CN115684510B - Grain intelligent sampling inspection method - Google Patents
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Abstract
The invention discloses an intelligent grain sampling inspection method, which relates to the technical field of grain sampling quality inspection and is used for solving the problems that the existing grain sampling inspection equipment cannot realize linkage of sampling and inspection, cannot be separated from manual intervention and has a single application range; the grain is the main grain species, including rice, wheat, corn, soybean, etc., the method includes: sending the primary sample to a workstation group for sample inspection to obtain inspection index data and uploading the inspection index data to an upper computer; the invention realizes the full-flow control of sampling and inspection, has wide range of applicable grain, more detection indexes and strong expandability; the whole process is automatically processed, the artificial interference is avoided in the sampling and testing process, the automation degree is high, the sampling link can completely replace the manual work, each workstation in the detection link can replace the work of 1-2 persons, and the detection process is free of artificial intervention.
Description
Technical Field
The invention relates to the technical field of grain sampling quality inspection, in particular to an intelligent grain sampling inspection method.
Background
China is a large country for grain production and consumption and also a large country for grain storage. The quality of grain purchasing directly influences the quality safety of grain during storage, and accurate determination of quality information such as grain grades is of great importance to grain storage rotation. In the actual storage work, the grain storage unit determines the grade according to the grain quality, and different purchasing prices are implemented at different grades.
At present, when the existing grain cutting detection passes through the equipment sampling and quality inspection, single equipment is adopted, only one or two functions can be realized, the single equipment can realize the automatic cutting sampling of samples, the existing similar equipment can only finish the sample collection, and the subsequent corresponding inspection equipment is not available, so that the linkage of sampling and inspection cannot be realized; at present, various inspection devices of grains are mostly operated manually or semi-automatically, and cannot be separated from manual intervention. The equipment inspection has a single application range, only can detect one or more indexes of one or more types of grains, and cannot detect all the multiple indexes of common grains at one time.
In order to solve the problems, the method is applied to a grain purchasing link and requires rapid detection of grain quality indexes, particularly in a busy season, the purchasing task is heavy, the detection amount is large, therefore, the method is necessary for rapidly detecting the quality indexes, meanwhile, the existing detection has high dependence on people, and the detection is not standardized and standardized enough, and the method can also prevent artificial cheating.
Disclosure of Invention
The invention aims to solve the problems that the existing grain sample inspection equipment cannot realize linkage of sampling and inspection, cannot be separated from manual intervention and has a single application range, and provides an intelligent grain sample inspection method which is applied to index inspection of grain quality in a purchasing link; the grain is the main grain species, including rice, wheat, corn, soybean, etc.
The invention adopts the technical scheme for solving the technical problems that: an intelligent grain sampling inspection method comprises the following steps:
a driver drives a transport vehicle filled with grains to an intelligent sampling area;
then identifying driver identity information through the self-service terminal, and registering the vehicle, wherein when the driver finishes registering the vehicle information; further comprising:
identifying license plate information, scanning a transport vehicle, generating a sampling coordinate point according to a sampling rule, and sampling the sampling coordinate point to obtain a cutting sample;
conveying the cuttage sample to a temporary storage hopper for temporary storage through a conveying pipeline;
the cutting sample is divided according to the proportion to obtain a primary sample, the grains of the rest abandoned samples are sent to a grain return pipeline, and the grains of the rest abandoned samples are sent back to a grain containing carriage through the grain return pipeline by positive pressure of a fan;
and (4) conveying the primary sample to a work station group for sample inspection to obtain inspection index data and uploading the inspection index data to an upper computer.
Furthermore, a weighing module and a vehicle information identification module are arranged on the intelligent sampling area;
the weighing module is used for weighing the transport vehicle filled with the grains;
the vehicle information identification module comprises a laser radar unit and a vehicle identification unit, the laser radar unit is used for scanning images of the transport vehicle and processing the images, judging vehicle positions and sampling areas, establishing a sampling coordinate system, generating sampling coordinate points according to sampling rules and sending coordinate information of the sampling coordinate points to the upper computer, and the vehicle identification unit is used for identifying license plate information of the transport vehicle filled with grains, confirming grain types and generating batch numbers.
Further, the workstation group comprises:
the first detection workstation is used for temporarily storing and processing the primary sample to obtain a reserved sample and a first sample;
the second detection workstation is used for screening, impurity removing and weighing the first sample to obtain a residual sample and a second sample, detecting the second sample to obtain detection result data and uploading the detection result data to the upper computer;
the third detection workstation is used for carrying out moisture detection and weighing on the residual samples to obtain second detection result data and uploading the second detection result data to the upper computer;
the fourth detection workstation is used for processing the second sample to obtain inspection waste and a third sample, detecting the third sample to obtain detection result data III and uploading the detection result data III to the upper computer;
and the fifth detection workstation is used for processing the third sample to obtain a fourth sample, detecting the fourth sample to obtain detection result data IV and uploading the detection result data IV to the upper computer.
Further, the first detection workstation is a sample temporary storage and pretreatment workstation, and the specific treatment process is as follows: conveying the primary sample to a sample temporary storage and pretreatment workstation, and carrying out division treatment according to proportion through the sample temporary storage and pretreatment workstation to divide the primary sample into a reserved sample and a first sample; packing, code spraying and temporary storage processing are carried out on the sample to be stored; and conveying the first sample to a second detection workstation through the multi-axis robot.
Further, the second detection workstation is impurity, the outer brown rice of millet, mineral substance detection workstation, and specific working process is: through impurity, the outer brown rice of millet, the mineral substance detection workstation screens first sample and weighs after removing impurity, the inspection sample after will weighing is divided according to the proportion and is obtained surplus sample and second sample, weigh back surplus sample and second sample, send surplus sample to third detection workstation, to the second sample, consider different grain types, carry out impurity through quick examination appearance, the outer brown rice of millet, mineral substance detection, if the outer brown rice of millet judgement galley proof impurity and millet, if the outer brown rice of wheat judgement galley proof impurity and mineral substance, if the maize judges galley proof impurity, the impurity that will detect, the outer brown rice of millet, pass on the mineral substance data to the host computer, send the second sample to the fourth detection workstation through the robot.
Further, the third detection workstation is a moisture, volume weight detection and weighing workstation, and the specific working process is: the rapid moisture detector in the moisture and volume weight detection and weighing workstation is used for weighing, moisture and volume weight detection, detected weight data, moisture data and volume weight data are sent to an upper computer, and detected residual samples are sent to a waste material collection tank for collection.
Further, the fourth detection workstation is a coarseness, imperfect, complete and damaged grain detection workstation, and the specific working process is as follows: the second sample is divided according to a proportion through the workstation to obtain a detection waste material and a third sample, the detection waste material is sent to a waste material collecting tank, after the grain type is identified, if the grain type is rice, the third sample is weighed and chaff is removed, and the removed chaff is sent to the waste material collecting tank; and weighing the third sample from which the chaff is removed, pouring the third sample into an imperfect grain rapid calibrating instrument for imperfect grain detection, uploading detected imperfect grain data to an upper computer, judging imperfect grains of brown rice if the third sample is rice, judging imperfect grains if the third sample is wheat, judging imperfect grains and mildewed grains if the third sample is corn, judging complete grains, damaged grains and heat-damaged grains if the third sample is soybean, and sending the detected third sample to a fifth detection workstation through a multi-axis robot.
Further, the fifth detection workstation is a whole polished rice and yellow rice detection workstation, and the specific working process is as follows: grinding the third sample through a fine rice and yellow rice detection workstation, removing bran and powder to obtain a fourth sample, and conveying the bran and powder obtained after grinding into a waste material collection tank; pouring the fourth sample into a fine rice and yellow rice rapid detector for identifying the fine rice and the yellow rice, and uploading the data of the fine rice and the yellow rice to an upper computer; and sending the fourth sample after detection to a waste material collecting tank.
Further, the skewing rule comprises a random algorithm.
Further, the sampling point positions generated by the random algorithm comprise a central point, at least two corner points and at least two side points.
Compared with the prior art, the invention has the beneficial effects that:
1. compared with the existing single equipment, the full-flow control of sampling and inspection is realized, the range of applicable grains is wide, the detection indexes are multiple, the expandability is strong, and the detection can be realized for common indexes; for some special detection indexes, detection can be realized by adding a special detection workstation;
2. according to the invention, the whole process is subjected to automatic treatment, artificial interference is avoided in the sampling and inspection process, the automation degree is high, the requirements on experience and technology of operators in the sampling and inspection process are reduced, and the phenomena of misoperation, cheating and the like are effectively avoided;
3. the invention saves the labor cost, the sampling link can completely replace the manpower, each workstation in the detection link can replace the work of 1-2 persons, and the detection process has no human intervention;
4. the equipment efficiency of the invention is greatly improved compared with the traditional detection, each detection workstation can operate in parallel, the workstation with large detection amount can add 1 or more equipment, the parallel operation efficiency is improved, and the overall efficiency is far higher than that of manual operation or single equipment operation;
5. the system has high informatization degree: the sample code is unique, the whole process of the sample can be traced, the sample has the unique code in the upper computer from the sampling, and the processing time and the inspection result of the sample in each workstation in the whole system can be tracked through the code.
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FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a workstation workflow diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an intelligent sampling inspection method for grain is applied to index inspection of grain quality in an acquisition link; wherein the grain is main grain species including rice, wheat, corn, soybean, etc.; the method comprises the following steps:
a driver drives a transport vehicle filled with grains to an intelligent sampling area; the intelligent sampling area is provided with a weighing module and a vehicle information identification module; the weighing module is used for weighing the transport vehicle filled with the grains; the vehicle information identification module comprises a laser radar unit and a vehicle identification unit, wherein the laser radar unit is used for scanning images of the transport vehicle for identification and processing the images, distinguishing the position of the vehicle and a sampling area, establishing a sampling coordinate system and sending the sampling coordinate system to an upper computer; the vehicle identification unit is used for identifying the license plate information of a transport vehicle filled with grains, confirming the grain types and generating batch numbers; the vehicle identification unit is used for determining the position of a carriage and the information of a license plate by using a camera and image identification software; the upper computer generates sampling coordinate points according to sampling rules; the sampling rule comprises a random algorithm, specifically, when the sampling coordinate points are generated by the random algorithm, side points and corner points which are easy to cheat are considered, the sampling point positions are ensured to comprise a central point, at least two corner points and at least two side points, so that the sampling data have wide representativeness, and meanwhile, the sampling rule also supports customization, can be customized according to the user requirement rule, and only needs to meet the inherent wide representativeness of the regional data;
then identifying driver identity information through a self-service terminal, carrying out vehicle registration, carrying out self-service driver registration, and carrying out vehicle information registration and query by adopting a card capable of identifying the unique code of the identity information; the outdoor display is used for inquiring, and the sampling progress and the sampling information can also be displayed;
after the driver finishes vehicle information registration, clicking a sample starting button to finish one-key sample collection, namely, the upper computer controls the sample collection robot to sample coordinate points through the main controller to obtain a cutting sample; the sampling robot moves on the track platform, samples according to coordinate information given by an upper computer, and finishes automatic sampling;
conveying the cuttage sample to a temporary storage hopper for temporary storage through a conveying pipeline, wherein the cuttage sample adopts compressed air as a conveying medium;
the cutting sample is divided according to the proportion to obtain a primary sample, the grains of the rest abandoned samples are sent to a grain return pipeline, and the grains of the rest abandoned samples are sent back to a grain loading compartment through positive pressure of a fan;
and conveying the primary samples to a plurality of detection workstations for detection.
Referring to fig. 2, the plurality of detection stations include a sample buffer and pretreatment station, an impurity detection station, an off-grain brown rice detection station, a mineral detection station, a brown rice rate detection station, an imperfect grain detection station, a complete grain detection station, a damaged grain detection station, a moisture detection and weighing station, a complete polished rice rate detection station, and a yellow rice detection station; wherein, the material is transmitted between each detection workstation by a mechanical arm, a multi-axis robot, a mechanical line body and the like; the workstations can be arranged in various forms such as annular, rectangular, strip and the like according to the working ranges of the mechanical arm, the multi-axis robot and the mechanical line body;
conveying the primary sample to a sample temporary storage and pretreatment workstation, and carrying out division treatment according to proportion through the sample temporary storage and pretreatment workstation to divide the primary sample into a reserved sample and a first sample; packing, code spraying and temporary storage processing are carried out on the sample to be stored; conveying the first sample to an impurity, grain-outside brown rice and mineral substance detection workstation through a multi-axis robot; wherein, sample buffering and pretreatment workstation: after division is carried out on 2 or more sample temporary storage tanks, one part of samples are packed and sprayed with codes (the sprayed codes have uniqueness and can be traced), and the other part of samples enter the next detection workstation;
screening a first sample through an impurity, off-grain brown rice and mineral substance detection workstation, removing impurities, weighing, dividing a weighed test sample into a residual sample and a second sample according to a proportion, weighing the residual sample and the second sample, sending the residual sample to the workstation, namely a moisture, volume weight detection and weighing workstation, weighing and moisture detection the residual sample through a moisture, volume weight detection and moisture fast detector in the weighing workstation, sending detected weight data and moisture data to an upper computer, and sending the detected residual sample to a waste material collection tank for collection; detecting impurities and the brown rice outside the grains of the second sample by a rapid detector, uploading the detected impurities and the data of the brown rice outside the grains to an upper computer, and sending the second sample to a brown rate and imperfect grain detecting workstation for finishing grains and damaging grains by a multi-axis robot; the impurity, the outer brown rice of millet, mineral substance detection workstation comprise automatic screening plant, division device, material temporary storage device, the quick calibrating installation of vision etc. for accomplish sample impurity detection (oversize thing, undersize thing are impurity, and the screen cloth can be changed according to the measuring requirement) and galley proof impurity and the outer brown rice content of millet, possess sample screening processing function, for moisture detects, go out the sample of roughness detection preparation.
The second sample is divided proportionally through a roughness yielding, imperfect grain, complete grain and damaged grain detection workstation to obtain inspection waste and a third sample, the inspection waste is sent to a waste material collection tank, the third sample is weighed and chaff is removed, and the removed chaff is sent to the waste material collection tank; weighing the third sample from which the chaff is removed, pouring the third sample into an imperfect grain rapid detection instrument for imperfect grain detection, uploading detected imperfect grain data to an upper computer, and sending the detected third sample to a polished rice rate and yellow rice detection workstation through a multi-axis robot; wherein, the roughness detection workstation comprises a reduction device, a rice huller, an imperfect grain detection device, a weighing device and the like. The detection of the roughness can be automatically completed, and samples are prepared for the detection of the whole polished rice rate and the yellow rice;
grinding the third sample through a polished rice rate and yellow rice detection workstation, removing bran and powder to obtain a fourth sample, and conveying the bran and powder obtained after grinding into a waste material collection tank; pouring the fourth sample into a fine rice and yellow rice rapid detector for identifying the fine rice and the yellow rice, and uploading the data of the fine rice and the yellow rice to an upper computer; and sending the fourth sample after detection to a waste material collecting tank.
According to the requirements of detection items, the workstations can be sequentially added, such as a workstation for detecting fatty acid value, a heavy metal element detection workstation, a mycotoxin detection workstation and the like;
the waste materials detected by the work stations are all sent to a detection waste material collecting station. The method is completed by a mechanical arm, a multi-axis robot, a mechanical line body or pneumatic transmission; various works in each workstation can be automatically completed, and the system has the functions of information communication and interaction; the sample is tested from sampling to each index, and has a unique code, and the test start and end time and the test result are transmitted to the upper computer.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand the invention for and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (4)
1. An intelligent grain sampling inspection method comprises the following steps:
the method comprises the steps that a driver drives a transport vehicle filled with grains to an intelligent sampling area, a vehicle information identification module is arranged on the intelligent sampling area and comprises a laser radar unit, the laser radar unit is used for scanning images of the transport vehicle and processing the images, judging the position of the vehicle and a sampling area, establishing a sampling coordinate system, generating sampling coordinate points according to sampling rules and sending coordinate information of the sampling coordinate points to an upper computer;
then identifying driver identity information through the self-service terminal, and registering the vehicle, wherein when the driver finishes registering the vehicle information; it is characterized by also comprising:
identifying license plate information, scanning a transport vehicle, generating sampling coordinate points according to sampling rules, and sampling the sampling coordinate points to obtain a cutting sample;
conveying the cuttage sample to a temporary storage hopper for temporary storage through a conveying pipeline;
the cutting sample is divided according to the proportion to obtain a primary sample, the grains of the rest abandoned samples are sent to a grain return pipeline, and the grains of the rest abandoned samples are sent back to a grain containing carriage through the grain return pipeline by positive pressure of a fan;
send preliminary sample to workstation group in carry out the sample inspection in order to obtain inspection index data and upload inspection index data to the host computer, workstation group includes:
the first detection workstation is used for temporarily storing and processing the primary sample to obtain a reserved sample and a first sample; the first detection workstation is a sample temporary storage and pretreatment workstation, and the specific treatment process is as follows: conveying the primary sample to a sample temporary storage and pretreatment workstation, and carrying out division treatment according to proportion through the sample temporary storage and pretreatment workstation to divide the primary sample into a reserved sample and a first sample; packing, code spraying and temporary storage treatment are carried out on the sample to be reserved; conveying the first sample to a second detection workstation through a multi-axis robot;
the second detection workstation is used for screening, impurity removing and weighing the first sample to obtain a residual sample and a second sample, detecting the second sample to obtain detection result data and uploading the detection result data to the upper computer; the second detection workstation is impurity, the outer brown rice of millet, mineral substance detection workstation, and specific working process is: screening a first sample through an impurity, non-grain brown rice and mineral substance detection workstation, removing impurities, weighing, dividing the weighed test sample into a residual sample and a second sample according to a proportion, weighing the residual sample and the second sample, sending the residual sample to a third detection workstation, detecting impurities, non-grain brown rice and mineral substances of the second sample through a rapid detector in view of different grain types, judging small-sample impurities and non-grain brown rice if the residual sample and the second sample are rice, judging small-sample impurities and mineral substances if the residual sample and the second sample are corn, uploading the detected data of the impurities, the non-grain brown rice and the mineral substances to an upper computer, and sending the second sample to a fourth detection workstation through a robot;
the third detection workstation is used for carrying out moisture detection and weighing on the residual samples to obtain second detection result data and uploading the second detection result data to the upper computer; the third detection workstation is a moisture and volume weight detection and weighing workstation, and the specific working process is as follows: weighing, moisture and volume weight detection are carried out through a moisture and volume weight detection and moisture rapid detector in a weighing workstation, detected weight data, moisture data and volume weight data are sent to an upper computer, and the detected residual sample is sent to a waste material collection tank for collection;
the fourth detection workstation is used for processing the second sample to obtain inspection waste and a third sample, detecting the third sample to obtain detection result data III and uploading the detection result data III to the upper computer; the fourth detection workstation is a coarseness rate, imperfect grain, complete grain and damaged grain detection workstation, and the specific working process is as follows: the second sample is divided according to a proportion through the workstation to obtain a detection waste material and a third sample, the detection waste material is sent to a waste material collecting tank, after the grain type is identified, if the grain type is rice, the third sample is weighed and chaff is removed, and the removed chaff is sent to the waste material collecting tank; weighing the third sample from which the chaff is removed, pouring the third sample into an imperfect grain rapid verification instrument for imperfect grain detection, uploading detected imperfect grain data to an upper computer, judging imperfect grains of brown rice if the grain is rice, judging imperfect grains of wheat if the grain is wheat, judging imperfect grains and moldy grains if the grain is corn, judging complete grains, damaged grains and heat-damaged grains if the grain is soybean, and conveying the detected third sample to a fifth detection workstation through a multi-axis robot;
the fifth detection workstation is used for processing the third sample to obtain a fourth sample, detecting the fourth sample to obtain detection result data IV and uploading the detection result data IV to the upper computer; the fifth detection workstation is a whole polished rice and yellow rice detection workstation, and the specific working process is as follows: grinding the third sample through a polished rice and yellow rice detection workstation, removing bran and powder to obtain a fourth sample, and conveying the bran and powder obtained after grinding into a waste material collection tank; pouring the fourth sample into a fine rice and yellow rice rapid detector for identifying the fine rice and the yellow rice, and uploading the data of the fine rice and the yellow rice to an upper computer; sending the detected fourth sample to a waste material collecting tank;
the material is transmitted between the detection workstations by a mechanical hand, a multi-axis robot or a mechanical line body; the detection work station is arranged in an annular, rectangular or strip shape according to the working range of the mechanical arm, the multi-axis robot or the mechanical line body.
2. The intelligent grain sampling inspection method as claimed in claim 1, wherein a weighing module is further provided on the intelligent sampling area;
the weighing module is used for weighing the transport vehicle filled with the grains;
the vehicle information identification module also comprises a vehicle identification unit, and the vehicle identification unit is used for identifying the license plate information of the transport vehicle filled with the grains, confirming the grain types and generating the batch numbers.
3. A grain intelligent sampling inspection method according to claim 1, wherein the sampling rules comprise a random algorithm.
4. A method for intelligent sampling inspection of grain according to claim 3 wherein the randomly generated sampling points comprise a center point, at least two corner points and at least two edge points.
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| CN116148809B (en) * | 2023-04-04 | 2023-06-20 | 中储粮成都储藏研究院有限公司 | Automatic generation method and system for grain vehicle sampling point based on laser radar scanning and positioning |
| CN116106568A (en) * | 2023-04-12 | 2023-05-12 | 中储粮成都储藏研究院有限公司 | Grain sampling and detecting system |
| CN117057678B (en) * | 2023-10-11 | 2024-02-02 | 沈阳卡得智能科技有限公司 | Intelligent grain collection monitoring control method and device |
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