Grain and oil material drying process moisture online nondestructive testing method and system based on multivariate information online perception and thermal analysis

Abstract

The invention discloses a grain and oil material drying process moisture online nondestructive testing method and system based on multivariate information online perception and thermal analysis, and the method comprises the steps: calculating ambient air absolute humidity according to ambient air temperature and relative humidity, and obtaining incident airflow absolute humidity according to the ambient air absolute humidity; calculating the average temperature of the wet material in the drying process; according to the absolute humidity of the incident airflow, the average temperature of the wet material, the temperature of the incident airflow, the temperature of the exhaust airflow and the total mass of the wet material, the dry basis moisture of the wet material at the sampling moment is directly calculated through a discretized dry basis moisture value calculation formula. The moisture value of the material is calculated through the numerical algorithm based on heat and humidity balance, and the method has the advantages that the material is not damaged in the detection process, the equipment cost is low, and the output moisture value interval time is short.

Description

Technical Field

[0001] The present invention relates to a method and system for detecting moisture in grain and oil materials, and in particular to an online nondestructive detection method and system for detecting moisture in a grain and oil material drying process based on online perception of multivariate information and thermal analysis. Background Art

[0002] Moisture content is crucial information in the drying process of grain and oil materials. It is the information basis for controlling the drying process and accurately implementing the drying process. Existing online moisture detectors mainly use the resistance method, which requires the material to be crushed and then the resistance value between the two electrodes is measured, and then the moisture value of the material is calculated based on the functional relationship between the resistance value and the moisture value. It is mainly used to measure grain materials with high starch content such as rice, wheat, and corn, and has poor adaptability to oil materials such as rapeseed, soybeans, and peanuts. Due to its characteristics of rolling processing and long measurement time, the moisture measurement cycle is relatively long, and real-time measurement results cannot be obtained. Summary of the invention

[0003] Purpose of the invention: One purpose of the present invention is to provide an online nondestructive moisture detection method based on online perception of multivariate information, which utilizes the drying process of grain and oil materials and calculates the moisture value of the material through a numerical algorithm based on heat and moisture balance.

[0004] Another object of the present invention is to provide a detection system for the method.

[0005] Technical solution: The method for online nondestructive detection of moisture in the drying process of grain and oil materials based on multivariate information online perception and thermal analysis of the present invention comprises the following steps:

[0006] Calculate the absolute humidity of the ambient air according to the ambient air temperature and relative humidity, and obtain the absolute humidity of the incident airflow according to the absolute humidity of the ambient air;

[0007] Calculate the average temperature of the wet material during the drying process;

[0008] According to the absolute humidity of the incident airflow, the average temperature of the wet material, the incident airflow temperature, the exhaust airflow temperature and the total mass of the wet material, the dry basis moisture of the wet material at the sampling time is directly calculated through the discretized dry basis moisture value calculation formula.

[0009] Furthermore, the calculation formula for the discretized dry basis moisture value is:

[0010]

[0011] Where X(i) is the dry basis moisture value of the wet material measured for the i-th time, W B is the dry air mass flow, c B is the specific heat of dry air, t g1 (i) is the incident airflow temperature measured at the i-th time, tg2 (i) is the exhaust air temperature measured at the i-th time, c vap is the specific heat of water vapor, Y g1 (i) is the absolute humidity of the incident airflow measured at the i-th time, m ws (i) is the total mass of wet material measured for the i-th time, m ws (i-1) is the total mass of wet material measured for the i-1th time, Δτ is the measurement time interval, h fg is the heat of vaporization of water, c w is the specific heat of water, t s (i) is the average temperature of the wet material measured for the i-th time, t s (i-1) is the average temperature of the wet material measured at the i-1th time, c s is the specific heat of dry matter in wet material.

[0012] Furthermore, the derivation process of the calculation formula for the discretized dry basis moisture value is:

[0013] According to the mass balance between wet material and air flow:

[0014]

[0015] After moving the items:

[0016]

[0017] Among them, m s is the mass of dry matter in the wet material, X is the dry basis moisture value of the wet material, τ is the drying time, W B is the dry air mass flow, Y g1 is the absolute humidity of the incident airflow, Y g2 is the absolute humidity of the exhaust air flow;

[0018] According to the heat balance between wet material and air flow:

[0019]

[0020] Among them, c s is the specific heat of dry matter in wet material, c w is the specific heat of water, t s is the average temperature of the wet material, i g1 is the incident airflow enthalpy, i g2 is the exhaust air flow enthalpy; i g1 and i g2 The expression is:

[0021] i g1 =c B t g1 +(c vap t g1+h fg )Y g1

[0022] i g2 =c B t g2 +(c vap t g2 +h fg )Y g2

[0023] Among them, c B is the specific heat of dry air, t g1 is the incident air flow temperature, t g2 is the exhaust air temperature, c vap is the specific heat of water vapor, h fg is the heat of vaporization of water;

[0024] will i g1 、i g2 and Y g2 Substitute the heat balance expression between the wet material and the air flow, calculate and shift the terms to get the dry basis moisture expression of the wet material:

[0025]

[0026] According to the law of conservation of mass:

[0027]

[0028] Among them, m ws is the total mass of the wet material;

[0029] Substituting the mass conservation formula into the dry basis moisture expression of the wet material yields:

[0030]

[0031] After further simplification:

[0032]

[0033] The differential term is expressed as:

[0034]

[0035] Among them, m ws (i) is the total mass of wet material measured for the i-th time, m ws (i-1) is the total mass of wet material measured for the i-1th time, Δτ is the measurement time interval, t s (i) is the average temperature of the wet material measured for the i-th time, t s (i-1) is the average temperature of the wet material measured at the i-1th time;

[0036] Substitute the differential term into the simplified dry basis moisture calculation formula of wet materials to obtain the discretized dry basis moisture value calculation formula.

[0037] Furthermore, the absolute humidity of the ambient air is calculated according to the ambient air temperature and relative humidity, and the absolute humidity of the incident airflow is obtained according to the absolute humidity of the ambient air; specifically:

[0038]

[0039] Y g1 =Y amb

[0040] Among them, Y amb is the absolute humidity of the ambient air, is the relative humidity of the ambient air, p sat is the saturated vapor pressure, T amb is the ambient air temperature, Y g1 is the absolute humidity of the incident airflow, and A, B, C, D, and E are parameters.

[0041] Furthermore, the average temperature of the wet material during the drying process is calculated as follows:

[0042]

[0043] Among them, t s is the average temperature of the wet material, T1, T2, T3, ...T N are the temperatures of wet materials in N different regions, V1, V2, V3, ... V N They are the volumes of wet materials corresponding to N different areas.

[0044] Furthermore, the temperatures of the wet materials in N different areas are respectively sampled by N grain temperature sensors.

[0045] Furthermore, the ambient air temperature and relative humidity are obtained by sampling through ambient temperature and humidity sensors, and the incident air flow temperature and exhaust air flow temperature are obtained by sampling through airflow incident temperature sensors and airflow exhaust temperature sensors arranged at the inlet and outlet of the dryer respectively; the total mass of the wet material is obtained by sampling through a material weight tester arranged at the bottom of the dryer.

[0046] Based on the same inventive concept, the online nondestructive detection system for moisture in the drying process of grain and oil materials based on multivariate information online perception and thermal analysis of the present invention comprises:

[0047] A data acquisition unit for periodically sampling ambient air temperature and relative humidity, the temperature of wet materials in different areas, incident air flow temperature, exhaust air flow temperature, and the total mass of wet materials;

[0048] The incident airflow absolute humidity calculation unit is used to calculate the absolute humidity of the ambient air according to the ambient air temperature and relative humidity, and obtain the incident airflow absolute humidity according to the ambient air absolute humidity;

[0049] Wet material average temperature calculation unit, used to calculate the average temperature of wet materials during the drying process;

[0050] The wet material dry basis moisture calculation unit is used to directly calculate the dry basis moisture of the wet material at the sampling time through a discretized dry basis moisture value calculation formula according to the absolute humidity of the incident airflow, the average temperature of the wet material, the incident airflow temperature, the exhaust airflow temperature and the total mass of the wet material.

[0051] An electronic device for storing and executing the above method, the device comprising:

[0052] A memory storing executable program code;

[0053] a processor coupled to the memory;

[0054] The processor calls the executable program code stored in the memory to execute the steps of the above-mentioned method for online non-destructive detection of moisture in the drying process of grain and oil materials based on online perception of multivariate information and thermal analysis.

[0055] A computer-readable storage medium for storing and executing the above method, wherein the computer-readable storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the steps of the above-mentioned method for online non-destructive detection of moisture in the drying process of grain and oil materials based on online perception of multivariate information and thermal analysis.

[0056] Beneficial effect: Compared with the prior art, the significant advantages of the present invention are: based on the perception of multiple information such as wet material temperature, quality, air flow temperature, ambient temperature and humidity, and utilizing the relationship between the moisture content of grain and oil materials during the drying process and the real-time measurement values ​​of the above physical quantities, the dry basis moisture value of the material is deduced through a numerical algorithm based on heat and moisture balance. It has the advantages of no damage to the material during the detection process, low equipment cost, short interval time for outputting dry basis moisture value, and high measurement accuracy. In particular, the measurement accuracy of materials with high moisture content is much higher than that of existing measurement methods such as resistance method and capacitance method. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a position distribution diagram of each sensor in the dryer of the present invention;

[0058] Figure 2 is a flow chart of the steps of the method of the present invention;

[0059] Figure 3 It is a logical relationship diagram between various physical quantities in the method of the present invention. DETAILED DESCRIPTION

[0060] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0061] The specific heat of grain and oil materials is closely related to their moisture content. The specific heat of dry matter is generally between 1.0-1.5 kJ / (kg℃), and the specific heat of water is about 4.2 kJ / (kg℃); the change of moisture content has a huge impact on the specific heat of wet materials. The size of the specific heat will significantly affect the temperature rise of the material during the drying process. Therefore, the moisture value of the wet material can be inferred based on the temperature rise of the material during the drying process.

[0062] like Figure 1 As shown, multiple grain temperature sensors ① are arranged in the dryer to collect the temperature of wet materials in different areas of the dryer; an airflow incident temperature sensor ② is arranged at the interface between the hot air furnace and the dryer to collect the incident airflow temperature; a material weight tester ③ is arranged at the bottom of the dryer to measure the total mass of the wet material; an airflow discharge temperature sensor ④ is arranged at the interface between the dryer and the dehumidification fan to measure the exhaust airflow temperature; an ambient temperature and humidity sensor ⑥ is arranged in the external environment to measure the ambient air temperature and relative humidity; each temperature sensor transmits the collected data to the host computer ⑦ through the data acquisition module ⑤, and the host computer calculates the moisture value according to its internal calculation module.

[0063] like Figure 2 and Figure 3 As shown, the method for online nondestructive detection of moisture in the drying process of grain and oil materials based on multivariate information online perception and thermal analysis of the present invention is specifically as follows:

[0064] S1. Calculate the absolute humidity of the ambient air according to the ambient air temperature and relative humidity, and obtain the absolute humidity of the incident airflow according to the absolute humidity of the ambient air; specifically:

[0065] Since the absolute humidity of the incident airflow remains unchanged before and after being heated by the hot air stove, we have:

[0066] Y g1 =Y amb (1)

[0067] Among them, Y amb is the absolute humidity of ambient air, kg 水 / kg 干空气 ; Y g1 is the absolute humidity of the incident airflow, kg 水 / kg 干空气 ; The absolute humidity of the ambient air can be calculated based on the values ​​measured by the ambient temperature and humidity sensor:

[0068]

[0069] in, is the relative humidity of ambient air, %; p sat is the saturated vapor pressure, kPa; T amb is the ambient air temperature, ℃; A, B, C, D, and E are parameters. In this embodiment, A is 0.622, B is 101.3, C is 16.376953, D is 3878.8223, and E is 229.861.

[0070] S2. Calculate the average temperature of the wet material during the drying process; specifically:

[0071] For the average material temperature t s It can be obtained by arranging multiple temperature sensors inside the dryer and calculating the volume average. For example, the dryer is divided into several areas (1, 2, 3, ..., N), and temperature sensors are arranged at representative positions in each area. The readings are recorded as T1, T2, T3, ...T N ; The material volume corresponding to each area is V1, V2, V3, ... V N The average temperature of the material can be calculated by the following formula:

[0072]

[0073] Reference for the location of each sensor in the dryer Figure 1 .

[0074] S3. According to the absolute humidity of the incident airflow, the average temperature of the wet material, the incident airflow temperature, the exhaust airflow temperature and the total mass of the wet material, the dry basis moisture of the wet material at the sampling time is directly calculated by the discretized dry basis moisture value calculation formula; specifically:

[0075] (1) According to the mass balance between wet material and air flow:

[0076]

[0077] After moving the items:

[0078]

[0079] Among them, m s is the mass of dry matter in wet material, kg; W B is the dry air mass flow, kg / min; Y g1 is the absolute humidity of the incident airflow, kg 水 / kg 干空气 ; Y g2 is the absolute humidity of the exhaust air, kg 水 / kg 干空气 ; X is the dry basis moisture value of the wet material, kg水 / kg 干物质 ; τ is the drying time, min.

[0080] (2) According to the heat balance between wet material and air flow:

[0081]

[0082] i g1 =c B t g1 +(c vap t g1 +h fg )Y g1 (8)

[0083] i g2 =c B t g2 +(c vap t g2 +h fg )Y g2 (9)

[0084] Among them, c s is the specific heat of dry matter in wet material, kJ / (kg℃); c w is the specific heat of water, kJ / (kg℃); t s is the average temperature of the wet material, °C; i g1 is the incident airflow enthalpy, kJ; i g2 is the exhaust air flow enthalpy, kJ; c B is the specific heat of dry air, t g1 is the incident air flow temperature, °C; t g2 is the exhaust air temperature, ℃; c vap is the specific heat of water vapor, kJ / (kg℃); h fg is the heat of vaporization of water, kJ / kg. Substituting equations (6), (8), and (9) into equation (7), the dry basis moisture expression of the wet material is obtained after calculation and transposition:

[0085]

[0086] Since the material weight tester outputs the total weight of the wet material in the dryer, that is, the total mass of the wet material, let its value be m ws , kg. According to the law of conservation of mass:

[0087]

[0088] Substituting equations (11) and (12) into (10), we obtain:

[0089]

[0090] After simplifying formula (13), we have:

[0091]

[0092] Since the detection system cannot obtain continuous measurement values, it is necessary to discretize equation (14). Let the time interval for the detection system to measure once be Δτ. The values ​​measured by each sensor or tester in the i-th measurement are represented by Γ(i), where Γ represents the measured physical quantity. Then the differential term in equation (14) can be solved by the following equation:

[0093]

[0094]

[0095] Among them, m ws (i) is the total mass of wet material measured for the i-th time, m ws (i-1) is the total mass of wet material measured for the i-1th time, Δτ is the measurement time interval, t s (i) is the average temperature of the wet material measured for the i-th time, t s (i-1) is the average temperature of the wet material measured for the i-1th time.

[0096] Substituting equations (15) and (16) into equation (14), the moisture value of the wet material at any measurement time can be calculated.

[0097]

[0098] Where X(i) is the dry basis moisture value of the wet material measured for the i-th time, t g1 (i) is the incident airflow temperature measured at the i-th time, t g2 (i) is the exhaust air temperature measured at the i-th time, Y g1 (i) is the absolute humidity of the incident airflow measured at the i-th time, m ws (i) is the total mass of wet material measured for the i-th time, m ws (i-1) is the total mass of wet material measured for the i-1th time, t s (i) is the average temperature of the wet material measured for the i-th time, t s (i-1) is the average temperature of the wet material measured for the i-1th time.

[0099] Based on the same inventive concept, the online nondestructive detection system for moisture in the drying process of grain and oil materials based on multivariate information online perception and thermal analysis of the present invention comprises:

[0100] A data acquisition unit for periodically sampling ambient air temperature and relative humidity, the temperature of wet materials in different areas, incident air flow temperature, exhaust air flow temperature, and the total mass of wet materials;

[0101] The incident airflow absolute humidity calculation unit is used to calculate the absolute humidity of the ambient air according to the ambient air temperature and relative humidity, and obtain the incident airflow absolute humidity according to the ambient air absolute humidity;

[0102] Wet material average temperature calculation unit, used to calculate the average temperature of wet materials during the drying process;

[0103] The wet material dry basis moisture calculation unit is used to directly calculate the dry basis moisture of the wet material at the sampling time through a discretized dry basis moisture value calculation formula according to the absolute humidity of the incident airflow, the average temperature of the wet material, the incident airflow temperature, the exhaust airflow temperature and the total mass of the wet material.

[0104] An electronic device for storing and executing the above method, the device comprising:

[0105] A memory storing executable program code;

[0106] a processor coupled to the memory;

[0107] The processor calls the executable program code stored in the memory to execute the steps of the above-mentioned method for online non-destructive detection of moisture in the drying process of grain and oil materials based on online perception of multivariate information and thermal analysis.

[0108] A computer-readable storage medium for storing and executing the above method, wherein the computer-readable storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the steps of the above-mentioned method for online non-destructive detection of moisture in the drying process of grain and oil materials based on online perception of multivariate information and thermal analysis.

Claims

1. An online nondestructive detection method for moisture in the drying process of grain and oil materials based on multivariate information online perception and thermal analysis, characterized in that: The following steps are involved: Calculate the absolute humidity of the ambient air according to the ambient air temperature and relative humidity, and obtain the absolute humidity of the incident airflow according to the absolute humidity of the ambient air; Calculate the average temperature of the wet material during the drying process; According to the absolute humidity of the incident airflow, the average temperature of the wet material, the incident airflow temperature, the exhaust airflow temperature and the total mass of the wet material, the dry basis moisture of the wet material at the sampling time is directly calculated through the discretized dry basis moisture value calculation formula.

2. The method for online nondestructive detection of moisture in the drying process of grain and oil materials based on multivariate information online perception and thermal analysis according to claim 1 is characterized in that: The calculation formula for the discretized dry basis moisture value is: Where X(i) is the dry basis moisture value of the wet material measured for the i-th time, W B is the dry air mass flow, c B is the specific heat of dry air, t g1 (i) is the incident airflow temperature measured at the i-th time, t g2 (i) is the exhaust air temperature measured at the i-th time, c vap is the specific heat of water vapor, Y g1 (i) is the absolute humidity of the incident airflow measured at the i-th time, m ws (i) is the total mass of wet material measured for the i-th time, m ws (i-1) is the total mass of wet material measured for the i-1th time, Δτ is the measurement time interval, h fg is the heat of vaporization of water, c w is the specific heat of water, t s (i) is the average temperature of the wet material measured for the i-th time, t s (i-1) is the average temperature of the wet material measured at the i-1th time, c s is the specific heat of dry matter in wet material.

3. The method for online nondestructive detection of moisture in the drying process of grain and oil materials based on multivariate information online perception and thermal analysis according to claim 1 is characterized in that: The derivation process of the calculation formula for the discretized dry basis moisture value is: According to the mass balance between wet material and air flow: After moving the items: Among them, m s is the mass of dry matter in the wet material, X is the dry basis moisture value of the wet material, τ is the drying time, W B is the dry air mass flow, Y g1 is the absolute humidity of the incident airflow, Y g2 is the absolute humidity of the exhaust air flow; According to the heat balance between wet material and air flow: Among them, c s is the specific heat of dry matter in wet material, c w is the specific heat of water, t s is the average temperature of the wet material, i g1 is the incident airflow enthalpy, i g2 is the exhaust air flow enthalpy; i g1 and i g2 The expression is: i g1 =c B t g1 +(c vap t g1 +h fg )Y g1 i g2 =c B t g2 +(c vap t g2 +h fg )Y g2 Among them, c B is the specific heat of dry air, t g1 is the incident air flow temperature, t g2 is the exhaust air temperature, c vap is the specific heat of water vapor, h fg is the heat of vaporization of water; will i g1 、i g2 and Y g2 Substitute the heat balance expression between the wet material and the air flow, calculate and shift the terms to get the dry basis moisture expression of the wet material: According to the law of conservation of mass: Among them, m ws is the total mass of the wet material; Substituting the mass conservation formula into the dry basis moisture expression of the wet material yields: After further simplification: The differential term is expressed as: Among them, m ws (i) is the total mass of wet material measured for the i-th time, m ws (i-1) is the total mass of wet material measured for the i-1th time, Δτ is the measurement time interval, t s (i) is the average temperature of the wet material measured for the i-th time, t s (i-1) is the average temperature of the wet material measured at the i-1th time; Substitute the differential term into the simplified dry basis moisture calculation formula of wet materials to obtain the discretized dry basis moisture value calculation formula.

4. The method for online nondestructive detection of moisture in the drying process of grain and oil materials based on multivariate information online perception and thermal analysis according to claim 1 is characterized in that: The absolute humidity of the ambient air is calculated according to the ambient air temperature and relative humidity, and the absolute humidity of the incident airflow is obtained according to the absolute humidity of the ambient air; specifically: AND g1 =And amb Among them, Y amb is the absolute humidity of the ambient air, is the relative humidity of the ambient air, p sat is the saturated vapor pressure, T amb is the ambient air temperature, Y g1 is the absolute humidity of the incident airflow, and A, B, C, D, and E are parameters.

5. The method for online nondestructive detection of moisture in the drying process of grain and oil materials based on multivariate information online perception and thermal analysis according to claim 1 is characterized in that: Calculate the average temperature of the wet material during the drying process as: Among them, t S is the average temperature of the wet material, T1, T2, T3, ...T N are the temperatures of wet materials in N different regions, V1, V2, V3, ... V N They are the volumes of wet materials corresponding to N different areas.

6. The method for online nondestructive detection of moisture in the drying process of grain and oil materials based on multivariate information online perception and thermal analysis according to claim 5 is characterized in that: The temperatures of wet materials in N different areas are sampled by N grain temperature sensors respectively.

7. The method for online nondestructive detection of moisture in the drying process of grain and oil materials based on multivariate information online perception and thermal analysis according to claim 1 is characterized in that: The ambient air temperature and relative humidity are obtained by sampling the ambient temperature and humidity sensors, and the incident air flow temperature and exhaust air flow temperature are obtained by sampling the airflow incident temperature sensor and airflow exhaust temperature sensor set at the inlet and outlet of the dryer respectively; the total mass of the wet material is obtained by sampling the material weight tester set at the bottom of the dryer.

8. An online nondestructive detection system for moisture in the drying process of grain and oil materials based on multivariate information online perception and thermal analysis, characterized in that: include: A data acquisition unit for periodically sampling ambient air temperature and relative humidity, the temperature of wet materials in different areas, incident air flow temperature, exhaust air flow temperature, and the total mass of wet materials; The incident airflow absolute humidity calculation unit is used to calculate the absolute humidity of the ambient air according to the ambient air temperature and relative humidity, and obtain the incident airflow absolute humidity according to the ambient air absolute humidity; Wet material average temperature calculation unit, used to calculate the average temperature of wet materials during the drying process; The wet material dry basis moisture calculation unit is used to directly calculate the dry basis moisture of the wet material at the sampling time through a discretized dry basis moisture value calculation formula according to the absolute humidity of the incident airflow, the average temperature of the wet material, the incident airflow temperature, the exhaust airflow temperature and the total mass of the wet material.

9. An electronic device, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the steps of the method for online non-destructive detection of moisture in the drying process of grain and oil materials based on online perception of multivariate information and thermal analysis as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, which, when called, are used to execute the steps of the online non-destructive detection method for moisture in the drying process of grain and oil materials based on online perception of multivariate information and thermal analysis as described in any one of claims 1 to 7.

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