineral sorting system and mineral sorting method |
Non-Patent Citations (2)
| Title |
|---|
| ANXU WU: "The Comprehensive Variation Analysis of Digital Observational Records of Sand Layer Strain", 《2010 3RD INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP2010)》 * |
| 杨静明 等: "砂石骨料含泥量现场快速测定方法", 《黑龙江水利科技》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115239790B (en) | 2023-06-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111339839B (en) | Intensive target detection metering method | |
| CN110187334B (en) | Target monitoring method and device and computer readable storage medium | |
| CN104034638B (en) | The diamond wire online quality detecting method of granule based on machine vision | |
| CN113375566A (en) | Method and system for accurately measuring size of object | |
| CN109523583B (en) | Infrared and visible light image registration method for power equipment based on feedback mechanism | |
| US9251418B2 (en) | Method of detection of points of interest in a digital image | |
| CN111814739B (en) | Method, device, equipment and storage medium for detecting express package volume | |
| CN112070759A (en) | Forklift pallet detection and positioning method and system | |
| CN103942786B (en) | The self adaptation block objects detection method of unmanned plane visible ray and infrared image | |
| CN113533145A (en) | Rockfill particle size identification and monitoring device and method based on camera set three-dimensional reconstruction | |
| CN111383174A (en) | Pile bursting data acquisition method for photogrammetry | |
| CN116255912A (en) | Method and system for measuring static volume of package | |
| CN115578310A (en) | Binocular vision detection method and system for refractory bricks | |
| CN115471542A (en) | Packaging object binocular recognition and positioning method based on YOLO v5 | |
| CN114842340A (en) | Robot binocular stereoscopic vision obstacle sensing method and system | |
| CN115239790B (en) | Sand and stone component screening analysis system based on image recognition | |
| CN114463269A (en) | Chip defect detection method based on deep learning method | |
| CN110197489A (en) | A kind of selection method and device of unmanned plane drop zone | |
| CN116129365B (en) | Method and system for detecting particle materials on conveying equipment | |
| CN116091706B (en) | Three-dimensional reconstruction method for multi-mode remote sensing image deep learning matching | |
| CN112614176A (en) | Belt conveyor material volume measuring method and device and storage medium | |
| CN117372335A (en) | Photoelectric simulation image processing method and system based on spearman level correlation coefficient | |
| CN110837775A (en) | Underground locomotive pedestrian and distance detection method based on binarization network | |
| CN216870297U (en) | Rockfill particle size identification and monitoring device based on three-dimensional reconstruction of camera set | |
| CN104820972A (en) | Infrared image ME noise removal method based on on-orbit classification statistics |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |