A rice processing monitoring and early warning method and system based on multi-dimensional data analysis

Abstract

The present invention relates to the technical field of rice processing, and in particular to a method and system for monitoring and warning rice processing based on multi-dimensional data analysis. The method includes: conveying rice through a conveyor belt to a pneumatic screening device for screening; constructing an amylose content model; determining the content ratio of heavy rice and light rice; forming several portions of soaked rice according to the content ratio, constructing a microwave sensor, establishing a regression equation between the initial moisture content and microwave parameters, and outputting soaked rice with qualified initial moisture content; detecting whether the cooled rice is stirred qualifiedly and giving an alarm; detecting the finished product moisture content of the dried rice and giving an alarm, and performing rehydration detection on the dried rice, adjusting the cooling temperature and giving an alarm; The method for monitoring and warning rice processing based on multi-dimensional data analysis provided by the present invention effectively screens the processed rice, improves the quality of the finished rice processing process, and effectively improves the accuracy of the rice processing monitoring and warning system.

Description

Technical Field

[0001] The present invention relates to the technical field of rice processing, and particularly to a rice processing monitoring and early warning method and system based on multi-dimensional data analysis. Background Art

[0002] With the development of Internet of Things technology, the intervention and early warning technology in the processing process has gradually been taken seriously. By monitoring the relevant parameters in the processing process and combining intelligent algorithms, it is possible to timely give an early warning of the processing process, avoid abnormalities in the processing process, and improve the processing efficiency. At present, the monitoring and early warning technology has been applied in various fields. For example, in the field of rice processing, by monitoring the rice processing process, it is possible to timely analyze the rice processing effect, give an early warning of the rice processing process, and ensure the processing quality.

[0003] Patent application publication number CN118644963A discloses a monitoring and alarm system for a fully automated self-heating rice production line based on the Internet of Things. The invention provides a monitoring and alarm system for a fully automated self-heating rice production line based on the Internet of Things, which relates to the technical field of monitoring and alarm; this monitoring and alarm system for a fully automated self-heating rice production line based on the Internet of Things generates a material production plan corresponding to the state through a production plan generation module, avoiding the situation that when only using the same self-heating rice production plan to produce materials in different states under different storage environments, different degrees of ripeness occur in the production of the same type of materials. At the same time, by generating corresponding solutions for the rice production result data with different comparison results in the data comparison module, it is avoided that due to the failure to timely discover abnormal data in the self-heating rice production process, the rice is in a half-cooked state or the rice nutrition is lost when discovered. At the same time, through the analysis of relevant data groups, it is possible to ensure the production effect of the self-heating rice with problems to the greatest extent.

[0004] It can be seen that this method has the following problems: only monitoring the rice processing process without classifying and screening the rice raw materials, and not effectively monitoring the various factors affecting the rice processing finished products. Summary of the Invention

[0005] Therefore, the present invention provides a rice processing monitoring and early warning method and system based on multi-dimensional data analysis to overcome the problems in the prior art that only monitor the rice processing process without classifying and screening the rice raw materials, and not effectively monitoring the various factors affecting the rice processing finished products.

[0006] To achieve the above object, on the one hand, the present invention provides a rice processing monitoring and early warning method based on multi-dimensional data analysis, including:

[0007] The rice is conveyed to a pneumatic screening device via a conveyor belt for screening. Based on machine vision, the air flow rate of the pneumatic screening device is adjusted to classify the rice into heavy rice, light rice, and broken rice.

[0008] The heavy rice and the light rice with different weights are respectively selected and ground into heavy rice powder and light rice powder. Based on a near-infrared spectroscopy device, a number of amylose contents of the heavy rice and a number of amylose contents of the light rice are respectively calculated to construct an amylose content model.

[0009] Based on the amylose content model and a preset amylose content, the content ratios of the heavy rice and the light rice are determined.

[0010] According to the content ratios, several portions of soaked rice are composed. A microwave sensor is constructed, and a regression equation between the initial moisture content and microwave parameters is established. The soaked rice is selected at a preset cycle time for compaction to collect microwave signals. Combining the regression equation between the initial moisture content and microwave parameters, the soaked rice with qualified initial moisture content is output.

[0011] The soaked rice is steamed and cooled, and the cooled rice is stirred. Based on machine vision, it is detected whether the stirring of the cooled rice is qualified, and a stirring alarm signal is issued in the state where it is determined that the stirring is unqualified.

[0012] The cooled rice is freeze-dried to produce dried rice. The finished product moisture content of the dried rice is detected. Based on the finished product moisture content, the drying time is adjusted or a drying alarm signal is issued. In addition, the dried rice is subjected to rehydration detection, and based on the detection result, it is determined whether to increase the cooling temperature and a temperature alarm signal is issued.

[0013] Further, the process of classifying the rice into heavy rice, light rice, and broken rice includes:

[0014] The rice is spread evenly on the conveyor belt.

[0015] The pneumatic screening device blows the rice falling from the conveyor belt horizontally to a falling area.

[0016] Based on the rice shape in the falling area photographed by machine vision, the air flow rate is adjusted to classify the rice into the heavy rice, the light rice, and the broken rice.

[0017] Further, the process of constructing an amylose content model based on a number of the amylose contents of the heavy rice and a number of the amylose contents of the light rice includes:

[0018] The heavy rice and the light rice with different weights are respectively selected and ground into heavy rice powder and light rice powder. The powder that cannot pass through the sieve in the ground powder is removed to reduce the powder particle size.

[0019] Combined with the near-infrared spectroscopy device, collect the heavy rice spectrogram and the light rice spectrogram, and calculate the amylose content of a number of heavy rices and the amylose content of a number of light rices respectively;

[0020] Combined with a number of the amylose content of the heavy rices and a number of the amylose content of the light rices, construct an amylose content model for heavy rices and light rices of different weights.

[0021] Further, the process of determining the content ratio of the heavy rices and the light rices based on the amylose content model and a preset amylose content includes:

[0022] Based on the amylose content model, establish an amylose content equation for the mixture;

[0023] Combined with the preset amylose content and the amylose content equation for the mixture, calculate and generate the content ratio;

[0024] The preset amylose content is negatively correlated with the shelf life of the finished instant rice.

[0025] Further, the process of constructing the microwave sensor, establishing the regression equation between the initial moisture content and the microwave parameters, and selecting the soaked rice for compaction to collect the microwave and output the soaked rice with qualified initial moisture content includes:

[0026] According to the content ratio, form a number of portions of soaked rice, and select soaked rices of different weights to calculate a number of standard moisture contents by the direct drying method;

[0027] Based on the microwave sensor and a number of the standard moisture contents, establish the regression equation between the initial moisture content and the microwave parameters;

[0028] Select the soaked rice for compaction at a preset cycle time to collect the microwave signal to generate microwave parameter values;

[0029] Substitute the microwave parameter values into the regression equation between the initial moisture content and the microwave parameters to calculate the initial moisture content of a number of portions of the soaked rice;

[0030] Compare the initial moisture content with the preset moisture content, and determine whether the soaked rice corresponding to the initial moisture content is qualified according to the comparison result;

[0031] The preset cycle time is positively correlated with the rice soaking time, and the preset moisture content is negatively correlated with the shelf life of the finished instant rice.

[0032] Further, the process of detecting whether the cooled rice is stirred qualified based on the machine vision includes:

[0033] Cook and cool the soaked rice to generate the cooled rice;

[0034] Collect the original images of the cooled rice after stirring, and generate a caking rate based on the area of the caked rice in the original images;

[0035] Compare the caking rate with a preset caking rate, and determine whether the cooled rice is stirred qualified according to the comparison result;

[0036] Send out the stirring alarm signal in the state of determining that the stirring is unqualified;

[0037] The preset caking rate is positively correlated with the weight of the cooled rice.

[0038] Further, the process of adjusting the drying time based on the moisture content of the finished product includes:

[0039] Freeze-dry the cooled rice to generate the dried rice, and detect the moisture content of the finished product of the dried rice;

[0040] Compare the moisture content of the finished product with a preset moisture content of the finished product, and increase or decrease the drying time according to the comparison result;

[0041] Send out the drying alarm signal in the state of determining to increase the drying time;

[0042] The preset moisture content of the finished product is negatively correlated with the shelf life of the finished instant rice.

[0043] Further, the process of rehydration detection of the dried rice and adjusting the cooling temperature based on the detection result includes:

[0044] Lay the dried rice flat in the pigment water for rehydration detection;

[0045] Press the dried rice after the rehydration detection is completed, and statistically calculate the white core area based on machine vision to generate the white core area occupancy rate;

[0046] Compare the white core area occupancy rate with a preset area occupancy rate, and determine whether to increase the cooling temperature according to the comparison result;

[0047] Send out the temperature alarm signal in the state of determining to increase the cooling temperature;

[0048] The preset area occupancy rate is positively correlated with the weight of the dried rice.

[0049] On the other hand, the present invention also provides a rice processing monitoring and warning system, including:

[0050] A screening unit for screening rice, and based on machine vision, adjusting the air flow rate of the pneumatic screening device to divide the rice into heavy rice, light rice and broken rice;

[0051] A starch detection unit, which is connected to the screening unit and is used to respectively select the heavy rice and the light rice of different weights, crush them into heavy rice powder and light rice powder, and calculate a number of amylose contents of the heavy rice and a number of amylose contents of the light rice based on a near-infrared spectroscopy device to construct an amylose content model;

[0052] A distribution unit, which is connected to the starch detection unit and is used to determine the content ratio of the heavy rice and the light rice based on the amylose content model and a preset amylose content;

[0053] Soaking unit, which is connected to the distribution unit and is used to form several portions of soaked rice according to the content ratio, construct a microwave sensor, establish a regression equation between the initial moisture content and microwave parameters, select the soaked rice for compaction to collect microwave signals at a preset cycle time, and output the soaked rice with qualified initial moisture content in combination with the regression equation between the initial moisture content and microwave parameters;

[0054] A cooling unit, which is connected to the soaking unit and is used to cook and cool the soaked rice, and stir the cooled rice, and detect whether the cooled rice is stirred qualified based on machine vision;

[0055] A finished product unit, which is connected to the cooling unit and is used to freeze-dry the cooled rice to generate dried rice, detect the moisture content of the finished product of the dried rice, adjust the drying time based on the moisture content of the finished product, and perform rehydration detection on the dried rice, and adjust the cooling temperature based on the detection result;

[0056] An alarm unit, which is respectively connected to the cooling unit and the finished product unit, and is used to send out a stirring alarm signal in the state of determining that the stirring is unqualified, and send out a drying alarm signal in the state of determining to increase the drying time, and send out a temperature alarm signal in the state of determining to increase the cooling temperature.

[0057] Further, the screening unit includes:

[0058] A conveyor belt, which is used to convey rice;

[0059] A pneumatic screening device, which is connected to the conveyor belt and is used to screen rice by jetting air;

[0060] A photographing device, which is connected to the pneumatic screening device and is used to collect images of rice in the dropping area.

[0061] Compared with the prior art, the beneficial effects of the present invention are as follows. The present invention uses a pneumatic screening device in combination with machine vision to remove broken rice, and at the same time divides the remaining intact rice into heavy rice and light rice, and conducts targeted screening for the processing of instant rice. Traditional manual screening requires a large amount of manpower and is prone to cause damage to rice grains (the loss rate is about 3% - 5%). However, the combination of machine vision and pneumatic screening is fully automated, and the loss rate can be controlled within 1%. At the same time, more than 50% of the labor cost is saved. The vision system can record the screening data of each batch of rice, such as the proportion of broken rice, the proportion of heavy and light rice. The removed broken rice can be separately collected and used for the production of by-products such as rice cakes and rice noodles, avoiding the waste of resources caused by the direct discard of broken rice in the traditional process. It not only improves the quality stability and functional adaptability of the end product, but also reduces the production cost and environmental burden through automation and resource utilization, effectively improving the accuracy of the rice processing monitoring and early warning system.

[0062] Furthermore, the present invention uses a near-infrared spectroscopy device to calculate the amylose content of heavy rice and light rice respectively, and at the same time constructs an amylose content model to determine the content ratio of heavy rice and light rice under the best sticky and glutinous taste. The near-infrared spectroscopy technology can complete the detection of the amylose content of a single sample within 10 seconds by analyzing the absorption intensity of rice grains to light of a specific wavelength. Compared with the traditional chemical method (such as the iodine colorimetric method which takes 2 hours), the efficiency is increased by more than 90%. The error rate of the traditional method is about ±3%, and the near-infrared detection error can be controlled within ±1%, meeting the stringent requirements of instant rice for ingredient accuracy. The amylose content directly determines the stickiness and glutinousness of cooked rice. Heavy rice has a higher amylose content, the cooked rice has a harder texture, stronger elasticity, and is prone to retrogradation after cooling. Light rice has a lower amylose content, and the cooked rice is softer, stickier, and has a higher viscosity. By combining different ratios of heavy rice and light rice, various tastes can be adjusted, improving the control of the taste of instant rice from the level of "empirical trial and error" to the level of "data precision". It not only solves the problems of unmeasurable ingredients and ratio depending on experience in the traditional process, but also reduces costs through raw material grading utilization and process standardization, further improving the accuracy of the rice processing monitoring and early warning system.

[0063] Furthermore, the present invention measures the moisture content of the soaked rice through a microwave sensor to ensure the quality of the rice during subsequent cooking, cooling, and drying processes. The microwave technology can achieve the full measurement of "surface + internal moisture", avoiding the "false saturation" phenomenon. For example, if the surface of the rice grain absorbs water but the inside is not soaked through and the moisture content is insufficient, it will cause the center of the rice grain to be undercooked and require secondary steaming. If the moisture content is too high, it is likely to cause the cooked rice to be mushy and broken. Microwave measurement and control can control the moisture content within the optimal range, increasing the qualified rate of the first steaming from 85% to 98%. The precise measurement and control of the moisture content of the soaked rice by the microwave sensor realizes the intelligent prediction and dynamic adjustment of the entire process chain through "data preposition". Its core value lies not only in solving the pain points of "unknown moisture and control relying on experience" in traditional processes, but also in realizing the upgrade of instant rice processing from "extensive production" to "precision manufacturing" by constructing a closed-loop system of "detection - modeling - execution", further improving the accuracy of the rice processing monitoring and early warning system.

[0064] Furthermore, the present invention stirs the rice that has completed cooking and cooling, and based on machine vision, it detects whether the cooled rice is stirred qualifiedly, detects the moisture content of the dried rice, and conducts a rehydration test on the dried rice. The paddle-type or spiral-ribbon-type stirring device is used to break up and mix the cooked and cooled rice grains evenly to avoid caking. The machine vision system can evaluate the state of the rice after stirring with extremely high precision and repeatability. It can quickly identify whether the rice grains are evenly distributed. If the stirring is unqualified, there may be local accumulation or separation of the rice grains. Through visual inspection, it can ensure that the quality of each batch of rice in the cooling and stirring link is consistent, avoiding quality fluctuations caused by subjective differences in human judgment. Moreover, the machine vision detection is fast and can detect a large amount of rice in a short time. The rehydration test can directly reflect whether the rice is damaged during the drying process. The rehydration test can simulate the usage process of instant rice, and through the rehydration test, it can be judged whether the processing quality of the rice meets the requirements, further improving the accuracy of the rice processing monitoring and early warning system. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 is a flowchart of the rice processing monitoring and early warning method based on multi-dimensional data analysis according to an embodiment of the present invention;

[0066] Figure 2 is a flowchart of classifying rice according to an embodiment of the present invention;

[0067] Figure 3 is a decision logic diagram for detecting the finished product moisture content of dried rice according to an embodiment of the present invention;

[0068] Figure 4 is a structural schematic diagram of the rice processing monitoring and early warning system according to an embodiment of the present invention. Detailed implementation manners

[0069] In order to make the objectives and advantages of the present invention more clear and understandable, the present invention will be further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0070] The preferred implementation manners of the present invention will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these implementation manners are only used to explain the technical principles of the present invention and do not limit the protection scope of the present invention.

[0071] It should be noted that in the description of the present invention, the terms indicating the direction or positional relationship such as "upper", "lower", "left", "right", "inner", "outer", etc. are based on the direction or positional relationship shown in the drawings. This is only for convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0072] In addition, it should also be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installation", "connection", and "connection" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0073] Please refer to Figure 1 As shown in the figure, it is a step diagram of the rice processing monitoring and early warning method based on multi-dimensional data analysis according to an embodiment of the present invention. The present invention provides a rice processing monitoring and early warning method based on multi-dimensional data analysis, including:

[0074] Step S1: Convey the rice to a pneumatic screening device via a conveyor belt for screening, and classify the rice into heavy rice, light rice, and broken rice based on machine vision by adjusting the air flow rate of the pneumatic screening device;

[0075] Step S2: Select heavy rice and light rice with different weights and crush them into heavy rice powder and light rice powder respectively, and calculate the amylose content of a number of heavy rice and a number of light rice respectively based on a near-infrared spectroscopy device to construct an amylose content model;

[0076] Step S3: Determine the content ratio of heavy rice and light rice based on the amylose content model and a preset amylose content;

[0077] Step S4: Soak several portions of rice according to the content ratio, construct a microwave sensor, establish a regression equation between the initial moisture content and microwave parameters, select the soaked rice for compaction to collect microwave signals at a preset periodic time, and output the soaked rice with qualified initial moisture content in combination with the regression equation between the initial moisture content and microwave parameters;

[0078] Step S5: Cook and cool the soaked rice, and stir the cooled rice. Based on machine vision, detect whether the cooled rice is stirred qualifiedly, and send out a stirring alarm signal in the state of determining that the stirring is unqualified;

[0079] Step S6: Freeze-dry the cooled rice to generate dried rice, detect the finished product moisture content of the dried rice, adjust the drying time or send out a drying alarm signal based on the finished product moisture content, and perform rehydration detection on the dried rice, and determine whether to increase the cooling temperature and send out a temperature alarm signal based on the detection result.

[0080] Please refer to Figure 2 shown, which is a flowchart for classifying rice in an embodiment of the present invention. In the step S1, the process of transporting the rice to a pneumatic screening device via a conveyor belt for screening and dividing the rice into heavy rice, light rice, and broken rice based on machine vision to adjust the air flow rate of the pneumatic screening device includes:

[0081] Step S101: Spread the rice flat on the conveyor belt;

[0082] Step S102: The pneumatic screening device blows the rice falling from the conveyor belt horizontally to the falling area;

[0083] Step S103: Adjust the air flow rate based on the rice morphology in the falling area photographed by machine vision to divide the rice into heavy rice, light rice, and broken rice.

[0084] It can be understood that the machine vision device takes pictures from above the falling area. Through image analysis, when there is no obvious piling of rice, the air flow rate is increased until the rice in the falling area is piled up. From near to far from the conveyor belt, there are heavy rice piles, light rice piles, and broken rice piles in sequence.

[0085] Specifically, the present invention uses a pneumatic screening device in combination with machine vision to remove broken rice, and at the same time divides the remaining intact rice into heavy rice and light rice, and conducts targeted screening on the processing of instant rice. Traditional manual screening requires a large amount of manpower and is prone to cause damage to rice grains (the loss rate is about 3% - 5%). However, the combination of machine vision and pneumatic screening is fully automated, and the loss rate can be controlled within 1%. At the same time, it saves more than 50% of the labor cost. The vision system can record the screening data of each batch of rice, such as the proportion of broken rice, the proportion of heavy and light rice. The removed broken rice can be separately collected and used to produce by-products such as rice cakes and rice flour, avoiding the waste of resources caused by the direct discard of broken rice in the traditional process. It not only improves the quality stability and functional adaptability of the end product, but also reduces the production cost and environmental burden through automation and resource utilization, effectively improving the accuracy of the rice processing monitoring and early warning system.

[0086] Specifically, in the step S2, the process of respectively selecting heavy rice and light rice with different weights, grinding them into heavy rice powder and light rice powder, and calculating a number of amylose contents of heavy rice and a number of amylose contents of light rice based on the near-infrared spectroscopy device to construct an amylose content model includes:

[0087] Respectively select heavy rice and light rice with different weights, and grind them into heavy rice powder and light rice powder. The powder that cannot pass through the sieve in the ground powder is used to reduce the particle size of the powder;

[0088] Combined with the near-infrared spectroscopy device, collect the heavy rice spectrogram and the light rice spectrogram, and calculate a number of amylose contents of heavy rice and a number of amylose contents of light rice respectively;

[0089] Combine a number of amylose contents of heavy rice and a number of amylose contents of light rice to construct an amylose content model for heavy rice and light rice with different weights.

[0090] In practice, respectively select different weights. Optionally, select 50g, 100g, and 150g of heavy rice and light rice samples. Use a mortar or a dedicated rice milling machine to grind the heavy rice and light rice into powder respectively. Pass the ground powder through a sieve. Optionally, use an 80-mesh sieve for screening. Put the processed heavy rice powder and light rice powder into the sample cell of the spectroscopy device respectively. The sample cell should be clean and free of impurities. Collect the near-infrared spectrogram of each sample respectively, record the acquisition parameters of the spectrogram. Each sample should be measured at least 3 times, and take the average value as the final result. Use a standard sample with a known amylose content, collect its spectrogram through the near-infrared spectroscopy device, and establish a standard curve. Compare the collected heavy rice and light rice spectrograms with the standard curve, calculate the amylose content of each sample, and record the calculation result to construct a model between the amylose content and the sample weight.

[0091] Specifically, in the step S3, the process of determining the content ratio of heavy rice and light rice based on the amylose content model and the preset amylose content includes:

[0092] Establish an amylose content equation for the mixture based on the amylose content model;

[0093] Calculate and generate the content ratio by combining the preset amylose content and the amylose content equation for the mixture;

[0094] It can be understood that the amylose content equation for the mixture is , where a is the weight of heavy rice, unit: kg; b is the weight of light rice, unit: kg; n is the amylose content of heavy rice; m is the amylose content of light rice.

[0095] It can be understood that when the weights of heavy rice and light rice are fixed, the content ratio of heavy rice and light rice can be calculated according to the preset amylose content.

[0096] The preset amylose content is negatively correlated with the shelf life of the finished instant rice.

[0097] It can be understood that amylose has strong hygroscopicity and is easy to absorb moisture. The increase in moisture will accelerate the growth and reproduction of microorganisms, thus shortening the shelf life. Amylose is prone to retrogradation during storage, reducing the shelf life. When the production shelf life increases, the amylose content needs to be appropriately reduced. Therefore, the preset amylose content is negatively correlated with the shelf life of the finished instant rice.

[0098] Optionally, the shelf life of the finished instant rice is 120 days, and the preset amylose content is 15%;

[0099] The shelf life of the finished instant rice is 90 days, and the preset amylose content is 20%;

[0100] The shelf life of the finished instant rice is 60 days, and the preset amylose content is 25%.

[0101] Specifically, the present invention calculates the amylose content of heavy rice and light rice respectively by using a near-infrared spectroscopy device, and constructs an amylose content model to determine the content ratio of heavy rice and light rice under the best sticky and glutinous taste. The near-infrared spectroscopy technology analyzes the absorption intensity of rice grains to light of a specific wavelength, and can complete the detection of the amylose content of a single sample within 10 seconds. Compared with the traditional chemical method (such as the iodine colorimetric method which takes 2 hours), the efficiency is increased by more than 90%. The error rate of the traditional method is about ±3%, and the near-infrared detection error can be controlled within ±1%, meeting the strict requirements of instant rice for ingredient accuracy. The amylose content directly determines the stickiness and glutinousness of rice. The amylose content of heavy rice is relatively high, the taste of the rice is hard and elastic, and it is easy to retrograde after cooling. The amylose content of light rice is relatively low, the rice is softer, waxy and has high viscosity. By combining different ratios of heavy rice and light rice, a variety of tastes can be blended, improving the taste control of instant rice from "empirical trial and error" to the level of "data precision". It not only solves the problems of unmeasurable ingredients and ratio depending on experience in the traditional process, but also reduces costs through raw material grading utilization and process standardization, further improving the accuracy of the rice processing monitoring and early warning system.

[0102] Specifically, in the step S4, several portions of soaked rice are composed according to the content ratio, a microwave sensor is constructed, a regression equation between the initial moisture content and microwave parameters is established, and the process of selecting soaked rice for compaction to collect microwave signals at a preset cycle time and outputting the soaked rice with qualified initial moisture content in combination with the regression equation between the initial moisture content and microwave parameters includes:

[0103] Several portions of soaked rice are composed according to the content ratio, and different weights of soaked rice are selected to calculate several standard moisture contents by the direct drying method;

[0104] A regression equation between the initial moisture content and microwave parameters is established based on the microwave sensor and several standard moisture contents;

[0105] Soaked rice is selected at a preset cycle time for compaction to collect microwave signals to generate microwave parameter values;

[0106] The microwave parameter values are substituted into the regression equation between the initial moisture content and microwave parameters to calculate the initial moisture contents of several portions of soaked rice;

[0107] In practice, prepare a microwave sensor to ensure that it can measure microwave parameters related to the moisture content, measure the microwave parameters of each soaked rice sample. Record the microwave parameter values of each sample, and establish a regression equation between the initial moisture content and microwave parameters, moisture content = a × microwave parameter + b, where a and b are regression coefficients.

[0108] In implementation, at a preset cycle time, optionally every 30 minutes or 1 hour, select the soaked rice samples for compaction treatment, use a microwave sensor to collect the microwave signals after compaction, generate microwave parameter values, substitute the collected microwave parameter values into the regression equation of the initial moisture content and microwave parameters, calculate the initial moisture content of the soaked rice, record the moisture content calculated each time, and analyze its change trend over time.

[0109] Compare the initial moisture content with the preset moisture content, and determine whether the soaked rice corresponding to the initial moisture content is qualified according to the comparison result;

[0110] If the initial moisture content is greater than or equal to the preset moisture content, it is determined that the soaked rice corresponding to the initial moisture content is qualified;

[0111] If the initial moisture content is less than the preset moisture content, it is determined that the soaked rice corresponding to the initial moisture content is unqualified;

[0112] In a specific embodiment, set the preset moisture content to 30%. If the initial moisture content is 40% which is greater than the preset moisture content, it is determined that the soaked rice corresponding to the initial moisture content is qualified;

[0113] If the initial moisture content is 25% which is less than the preset moisture content, it is determined that the soaked rice corresponding to the initial moisture content is unqualified;

[0114] The preset cycle time is positively correlated with the rice soaking time, and the preset moisture content is negatively correlated with the shelf life of the finished instant rice.

[0115] It can be understood that the longer the rice soaking time, the longer the interval time for sample selection. Therefore, the preset cycle time is positively correlated with the rice soaking time.

[0116] Optionally, the rice soaking time is 0.5 hour and the preset cycle time is 1 hour;

[0117] The rice soaking time is 1 hour and the preset cycle time is 2 hours;

[0118] The rice soaking time is 2 hours and the preset cycle time is 3 hours.

[0119] It can be understood that the higher the moisture content, the shorter the shelf life of the rice. Therefore, the preset moisture content is negatively correlated with the shelf life of the finished instant rice.

[0120] Optionally, the shelf life of the finished instant rice is 120 days and the preset moisture content is 30%;

[0121] The shelf life of the finished instant rice is 90 days and the preset moisture content is 35%;

[0122] The shelf life of the finished instant rice is 60 days and the preset moisture content is 40%;

[0123] Specifically, the present invention measures the moisture content of soaked rice through a microwave sensor to ensure the quality of rice during subsequent cooking, cooling, and drying processes. The microwave technology can achieve the full measurement of "surface + internal moisture", avoiding the "false saturation" phenomenon. For example, if the surface of the rice grain absorbs water but the inside is not soaked through, and the moisture content is insufficient, it will cause the center of the rice grain to be undercooked and require secondary steaming. If the moisture content is too high, it is likely to cause the cooked rice to be mushy and broken. The microwave measurement and control can control the moisture content within the optimal range, increasing the qualified rate of one-time steaming from 85% to 98%. The precise measurement and control of the moisture content of soaked rice by the microwave sensor realizes the intelligent prediction and dynamic adjustment of the entire process chain through "data preposition". Its core value lies not only in solving the pain points of "unknown moisture and control relying on experience" in traditional processes, but also in realizing the upgrade of instant rice processing from "extensive production" to "precision manufacturing" by constructing a closed-loop system of "detection - modeling - execution", further improving the accuracy of the rice processing monitoring and early warning system.

[0124] Specifically, in the step S5, the process of cooking and cooling the soaked rice, and stirring and cooling the rice, and detecting whether the cooled rice is stirred qualified based on machine vision includes:

[0125] Cook and cool the soaked rice to produce cooled rice;

[0126] Collect the original image of the cooled rice after stirring is completed, and generate a caking rate based on the area of the caked rice in the original image;

[0127] It can be understood that the caking rate = caking area / total image area x 100%.

[0128] Compare the caking rate with the preset caking rate, and determine whether the cooled rice is stirred qualified according to the comparison result;

[0129] Send a stirring alarm signal in the state where it is determined that the stirring is unqualified;

[0130] If the caking rate is greater than or equal to the preset caking rate, it is determined that the cooled rice is stirred unqualified and a stirring alarm signal is sent;

[0131] If the caking rate is less than the preset caking rate, it is determined that the cooled rice is stirred qualified;

[0132] In a specific embodiment, the preset caking rate is set to 10%. If the caking rate is 14% which is greater than the preset caking rate, it is determined that the cooled rice is stirred unqualified and a stirring alarm signal is sent;

[0133] If the caking rate is 8% which is less than the preset caking rate, it is determined that the cooled rice is stirred qualified;

[0134] The preset caking rate is positively correlated with the weight of the cooled rice.

[0135] It can be understood that the greater the weight of the cooled rice, the more difficult it is to stir, and the higher the probability of agglomeration during stirring. Therefore, the preset agglomeration rate is positively correlated with the weight of the cooled rice.

[0136] Optionally, the weight of the cooled rice is 100 grams, and the preset agglomeration rate is 5%;

[0137] The weight of the cooled rice is 200 grams, and the preset agglomeration rate is 10%;

[0138] The weight of the cooled rice is 300 grams, and the preset agglomeration rate is 15%.

[0139] Please refer to Figure 3 As shown, it is the determination logic diagram for detecting the moisture content of the finished product of the dried rice in the embodiment of the present invention. In the step S6, the process of freeze-drying the cooled rice to generate dried rice, detecting the moisture content of the finished product of the dried rice, and adjusting the drying time based on the moisture content of the finished product includes:

[0140] Freeze-dry the cooled rice to generate dried rice, and detect the moisture content of the finished product of the dried rice;

[0141] Compare the moisture content of the finished product with the preset moisture content of the finished product, and increase or decrease the drying time according to the comparison result;

[0142] Send a drying alarm signal in the state of determining to increase the drying time;

[0143] If the moisture content of the finished product is greater than or equal to the preset moisture content of the finished product, it is determined to increase the drying time and send a drying alarm signal;

[0144] If the moisture content of the finished product is less than the preset moisture content of the finished product, it is determined to reduce the drying time;

[0145] In a specific embodiment, the preset moisture content of the finished product is set to 8%. If the moisture content of the finished product is 14% which is greater than the preset moisture content of the finished product, it is determined to increase the drying time and send a drying alarm signal;

[0146] If the moisture content of the finished product is 5% which is less than the preset moisture content of the finished product, it is determined to reduce the drying time;

[0147] The preset moisture content of the finished product is negatively correlated with the shelf life of the finished instant rice.

[0148] It can be understood that the longer the shelf life of the finished instant rice, the lower its moisture content of the finished product. Therefore, the preset moisture content of the finished product is negatively correlated with the shelf life of the finished instant rice.

[0149] Optionally, the shelf life of the finished instant rice is 180 days, and the preset moisture content of the finished product is 5%;

[0150] The shelf life of the finished instant rice is 120 days, and the preset moisture content of the finished product is 8%;

[0151] The shelf life of the finished instant rice is 900 days, and the preset moisture content of the finished product is 10%.

[0152] Specifically, in the step S6, the process of rehydration detection of the dried rice and adjusting the cooling temperature based on the detection results includes:

[0153] Lay the dried rice flat in the pigment water for rehydration detection;

[0154] Press the dried rice that has completed the rehydration detection, and based on machine vision, count the white core area to generate the occupancy rate of the white core area;

[0155] It can be understood that the occupancy rate of the white core area = white core area / total image area x 100%.

[0156] Compare the occupancy rate of the white core area with the preset occupancy rate, and determine whether to increase the cooling temperature according to the comparison result;

[0157] Send a temperature alarm signal in the state of determining to increase the cooling temperature;

[0158] If the occupancy rate of the white core area is greater than or equal to the preset occupancy rate, it is determined to increase the cooling temperature and send a temperature alarm signal;

[0159] If the occupancy rate of the white core area is less than the preset occupancy rate, it is determined that the cooling temperature remains unchanged;

[0160] In a specific embodiment, the preset occupancy rate is set to 10%. If the occupancy rate of the white core area is 24% which is greater than the preset occupancy rate, it is determined to increase the cooling temperature and send a temperature alarm signal;

[0161] If the occupancy rate of the white core area is 8% which is less than the preset occupancy rate, it is determined that the cooling temperature remains unchanged;

[0162] The preset occupancy rate is positively correlated with the weight of the dried rice.

[0163] It can be understood that the greater the weight of the dried rice, the more rice that generates white cores during rehydration detection, and the greater the probability of generating white cores. Therefore, the preset occupancy rate is positively correlated with the weight of the dried rice.

[0164] Optionally, the weight of the dried rice is 100 grams, and the preset occupancy rate is 5%;

[0165] The weight of the dried rice is 200 grams, and the preset occupancy rate is 8%;

[0166] The weight of the dried rice is 300 grams, and the preset occupancy rate is 10%;

[0167] Specifically, the present invention stirs the cooked and cooled rice, detects whether the cooled rice is stirred qualified based on machine vision, detects the moisture content of the dried rice, and conducts rehydration detection on the dried rice. The paddle type or screw ribbon type stirring device is used to break up and mix the cooked and cooled rice grains evenly to avoid caking. The machine vision system can evaluate the state of the rice after stirring with extremely high precision and repeatability. It can quickly identify whether the rice grains are evenly distributed. If the stirring is unqualified, there may be local accumulation or separation of the rice grains. Through visual detection, it can ensure that the quality of each batch of rice in the stirring link after cooling is consistent, avoiding quality fluctuations caused by subjective differences in human judgment. Moreover, the machine vision detection is fast and can detect a large amount of rice in a short time. The rehydration detection can intuitively reflect whether the rice is damaged during the drying process. The rehydration detection can simulate the use process of instant rice, and through the rehydration detection, it can be judged whether the processing quality of the rice meets the requirements, further improving the accuracy of the rice processing monitoring and warning system.

[0168] Please refer to Figure 4 As shown, it is a schematic structural diagram of the rice processing monitoring and warning system according to the embodiment of the present invention. The present invention also provides a rice processing monitoring and warning system, including:

[0169] A screening unit, which is used to screen the rice and divide the rice into heavy rice, light rice and broken rice based on the air flow rate of the pneumatic screening device adjusted by machine vision;

[0170] A starch detection unit, which is connected to the screening unit and is used to respectively select heavy rice and light rice with different weights and grind them into heavy rice powder and light rice powder, and calculate the amylose content of a number of heavy rice and a number of light rice respectively based on the near-infrared spectroscopy device to construct an amylose content model;

[0171] A distribution unit, which is connected to the starch detection unit and is used to determine the content ratio of heavy rice and light rice based on the amylose content model and the preset amylose content;

[0172] An immersion unit, which is connected to the distribution unit and is used to form several portions of soaked rice according to the content ratio, construct a microwave sensor, establish a regression equation between the initial moisture content and the microwave parameters, collect microwave signals by compacting the soaked rice at a preset cycle time, and output the soaked rice with qualified initial moisture content in combination with the regression equation between the initial moisture content and the microwave parameters;

[0173] A cooling unit, which is connected to the immersion unit and is used to cook and cool the soaked rice, and stir the cooled rice, and detect whether the cooled rice is stirred qualified based on machine vision;

[0174] A finished product unit, which is connected to a cooling unit, is used to freeze-dry the cooled rice to produce dried rice, detect the moisture content of the finished dried rice, adjust the drying time based on the moisture content of the finished product, and perform rehydration detection on the dried rice, and adjust the cooling temperature based on the detection result;

[0175] An alarm unit, which is respectively connected to the cooling unit and the finished product unit, is used to send out a stirring alarm signal in the state of determining that the stirring is unqualified, send out a drying alarm signal in the state of determining that the drying time needs to be increased, and send out a temperature alarm signal in the state of determining that the cooling temperature needs to be increased.

[0176] Specifically, the screening unit includes:

[0177] A conveyor belt, which is used to convey rice;

[0178] A pneumatic screening device, which is connected to the conveyor belt, is used to screen rice by spraying air;

[0179] A photographing device, which is connected to the pneumatic screening device, is used to collect images of the rice in the dropping area.

[0180] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0181] The above are only the preferred embodiments of the present invention and are not used to limit the present invention; for those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A rice processing monitoring and early warning method based on multi-dimensional data analysis, characterized in that Including: Convey the rice to a pneumatic screening device via a conveyor belt for screening, and based on machine vision, adjust the air flow rate of the pneumatic screening device to divide the rice into heavy rice, light rice and broken rice; Select the heavy rice and the light rice with different weights respectively and grind them into heavy rice powder and light rice powder, and calculate a number of amylose contents of the heavy rice and a number of amylose contents of the light rice respectively based on a near-infrared spectroscopy device to construct an amylose content model; Determine the content ratio of the heavy rice and the light rice based on the amylose content model and a preset amylose content; Compose several portions of soaked rice according to the content ratio, construct a microwave sensor, establish a regression equation between the initial moisture content and microwave parameters, select the soaked rice at a preset cycle time for compaction to collect microwave signals, and output the soaked rice with qualified initial moisture content in combination with the regression equation between the initial moisture content and microwave parameters; Cook and cool the soaked rice, and stir and cool the rice. Based on machine vision, detect whether the cooled rice is stirred qualified, and send a stirring alarm signal in the state of determining that the stirring is unqualified; Freeze-dry the cooled rice to generate dried rice, detect the finished product moisture content of the dried rice, adjust the drying time based on the finished product moisture content or send a drying alarm signal, and perform rehydration detection on the dried rice, and determine whether to increase the cooling temperature and send a temperature alarm signal based on the detection result.

2. The rice processing monitoring and early warning method based on multi-dimensional data analysis according to claim 1, wherein The process of dividing the rice into heavy rice, light rice and broken rice includes: Lay the rice flat on the conveyor belt; The pneumatic screening device blows the rice falling from the conveyor belt horizontally to a falling area; Adjust the air flow rate based on the rice form in the falling area photographed by machine vision to divide the rice into the heavy rice, the light rice and the broken rice.

3. The rice processing monitoring and early warning method based on multi-dimensional data analysis according to claim 2, wherein The process of constructing an amylose content model based on a number of the amylose contents of the heavy rice and a number of the amylose contents of the light rice includes: Select the heavy rice and the light rice with different weights respectively and grind them into heavy rice powder and light rice powder, and grind the powder that cannot pass through the sieve in the ground powder to reduce the powder particle size; Collect a heavy rice spectrogram and a light rice spectrogram in combination with a near-infrared spectroscopy device and calculate a number of amylose contents of the heavy rice and a number of amylose contents of the light rice respectively; Construct an amylose content model of heavy rice and light rice with different weights in combination with a number of the amylose contents of the heavy rice and a number of the amylose contents of the light rice.

4. The rice processing monitoring and early warning method based on multi-dimensional data analysis according to claim 3, characterized in that, The process of determining the content ratio of the heavy rice and the light rice based on the amylose content model and a preset amylose content includes: Establish a mixture amylose content equation based on the amylose content model; Calculate and generate the content ratio in combination with the preset amylose content and the mixture amylose content equation; The preset amylose content is negatively correlated with the shelf life of the finished instant rice.

5. The rice processing monitoring and early warning method based on multi-dimensional data analysis according to claim 4, characterized in that The process of constructing the microwave sensor, establishing the regression equation between the initial moisture content and microwave parameters, selecting the soaked rice for compaction to collect the microwave and outputting the soaked rice with qualified initial moisture content includes: Soak several portions of rice according to the described content ratio, select soaked rice of different weights, and calculate several standard moisture contents through the direct drying method; Based on the microwave sensor and several of the standard moisture contents, establish a regression equation between the initial moisture content and microwave parameters; Select the soaked rice at preset cycle times, compact it, collect the microwave signals, and generate microwave parameter values; Substitute the microwave parameter values into the regression equation between the initial moisture content and microwave parameters to calculate the initial moisture contents of several portions of the soaked rice; Compare the initial moisture content with a preset moisture content, and determine whether the soaked rice corresponding to the initial moisture content is qualified according to the comparison result; The preset cycle time is positively correlated with the rice soaking time, and the preset moisture content is negatively correlated with the shelf life of the finished instant rice; 6. The rice processing monitoring and early warning method based on multi-dimensional data analysis according to claim 5, characterized in that The process of detecting whether the cooled rice is stirred evenly based on machine vision includes: Cook and cool the soaked rice to generate the cooled rice; Collect the original image of the cooled rice after stirring is completed, and generate a caking rate based on the area of the caked rice in the original image; Compare the caking rate with a preset caking rate, and determine whether the cooled rice is stirred evenly according to the comparison result; Send out the stirring alarm signal in the state where it is determined that the stirring is unqualified; The preset caking rate is positively correlated with the weight of the cooled rice; 7. The rice processing monitoring and early warning method based on multi-dimensional data analysis according to claim 6, characterized in that, The process of adjusting the drying time based on the finished product moisture content includes: Freeze-dry the cooled rice to generate the dried rice, and detect the finished product moisture content of the dried rice; Compare the finished product moisture content with a preset finished product moisture content, and increase or decrease the drying time according to the comparison result; Send out the drying alarm signal in the state where it is determined to increase the drying time; The preset finished product moisture content is negatively correlated with the shelf life of the finished instant rice; 8. The method for monitoring and warning rice processing based on multi-dimensional data analysis according to claim 7, wherein, The process of rehydration detection of the dried rice and adjusting the cooling temperature based on the detection result includes: Lay the dried rice flat in pigment water for rehydration detection; Press the dried rice after the rehydration detection is completed, and based on machine vision, count the white core area to generate the white core area occupancy rate; Compare the white core area occupancy rate with a preset area occupancy rate, and determine whether to increase the cooling temperature according to the comparison result; Send out the temperature alarm signal in the state where it is determined to increase the cooling temperature; The preset area occupancy rate is positively correlated with the weight of the dried rice; 9. A rice processing monitoring and early warning system applying the rice processing monitoring and early warning method based on multi-dimensional data analysis according to any one of claims 1-8, characterized in that, Includes: A screening unit for screening rice, and based on machine vision, adjusting the air flow rate of the pneumatic screening device to classify the rice into heavy rice, light rice, and broken rice; A starch detection unit connected to the screening unit, which is used to separately select heavy rice and light rice of different weights, crush them into heavy rice powder and light rice powder, and calculate several heavy rice amylose contents and several light rice amylose contents based on the near-infrared spectroscopy device to construct an amylose content model; A distribution unit connected to the starch detection unit, which is used to determine the content ratio of the heavy rice and the light rice based on the amylose content model and a preset amylose content; Soaking unit, which is connected to the dispensing unit, is used to form several portions of soaked rice according to the content ratio, construct a microwave sensor, establish a regression equation between the initial moisture content and microwave parameters, select the soaked rice at a preset cycle time for compaction to collect microwave signals, and output the soaked rice with qualified initial moisture content in combination with the regression equation between the initial moisture content and microwave parameters; Cooling unit, which is connected to the soaking unit, is used to steam and cool the soaked rice, and stir the cooled rice, and detect whether the cooled rice is stirred qualified based on machine vision; Finished product unit, which is connected to the cooling unit, is used to freeze-dry the cooled rice to generate dried rice, detect the moisture content of the finished dried rice, adjust the drying time based on the moisture content of the finished product, and perform rehydration detection on the dried rice, and adjust the cooling temperature based on the detection result; Alarm unit, which is respectively connected to the cooling unit and the finished product unit, is used to emit a stirring alarm signal in the state of determining unqualified stirring, emit a drying alarm signal in the state of determining to increase the drying time, and emit a temperature alarm signal in the state of determining to increase the cooling temperature.

10. The rice processing monitoring and early warning system according to claim 9, characterized in that, The screening unit includes: Conveyor belt, which is used to convey rice; Pneumatic screening device, which is connected to the conveyor belt, is used to screen rice by jetting air; Imaging device, which is connected to the pneumatic screening device, is used to collect images of rice in the dropping area.

Images