A small corn drying equipment with intelligent temperature control system

Abstract

The present invention relates to the field of energy-saving drying equipment control, and more specifically, to a small corn drying equipment with an intelligent temperature control system. The system comprises: a small corn drying equipment body, a corn drying temperature analysis module, the corn drying temperature analysis module being mounted on the small corn drying equipment body, the corn drying temperature analysis module comprising a data acquisition module, a computing chip, and a corn drying temperature control module; the corn drying temperature control module being used to control the temperature and heat received by corn in the small corn drying equipment; the data acquisition module being used to collect drying temperature data sequences from different detection points on the top of the drying chamber; and the computing chip being used to determine an intelligent speed adjustment coefficient based on the position distribution of the drying temperature data sequences and the characteristics of hot air flow, and output control instructions. The present invention reduces heat waste during corn drying and makes the heat generated by the temperature during corn drying more intelligent.

Description

Technical Field

[0001] The present invention relates to the field of energy-saving drying equipment control, and in particular to small-sized corn drying equipment with an intelligent temperature control system. Background Art

[0002] With the deepening modernization of agriculture, agricultural labor relations and labor entities are changing. The emergence of new agricultural operators has enabled centralized land management, leading to a significant concentration of grain production capacity. Corn, as a staple grain, is widely grown due to its relatively flexible growing conditions. However, relatively outdated grain warehouses and inefficient grain storage methods no longer meet current corn storage requirements. Newly harvested corn must be dried to a safe moisture content before long-term storage. Currently available drying equipment is large and sparsely distributed, making it suitable for large agricultural enterprises. However, for farmers and some small and medium-sized cooperatives, the drying equipment generally needs to be transported to a designated location, but the time cost of transportation is too high, resulting in farmers and some small and medium-sized cooperatives being unable to effectively dry their newly harvested corn in a timely manner.

[0003] Existing corn drying equipment is usually a device that uses hot air to flow and dry the moisture of the corn. In the actual corn drying process, the equipment needs to be started first for a certain period of preheating, and then the newly harvested corn is put into the drying equipment. When the corn is transported in the drying equipment, it will form different degrees of accumulation. As the corn moves in the drying equipment, the hot air flow at different positions inside the drying equipment will be different, resulting in different drying temperatures at different positions. This may cause the corn to become burnt or have a high moisture content, reducing the effective utilization rate of the energy of the drying equipment and reducing the drying efficiency of the corn. Summary of the Invention

[0004] The present invention provides a small-scale corn drying equipment with an intelligent temperature control system to solve the existing problem that corn will form different degrees of accumulation when being transported in the drying equipment. As the corn moves in the drying equipment, the hot air flow at different positions inside the drying equipment will be different, resulting in different drying temperatures at different positions, which may cause the corn to become burnt or have a high moisture content.

[0005] The purpose of the present invention is to provide a small corn drying equipment with an intelligent temperature control system. The technical solutions adopted are as follows:

[0006] A small corn drying device with an intelligent temperature control system includes a small corn drying device body, the small corn drying device body includes a corn drying temperature analysis module, the corn drying temperature analysis module is installed on the small corn drying device body, the corn drying temperature analysis module includes a data acquisition module, a computing chip and a corn drying temperature control module;

[0007] The data acquisition module is connected to the signal input end of the computing chip, and the signal output end of the computing chip is connected to the corn drying temperature control module. The corn drying temperature control module is used to control the temperature and heat received by the corn in the small corn drying equipment; the data acquisition module is used to collect the drying temperature data sequence of the detection points at the top of different drying chambers and transmit it to the computing chip;

[0008] Within the drying temperature data sequence of any drying chamber top detection point, analyze the temperature difference between the hot air in the drying chamber and the drying chamber top. Use the proportional relationship between the extreme fluctuations in different local data within the drying temperature data sequence as the continuous stability of the drying environment at the drying chamber top detection point. Analyze the magnitude of the extreme temperature changes at the latest moment within the drying temperature data sequence, and combine the value obtained after the continuous stability of the drying environment to determine the completion degree of the chamber preheating at the drying chamber top detection point.

[0009] The temperature variation range within the drying temperature data sequence is analyzed and used as the corn drying suitability of the detection point at the top of the drying chamber. Based on the corn drying suitability and the completion degree of preheating in the chamber, the corn moisture evaporation efficiency of the detection point at the top of the drying chamber in the corresponding drying chamber is analyzed, and the proportional relationship between the corn drying suitability and the completion degree of preheating in the chamber is used as the corn control weight of the detection point at the top of the drying chamber. Based on the distribution distance of different detection points at the top of the drying chamber in the corresponding drying chamber, the corn control weight is fitted and corrected to the value, which is used as the actual control weight of the corn at the detection point at the top of the drying chamber. Based on the actual control weight of the corn, the distance from the detection point at the top of the drying chamber to the end of the drying chamber is comprehensively analyzed to obtain the intelligent speed adjustment coefficient of the drying roller.

[0010] Output control instructions based on the intelligent speed adjustment coefficient to control the rotation speed of the drying roller and perform intelligent temperature control.

[0011] Preferably, the method for obtaining the continuous stability of the drying environment is:

[0012] The heat wave temperature fluctuation period at the top detection point of the drying chamber is obtained based on the extreme value distribution relationship within the drying temperature data sequence. The proportional relationship between the chamber temperature stability and the heat wave temperature fluctuation period is used as the continuous stability of the drying environment at the top detection point of the drying chamber.

[0013] Preferably, the method for obtaining the heat wave temperature fluctuation period is:

[0014] The average distribution interval between adjacent maximum values ​​in the comprehensive drying temperature data sequence is used as the heat wave temperature fluctuation period of the detection point on the top of the drying chamber.

[0015] Preferably, the method for obtaining the cavity temperature stability is:

[0016] In the drying temperature data sequence, the average temperature difference between different minimum values ​​within the preset minimum value range is integrated to obtain the cavity temperature stability of the detection point at the top of the drying cavity.

[0017] Preferably, the method for obtaining the intracavity preheating completion degree is:

[0018] According to the drying temperature data sequence, the heat wave cavity temperature similarity of the detection point at the top of the drying cavity is obtained; the product of the continuous stability of the drying environment and the heat wave cavity temperature similarity is used as the cavity preheating completion degree of the detection point at the top of the drying cavity.

[0019] Preferably, the method for obtaining the heat wave cavity temperature similarity is:

[0020] The minimum and maximum values ​​under the latest conditions in the drying temperature data sequence are obtained, and the inverse proportional value of the temperature difference between the minimum and maximum values ​​under the latest conditions is used as the heat wave cavity temperature similarity of the detection point at the top of the drying cavity.

[0021] Preferably, the method for obtaining the corn drying suitability is:

[0022] Obtain the median temperature in the cavity; use the mean of the extreme values ​​in the drying temperature data sequence of the detection point at the top of the drying cavity as the mean of the overall ambient temperature in the cavity at the detection point at the top of the drying cavity; and use the proportional relationship between the mean of the overall ambient temperature in the cavity and the median temperature in the cavity as the corn drying suitability at the detection point at the top of the drying cavity.

[0023] Preferably, the method for obtaining the corn regulation weight is:

[0024] The ratio between the corn drying suitability and the completion of the preheating in the drying chamber is used as the corn control weight at the top detection point of the drying chamber.

[0025] Preferably, the method for obtaining the actual control weight of corn is:

[0026] The horizontal distribution line of different drying chamber top detection points in the drying chamber is used as the two-dimensional horizontal axis reference baseline; the horizontal line after the two-dimensional horizontal axis reference baseline is proportionally shrunk is used as the two-dimensional horizontal axis, and the actual control weight of corn is used as the two-dimensional vertical coordinate; a two-dimensional spatial coordinate system is constructed according to the two-dimensional horizontal axis and the two-dimensional vertical coordinate, and the actual control weight of corn is curve fitted, and the value after fitting the actual control weight of corn is used as the actual control weight of corn.

[0027] Preferably, the method for obtaining the intelligent speed adjustment coefficient is:

[0028] The distance from the top detection point of the drying chamber to the end of the drying chamber is used as the cavity detection point extension distance of the drying chamber top detection point; the proportional relationship between the actual control weight of the corn and the cavity detection point extension distance is used as the corn transmission speed adjustment coefficient of the drying chamber top detection point; the accumulated result of the corn transmission speed adjustment coefficients of all the drying chamber top detection points is used as the intelligent speed adjustment coefficient of the drying roller.

[0029] The beneficial effects of the technical solution of the present invention are as follows: by analyzing the temperature difference between the hot air in the drying chamber and the top of the drying chamber, and combining the analysis of the extreme temperature change at the latest moment in the drying temperature data sequence, the cavity preheating completion degree of the top detection point of the drying chamber is obtained; wherein the cavity preheating completion degree is used to describe the degree to which the corn is affected by the preheating effect when it stays in the area below the position of different drying chamber top detection points, and quantifies the drying effect of the corn when it is transferred to the area below different drying chamber top detection points in the drying chamber; then, the temperature change range in the drying temperature data sequence is analyzed, and combined with the cavity preheating completion degree, the influence of the preheating completion degree on the corn in the drying chamber to which the top detection point of the drying chamber belongs is analyzed. The method can obtain the corn control weight of the detection point on the top of the drying chamber by analyzing the distance from different detection points on the top of the drying chamber to the end of the drying chamber, and obtain the intelligent speed adjustment coefficient of the drying roller; the method analyzes the response of different detection points on the top of the drying chamber to the hot air inside the cavity, further analyzes the drying intensity of the corn itself when it passes through different detection points on the top of the drying chamber and approaches the end of the drying chamber, obtains the intelligent speed adjustment coefficient of the drying roller, and intelligently controls the temperature and heat received by the corn; the method reduces the difficulty of transportation of the drying equipment, reduces the heat waste when drying corn, makes the heat generated by the temperature during drying more intelligent, and improves the drying efficiency of the corn. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0031] Figure 1 This is a structural schematic diagram of a small corn drying device with an intelligent temperature control system according to the present invention;

[0032] Figure 2 This is a schematic diagram of the flow of processing of a drying temperature data sequence by a computing chip in a small-sized corn drying device with an intelligent temperature control system according to the present invention;

[0033] Figure 3 A schematic diagram of the rotation cross section of the drying roller of the present invention;

[0034] Figure 4 Schematic diagram of the two-dimensional space coordinate system of the drying chamber of the present invention.

[0035] Figure 1 The numbers in the figure are: 1. servo motor; 2. feed motor; 3. feed chute; 4. conveyor belt; 5. drive shaft; 6. belt; 7. temperature sensor; 8. mesh grille; 9. drying roller; 10. air hole; 11. blower; 12. discharge port; 13. air pipe; 14. drying chamber; 15. spiral fan; 16. guide groove; 17. gas diversion pipe; 18. power supply. DETAILED DESCRIPTION

[0036] To further illustrate the technical means and effectiveness of the present invention in achieving its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a small-scale corn drying device with an intelligent temperature control system according to the present invention. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0037] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0038] This embodiment provides a small-scale corn drying device with an intelligent temperature control system. The device includes a main body and a corn drying temperature analysis module mounted thereon. The module evaluates the drying roller speed based on the position distribution of drying temperature data and the characteristics of hot air flow, thereby determining the optimal drying roller speed. The module comprises a data acquisition module, a computing chip, and a corn drying temperature control module. The data acquisition module is connected to the computing chip, which is a field-programmable gate array (FPGA) chip used for data processing and machine control. The chip receives information from the data acquisition module and sends control instructions to the corn drying temperature control module.

[0039] The specific solution of a small corn drying device with an intelligent temperature control system provided by the present invention is described in detail below with reference to the accompanying drawings.

[0040] See also Figure 1The diagram shows the structure of a small-sized corn drying device with an intelligent temperature control system according to one embodiment of the present invention. The small-sized corn drying device includes a servo motor 1; a feed motor 2; a feed trough 3; a conveyor belt 4; a drive shaft 5; a belt 6; a temperature sensor 7; a mesh grille 8; a drying roller 9; air holes 10; a blower 11; a discharge port 12; an air pipe 13; a drying chamber 14; a spiral fan 15; a guide trough 16; a gas diversion pipe 17; and a power supply 18. The feed trough 3 and the conveyor belt 4 form a conveying mechanism for corn. Corn is poured into the feed trough 3. The feed motor 2 generates constant power, causing the conveyor belt 4 to transport the corn into the drying chamber 14. The guide trough 16 transports the corn from the upper layer to the lower layer, and the corn is discharged through the discharge port 12. The top of the drying chamber 14 is openable and closable. The interior of the drying roller 9 is hollow, allowing the hot air generated by the external combustion of straw, generated by the blower 11, to be introduced into the drying roller 9 through the air pipe 13 and into the drying chamber 14 through the air holes 10. The corn enters the mesh grille 8 via the conveyor belt 4. The drying roller 9 rotates, and the spiral fan 15 drives the corn to tumble. The small diameter of the mesh grille 8 ensures that the corn does not clog the mesh and ensures the flow of hot air within the chamber. Temperature sensors 7 are installed at regular intervals on the top of the drying chamber 14.

[0041] The data acquisition module of this embodiment includes a temperature sensor 7; the temperature sensor is used to measure the drying temperature data of the detection point at the top of the drying chamber. The drying temperature data of the detection point at the top of the drying chamber can be measured to help determine the intelligent speed adjustment coefficient.

[0042] In this embodiment, the corn drying temperature control module includes a drying roller 10, which is used to receive control instructions from the computing chip and control the rotation speed of the drying roller. When the corn drying temperature control module receives the control instructions, it drives the drying roller 10 to rotate to the optimal rotation speed.

[0043] The data acquisition module is connected to the signal input end of the computing chip, and the signal output end of the computing chip is connected to the corn drying temperature control module. The corn drying temperature control module is used to control the rotation speed of the drying roller; the data acquisition module is used to collect the drying temperature data sequence of different detection points on the top of the drying chamber and transmit it to the computing chip.

[0044] In this embodiment, the time interval and the total collection time can be preset, and the drying temperature data sequence of different detection points on the top of the drying chamber can be obtained. As a specific example, the blower and the drying roller are first started to adjust the drying chamber temperature to the preset temperature range. After that, start preheating the drying chamber and adjust the drying roller to the preset speed. , during the preheating preset time After that, pour the newly harvested corn into the feed trough; start to collect the temperature data of each detection point on the top of the drying chamber as the drying temperature data every 2 seconds, and collect the data for 1 hour; obtain all the drying temperature data of each detection point on the top of the drying chamber; and use the sequence formed by all the drying temperature data of each detection point on the top of the drying chamber as the drying temperature data sequence of each detection point on the top of the drying chamber. This example is described as an example, and this embodiment is not specifically limited. It may depend on the specific implementation situation.

[0045] For further information, see Figure 2 , which shows a schematic diagram of a flow chart of processing a drying temperature data sequence by a computing chip in a small corn drying device with an intelligent temperature control system provided by one embodiment of the present invention, including the following steps:

[0046] Step S001: In the drying temperature data sequence of any drying chamber top detection point, analyze the temperature difference between the hot air in the drying chamber and the drying chamber top, and use the proportional relationship between the extreme fluctuations of different local data in the drying temperature data sequence as the continuous stability of the drying environment at the drying chamber top detection point; analyze the extreme temperature changes at the latest moment in the drying temperature data sequence, and combine the value after the continuous stability of the drying environment as the completion degree of the chamber preheating at the drying chamber top detection point.

[0047] It should be noted that, starting from the preheating of the drying chamber, after the blower starts working, the flowing air generated by the blower will flow along the hollow drying roller and flow outward through the air holes at various positions; but since the power of the blower is constant, the flowing air generated increases with the flow distance and the outward divergence of the air holes, resulting in the flowing air still in the drying roller moving forward at a slower speed; at this time, under the operation of the blower, the temperature of the surrounding air rises. During the preheating process, the flowing air discharged from different air holes has different initial speeds leaving the air holes based on the above logic, and the high-temperature heat wave generated by the air flow reaches the detection point at the top of the drying chamber at different times. At this time, there will be certain errors in the temperature data monitored at different detection points at the top of the drying chamber.

[0048] It should be further explained that, affected by the rotation of the drying roller, the temperature data collected by all the detection points on the top of the drying chamber will fluctuate periodically. However, since the initial speeds of the heat waves formed by the hot air flow are different during the flow process, and the speed attenuation coefficients of all the heat waves in the chamber are the same, the fluctuation periods of the temperature data collected by different detection points on the top of the drying chamber are different. Therefore, within the drying temperature data sequence of any detection point on the top of the drying chamber, the temperature difference between the hot air in the drying chamber and the top of the drying chamber can be analyzed, and the proportional relationship between the extreme fluctuations of different local data in the drying temperature data sequence can be used as the continuous stability of the drying environment at the detection point on the top of the drying chamber. The extreme temperature changes at the latest moment in the drying temperature data sequence can be analyzed, and the value after the continuous stability of the drying environment can be used as the completion degree of the cavity preheating at the detection point on the top of the drying chamber. Please refer to Figure 3 , which shows a schematic diagram of the cross-section rotation of the drying roller.

[0049] Preferably, in some implementations of the present invention, the method for obtaining the continuous stability of the drying environment is as follows: based on the extreme value distribution relationship within the drying temperature data sequence of the drying chamber top detection point, the heat wave temperature fluctuation period of the drying chamber top detection point is obtained; and the proportional relationship between the chamber temperature stability and the heat wave temperature fluctuation period is used as the continuous stability of the drying environment at the drying chamber top detection point. The specific process is as follows:

[0050] It's important to note that during the preheating process, the temperature inside the drying chamber gradually approaches the ideal temperature for corn drying. The difference between the generated heat wave and the chamber temperature at the current sensing point at the top of the drying chamber gradually decreases. In the temperature curve, the maximum point is the temperature measured when the heat wave arrives, and the minimum point is the chamber temperature at the sensor's location.

[0051] Preferably, in some implementations of the present invention, the heat wave temperature fluctuation period is obtained by calculating the average distribution interval between adjacent maximum values ​​in the drying temperature data sequence as the heat wave temperature fluctuation period at the detection point at the top of the drying chamber. The specific process is as follows:

[0052] Taking the drying temperature data sequence of any detection point on the top of the drying chamber as an example, the number of data intervals between any two adjacent maximum values ​​in the drying temperature data sequence is used as the distribution interval between the two maximum values; the distribution intervals between all maximum values ​​in the drying temperature data sequence are obtained; and the mean of the distribution intervals between all maximum values ​​in the drying temperature data sequence is used as the heat wave temperature fluctuation period of the detection point on the top of the drying chamber.

[0053] Preferably, in some implementations of the embodiments of the present invention, the method for obtaining the cavity temperature stability is: in the drying temperature data sequence, the average temperature difference between different minimum values ​​within the preset minimum value range is comprehensively calculated to obtain the cavity temperature stability of the detection point at the top of the drying cavity.

[0054] Preset a minimum number , the last minimum value in the drying temperature data sequence is taken as the target real-time minimum value, and the value before the target real-time minimum value is taken as The data segment consisting of the minimum value and the target real-time minimum value is used as the cavity temperature data segment of the target real-time minimum value; in the cavity temperature data segment of the target real-time minimum value, the absolute value of the difference between any two adjacent minimum values ​​is used as the temperature difference value between any two adjacent minimum values; the temperature difference value between all adjacent minimum values ​​in the cavity temperature data segment of the target real-time minimum value is obtained; the average of the temperature difference values ​​between all adjacent minimum values ​​is used as the cavity temperature stability of the detection point at the top of the drying chamber. This example is described as an example, and this embodiment is not specifically limited. It may depend on the specific implementation situation.

[0055] It is particularly noted that the cavity temperature data segment of the target real-time minimum value only contains the minimum value in the drying temperature data sequence; and if the number of minimum values ​​actually existing before the target real-time minimum value does not meet , then the cavity temperature data segment of the target real-time minimum value is obtained based on the actual number of minimum values.

[0056] Furthermore, the ratio of the cavity temperature stability to the heat wave temperature fluctuation period is used as the continuous stability of the drying environment at the top detection point of the drying cavity.

[0057] It should be noted that if the drying environment is more stable, the temperature change at the detection point on the top of the drying chamber will be less drastic, and the overall continuous effect will be longer-lasting, which means that the temperature at the detection point on the top of the drying chamber can reach a temperature suitable for drying newly harvested corn.

[0058] Preferably, in some implementations of the present invention, the method for obtaining the cavity preheating completion degree is as follows: based on the drying temperature data sequence, obtain the heat wave cavity temperature similarity of the detection point at the top of the drying cavity; and multiply the drying environment continuous stability and the heat wave cavity temperature similarity as the cavity preheating completion degree of the detection point at the top of the drying cavity. The specific process is as follows:

[0059] Preferably, in some implementations of the present invention, the method for obtaining the heat wave cavity temperature similarity is to obtain the minimum and maximum values ​​under the latest conditions in the drying temperature data sequence, and use the inverse proportional value of the temperature difference between the minimum and maximum values ​​under the latest conditions as the heat wave cavity temperature similarity of the detection point at the top of the drying cavity. The specific process is as follows:

[0060] The last maximum value in the drying temperature data sequence is taken as the target real-time maximum value; the inversely proportional normalized value of the absolute value of the difference between the target real-time minimum value and the target real-time maximum value is taken as the heat wave cavity temperature similarity of the detection point at the top of the drying cavity.

[0061] It is particularly noted that the embodiment adopts Model to present inverse proportional relationship and normalization processing, As the input of the model, the implementer can choose the inverse proportional function and normalization function according to the actual situation.

[0062] Furthermore, the product of the drying environment continuity stability at the drying chamber top detection point and the heat wave chamber temperature proximity is used as the cavity preheating completion degree at the drying chamber top detection point. The cavity preheating completion degree of each drying chamber top detection point is obtained.

[0063] It should be noted that the greater the degree of preheating completion in the drying chamber, the better the moisture drying effect of the corn when it stays in the area below the detection point at the top of the drying chamber, which reflects the better preheating effect in the drying chamber.

[0064] At this point, the cavity preheating completion degree at each drying cavity top detection point is obtained through the above method.

[0065] Step S002: Analyze the temperature variation range within the drying temperature data sequence and use it as the corn drying suitability of the detection point at the top of the drying chamber; analyze the corn moisture evaporation efficiency of the detection point at the top of the drying chamber in the drying chamber to which it belongs based on the corn drying suitability and the completion degree of preheating in the chamber, and use the proportional relationship between the corn drying suitability and the completion degree of preheating in the chamber as the corn control weight of the detection point at the top of the drying chamber; according to the distribution distance of different detection points at the top of the drying chamber in the drying chamber to which they belong, fit the corn control weight to the corrected value and use it as the actual control weight of the corn at the detection point at the top of the drying chamber; based on the actual control weight of the corn, comprehensively analyze the distance from the detection point at the top of the drying chamber to the end of the drying chamber to obtain the intelligent speed adjustment coefficient of the drying roller.

[0066] It should be noted that the completion degree of preheating in the drying chamber mainly describes the degree of preheating in the drying chamber, and reflects the evaporation efficiency of the moisture in the corn after being preheated in the drying chamber during the drying operation; and before the corn is conveyed out of the drying chamber, it will continue to receive high-temperature drying in the drying chamber. When the corn enters the drying chamber from the feed trough for drying, the drying roller with its spiral fan surface rotates, and the corn will be continuously pushed forward. When passing through the area below the detection point at the top of the drying chamber, the local drying temperature may be different, but the overall moisture will continue to evaporate. Therefore, in order to ensure that the corn is not over-dried or has a high moisture content after leaving the drying chamber, it is necessary to analyze the drying temperature data series. The temperature change range in the drying chamber is used as the corn drying suitability of the detection point on the top of the drying chamber; according to the corn drying suitability and the completion degree of preheating in the chamber, the corn water evaporation efficiency of the detection point on the top of the drying chamber in the drying chamber to which it belongs is analyzed, and the proportional relationship between the corn drying suitability and the completion degree of preheating in the chamber is used as the corn control weight of the detection point on the top of the drying chamber; according to the distribution distance of different detection points on the top of the drying chamber in the drying chamber to which they belong, the corn control weight is fitted and corrected to the value, which is used as the real control weight of the corn at the detection point on the top of the drying chamber; according to the real control weight of the corn, the distance from the detection point on the top of the drying chamber to the end of the drying chamber is comprehensively analyzed to obtain the intelligent speed adjustment coefficient of the drying roller.

[0067] Preferably, in some implementations of the present invention, the method for obtaining corn drying suitability is as follows: obtaining the median temperature in the drying chamber; using the mean of the extreme values ​​in the drying temperature data sequence at the top detection point of the drying chamber as the mean of the overall ambient temperature in the drying chamber at the top detection point; and using the proportional relationship between the mean of the overall ambient temperature in the drying chamber and the median temperature in the drying chamber as the corn drying suitability at the top detection point of the drying chamber. The specific process is as follows:

[0068] Set the preset temperature range The median of the values ​​in the data sequence is used as the median of the temperature inside the drying chamber at each detection point on the top of the drying chamber; taking the drying temperature data sequence of any detection point on the top of the drying chamber as an example, the mean of all extreme values ​​in the drying temperature data sequence is used as the mean of the overall ambient temperature inside the drying chamber at the detection point on the top of the drying chamber; the ratio between the mean of the overall ambient temperature inside the chamber and the median of the temperature inside the chamber is used as the corn drying suitability at the detection point on the top of the drying chamber.

[0069] Preferably, in some implementations of the present invention, the corn control weight is obtained by taking the ratio between the corn drying suitability and the preheating completion degree in the drying chamber as the corn control weight at the top detection point of the drying chamber. The specific process is as follows:

[0070] The ratio of the corn drying suitability to the preheating completion degree in the drying chamber is used as the corn control weight for the top detection point of the drying chamber. The corn control weight for each top detection point of the drying chamber is obtained.

[0071] Preferably, in some implementations of the present invention, the method for obtaining the actual control weight of corn is as follows: the horizontal distribution line of different drying chamber top detection points in the drying chamber is used as the two-dimensional horizontal axis reference baseline; the horizontal line after the two-dimensional horizontal axis reference baseline is proportionally shrunk as the two-dimensional horizontal axis, and the actual control weight of corn is used as the two-dimensional vertical coordinate; a two-dimensional spatial coordinate system is formed based on the two-dimensional horizontal axis and the two-dimensional vertical coordinate, and the actual control weight of corn is curve fitted, and the value after the actual control weight of corn is used as the actual control weight of corn. The specific process is as follows:

[0072] The position distribution line formed by all the detection points on the top of the drying chamber in the horizontal direction in the drying chamber is used as the two-dimensional horizontal axis reference baseline; a scaling ratio is preset , the 2D horizontal axis reference line is The reduced position distribution line is used as the two-dimensional horizontal axis; each drying chamber top detection point on the two-dimensional horizontal axis is used as the horizontal coordinate, and the corn real control weight of each drying chamber top detection point is used as the vertical coordinate. Based on the horizontal and vertical coordinates, a two-dimensional spatial coordinate system of the drying chamber is constructed. A curve fitting is performed on all corn real control weights to obtain a fitting curve; the value of each corn real control weight on the fitting curve is used as the corn real control weight. Figure 4 , which shows a schematic diagram of the two-dimensional space coordinate system of the drying chamber, Figure 4 The black dot in the middle represents the detection point at the top of the drying chamber, and the white dot represents the actual control weight of the corn corresponding to the detection point at the top of the drying chamber. This example is described as an example, and this embodiment is not specifically limited. It can be determined according to the specific implementation situation; in addition, each detection point on the top of the drying chamber corresponds to a real control weight of corn.

[0073] Preferably, in some implementations of the present invention, the method for obtaining the intelligent speed adjustment coefficient is as follows: the distance from the drying chamber top detection point to the drying chamber end is used as the cavity detection point extension distance of the drying chamber top detection point; the proportional relationship between the actual corn control weight and the cavity detection point extension distance is used as the corn conveying speed adjustment coefficient of the drying chamber top detection point; and the cumulative result of the corn conveying speed adjustment coefficients of all the drying chamber top detection points is used as the intelligent speed adjustment coefficient of the drying roller. The specific process is as follows:

[0074] Taking any detection point at the top of the drying chamber as an example, the distance from the detection point at the top of the drying chamber to the end of the drying chamber is used as the cavity detection point extension distance of the detection point at the top of the drying chamber; the normalized value of the ratio of the actual control weight of the corn at the detection point at the top of the drying chamber to the cavity detection point extension distance is used as the corn conveying speed adjustment coefficient of the detection point at the top of the drying chamber; the corn conveying speed adjustment coefficient of each detection point at the top of the drying chamber is obtained; the accumulated value of the corn conveying speed adjustment coefficients of all the detection points at the top of the drying chamber is used as the intelligent speed adjustment coefficient of the drying roller.

[0075] It is particularly noted that in this embodiment, The normalization process is performed by taking the function as an example, wherein the normalization function can be determined according to the specific implementation situation, and will not be described in detail in this embodiment.

[0076] It should be noted that if the intelligent speed adjustment coefficient of the drying roller is larger, it means that the water evaporation efficiency of the corn in the drying chamber is higher, and the corn is more likely to be burnt after drying. This means that the drying roller needs to rotate faster, shorten the corn drying time, and reduce the probability of the corn being burnt after drying.

[0077] At this point, the intelligent speed adjustment coefficient of the drying roller is obtained through the above method.

[0078] Step S003: Outputting a control instruction according to the intelligent speed adjustment coefficient to control the rotation speed of the drying roller and perform intelligent temperature control.

[0079] In a specific implementation of the embodiment of the present invention, the specific process of intelligent temperature control is as follows: the intelligent speed adjustment coefficient of the drying roller is adjusted to the preset speed. Multiply them, and round off the multiplied value to the nearest integer to use as the intelligent control speed of the drying roller.

[0080] Furthermore, the intelligently controlled speed is used as a control instruction to drive the drying roller to rotate to a speed that is the same as the value of the intelligently controlled speed.

[0081] At this point, this embodiment is completed.

[0082] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A small corn drying equipment with an intelligent temperature control system, comprising a small corn drying equipment body, characterized in that: The small corn drying equipment body includes a corn drying temperature analysis module, which is installed on the small corn drying equipment body. The corn drying temperature analysis module includes a data acquisition module, a computing chip and a corn drying temperature control module; The data acquisition module is connected to the signal input end of the computing chip, and the signal output end of the computing chip is connected to the corn drying temperature control module. The corn drying temperature control module is used to control the temperature and heat received by the corn in the small corn drying equipment; the data acquisition module is used to collect the drying temperature data sequence of the detection points at the top of different drying chambers and transmit it to the computing chip; In the drying temperature data sequence of any detection point at the top of the drying chamber, the temperature difference between the hot air in the drying chamber and the top of the drying chamber is analyzed. The proportional relationship between the extreme fluctuations of different local data in the drying temperature data sequence is used as the continuous stability of the drying environment at the detection point at the top of the drying chamber. Analyze the extreme temperature changes at the latest moment in the drying temperature data series, and combine the value after the continuous stability of the drying environment as the preheating completion degree of the drying chamber top detection point; Analyze the temperature variation range within the drying temperature data series and use it as the corn drying suitability test point at the top of the drying chamber; Based on the corn drying suitability and the completion of the cavity preheating, the corn moisture evaporation efficiency at the top detection point of the drying cavity in the drying cavity is analyzed. The proportional relationship between the corn drying suitability and the completion of the cavity preheating is used as the corn control weight of the top detection point of the drying cavity. According to the distribution distance of different drying chamber top detection points in the drying chamber, the corn control weight is fitted and corrected to the value as the actual corn control weight of the drying chamber top detection point; Based on the actual control weight of corn, the distance from the top detection point to the end of the drying chamber is comprehensively analyzed to obtain the intelligent speed adjustment coefficient of the drying roller; Output control instructions based on the intelligent speed adjustment coefficient to control the rotation speed of the drying roller and perform intelligent temperature control; The method for obtaining the continuous stability of the drying environment is: Based on the extreme value distribution relationship in the drying temperature data series of the drying chamber top detection point, the heat wave temperature fluctuation period of the drying chamber top detection point is obtained; the proportional relationship between the chamber temperature stability and the heat wave temperature fluctuation period is used as the continuous stability of the drying environment at the drying chamber top detection point; The method for obtaining the intracavity preheating completion degree is as follows: According to the drying temperature data sequence, the heat wave cavity temperature similarity of the detection point at the top of the drying cavity is obtained; the product of the continuous stability of the drying environment and the heat wave cavity temperature similarity is used as the cavity preheating completion degree of the detection point at the top of the drying cavity; The method for obtaining the heat wave cavity temperature similarity is: Obtain the minimum and maximum values ​​of the drying temperature data sequence under the latest conditions, and use the inverse proportional value of the temperature difference between the minimum and maximum values ​​under the latest conditions as the heat wave cavity temperature similarity of the detection point at the top of the drying cavity; The method for obtaining the corn drying suitability is: Obtain the median temperature inside the drying chamber; use the mean of the extreme values ​​in the drying temperature data series at the top detection point of the drying chamber as the mean of the overall ambient temperature inside the drying chamber at the top detection point; and use the proportional relationship between the mean of the overall ambient temperature inside the drying chamber and the median temperature inside the drying chamber as the corn drying suitability at the top detection point of the drying chamber. The method for obtaining the intelligent speed adjustment coefficient is: The distance from the top detection point of the drying chamber to the end of the drying chamber is used as the cavity detection point extension distance of the top detection point of the drying chamber; The proportional relationship between the actual control weight of corn and the extension distance of the cavity detection point is used as the corn conveying speed adjustment coefficient of the top detection point of the drying cavity; The accumulated result of the corn conveying speed adjustment coefficients of all the detection points on the top of the drying chamber is used as the intelligent speed adjustment coefficient of the drying roller.

2. The small corn drying equipment with an intelligent temperature control system according to claim 1, characterized in that: The method for obtaining the heat wave temperature fluctuation period is: The average distribution interval between adjacent maximum values ​​in the comprehensive drying temperature data sequence is used as the heat wave temperature fluctuation period of the detection point on the top of the drying chamber.

3. The small corn drying equipment with an intelligent temperature control system according to claim 1, characterized in that: The method for obtaining the cavity temperature stability is: In the drying temperature data sequence, the average temperature difference between different minimum values ​​within the preset minimum value range is integrated to obtain the cavity temperature stability of the detection point at the top of the drying cavity.

4. The small corn drying equipment with an intelligent temperature control system according to claim 1, characterized in that: The method for obtaining the corn regulation weight is: The ratio between the corn drying suitability and the completion of the preheating in the drying chamber is used as the corn control weight at the top detection point of the drying chamber.

5. The small corn drying equipment with an intelligent temperature control system according to claim 1, characterized in that: The method for obtaining the actual control weight of corn is: The horizontal distribution lines of the different drying chamber top detection points in the drying chamber are used as the two-dimensional horizontal axis reference baseline; The horizontal line after the two-dimensional horizontal axis reference baseline is proportionally shrunk is used as the two-dimensional horizontal axis, and the actual control weight of corn is used as the two-dimensional vertical coordinate; a two-dimensional space coordinate system is formed according to the two-dimensional horizontal axis and the two-dimensional vertical coordinate, and the actual control weight of corn is curve fitted, and the value after the actual control weight of corn is fitted is used as the actual control weight of corn.

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