CN113566891A - Multi-factor on-site detection method and device in loading and unloading process of bulk grains - Google Patents
Multi-factor on-site detection method and device in loading and unloading process of bulk grains Download PDFInfo
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Abstract
The invention discloses a multi-element on-site detection method and a device in the loading and unloading process of bulk grain, which assemble grain through a loading and unloading funnel module, convey sample material through a chute module, stop sampling in the grain blanking process through a sampling module, detect, screen and weigh the sample material through a multi-element detection module, screen out imperfect grain particles through a sorting module and weigh, weigh perfect grain particles through a volume weight and thousand particle detection module, return the detected sample material into a hopper through a return module, and summarize and process information of each module through a multi-element information processing module. The invention has the advantages of improving the coverage rate through high-density sampling, improving the efficiency by carrying out single batch analysis on the spot, reducing deviation and improving the accuracy by multi-element detection and data comparison, and lightening the labor intensity without a separate sampling process.
Description
Technical Field
The invention relates to the field of multi-element detection of bulk grains in the loading, unloading and transporting processes, in particular to a multi-element on-site detection method and a multi-element on-site detection device in the loading, unloading and transporting processes of bulk grains.
Background
Aiming at the import quarantine of a large amount of grains, particularly the import grain quality inspection and the detection and supervision of solid wastes, harmful grass seeds and insects, the method is generally adopted, after samples are mechanically or manually collected and prepared, samples are subjected to artificial chemical analysis, impurities, broken grains, thin grains, mildewed grains, damaged grains, heat damaged grains and volume weight are manually screened and selected and calculated, the water content is calculated by manual drying and weighing, solid wastes and harmful grass seeds are identified by sense organs, and the insects are used as main detection methods.
However, manual sampling, preparation and chemical detection are adopted, the total sampling coverage density is low, batch sampling is concentrated, and segregation is easy to generate; the sampling and sample preparation workload is large, the influence of artificial, climate and industrial and mining factors is large, the labor consumption is large, the labor intensity is high, the working environment is poor, the danger degree is high, the efficiency is low, the systematic deviation fluctuation in the whole process of sampling, preparation and chemical detection is large, the representativeness of trace samples to the whole batch of grain bulk materials is weak, the detection report is lagged, and the response efficiency is low.
Disclosure of Invention
Aiming at the situation and overcoming the defects of the prior art, the invention provides a multi-element on-site detection method and a device in the loading and unloading process of bulk grain, which have no random sampling process, no sample separation and sample preparation process, carry out high-density sampling on the apparent characteristics and the physicochemical characteristics of the grain in an unfolded state by a multi-technical unit, carry out composite detection and comparison judgment, realize intelligent real-time detection, erect a multi-element on-site detection device in the loading and unloading process of the bulk grain, install a multi-element detection module, detect the apparent impurities, broken grains, thin grains, mildewed grains, damaged grains, heat damaged grains, solid wastes and other harmful grass seeds and insects of the grain in real time at the frequency of 10-20 times/second, detect the physicochemical indexes of the bulk grain in real time, use the multi-element detection module, a material level positioning module and a multi-element information processing module and carry out real-time sampling analysis, comprehensively comparing and processing the multivariate data to obtain apparent quality data and physical and chemical index data of grains, superposing and integrating the data at any time interval, describing the single-batch integral multi-factor characteristics of the grain and grain bulk materials by high-density detection data, screening out imperfect grains in the sample materials by using a sorting module and weighing, installing a unit weight and thousand grain detection module, carrying out standard volume weighing and perfect thousand grain weighing on the perfect grains, and finally returning the detected grains and impurities to a bulk grain loading and unloading transportation hopper.
In order to achieve the above object, the present invention provides the following technical solutions, and the present invention includes:
the loading and unloading funnel module is used for grain assembly;
the chute module is used for conveying sample materials;
the sampling module is used for sampling in a layering manner in the grain blanking process and weighing during sampling, stopping sampling when the blanking amount reaches 10KG, shifting the material sample exceeding 8KG into a non-water-loss material belt for sealing storage, and making a time point sequencing mark corresponding to the near-infrared NIR detection unit;
the multi-element detection module is used for detecting, screening and weighing the sample materials;
the sorting module is used for screening imperfect grains in the sample material and weighing the imperfect grains;
the volume weight and thousand grain detection module is used for carrying out standard volume weighing on the perfect grains and weighing the perfect grains;
the back-feeding module is used for feeding the detected grains and impurities back to the bulk grain loading and unloading transportation hopper;
the multivariate information processing module is used for summarizing and processing the information of each module and calculating and comparing the information to generate a visual report;
the multi-element detection module comprises a bulk material flow velocity and thickness detection unit, a detection system positioning and timing unit, a bulk material screening and weighing unit, a machine vision detection unit and a near infrared NIR detection unit.
The sorting module comprises a color sorting unit and a blowing unit.
Furthermore, the bulk material flow velocity and thickness detection unit records a detection starting point and randomly detects the flow velocity and the thickness of the grain.
Furthermore, the detection system positioning and timing unit is used for detecting grain entering the detection device, and carrying out starting time metering on the grain entering the detection device and summarizing the grain entering the detection device into timing data.
Furthermore, the bulk screening and weighing unit is used for screening and weighing large sample impurities and small sample impurities in the sample material in a vibration mode.
Furthermore, the machine vision detection unit is a video detection device and utilizes high-speed photographing to obtain image videos, detects impurities, broken grains, thin small grains, moldy grains, damaged grains and heat damaged grains contained in grains in a flowing transmission state, and doped solid wastes and harmful grass seed insects, obtains apparent quality data and harmful grass seed and insect data of various stacking states of surface grains with the thickness of 20mm paved on a chute at the frequency of 10-20 times/second, and realizes layered, continuous and random apparent detection and summarization of whole batches of grains into apparent data.
Furthermore, the near-infrared NIR detection unit detects grain moisture, fat, protein, crude fiber and solid waste in a flowing state by sending infrared light to grain and collecting infrared spectrum, the sampling time length can be manually set, the content data of grain components on a surface layer which is paved on the chute and has the thickness of 20mm are obtained, and layered and continuous random physicochemical detection of a whole batch of grain is realized and summarized into physicochemical data.
Furthermore, the sorting module analyzes different apparent characteristics of the grains through the color sorting unit to distinguish grains with incomplete apparent mass, and the imperfect grains are blown out of the sample through the blowing unit and weighed.
Furthermore, the sampling module, the multi-element detection module, the sorting module, the volume weight, the thousand-grain detection module and the multivariate information processing module are in communication connection.
Has the advantages that: the invention improves the coverage rate through high-density sampling, improves the efficiency through online real-time period data analysis, avoids the methodical deviation of sampling and material mixing division extraction through multivariate detection, a large number of samples comparison and self-learning correction, can superpose and assemble multi-period data, and randomly intercepts the integral multi-element characteristic report of a period.
Drawings
Embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.
FIG. 1 is a block control schematic of the present invention;
FIG. 2 is a flow chart of the operation of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious 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 scope of the present invention.
The method and the device for detecting multiple elements in the loading and unloading process of bulk grains in the field by adopting the method are shown in figure 1 and comprise the following steps:
the loading and unloading funnel module is used for grain assembly;
the chute module is used for conveying sample materials;
the sampling module is used for sampling in a layering manner in the grain blanking process and weighing during sampling, stopping sampling when the blanking amount reaches 10KG, shifting the material sample exceeding 8KG into a non-water-loss material belt for sealing storage, and making a time point sequencing mark corresponding to the near-infrared NIR detection unit;
the multi-element detection module is used for detecting, screening and weighing the sample materials;
the sorting module is used for screening imperfect grains in the sample material and weighing the imperfect grains;
the volume weight and thousand grain detection module is used for carrying out standard volume weighing on the perfect grains and weighing the perfect grains;
the back-feeding module is used for feeding the detected grains and impurities back to the bulk grain loading and unloading transportation hopper;
the multivariate information processing module is used for summarizing and processing the information of each module and calculating and comparing the information to generate a visual report;
the multi-element detection module comprises a bulk material flow velocity and thickness detection unit, a detection system positioning and timing unit, a bulk material screening and weighing unit, a machine vision detection unit and a near infrared NIR detection unit.
The sorting module comprises a color sorting unit and a blowing unit.
The multi-element detection module comprises a bulk flow velocity and thickness detection unit, a detection system positioning and timing unit, a machine vision detection unit and a near infrared NIR detection unit
Specifically, the bulk material flow velocity and thickness detection unit records a detection starting point and randomly detects the flow velocity and thickness of the grain. The bulk material flow velocity and thickness detection unit acquires a detection position point of grain flowing through the sensor, and enters a working state after sending a starting instruction.
Specifically, the detection system positioning and timing unit is used for detecting grain entering the detection device, measuring the starting time of the grain entering the detection device and summarizing the grain entering time into timing data. The device is used as a positioning original point and a timing original point of the whole detection device, and sends a preheating signal and a starting detection signal to each detection module for detecting that the grain enters the detection device and performing initial timing measurement on the grain entering the detection device.
Specifically, the bulk cargo screening weighing unit is used for sorting and weighing large sample impurities and small sample impurities in the sample materials in a vibration mode. Each component weight in the sample material is different, and the impurities of the large sample are screened out faster than the impurities of the small sample by vibration, and then the impurities of the large sample and the impurities of the small sample are weighed.
Specifically, the machine vision detection unit utilizes high-speed photographing to obtain image videos for the video detection device, detects impurities, broken grains, thin small grains, moldy grains, damaged grains and heat damaged grains contained in grains in a flowing transmission state, obtains apparent quality data and harmful grass seeds and insect data of various stacking states of grains on the surface layer with the thickness of 20mm paved on a chute at the frequency of 10-20 times/second, and realizes layering, continuous and random apparent detection and summarization of whole batches of grains into apparent data. After the machine vision detection unit obtains the working state entering signal, high-definition images of various stacking forms of grains paved on the upper surface layer of the conveying belt are obtained at the sampling frequency of 10-20 times/second, the whole batch of grains containing impurities, broken grains, thin grains, mildew grains, damaged grains, heat damaged grains and harmful grass seeds and insects mixed in the grains are sampled, and the high-definition images are subjected to quantity ratio analysis aiming at all inspection items.
Specifically, the near-infrared NIR detection unit detects grain moisture, fat, protein, crude fiber and solid waste in a flowing state by sending infrared light to grain and collecting infrared spectrum, the sampling time length can be manually set, the content data of grain components on a surface layer which is paved on a chute and has the thickness of 20mm are obtained, and layered and continuous random physicochemical detection and summarization of a whole batch of grain are realized to form physicochemical data. After the near infrared NIR detection unit obtains the signal of the working state, the moisture, fat and protein spectrograms of the grains are measured, the spectrogram information is processed in a segmented mode, and the physicochemical quality detection values of the grains are given in a segmented or batch mode.
Specifically, the selecting module analyzes different apparent characteristics of grains through the color selecting unit to distinguish grains with incomplete apparent mass, and the imperfect grains are blown out of the sample through the blowing unit and weighed. And in the falling process of the sample material, imperfect grains are distinguished by using different apparent characteristics of grains, and the imperfect grains are blown out of the sample material by using an air nozzle.
Specifically, the sampling module, the multi-element detection module, the sorting module, the volume weight, the thousand-grain detection module and the multivariate information processing module are in communication connection. The information detected by each module is transmitted to the multi-element information processing module through communication connection.
Finally, the above examples are merely illustrative of the present invention and should not be construed as limiting the scope of the present invention, and all designs identical or similar to the present invention are within the scope of the present invention.
Claims (9)
1. Many key elements of bulk grain handling in-process are at-the-spot detection device includes:
the loading and unloading funnel module is used for grain assembly;
the chute module is used for conveying sample materials;
the sampling module is used for sampling in a layering manner in the grain blanking process and weighing during sampling, stopping sampling when the blanking amount reaches 10KG, shifting the material sample exceeding 8KG into a non-water-loss material belt for sealing storage, and making a time point sequencing mark corresponding to the near-infrared NIR detection unit;
the multi-element detection module is used for detecting, screening and weighing the sample materials;
the sorting module is used for screening imperfect grains in the sample material and weighing the imperfect grains;
the volume weight and thousand grain detection module is used for carrying out standard volume weighing on the perfect grains and weighing the perfect grains;
the back-feeding module is used for feeding the detected grains and impurities back to the bulk grain loading and unloading transportation hopper;
the multivariate information processing module is used for summarizing and processing the information of each module and calculating and comparing the information to generate a visual report;
the multi-element detection module comprises a bulk material flow velocity and thickness detection unit, a detection system positioning and timing unit, a bulk material screening and weighing unit, a machine vision detection unit and a near infrared NIR detection unit.
2. The sorting module comprises a color sorting unit and a blowing unit;
the bulk grain handling in-situ multi-factor detection device of claim 1, wherein: the bulk material flow velocity and thickness detection unit records a detection starting point and randomly detects the flow velocity and thickness of the grain.
3. The bulk grain handling in-situ multi-factor detection device of claim 1, wherein: the detection system positioning and timing unit is used for detecting grain entering the detection device and measuring the time of entering the detection device at the beginning.
4. The bulk grain handling in-situ multi-factor detection device of claim 1, wherein: the bulk screening and weighing unit is used for sorting and weighing large sample impurities and small sample impurities in the sample materials in a vibration mode.
5. The bulk grain handling in-situ multi-factor detection device of claim 1, wherein: the machine vision detection unit utilizes high-speed photographing to obtain image videos for the video detection device, detects impurities, broken grains, thin small grains, moldy grains, damaged grains and heat damaged grains contained in grains in a flowing transmission state, obtains apparent quality data and harmful grass seeds and insect data of various stacking states of grains with the thickness of 20mm paved on a chute at the frequency of 10-20 times/second, and realizes layered, continuous and random apparent detection of whole batches of grains.
6. The bulk grain handling in-situ multi-factor detection device of claim 1, wherein: the near-infrared NIR detection unit detects grain moisture, fat, protein, coarse fiber and solid waste in a flowing state by sending infrared light to grain and collecting infrared spectrum, the sampling time length can be manually set, the content data of grain components on a surface layer which is paved on a chute and has the thickness of 20mm are obtained, layered and continuous random physicochemical detection of whole batches of grain is realized, and physicochemical monitoring data of single batch of material samples can be given.
7. The bulk grain handling in-situ multi-factor detection device of claim 1, wherein: the sorting module analyzes different apparent characteristics of grains through the color sorting unit to distinguish grains with incomplete apparent mass, and the imperfect grains are blown out of the sample through the blowing unit and weighed.
8. The bulk grain handling in-situ multi-factor detection device of claim 1, wherein: the sampling module, the multi-element detection module, the sorting module, the volume weight, the thousand-grain detection module and the multi-element information processing module are in communication connection.
9. The on-site detection method for multiple factors in the loading and unloading process of bulk grains is characterized by comprising the following steps:
s1, judging the weight of the bulk grain sample and controlling the working state of the sampling module according to the set sampling amount;
s2, weighing the weight of the bulk grain sample, the weight of impurities in the bulk grain sample, the weight of imperfect particles, the volume weight of perfect particles and the weight of thousand particles, and realizing the apparent mass-to-weight ratio detection data of the bulk grain sample;
s3, processing the multivariate data collected in the detection process, calculating the apparent mass of a single-batch grain sample, detecting the data and the physicochemical characteristic data, calculating the quantity ratio data of inclusions such as solid waste, harmful grass seeds and pests contained in the single-batch bulk grain sample, and setting the discovery times and the quantity ratio threshold value, and alarming and tracing information beyond the limit;
s4, detecting bulk grain samples by a near infrared NIR detection unit and a machine vision detection unit, then sorting and detecting appearance and shape characteristics of grains, distinguishing perfect grains and imperfect grains in the grains of the bulk grain samples, allocating finished grain samples for volume weight detection and thousand grain weight detection, and completing weight ratio calculation;
s5, the detection system preheats from the sample introduction, starts the detection, interrupts the detection, restarts the detection, distributes the material sample, collects the material sample, finishes the detection, stops the detection system work, and marks the node counting information weight information of the detection system work process in the detection data mark, processes the detection data according to single batch;
s6, comparing the data of the quantity ratio of the machine vision detection units with the data of the weight ratio of the bulk screening and weighing units;
s7, recording inclusions such as solid waste, harmful grass seeds and pests, and performing single-batch detection to set the number of times of discovery, the quantity threshold and the detection record;
s8, storing the data of the multiple detection spectrogram, the photo, the weighing, the count ratio, the given mark of the weighing ratio data and the time sequence mark;
and S9, carrying out manual inspection and test on the single batch of bulk grain samples, comparing and checking the inspection and test results with machine vision and NIR detection data sequenced at corresponding time points, and continuously correcting the data processing algorithm.
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| CN114112547A (en) * | 2021-11-30 | 2022-03-01 | 江苏丰尚智能科技有限公司 | On-line quality detection device |
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| CN114112547A (en) * | 2021-11-30 | 2022-03-01 | 江苏丰尚智能科技有限公司 | On-line quality detection device |
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Application publication date: 20211029 |