Superheated water intelligent control method based on material drying process

Abstract

The invention relates to the technical field of drying control, in particular to a superheated water intelligent control method based on a material drying process. The method comprises the following steps: firstly, analyzing the temperature state difference between a material inlet and a material outlet of the drying device to obtain an inlet and outlet temperature difference coefficient, obtaining the temperature correlation degree of the material inlet at each moment according to the time sequence correlation between the temperature data and the pressure data of the material inlet, and calculating the temperature correlation degree of the material inlet at the same moment according to the temperature correlation degree difference between the material inlet and the material outlet at the same moment. Obtaining the correlation difference degree of each moment, obtaining the temperature control abnormity degree of the drying device according to the correlation between the correlation difference degree and the water content of the material in the time sequence, obtaining the superheated water temperature control parameter of the drying device according to the inlet and outlet temperature difference coefficient and the temperature control abnormity degree in combination with the correlation difference degree of each moment, and obtaining the superheated water temperature control parameter of the drying device based on the superheated water temperature control parameter. And the temperature of superheated water in the next drying stage is controlled. The effect of controlling the temperature of superheated water in the material drying process can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of drying control, and in particular to a superheated water intelligent control method based on a material drying process. Background Art

[0002] Many materials contain a certain amount of moisture, such as agricultural products, grains, and fruits. Excessive moisture during storage is more likely to breed microorganisms and mildew, thus affecting the quality of the materials. Since superheated water has a higher heat carrying capacity and heat transfer coefficient, compared with traditional steam drying, superheated water can effectively transfer heat to the material, improving drying efficiency and reducing energy consumption. At the same time, it can also be carried out at a relatively mild temperature to avoid thermal damage to the material caused by high temperature.

[0003] In the related art, the temperature of the superheated water in the drying device is usually monitored in real time, the temperature of the superheated water is controlled within a normal range, and the superheated water heat is used to dry the material. However, since the material itself contains a certain amount of moisture during the drying process, the moisture contained in the material will interfere with the monitoring of the superheated water temperature, resulting in the monitored temperature data being unable to accurately reflect the temperature status of the superheated water, and thus the existing method is unable to effectively control the temperature of the superheated water. Summary of the Invention

[0004] In order to solve the technical problem that existing methods cannot effectively control the temperature of superheated water, the purpose of the present invention is to provide a superheated water intelligent control method based on the material drying process. The technical solution adopted is as follows: The present invention proposes a superheated water intelligent control method based on a material drying process, the method comprising: Real-time acquisition of temperature and pressure data of a material port of a drying device within a preset time period, and real-time acquisition of the moisture content of the material, wherein the material port includes a material inlet and a material outlet; Taking any material port as the material port to be tested, the temperature stability of the material port to be tested is obtained based on the time series change of the temperature data of the material port to be tested; the inlet and outlet temperature difference coefficient of the drying device is obtained based on the difference in temperature data at the same time between the material inlet and the material outlet, and the difference in temperature stability between the material inlet and the material outlet; Based on the time-series correlation between the temperature data and pressure data at the material port to be tested, the temperature correlation degree of the material port to be tested at each moment is obtained; based on the difference in the temperature correlation degrees between the material inlet and the material outlet at the same moment, the correlation difference degree of the drying device at each moment is obtained; based on the time-series correlation between the correlation difference degree of the drying device and the moisture content of the material, the temperature control anomaly degree of the drying device is obtained; based on the inlet and outlet temperature difference coefficient and the temperature control anomaly degree, and in combination with the correlation difference degree at each moment, the superheated water temperature control parameter of the drying device is obtained; Based on the superheated water temperature control parameter, the temperature of the superheated water in the next drying stage is controlled.

[0005] Furthermore, obtaining the temperature stability of the material port to be tested includes: The difference between the temperature data of the material port to be tested at each moment and the temperature data of the next adjacent moment is used as the temperature change of the material port to be tested at each moment; The absolute value of the difference between the number of moments when the temperature change is negative and the number of moments when the temperature change is positive is used as the first temperature fluctuation coefficient of the material port to be tested; The absolute value of the average value of the temperature variation of the material port to be measured at all times is used as the second temperature fluctuation coefficient of the material port to be measured; The first temperature fluctuation coefficient and the second temperature fluctuation coefficient are integrated and normalized for negative correlation to obtain the temperature stability of the material port to be measured.

[0006] Furthermore, obtaining the inlet and outlet temperature difference coefficient of the drying device includes: The difference between the temperature data of the material inlet and the material outlet at the same time is used as the temperature difference value between the material inlet and the material outlet at each time; Analyzing the discreteness of the temperature difference values ​​between the material inlet and the material outlet at all times to obtain the temperature difference disorder between the material inlet and the material outlet; The absolute value of the difference in temperature stability between the material inlet and the material outlet is used as the temperature stability difference between the material inlet and the material outlet; The temperature difference disorder degree and the temperature stability difference degree are integrated and normalized to obtain the inlet and outlet temperature difference coefficient of the drying device.

[0007] Furthermore, obtaining the temperature correlation of the material port to be tested at each moment includes: Taking any moment within the preset time period as the target moment, and taking any one of the preset left time domain or the preset right time domain of the target moment as the target preset time domain, wherein the lengths of the preset left time domain and the preset right time domain are the same; According to the time sequence, the sequence composed of the temperature data of the material port to be tested at all moments in the target preset time domain is used as the temperature time series sequence of the material port to be tested in the target preset time domain, and the sequence composed of the pressure data of the material port to be tested at all moments in the target preset time domain is used as the pressure time series sequence of the material port to be tested in the target preset time domain; Normalizing the Pearson correlation coefficient between the temperature time series and the pressure time series to obtain a correlation parameter of the material to be tested in a target preset time domain; The temperature correlation of the material port to be tested at the target time is obtained according to the correlation parameters of the preset left time domain and the preset right time domain at the target time, and the difference between the correlation parameters of the preset left time domain and the preset right time domain.

[0008] Furthermore, obtaining the temperature correlation of the material port to be tested at the target time according to the correlation parameters of the preset left time domain and the preset right time domain of the material port to be tested at the target time, and the difference between the correlation parameters of the preset left time domain and the preset right time domain, includes: The average value of the correlation parameters in the preset left time domain and the preset right time domain of the material port to be tested at the target time is used as the local correlation degree of the material port to be tested at the target time; Normalizing the difference between the correlation parameter of the preset right time domain and the correlation parameter of the preset left time domain at the material port to be tested at the target time to obtain the local correlation change degree of the material port to be tested at the target time; The product value of the local correlation degree and the local correlation variation degree is used as the temperature correlation degree of the material port to be measured at the target time.

[0009] Furthermore, obtaining the correlation difference of the drying device at each moment includes: The absolute value of the difference in the temperature correlation between the material inlet and the material outlet at the same time is used as the correlation difference of the drying device at each time.

[0010] Furthermore, obtaining the temperature control abnormality of the drying device includes: According to the time sequence, the sequence of the correlation difference degrees of the drying device at all times is used as the correlation difference degree sequence of the drying device, and the sequence of the moisture content of the material at all times is used as the moisture content sequence of the material; A negative correlation normalization process is performed on the Pearson correlation coefficient between the correlation difference sequence and the moisture content sequence to obtain the temperature control abnormality of the drying device.

[0011] Furthermore, obtaining the superheated water temperature control parameters of the drying device includes: The inlet and outlet temperature difference coefficient and the temperature control abnormality of the drying device are integrated and normalized to obtain an initial superheated water temperature control value of the drying device; Performing abnormality detection on the correlation difference of the drying device at all times, and taking the time corresponding to the detected abnormal correlation difference as the abnormal time, and obtaining the temperature control influence weight of the drying device based on the change in the number of abnormal times in the preset local time domain at each time; The product of the initial superheated water temperature control value of the drying device and the temperature control influence weight is used as the temperature control value adjustment amount of the drying device; The difference between the initial superheated water temperature control value and the temperature control value adjustment amount is used as the superheated water temperature control parameter of the drying device.

[0012] Furthermore, obtaining the temperature control influence weight of the drying device includes: The number of abnormal moments in the preset local time domain at each moment is used as the number of local abnormal moments at each moment; Performing linear fitting on the number of local abnormal moments at all moments, and performing negative correlation normalization processing on the slope of the fitted straight line to obtain a first temperature control influence coefficient of the drying device; Performing negative correlation mapping on the average value of the number of local abnormal moments at all moments to obtain a second temperature control influence coefficient of the drying device; The first temperature control influence coefficient and the second temperature control influence coefficient are integrated and normalized to obtain a temperature control influence weight of the drying device.

[0013] Furthermore, the controlling of the temperature of the superheated water in the next drying stage includes: The product of the superheated water temperature control parameter of the drying device and the standard temperature value of the superheated water in the next drying stage at each moment is used as the temperature adjustment amount of the superheated water in the next drying stage at each moment; The sum of the standard temperature value of the superheated water in the next drying stage at each moment and the temperature adjustment amount is used as the adjusted temperature value of the superheated water in the next drying stage at each moment.

[0014] The present invention has the following beneficial effects: Considering that existing methods are unable to effectively control the temperature of superheated water, the present invention first acquires real-time temperature and pressure data at the material inlet of the drying device, as well as the moisture content of the material. Considering that the material itself contains a certain amount of moisture, the superheated water consumes some heat when drying the material, causing the superheated water temperature to drop. This temperature drop is a normal phenomenon in the drying process. To eliminate the possibility of small temporal temperature difference fluctuations during the later drying process, the present invention first analyzes the temporal changes in the temperature data at the material inlet to be measured. The temperature stability reflects the stability of the temperature changes at the material inlet to be measured. Since changes in the material inlet temperature affect changes in the material outlet temperature, temperature fluctuations may be normal temperature changes caused by adjustments to the material inlet temperature. Therefore, the obtained inlet and outlet temperature difference coefficient reflects the degree of difference in temperature between the material inlet and outlet. Considering that temperature and pressure changes are consistent under normal circumstances during the drying process, the temperature correlation reflects the correlation between the local temperature and pressure at the material inlet to be measured at each moment. Furthermore, the obtained superheated water temperature control parameter reflects the degree of superheated water temperature adjustment required, and the temperature of the superheated water in the next drying stage is controlled to improve the temperature control effect of the superheated water in the drying device. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. 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.

[0016] Figure 1 This is a flow chart of a superheated water intelligent control method based on a material drying process provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0017] To further illustrate the technical means and effectiveness of the present invention to achieve its intended objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effectiveness of an intelligent superheated water control method for a material drying process, as proposed by 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.

[0018] 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.

[0019] The specific scheme of the superheated water intelligent control method based on the material drying process provided by the present invention is described in detail below with reference to the accompanying drawings.

[0020] See also Figure 1 , which shows a flow chart of a superheated water intelligent control method based on a material drying process provided by one embodiment of the present invention, the method comprising: Step S1: acquiring temperature data and pressure data of a material port of a drying device in a preset time period in real time, and acquiring the moisture content of the material in real time, wherein the material port includes a material inlet and a material outlet.

[0021] In an embodiment of the present invention, a temperature sensor and a pressure sensor are first installed at the material inlet and the material outlet of the drying device respectively, and the temperature sensor is used to collect the temperature data of the material inlet of the drying device at each moment and the temperature data of the material outlet at each moment within a preset time period. At the same time, the pressure sensor is used to collect the pressure data of the material inlet of the drying device at each moment and the pressure data of the material outlet at each moment within the preset time period. At the same time, microwave technology is used to detect the moisture content of the material in the drying device at each moment within the preset time period, wherein the length of the preset time period ranges from 3 to 5 minutes. In one embodiment of the present invention, the length of the preset time period is set to 3 minutes. The specific length of the preset time period can also be set by the implementer according to the specific implementation scenario, which is not limited here, and the sampling frequency of various data is the same. In one embodiment of the present invention, the sampling frequency of each data is set to 1 Hz. wherein, the use of microwave technology to detect moisture content is a technical means well known to those skilled in the art and will not be elaborated here.

[0022] It should be noted that different types of data have different dimensions. Therefore, the embodiments of the present invention also need to standardize the collected different types of data to eliminate the impact of dimensions. Among them, data standardization is a technical means well known to those skilled in the art and will not be elaborated here.

[0023] Step S2: Take any material port as the material port to be tested, and obtain the temperature stability of the material port to be tested based on the time series change of the temperature data of the material port to be tested; obtain the inlet and outlet temperature difference coefficient of the drying device based on the difference in temperature data between the material inlet and the material outlet at the same time, and the difference in temperature stability between the material inlet and the material outlet.

[0024] During the material drying process, stable temperatures at the material inlet and outlet are an important factor in ensuring the quality of material drying. Unstable temperatures can cause the material to burn, discolor, or even change its physical structure due to drastic temperature changes during the drying process. Traditional methods usually judge whether the drying process is normal based on temperature fluctuations, and thus determine whether intelligent temperature control is needed.

[0025] Since the material itself contains a certain amount of moisture during the actual drying process, the superheated water will consume some heat when drying the material, causing the superheated water temperature to drop. However, this temperature drop is normal. At the same time, in the early stage of the drying process, due to the high moisture content of the material, the temperature changes rapidly. After reaching the normal moisture content, the temperature remains stable. Therefore, when the temperature fluctuation may be small, it shows a trend characteristic. At this time, in order to maintain temperature stability, the superheated water temperature needs to be regulated. In order to eliminate the small fluctuation of the temporal temperature difference in the later drying process, it is necessary to first analyze any material port of the drying device, use any material port as the material port to be tested, and analyze the temporal changes of the temperature data of the material port to be tested. The stability of the temperature change of the material port to be tested is reflected by the obtained temperature stability.

[0026] Preferably, in one embodiment of the present invention, the method for obtaining the temperature stability of the material port to be measured specifically includes: The difference between the temperature data of the material port to be measured at each moment and the temperature data of the next adjacent moment is taken as the temperature variation of the material port to be measured at each moment.

[0027] It should be noted that there is no adjacent next moment after the last moment. Therefore, in order to facilitate the smooth progress of subsequent calculations, the average value of the temperature changes of all moments before the last moment can be used as the temperature change of the last moment.

[0028] The smaller the difference between the number of moments when the temperature change is negative and the number of moments when the temperature change is positive, it means that there is no obvious tendency for the temperature to increase or decrease for a long time at the position of the material port to be measured, and further indicates that the temperature change of the material port to be measured is relatively stable. Therefore, the absolute value of the difference between the number of moments when the temperature change is negative and the number of moments when the temperature change is positive can be used as the first temperature fluctuation coefficient of the material port to be measured. The smaller the first temperature fluctuation coefficient, the more stable the temperature change of the material port to be measured.

[0029] The absolute value of the average value of the temperature change of the material port to be tested at all times is taken as the second temperature fluctuation coefficient of the material port to be tested. The smaller the second fluctuation coefficient is, the smaller the overall level of the temperature change of the material port to be tested at each time is. This further indicates that the less obvious the temperature fluctuation of the material port to be tested is, and the more stable the temperature change of the material port to be tested is.

[0030] Then, the first temperature fluctuation coefficient and the second temperature fluctuation coefficient are integrated and normalized to achieve negative correlation, and the calculation results are limited to range, thereby obtaining the temperature stability of the material port to be tested.

[0031] In an embodiment of the present invention, the combination of the first temperature fluctuation coefficient and the second temperature fluctuation coefficient can be achieved by calculating the sum or product of the two, which is not limited here, and the subsequent steps of comprehensive processing of two or more data can also be achieved using the same method.

[0032] In the embodiment of the present invention, the natural constant A negative exponential function with base The functional form of is used to realize the normalization of negative correlation. In addition, the same method can be used in subsequent steps to realize the normalization of negative correlation. Represents a normalization function, which is used for normalization processing. In the embodiment of the present invention, an activation function or a hyperbolic tangent function can be used to implement normalization processing, which is not limited here.

[0033] As an example, in one embodiment of the present invention, the expression for the temperature stability of the material port to be measured can be specifically, for example, as follows: in, Indicates the temperature stability of the material port to be tested; Indicates the number of times when the temperature change at the material outlet to be measured is negative; Indicates the number of moments when the temperature change at the material outlet to be measured is a positive number; Indicates the first temperature fluctuation coefficient of the material port to be tested; Indicates that the material to be tested is at The temperature change at each moment; Indicates the second temperature fluctuation coefficient of the material port to be tested; Indicates the number of all moments included in the preset time period; Represents the hyperbolic tangent function, which is used for normalization processing, then Used for normalization of negative correlation.

[0034] The temperature stability of the material inlet and the temperature stability of the material outlet of the drying device can be obtained by the same method as above.

[0035] Since changes in the material inlet temperature will affect changes in the material outlet temperature, temperature fluctuations may be normal temperature changes caused by adjustments to the material inlet temperature. In the normal drying process, the temperature change states between the material inlet and outlet are consistent. Therefore, the difference in temperature data at the same time between the material inlet and outlet, as well as the difference in temperature stability between the material inlet and outlet, can be analyzed. The obtained inlet and outlet temperature difference coefficient reflects the degree of difference in temperature states between the material inlet and outlet. The larger the inlet and outlet temperature difference coefficient of the drying device, the more obvious the abnormality in the inlet and outlet temperature of the drying device. A larger temperature adjustment is required to avoid more serious temperature abnormalities and quickly return the abnormal temperature in the drying process to normal. Subsequently, the temperature of the superheated water can be effectively adjusted based on the inlet and outlet temperature difference coefficient.

[0036] Preferably, in one embodiment of the present invention, the method for obtaining the inlet and outlet temperature difference coefficient of the drying device specifically includes: The difference in temperature data between the material inlet and the material outlet at the same time is taken as the temperature difference value between the material inlet and the material outlet at each time. The larger the temperature difference value, the greater the relative difference in temperature between the material inlet and the material outlet at the same time. Then, the discrete degree of the temperature difference value between the material inlet and the material outlet at all times is analyzed to obtain the temperature difference disorder between the material inlet and the material outlet. The larger the temperature difference disorder, the more inconsistent the temperature difference between the material inlet and the material outlet, and then the greater the difference in the temperature change state of the material inlet and the material outlet.

[0037] In an embodiment of the present invention, statistics such as the standard deviation or variance of the temperature difference values ​​between the material inlet and the material outlet at all times can be used as the temperature difference disorder between the material inlet and the material outlet to analyze the degree of discreteness of the temperature difference values ​​between the material inlet and the material outlet at all times, which is not limited here.

[0038] The absolute value of the difference in temperature stability between the material inlet and the material outlet is taken as the temperature stability difference between the material inlet and the material outlet. The larger the temperature stability difference, the greater the difference in temperature stability state between the material inlet and outlet, and further the greater the difference in temperature change state between the material inlet and outlet.

[0039] Then, the temperature difference chaos and temperature stability difference are integrated and normalized, and the calculation results are limited to range, thereby obtaining the inlet and outlet temperature difference coefficient of the drying device.

[0040] As an example, in one embodiment of the present invention, the expression of the inlet and outlet temperature difference coefficient of the drying device can be specifically, for example, as follows: in, Indicates the inlet and outlet temperature difference coefficient of the drying device; Indicates the degree of temperature difference between the material inlet and the material outlet; Indicates the temperature stability of the material inlet; Indicates the temperature stability of the material outlet; Indicates the temperature stability difference between the material inlet and the material outlet; Represents the activation function, which is used for normalization.

[0041] Step S3: Based on the time-series correlation between the temperature data and pressure data at the material port to be tested, the temperature correlation degree of the material port to be tested at each moment is obtained; based on the difference in the temperature correlation degree between the material inlet and the material outlet at the same moment, the correlation difference degree of the drying device at each moment is obtained; based on the time-series correlation between the correlation difference degree of the drying device and the moisture content of the material, the temperature control anomaly degree of the drying device is obtained; based on the inlet and outlet temperature difference coefficient and the temperature control anomaly degree, and in combination with the correlation difference degree at each moment, the superheated water temperature control parameter of the drying device is obtained.

[0042] Since the monitoring of pressure data will also be affected during the temperature control of superheated water, the changes in temperature and pressure should be consistent. If there is an abnormality in temperature control during the drying process, it will cause anomalies in the temperature and pressure at the material port, resulting in poor correlation between the two. For example, superheated water with improper temperature control will cause the superheated water to boil over, causing the pressure in the pipeline to increase rapidly without a significant change in temperature, resulting in poor correlation between the data. Therefore, the temperature correlation of the material port to be tested at each moment can be obtained based on the time-series correlation between the temperature data and pressure data at the material port to be tested. The temperature correlation reflects the correlation between the local temperature and pressure at the material port to be tested at each moment. The larger the temperature correlation, the stronger the correlation between the local temperature and pressure at the material port to be tested at each moment, which further indicates that the temperature control of the material drying process is normal. Subsequently, based on the difference in temperature correlation between the material inlet and outlet at the same time, combined with the moisture content of the material, the temperature control abnormality of the drying device can be accurately analyzed.

[0043] Preferably, in one embodiment of the present invention, the method for obtaining the temperature correlation of the material port to be measured at each moment specifically includes: First, any moment within the preset time period is taken as the target moment, and any one of the preset left time domain or the preset right time domain of the target moment is taken as the target preset time domain, wherein the lengths of the preset left time domain and the preset right time domain of the target moment are the same, and the lengths of the preset left time domain and the preset right time domain are in the range of In one embodiment of the present invention, the lengths of the preset left time domain and the preset right time domain are set to 25, that is, the preset left time domain includes the 25 moments before and closest to the target moment, and the preset right time domain includes the 25 moments after and closest to the target moment. The specific values ​​of the lengths of the preset left time domain and the preset right time domain can also be set by the implementer according to the specific implementation scenario and are not limited here.

[0044] Then, according to the time sequence, the sequence of temperature data of the material port to be tested at all moments in the target preset time domain is used as the temperature time series sequence of the material port to be tested in the target preset time domain, and the sequence of pressure data of the material port to be tested at all moments in the target preset time domain is used as the pressure time series sequence of the material port to be tested in the target preset time domain. The Pearson correlation coefficient between the temperature time series and the pressure time series is normalized, and the calculation result is limited to range, thereby obtaining the correlation parameter of the material port to be tested in the target preset time domain. The larger the correlation parameter, the stronger the correlation between the temperature and pressure of the material port to be tested in the target preset time domain at the target moment.

[0045] The same method as above can be used to obtain the correlation parameters of the preset left time domain and the preset right time domain of the material port to be tested at the target moment. There is a strong correlation between the temperature and pressure on the left and right sides of the target moment, indicating that the temperature change at the target moment is a normal change, and the correlation between temperature and pressure decreases with the passage of time, that is, the correlation parameter of the preset left time domain is larger than the correlation parameter of the preset right time domain, indicating that there is abnormal temperature control at the target moment. If the correlation between temperature and pressure increases with the passage of time, that is, the correlation parameter of the preset left time domain is smaller than the correlation parameter of the preset right time domain, indicating that the temperature control at the target moment is normal. Therefore, the temperature correlation degree of the material port to be tested at the target moment can be obtained based on the correlation parameters of the preset left time domain and the preset right time domain of the material port to be tested at the target moment, and the difference in the correlation parameters between the preset left time domain and the preset right time domain.

[0046] Preferably, in one embodiment of the present invention, the method for obtaining the temperature correlation of the material port to be measured at the target time further includes: The average value of the correlation parameters of the preset left time domain and the preset right time domain of the material port to be tested at the target time is used as the local correlation degree of the material port to be tested at the target time. The larger the local correlation degree, the stronger the correlation between the temperature and pressure on the left and right sides of the target time.

[0047] Normalize the difference between the correlation parameter of the preset right time domain and the correlation parameter of the preset left time domain of the material port to be tested at the target time, and limit the calculation result to range, thereby obtaining the local correlation variation degree of the material port to be tested at the target time.

[0048] The product of the local correlation degree and the local correlation change degree is used as the temperature correlation degree of the material port to be tested at the target time.

[0049] As an example, in one embodiment of the present invention, the expression for the temperature correlation of the material port to be tested at the target time can be specifically, for example, as follows: in, Indicates the temperature correlation of the material outlet to be tested at the target time; Represents the correlation parameter of the preset right time domain of the material port to be tested at the target time; Represents the correlation parameter of the preset left time domain of the material port to be tested at the target time; Represents the activation function, which is used for normalization processing; Indicates the local correlation of the material port to be tested at the target time; Indicates the degree of change in the local correlation of the material to be tested at the target time.

[0050] The same method as above can be used to obtain the temperature correlation of the material port to be tested at each moment, as well as the temperature correlation of the material inlet and material outlet at each moment. Since the material contains a certain amount of moisture, this moisture needs to be removed during the drying process to affect the consistency of the inlet and outlet temperatures. In the normal material drying process, the higher the moisture content of the material, the more heat is absorbed. Therefore, the temperature difference between the material inlet and outlet is greater. As the moisture content of the material decreases during the drying process, the temperature difference between the inlet and outlet decreases. When the moisture content reaches near the standard moisture content, the moisture content remains stable and the temperature difference also remains stable. Therefore, the correlation difference of the drying device at each moment can be obtained based on the difference in temperature correlation between the material inlet and material outlet at the same moment. Subsequently, the temporal correlation between the correlation difference and the moisture content of the material can be analyzed, thereby accurately analyzing the abnormality of temperature control of the drying device during the material drying process.

[0051] Preferably, in one embodiment of the present invention, the absolute value of the difference in temperature correlation between the material inlet and the material outlet at the same moment can be used as the correlation difference of the drying device at each moment.

[0052] During the material drying process, when the moisture content no longer changes significantly, under normal circumstances, the difference in temperature correlation between the material inlet and outlet also remains stable. Therefore, if the correlation between the correlation difference of the drying device and the moisture content of the material is smaller in time series, it means that the temperature control of the drying device during the material drying process is more likely to be abnormal. Therefore, the temperature control abnormality of the drying device can be obtained according to the correlation between the correlation difference of the drying device and the moisture content of the material in time series. The greater the temperature control abnormality, the greater the possibility of abnormality in the temperature control of the superheated water during the material drying process, and further indicates that the superheated water temperature in the drying device needs to be adjusted to a greater extent. Subsequently, the temperature difference coefficient between the inlet and outlet of the drying device and the temperature control abnormality can be combined to effectively control the temperature of the superheated water.

[0053] Preferably, in one embodiment of the present invention, the method for obtaining the temperature control abnormality of the drying device specifically includes: According to the time sequence, the sequence of correlation difference of the drying device at all times is taken as the correlation difference sequence of the drying device, and the sequence of moisture content of the material at all times is taken as the moisture content sequence of the material. The Pearson correlation coefficient between the correlation difference sequence and the moisture content sequence is normalized to negative correlation, and the calculation result is limited to range, thereby obtaining the temperature control abnormality of the drying device.

[0054] As an example, in one embodiment of the present invention, the expression for the temperature control abnormality of the drying device may be specifically, for example, as follows: in, Indicates the abnormality of temperature control of the drying device; represents the Pearson correlation coefficient between the correlation difference series and the moisture content series; Represents the activation function, which is used for normalization processing. Used for normalization of negative correlation.

[0055] The greater the difference in temperature between the material inlet and outlet of the drying device, and the greater the likelihood of anomalies during the temperature control process, the greater the need for adjusting the superheated water temperature in the drying device. Considering that during normal temperature control, the control amplitude should gradually decrease as the regulated temperature stabilizes, the temperature requirements at different material drying stages vary. This may result in the actual temperature control process not conforming to the characteristic of decreasing control amplitude. The temperature correlation reflects whether the temperature data at each moment in the time series may contain anomalies. During a normal control process, temperature changes should be consistent with pressure changes and affect the material inlet and outlet temperatures. If the outlet temperature changes follow the same trend as the inlet temperature, it indicates normal temperature control. If the material inlet and outlet temperatures do not change synchronously during this process, it indicates a true anomaly in the temperature control of the material drying process. Therefore, the embodiments of the present invention determine the superheated water temperature control parameters of the drying device based on the inlet and outlet temperature difference coefficient and the temperature control anomaly degree, combined with the correlation difference at each moment. The superheated water temperature control parameters can then be used to effectively adjust the superheated water temperature in subsequent material drying processes.

[0056] Preferably, in one embodiment of the present invention, the method for obtaining the temperature control parameters of the superheated water of the drying device specifically includes: First, the inlet and outlet temperature difference coefficient and temperature control anomaly of the drying device are synthesized and normalized, and the calculation results are limited to range, thereby obtaining the initial superheated water temperature control value of the drying device.

[0057] As an example, in one embodiment of the present invention, the expression of the initial superheated water temperature control value of the drying device can be specifically, for example, as follows: in, Indicates the initial superheated water temperature control value of the drying device; Indicates the inlet and outlet temperature difference coefficient of the drying device; Indicates the abnormality of temperature control of the drying device; Represents the hyperbolic tangent function, which is used for normalization.

[0058] Then, anomaly detection is performed on the correlation difference of the drying device at all times, and the moment corresponding to the detected abnormal correlation difference is used as the abnormal moment. In one embodiment of the present invention, the existing box plot technology can be used to perform anomaly detection on the correlation difference of the drying device at all times, which is not limited or elaborated here, and the temperature control influence weight of the drying device is obtained according to the change in the number of abnormal moments in the preset local time domain at each moment. The larger the temperature control influence weight, the more the temperature is normally regulated, and the greater the degree to which the initial superheated water temperature control value of the drying device needs to be lowered.

[0059] Preferably, in one embodiment of the present invention, the method for obtaining the temperature control influence weight of the drying device specifically includes: The number of abnormal moments in the preset local time domain at each moment is taken as the number of local abnormal moments at each moment, wherein the length of the preset local time domain ranges from In one embodiment of the present invention, the length of the preset local time domain is set to 15, that is, the preset local time domain of a certain moment includes the 14 moments closest to the moment and the moment itself. The length of the preset local time domain can also be set by the implementer according to the specific implementation scenario and is not limited here.

[0060] Perform linear fitting on the number of local abnormal moments at all times, and perform negative correlation normalization on the slope of the fitted straight line, limiting the calculation results to range, thereby obtaining the first temperature control influence coefficient of the drying device. In one embodiment of the present invention, the existing least squares method can be used to achieve straight-line fitting, which is not limited or elaborated here. Then, a negative correlation mapping is performed on the average value of the number of local abnormal moments at all times to obtain the second temperature control influence coefficient of the drying device.

[0061] After integrating the first temperature control influence coefficient and the second temperature control influence coefficient and normalizing them, the calculation results are limited to range, thereby obtaining the temperature control influence weight of the drying device.

[0062] As an example, in one embodiment of the present invention, the expression of the temperature control influence weight of the drying device can be specifically, for example, as follows: in, Indicates the temperature control influence weight of the drying device; Indicates the first temperature control influence coefficient of the drying device; Indicates the second temperature control influence coefficient of the drying device; represents the slope of the fitted straight line; Indicates the The number of local abnormal moments at a given moment; Indicates the number of all moments included in the preset time period; represents the hyperbolic tangent function, which is used for normalization; Represents the activation function, which is used for normalization processing. Used for normalization of negative correlation; Indicates the preset adjustment parameter, used to prevent the denominator from being 0. The value range is In one embodiment of the present invention, Set to 0.01, The specific value of can also be set by the implementer according to the specific implementation scenario and is not limited here.

[0063] Furthermore, the product of the initial superheated water temperature control value of the drying device and the temperature control influence weight is used as the temperature control value adjustment amount of the drying device, and the difference between the initial superheated water temperature control value and the temperature control value adjustment amount is used as the superheated water temperature control parameter of the drying device.

[0064] As an example, in one embodiment of the present invention, the expression of the superheated water temperature control parameter of the drying device can be specifically, for example, as follows: in, Indicates the superheated water temperature control parameters of the drying device; Indicates the initial superheated water temperature control value of the drying device; Indicates the temperature control influence weight of the drying device; Indicates the temperature control value adjustment of the drying device.

[0065] Step S4: Based on the superheated water temperature control parameter, the temperature of the superheated water in the next drying stage is controlled.

[0066] The larger the superheated water temperature control parameter of the drying device is, the greater the need to adjust the superheated water temperature in the next drying stage, thereby ensuring that the superheated water temperature can dry the material more effectively and improving the effect of superheated water temperature control. The next drying stage can be considered as the next time period, for example, the next preset time period.

[0067] Preferably, in one embodiment of the present invention, the method for controlling the temperature of the superheated water in the next drying stage specifically includes: The product of the superheated water temperature control parameter of the drying device and the standard temperature value of the superheated water in the next drying stage at each moment is used as the temperature adjustment value of the superheated water in the next drying stage at each moment. Since the material itself contains a certain amount of moisture during the actual drying process, the superheated water will consume some heat when drying the material, resulting in a lower superheated water temperature. Therefore, the superheated water temperature in the next drying stage needs to be appropriately increased. Therefore, the sum of the standard temperature value of the superheated water in the next drying stage at each moment and the temperature adjustment value can be used as the adjusted temperature value of the superheated water in the next drying stage at each moment, wherein the standard temperature value is a known value preset for the next drying stage.

[0068] As an example, in one embodiment of the present invention, the expression for the adjusted temperature value of the superheated water in the next drying stage at each moment can be specifically, for example, as follows: in, Indicates that the superheated water in the next drying stage is Adjust the temperature value at each moment; Indicates that the superheated water in the next drying stage is Standard temperature value at a certain moment; Indicates the superheated water temperature control parameters of the drying device; Indicates that the superheated water in the next drying stage is The temperature adjustment at each moment.

[0069] After obtaining the adjusted temperature value of the superheated water in the next drying stage at each moment, the temperature of the superheated water in the next drying stage can be controlled in real time to complete the drying process of the material.

[0070] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0071] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A superheated water intelligent control method based on material drying process, characterized in that: The method comprises: Real-time acquisition of temperature and pressure data of a material port of a drying device within a preset time period, and real-time acquisition of the moisture content of the material, wherein the material port includes a material inlet and a material outlet; Taking any material port as the material port to be tested, the temperature stability of the material port to be tested is obtained based on the time series change of the temperature data of the material port to be tested; the inlet and outlet temperature difference coefficient of the drying device is obtained based on the difference in temperature data at the same time between the material inlet and the material outlet, and the difference in temperature stability between the material inlet and the material outlet; Based on the time-series correlation between the temperature data and pressure data at the material port to be tested, the temperature correlation degree of the material port to be tested at each moment is obtained; based on the difference in the temperature correlation degrees between the material inlet and the material outlet at the same moment, the correlation difference degree of the drying device at each moment is obtained; based on the time-series correlation between the correlation difference degree of the drying device and the moisture content of the material, the temperature control anomaly degree of the drying device is obtained; based on the inlet and outlet temperature difference coefficient and the temperature control anomaly degree, and in combination with the correlation difference degree at each moment, the superheated water temperature control parameter of the drying device is obtained; Based on the superheated water temperature control parameter, the temperature of the superheated water in the next drying stage is controlled.

2. The superheated water intelligent control method based on the material drying process according to claim 1 is characterized in that: The obtaining of the temperature stability of the material port to be measured comprises: The difference between the temperature data of the material port to be tested at each moment and the temperature data of the next adjacent moment is used as the temperature change of the material port to be tested at each moment; The absolute value of the difference between the number of moments when the temperature change is negative and the number of moments when the temperature change is positive is used as the first temperature fluctuation coefficient of the material port to be tested; The absolute value of the average value of the temperature variation of the material port to be measured at all times is used as the second temperature fluctuation coefficient of the material port to be measured; The first temperature fluctuation coefficient and the second temperature fluctuation coefficient are integrated and normalized for negative correlation to obtain the temperature stability of the material port to be measured.

3. The method for intelligently controlling superheated water based on a material drying process according to claim 1, characterized in that: The method of obtaining the inlet and outlet temperature difference coefficient of the drying device includes: The difference between the temperature data of the material inlet and the material outlet at the same time is used as the temperature difference value between the material inlet and the material outlet at each time; Analyzing the discreteness of the temperature difference values ​​between the material inlet and the material outlet at all times to obtain the temperature difference disorder between the material inlet and the material outlet; The absolute value of the difference in temperature stability between the material inlet and the material outlet is used as the temperature stability difference between the material inlet and the material outlet; The temperature difference disorder degree and the temperature stability difference degree are integrated and normalized to obtain the inlet and outlet temperature difference coefficient of the drying device.

4. The method for intelligently controlling superheated water based on a material drying process according to claim 1, characterized in that: The step of obtaining the temperature correlation of the material port to be tested at each moment includes: Taking any moment within the preset time period as the target moment, and taking any one of the preset left time domain or the preset right time domain of the target moment as the target preset time domain, wherein the lengths of the preset left time domain and the preset right time domain are the same; According to the time sequence, the sequence composed of the temperature data of the material port to be tested at all moments in the target preset time domain is used as the temperature time series sequence of the material port to be tested in the target preset time domain, and the sequence composed of the pressure data of the material port to be tested at all moments in the target preset time domain is used as the pressure time series sequence of the material port to be tested in the target preset time domain; Normalizing the Pearson correlation coefficient between the temperature time series and the pressure time series to obtain a correlation parameter of the material to be tested in a target preset time domain; The temperature correlation of the material port to be tested at the target time is obtained according to the correlation parameters of the preset left time domain and the preset right time domain at the target time, and the difference between the correlation parameters of the preset left time domain and the preset right time domain.

5. The method for intelligently controlling superheated water based on a material drying process according to claim 4, characterized in that: Obtaining the temperature correlation of the material port to be tested at the target time according to the correlation parameters of the preset left time domain and the preset right time domain of the material port to be tested at the target time, and the difference between the correlation parameters of the preset left time domain and the preset right time domain, includes: The average value of the correlation parameters in the preset left time domain and the preset right time domain of the material port to be tested at the target time is used as the local correlation degree of the material port to be tested at the target time; Normalizing the difference between the correlation parameter of the preset right time domain and the correlation parameter of the preset left time domain at the material port to be tested at the target time to obtain the local correlation change degree of the material port to be tested at the target time; The product value of the local correlation degree and the local correlation variation degree is used as the temperature correlation degree of the material port to be measured at the target time.

6. The method for intelligently controlling superheated water based on a material drying process according to claim 1, characterized in that: The obtaining of the correlation difference of the drying device at each moment comprises: The absolute value of the difference in the temperature correlation between the material inlet and the material outlet at the same time is used as the correlation difference of the drying device at each time.

7. The method for intelligently controlling superheated water based on a material drying process according to claim 1, characterized in that: Obtaining the temperature control abnormality of the drying device includes: According to the time sequence, the sequence of the correlation difference degrees of the drying device at all times is used as the correlation difference degree sequence of the drying device, and the sequence of the moisture content of the material at all times is used as the moisture content sequence of the material; A negative correlation normalization process is performed on the Pearson correlation coefficient between the correlation difference sequence and the moisture content sequence to obtain the temperature control abnormality of the drying device.

8. The method for intelligently controlling superheated water based on a material drying process according to claim 1, characterized in that: The method of obtaining the superheated water temperature control parameters of the drying device includes: The inlet and outlet temperature difference coefficient and the temperature control abnormality of the drying device are integrated and normalized to obtain an initial superheated water temperature control value of the drying device; Performing abnormality detection on the correlation difference of the drying device at all times, and taking the time corresponding to the detected abnormal correlation difference as the abnormal time, and obtaining the temperature control influence weight of the drying device based on the change in the number of abnormal times in the preset local time domain at each time; The product of the initial superheated water temperature control value of the drying device and the temperature control influence weight is used as the temperature control value adjustment amount of the drying device; The difference between the initial superheated water temperature control value and the temperature control value adjustment amount is used as the superheated water temperature control parameter of the drying device.

9. The method for intelligently controlling superheated water based on a material drying process according to claim 8, characterized in that: Obtaining the temperature control influence weight of the drying device includes: The number of abnormal moments in the preset local time domain at each moment is used as the number of local abnormal moments at each moment; Performing linear fitting on the number of local abnormal moments at all moments, and performing negative correlation normalization processing on the slope of the fitted straight line to obtain a first temperature control influence coefficient of the drying device; Performing negative correlation mapping on the average value of the number of local abnormal moments at all moments to obtain a second temperature control influence coefficient of the drying device; The first temperature control influence coefficient and the second temperature control influence coefficient are integrated and normalized to obtain a temperature control influence weight of the drying device.

10. The method for intelligently controlling superheated water based on a material drying process according to claim 1, characterized in that: The controlling of the temperature of the superheated water in the next drying stage includes: The product of the superheated water temperature control parameter of the drying device and the standard temperature value of the superheated water in the next drying stage at each moment is used as the temperature adjustment amount of the superheated water in the next drying stage at each moment; The sum of the standard temperature value of the superheated water in the next drying stage at each moment and the temperature adjustment amount is used as the adjusted temperature value of the superheated water in the next drying stage at each moment.

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