A digital chemical production information data management method, platform and system

Abstract

The present invention relates to the field of temperature risk warning, and in particular to a digital chemical production information data management method, platform and system. The method first obtains the actual temperature data of each production process at each historical moment before the current moment, predicts the temperature of the target production process at the historical moment and the current moment, and based on the difference between the actual temperature data and the predicted temperature data of the target production process at the historical moment, adjusts the predicted temperature data at the current moment to obtain an adjusted predicted temperature, adjusts the standard temperature range of the target production process according to the difference between the adjusted predicted temperature at the current moment between the target production process and the subsequent production process, and the position of the target production process, obtains a risk assessment value at the current moment, and then performs a risk warning on the temperature of the target production process at the current moment. The present invention can improve the accuracy of chemical production temperature prediction and promptly issue an early warning for abnormal temperatures in the production process.

Description

Technical Field

[0001] The present invention relates to the field of temperature risk early warning, and in particular to a digital chemical production information data management method, platform and system. Background Art

[0002] Chemical production processes require strict environmental control and complex chemical reactions to ensure the production of high-purity chemical products. Temperature is an important environmental factor in chemical production, affecting the activity and reaction efficiency of catalysts during chemical reactions, and even determining the purity of reaction products. Therefore, in such chemical production processes, monitoring and management of temperature data is very important.

[0003] In order to ensure timely warning of temperature anomalies in each process during the chemical production process, in related technologies, historical temperature data is usually used to predict future temperature data, and the predicted data is compared with the temperature range to determine whether a temperature anomaly warning is needed. However, since the existing method only uses historical temperature data itself for prediction, the endothermic and exothermic phenomena in the chemical reaction process that also cause temperature changes are not considered in the prediction process, resulting in low prediction accuracy. At the same time, chemical production usually includes multiple interconnected production processes. Different production processes have different importance in chemical production and different sensitivity requirements for temperature warnings, which makes the existing method unable to make timely warnings for temperature anomalies in different production processes. Summary of the Invention

[0004] In order to solve the technical problem that existing methods cannot provide timely warnings for temperature anomalies in different production processes, the purpose of the present invention is to provide a digital chemical production information data management method, platform and system. The technical solutions adopted are as follows:

[0005] The present invention proposes a digital chemical production information data management method, the method comprising:

[0006] Obtain the actual temperature data of each production process at each historical moment within a preset time period before the current moment;

[0007] Taking any production process as the target production process, based on the actual temperature data of the target production process at each historical moment, predict the predicted temperature data of the target production process at the historical moment and the current moment; based on the difference between the actual temperature data of the target production process at the historical moment and the predicted temperature data, adjust the predicted temperature data of the target production process at the current moment to obtain the adjusted predicted temperature of the target production process at the current moment;

[0008] Other production processes that are adjacent to and follow the target production process are regarded as successor production processes of the target production process. Based on the difference in the adjusted predicted temperature between the target production process and each successor production process at the current moment, and the position of the target production process among all production processes, the early warning sensitivity of the target production process at the current moment is obtained; based on the early warning sensitivity, the standard temperature range of the target production process is adjusted, and combined with the adjusted predicted temperature of the target production process at the current moment, the risk assessment value of the target production process at the current moment is obtained;

[0009] Based on the risk assessment value, a risk warning is issued for the temperature of the target production process at the current moment.

[0010] Furthermore, the predicted temperature data of the target production process at the historical moment and the current moment include:

[0011] In the preset time period, other historical moments except the previous preset number of historical moments are used as the historical moments to be predicted;

[0012] The current moment or any historical moment to be predicted is used as the target moment to be predicted, and curve fitting is performed on the actual temperature data of the target production process at all moments before the target moment to be predicted to obtain a fitting function of the target production process at the target moment to be predicted. The target moment to be predicted is input into the fitting function, and the predicted temperature data of the target production process at the target moment to be predicted is output.

[0013] Furthermore, obtaining the adjusted predicted temperature of the target production process at the current moment includes:

[0014] The difference between the actual temperature data and the predicted temperature data of the target production process at each historical moment to be predicted is used as the temperature prediction deviation value of the target production process at each historical moment to be predicted;

[0015] The serial number value corresponding to each historical moment to be predicted is used as the numerator, the cumulative value of the serial number values corresponding to all historical moments to be predicted is used as the denominator, and the ratio is used as the reference weight of each historical moment to be predicted;

[0016] Using the reference weights of the historical moments to be predicted, weighted summation is performed on the temperature prediction deviation values of the target production process at the historical moments to be predicted to obtain the temperature adjustment value of the target production process at the current moment;

[0017] The sum of the predicted temperature data and the temperature adjustment amount of the target production process at the current moment is used as the adjusted predicted temperature of the target production process at the current moment.

[0018] Furthermore, obtaining the warning sensitivity of the target production process at the current moment includes:

[0019] Performing negative correlation mapping on the absolute value of the difference between the target production process and each subsequent production process at the current moment, to obtain the temperature similarity between the target production process and each subsequent production process at the current moment;

[0020] The average value of the temperature similarities between the target production process and all subsequent production processes at the current moment is used as the temperature importance of the target production process at the current moment;

[0021] The number of all other production processes after the target production process is used as the numerator, the number of all other production processes before the target production process and the sum of the preset adjustment parameters are used as the denominator, and the ratio is used as the position parameter of the target production process;

[0022] The temperature importance and the position parameter are integrated and normalized to obtain the early warning sensitivity of the target production process at the current moment.

[0023] Furthermore, obtaining the risk assessment value of the target production process at the current moment includes:

[0024] Narrowing the standard temperature range of the target production process according to the warning sensitivity of the target production process at the current moment to obtain an adjusted temperature range of the target production process at the current moment;

[0025] When the adjusted predicted temperature of the target production process at the current moment falls within the adjusted temperature range, the risk assessment value of the target production process at the current moment is set to 0;

[0026] When the adjusted predicted temperature of the target production process at the current moment is greater than the upper limit of the adjusted temperature range, a risk assessment value of the target production process at the current moment is obtained based on the difference between the adjusted predicted temperature of the target production process at the current moment and the upper limit of the adjusted temperature range;

[0027] When the adjusted predicted temperature of the target production process at the current moment is less than the lower limit value of the adjusted temperature range, the risk assessment value of the target production process at the current moment is obtained based on the difference between the adjusted predicted temperature of the target production process at the current moment and the lower limit value of the adjusted temperature range.

[0028] Furthermore, obtaining the adjustment temperature range of the target production process at the current moment includes:

[0029] half of the product of the warning sensitivity of the target production process at the current moment and the length of the standard temperature range of the target production process is used as the endpoint adjustment amount of the standard temperature range of the target production process at the current moment;

[0030] Obtain the adjustment temperature range of the target production process at the current moment, the lower limit value of the adjustment temperature range is equal to the sum of the lower limit value of the standard temperature range of the target production process and the endpoint adjustment amount, and the upper limit value of the adjustment temperature range is equal to the difference between the upper limit value of the standard temperature range of the target production process and the endpoint adjustment amount.

[0031] Furthermore, the risk warning of the temperature of the target production process at the current moment includes:

[0032] If the risk assessment value of the target production process at the current moment is equal to 0, no risk warning will be issued;

[0033] If the risk assessment value of the target production process at the current moment is greater than 0, different levels of risk warnings will be issued to the target production process based on other production processes adjacent to the target production process and the risk assessment value of the target production process at the current moment.

[0034] Furthermore, the issuing of different levels of risk warnings for the target production process includes:

[0035] Normalizing the average of the risk assessment values of all other production processes adjacent to the target production process and the target production process at the current moment to obtain the warning level coefficient of the target production process at the current moment;

[0036] If the warning level coefficient is less than the preset first threshold, a first-level risk warning is issued; if the warning level coefficient is not less than the preset first threshold and less than the preset second threshold, a second-level risk warning is issued; if the warning level coefficient is not less than the preset second threshold, a third-level risk warning is issued, wherein the severity of the first-level risk warning, the second-level risk warning and the third-level risk warning gradually increases.

[0037] The present invention also proposes a digital chemical production information data management platform, which includes:

[0038] The data acquisition module is used to obtain the actual temperature data of each production process at each historical moment in a preset time period before the current moment;

[0039] The temperature prediction module is used to take any production process as the target production process, and predict the predicted temperature data of the target production process at the historical moment and the current moment based on the actual temperature data of the target production process at each historical moment; based on the difference between the actual temperature data of the target production process at the historical moment and the predicted temperature data, adjust the predicted temperature data of the target production process at the current moment to obtain the adjusted predicted temperature of the target production process at the current moment;

[0040] a risk assessment module for treating other production processes adjacent to and following a target production process as subsequent production processes of the target production process, and obtaining the early warning sensitivity of the target production process at the current moment based on the difference in the adjusted predicted temperature between the target production process and each subsequent production process at the current moment, as well as the position of the target production process among all production processes; adjusting the standard temperature range of the target production process based on the early warning sensitivity, and obtaining a risk assessment value of the target production process at the current moment in combination with the adjusted predicted temperature of the target production process at the current moment;

[0041] The temperature warning module is used to issue a risk warning for the temperature of each production process at the current moment based on the risk assessment value.

[0042] The present invention also proposes a digital chemical production information data management system, which includes a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, it implements any one of the steps of a digital chemical production information data management method.

[0043] The present invention has the following beneficial effects:

[0044] The present invention takes into account the inability of existing methods to provide timely warnings for temperature anomalies in different production processes. Therefore, the actual temperature data of each production process at each historical moment in a preset time period before the current moment is first obtained, and then the predicted temperature data of the target production process at the historical moment and the current moment are predicted. Considering that the endothermic and exothermic phenomena in the actual chemical reaction process will cause temperature changes, the prediction results obtained based solely on the temperature data at the historical moment will have a large deviation compared to the actual temperature. Therefore, the difference between the actual temperature data and the predicted temperature data of the target production process at the historical moment is analyzed, and the deviation between the actual temperature and the predicted temperature is then adjusted. The obtained adjusted predicted temperature is closer to the actual temperature, thereby improving the accuracy of the prediction result and ensuring that a timely warning can be issued subsequently. At the same time, chemical production usually includes multiple interconnected production processes. Different production processes have different importance in chemical production and different sensitivity requirements for temperature warning. Therefore, the obtained warning sensitivity reflects the sensitivity of the target production process at the current moment to provide a temperature anomaly warning. Then, the obtained risk assessment value is used to provide a timely warning for the temperature situation of the target production process at the current moment. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] 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.

[0046] Figure 1 A flow chart of a digital chemical production information data management method provided by one embodiment of the present invention;

[0047] Figure 2 A framework diagram of a digital chemical production information data management platform provided by one embodiment of the present invention;

[0048] Figure 3 A schematic diagram comparing the temperature prediction effects of a catalytic reaction process provided by one embodiment of the present invention;

[0049] Figure 4 A schematic diagram of correlation analysis between sensitivity and temperature deviation provided by one embodiment of the present invention;

[0050] Figure 5 A schematic diagram of the relationship between dynamic threshold intervals and risk levels provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0051] To further illustrate the technical means and effects employed by the present invention to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail a digital chemical production information data management method, platform, and system according to the present invention, including its specific implementation, structure, features, and effects. In the following description, different 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.

[0052] 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.

[0053] The following describes in detail a digital chemical production information data management method, platform and system provided by the present invention with reference to the accompanying drawings.

[0054] See also Figure 1 , which shows a flow chart of a digital chemical production information data management method provided by one embodiment of the present invention, the method comprising:

[0055] Step S1: Acquire the actual temperature data of each production process at each historical moment within a preset time period before the current moment.

[0056] Since the chemical production process usually involves multiple production processes, and different production processes have different temperature requirements, the embodiment of the present invention first deploys temperature sensors in the environment of each production process in the chemical production, and uses temperature sensors to collect the actual temperature data of each production process at each historical moment in a preset time period before the current moment. The actual temperature data at the current moment is unknown, and it is necessary to predict the temperature at the current moment and determine whether to issue an early warning. The time interval for data collection is set to 5~10 seconds, and the preset time period is usually 1~2 hours. In one embodiment of the present invention, the time interval for data collection is set to 10 seconds, and the preset time period is set to 1 hour. The specific values of the time interval for data collection and the preset time period can also be set by the implementer according to the specific implementation scenario, and are not limited here.

[0057] It should be noted that the various production processes of chemical production are interconnected, and in actual chemical production, the various production processes are run simultaneously. For any production process except the first production process and the last production process, there are multiple adjacent production processes after it, and there are multiple adjacent production processes before it. Adjacent here means directly connected. For example, the adjacent production processes before production process C are A and B, and the adjacent production processes before production process C are D and E. After production processes A and B are completed, they will directly enter production process C, and after production process C is completed, they will directly enter production processes D and E.

[0058] Step S2: Take any production process as the target production process, and predict the predicted temperature data of the target production process at historical moments and the current moment based on the actual temperature data of the target production process at each historical moment; adjust the predicted temperature data of the target production process at the current moment based on the difference between the actual temperature data and the predicted temperature data of the target production process at the historical moment to obtain the adjusted predicted temperature of the target production process at the current moment.

[0059] Since different production processes have different requirements for temperature control, any production process is first analyzed and any production process is taken as the target production process. In order to make a timely warning of temperature anomalies in the target production process, it is necessary to predict the temperature of the target production process at the current moment, and the actual temperature data of the target production process changing over time can show its changing trend in the future. At the same time, since the endothermic and exothermic phenomena in the actual chemical reaction process will cause temperature changes, the prediction results obtained based only on the temperature data at historical moments have a large deviation compared to the actual temperature. Therefore, the embodiment of the present invention also needs to predict the temperature of the target production process at historical moments, so as to obtain the predicted temperature data of the target production process at historical moments and the current moment. Subsequently, the predicted temperature data at the current moment can be adjusted based on the difference between the predicted temperature data and the actual temperature data of the target production process at historical moments to improve the accuracy of the temperature prediction of the target production process at the current moment, so as to facilitate the subsequent timely warning of temperature anomalies in the target production process at the current moment.

[0060] Preferably, in one embodiment of the present invention, the method for obtaining the predicted temperature data of the target production process at the historical moment and the current moment specifically includes:

[0061] In order to ensure the reliability of the temperature prediction of the target production process at the historical moment, it is necessary to reserve enough actual temperature data. Therefore, within the preset time period, other historical moments except the first preset number of historical moments will be used as the historical moments to be predicted. Subsequently, the temperature of the target production process at the historical moments to be predicted and the current moment can be predicted. Among them, the preset number is generally 20~50. In one embodiment of the present invention, the preset number is set to 30. The specific value of the preset number can also be set by the implementer according to the specific implementation scenario, and is not limited here.

[0062] The current moment or any historical moment to be predicted is used as the target moment to be predicted, and curve fitting is performed on the actual temperature data of the target production process at all moments before the target moment to be predicted to obtain the fitting function of the target production process at the target moment to be predicted. The fitting function is the function corresponding to the fitting curve and is a function of time. Therefore, the target moment to be predicted can be input into the fitting function, and the predicted temperature data of the target production process at the target moment to be predicted is output. In the embodiment of the present invention, the least squares method or other methods can be selected for curve fitting, which is not limited here.

[0063] In other embodiments of the present invention, a time series prediction algorithm may be used to perform temperature prediction, for example, an autoregressive integrated moving average (ARIMA) model or an exponential smoothing algorithm may be used, which is not limited here.

[0064] The same method as above can be used to obtain the predicted temperature data of the target production process at each historical moment to be predicted and the current moment. From the above analysis, it can be seen that there is a deviation between the prediction result based only on the actual temperature data itself and the actual temperature data. The reason for this deviation is that the heat absorption and heat generation phenomena in the actual chemical production process will cause temperature changes. Therefore, the embodiment of the present invention is based on the difference between the actual temperature data and the predicted temperature data of the target production process at historical moments, and analyzes the deviation between the predicted temperature data and the actual temperature data under the influence of heat absorption and heat generation in the actual chemical production process. The predicted temperature data of the target production process at the current moment is adjusted accordingly to obtain the adjusted predicted temperature of the target production process at the current moment, thereby improving the accuracy of the temperature prediction of the target production process at the current moment, so as to facilitate timely early warning in the future.

[0065] Preferably, in one embodiment of the present invention, the method for obtaining the adjusted predicted temperature of the target production process at the current moment specifically includes:

[0066] The difference between the actual temperature data and the predicted temperature data of the target production process at each historical moment to be predicted is used as the temperature prediction deviation value of the target production process at each historical moment to be predicted.

[0067] Taking into account that in the process of adjusting the predicted temperature data at the current moment, the reference value of the temperature prediction deviation value of the historical moment to be predicted that is closer to the current moment is greater, the serial number value corresponding to each historical moment to be predicted can be used as the numerator, and the cumulative value of the serial number values corresponding to all historical moments to be predicted can be used as the denominator. The ratio can be used as the reference weight of each historical moment to be predicted, and the reference weight of each historical moment to be predicted can be used to perform weighted summation on the temperature prediction deviation values of the target production process at each historical moment to be predicted to obtain the temperature adjustment amount of the target production process at the current moment.

[0068] Then, the sum of the predicted temperature data of the target production process at the current moment and the temperature adjustment amount is used as the adjusted predicted temperature of the target production process at the current moment.

[0069] As an example, in one embodiment of the present invention, the expression for the adjusted predicted temperature of the target production process at the current moment may be specifically, for example, as follows:

[0070]

[0071]

[0072] in, represents the adjusted predicted temperature of the target production process at the current moment; Represents the predicted temperature data of the target production process at the current moment; Indicates the The reference weight of each historical moment to be predicted; Indicates that the target production process is in Actual temperature data of the historical moment to be predicted; Indicates that the target production process is in The predicted temperature data for the historical moment to be predicted; Indicates that the target production process is in The temperature prediction deviation value of the historical moment to be predicted; represents the number of historical moments to be predicted; Indicates the temperature adjustment amount of the target production process at the current moment; Indicates the The serial number value corresponding to the historical moment to be predicted; Indicates the The serial number value corresponding to the historical moment to be predicted; Indicates the cumulative value of the sequence number values corresponding to all historical moments to be predicted.

[0073] The same method as above can be used to obtain the adjusted predicted temperature of each production process at the current moment.

[0074] Step S3: other production processes that are adjacent to the target production process and are located after the target production process are regarded as subsequent production processes of the target production process. According to the difference in the adjusted predicted temperature between the target production process and each subsequent production process at the current moment, and the position of the target production process in all production processes, the early warning sensitivity of the target production process at the current moment is obtained; according to the early warning sensitivity, the standard temperature range of the target production process is adjusted, and combined with the adjusted predicted temperature of the target production process at the current moment, the risk assessment value of the target production process at the current moment is obtained.

[0075] For the target production process, there may be multiple adjacent production processes after it. When there is a problem with the temperature control of the target production process, it will directly affect the chemical production quality of the adjacent production processes after it. Therefore, the embodiment of the present invention first uses other production processes that are adjacent to the target production process and are located after the target production process as the subsequent production processes of the target production process. The closer the adjusted predicted temperatures between the target production process and the subsequent production processes at the current moment are, the more serious the impact on the subsequent production processes when the temperature of the target production process is abnormal. Therefore, it is necessary to perform a more stringent and sensitive temperature anomaly warning on the target production process. At the same time, when the target production process is in all the production processes of the entire chemical production, The closer the position is to the front, the more serious the impact on the entire chemical production will be when the temperature of the target production process is abnormal, and a more stringent and sensitive temperature anomaly warning will be required for the target production process. Therefore, the warning sensitivity of the target production process at the current moment can be obtained based on the difference in the adjusted predicted temperature between the target production process and each subsequent production process at the current moment, as well as the position of the target production process in all production processes. The warning sensitivity reflects the sensitivity of the temperature anomaly warning for the target production process at the current moment. Subsequently, the standard temperature range of the target production process can be adjusted through the warning sensitivity to ensure that a timely warning can be made when the temperature of the target production process at the current moment is abnormal.

[0076] Preferably, in one embodiment of the present invention, the method for obtaining the warning sensitivity of the target production process at the current moment specifically includes:

[0077] A negative correlation mapping is performed on the absolute value of the difference in the adjusted predicted temperature between the target production process and each subsequent production process at the current moment to obtain the temperature similarity between the target production process and each subsequent production process at the current moment. The greater the temperature similarity, the closer the adjusted predicted temperature between the target production process and each subsequent production process at the current moment is. The average value of the temperature similarity between the target production process and all subsequent production processes at the current moment can be used as the temperature importance of the target production process at the current moment. The greater the temperature importance, the greater the impact on the production quality of the subsequent production process when the temperature of the target production process is abnormal at the current moment, which means that a more sensitive temperature anomaly warning is needed for the target production process.

[0078] It should be noted that for the last production process, there is no other adjacent production process after it, that is, the last production process has no subsequent production process. Therefore, the temperature importance of the last production process can be set to a value of 0 to ensure the smooth progress of subsequent calculations.

[0079] The number of all other production processes after the target production process is used as the numerator, the number of all other production processes before the target production process and the sum of the preset adjustment parameters are used as the denominator, and the ratio is used as the position parameter of the target production process. The larger the position parameter is, the closer the target production process is to the front, and thus the more sensitive the temperature anomaly warning is needed for the target production process.

[0080] Then, the importance of temperature and position parameters are integrated and normalized, and the calculation results are limited to range, thereby obtaining the early warning sensitivity of the target production process at the current moment.

[0081] In the embodiment of the present invention, the integration of temperature importance and position parameter can be achieved by calculating the sum or product of the two, which is not limited here.

[0082] As an example, in one embodiment of the present invention, the expression of the warning sensitivity of the target production process at the current moment can be specifically, for example, as follows:

[0083]

[0084] in, Indicates the warning sensitivity of the target production process at the current moment; Represents the quantity of all other production processes that follow the target production process; represents the quantity of all other production processes preceding the target production process; 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; Position parameters representing the target production process; represents the adjusted predicted temperature of the target production process at the current moment; The target production process The adjusted predicted temperature of each subsequent production process at the current moment; Indicates the target production process and The temperature similarity between the subsequent production processes at the current moment; Indicates the preset adjustment coefficient, used to prevent the denominator from being 0. The value range is In one embodiment of the present invention, Set to 0.001, The specific value of can also be set by the implementer according to the specific implementation scenario and is not limited here; Indicates the temperature importance of the target production process at the current moment; Indicates the number of subsequent production processes of the target production process; represents a hyperbolic tangent function, which is used for normalization processing. In other embodiments of the present invention, other functions such as activation functions may also be used for normalization processing, which is not limited here.

[0085] It should be noted that in other embodiments of the present invention, negative correlation mapping may be achieved through other basic mathematical operations, which will not be described in detail here.

[0086] The greater the warning sensitivity of the target production process at the current moment, the more sensitive the abnormal temperature warning of the target production process is needed at the current moment. Therefore, based on the warning sensitivity of the target production process at the current moment, the standard temperature range of the target production process can be adjusted, and combined with the adjusted predicted temperature of the target production process at the current moment, the risk assessment value of the target production process at the current moment can be obtained. Subsequently, based on the risk assessment value, it can be judged whether it is necessary to issue a temperature abnormality warning for the target production process at the current moment, thereby improving the timeliness of the temperature warning. Among them, the standard temperature range of the production process is a known range to ensure that the temperature of each production process is maintained within the corresponding standard temperature range. Each production process has a standard temperature range, and there are certain differences in the standard temperature ranges of different production routes.

[0087] Preferably, in one embodiment of the present invention, the method for obtaining the risk assessment value of the target production process at the current moment specifically includes:

[0088] First, in order to improve the sensitivity of abnormal temperature warning for the target production process, it is necessary to narrow the standard temperature range of the target production process according to the warning sensitivity of the target production process at the current moment, and obtain the adjusted temperature range of the target production process at the current moment.

[0089] Preferably, in one embodiment of the present invention, the method for obtaining the adjustment temperature range of the target production process at the current moment specifically includes:

[0090] Half of the product of the warning sensitivity of the target production process at the current moment and the length of the standard temperature range of the target production process is used as the endpoint adjustment amount of the standard temperature range of the target production process at the current moment, where the length of the standard temperature range of the target production process is equal to the difference between the upper limit and the lower limit of the standard temperature range.

[0091] Obtain the adjustment temperature range of the target production process at the current moment. The lower limit value of the adjustment temperature range is equal to the sum of the lower limit value of the standard temperature range of the target production process and the endpoint adjustment amount. The upper limit value of the adjustment temperature range is equal to the difference between the upper limit value of the standard temperature range of the target production process and the endpoint adjustment amount.

[0092] As an example, in one embodiment of the present invention, the adjustment temperature range of the target production process at the current moment can be specifically expressed as:

[0093]

[0094] in, Indicates the lower limit of the adjustment temperature range of the target production process at the current moment; Indicates the upper limit of the adjustment temperature range of the target production process at the current moment; Indicates the lower limit of the standard temperature range of the target production process; Indicates the upper limit of the standard temperature range of the target production process; Indicates the length of the standard temperature range for the target production process; Indicates the warning sensitivity of the target production process at the current moment; Indicates the endpoint adjustment amount of the standard temperature range of the target production process at the current moment.

[0095] When the adjusted predicted temperature of the target production process at the current moment falls within the adjustment temperature range, it indicates that the temperature of the target production process at that moment is not abnormal, and the risk assessment value of the target production process at the current moment is set to 0.

[0096] When the adjusted predicted temperature of the target production process at the current moment is greater than the upper limit value of the adjustment temperature range, it means that the temperature of the target production process at that moment is abnormally too high. Based on the difference between the adjusted predicted temperature of the target production process at the current moment and the upper limit value of the adjustment temperature range, the risk assessment value of the target production process at the current moment is obtained.

[0097] In an embodiment of the present invention, the difference between the adjusted predicted temperature of the target production process at the current moment and the upper limit value of the adjusted temperature range, or the square of the difference, can be used as the risk assessment value of the target production process at the current moment, which is not limited here.

[0098] When the adjusted predicted temperature of the target production process at the current moment is less than the lower limit of the adjustment temperature range, it means that the temperature of the target production process at that moment is abnormally too low. Based on the difference between the adjusted predicted temperature of the target production process at the current moment and the lower limit of the adjustment temperature range, the risk assessment value of the target production process at the current moment is obtained.

[0099] In an embodiment of the present invention, the difference between the lower limit value of the adjustment temperature range and the adjusted predicted temperature of the target production process at the current moment, or the square of the difference, can be used as the risk assessment value of the target production process at the current moment, which is not limited here.

[0100] As an example, in one embodiment of the present invention, the risk assessment value of the target production process at the current moment may be expressed as follows:

[0101]

[0102] in, Indicates the risk assessment value of the target production process at the current moment; represents the adjusted predicted temperature of the target production process at the current moment; Indicates the lower limit of the adjustment temperature range of the target production process at the current moment; Indicates the upper limit of the adjustment temperature range of the target production process at the current moment.

[0103] At this point, the risk assessment value of the target production process at the current moment is obtained.

[0104] Step S4: Based on the risk assessment value, a risk warning is issued for the temperature of the target production process at the current moment.

[0105] After obtaining the risk assessment value of the target production process at the current moment, a risk warning can be issued for the temperature of the target production process at the current moment based on the risk assessment value, thereby making timely warnings for temperature anomalies in the target production process.

[0106] Preferably, in one embodiment of the present invention, the method for providing a risk warning for the temperature of the target production process at the current moment specifically includes:

[0107] If the risk assessment value of the target production process at the current moment is equal to 0, it means that there is no abnormality in the temperature of the target production process at the current moment, and no risk warning is issued.

[0108] If the risk assessment value of the target production process at the current moment is greater than 0, it means that the temperature of the target production process at the current moment is abnormal. Then, different levels of risk warnings can be issued to the target production process based on other production processes adjacent to the target production process and the risk assessment value of the target production process at the current moment.

[0109] Preferably, in one embodiment of the present invention, the method for issuing risk warnings of different levels for a target production process specifically includes:

[0110] The greater the risk assessment value of the target production process at the current moment, and the greater the risk assessment values of other production processes adjacent to the target production process at the current moment, the more the temperature of the target production process and the adjacent production processes deviate from the normal temperature range at the current moment, and a more serious early warning information needs to be issued for the target production process. Therefore, the average value of the sum of the risk assessment values of all other production processes adjacent to the target production process and the target production process at the current moment can be normalized, and the calculation result can be limited to range, thereby obtaining the warning level coefficient of the target production process at the current moment.

[0111] In one embodiment of the present invention, the normalization process may specifically be, for example, maximum and minimum value normalization process. In other embodiments of the present invention, other normalization methods may be selected according to a specific range of numerical values, which will not be described in detail.

[0112] As an example, in one embodiment of the present invention, the expression of the warning level coefficient of the target production process at the current moment can be specifically, for example, as follows:

[0113]

[0114] in, Indicates the warning level coefficient of the target production process at the current moment; Indicates the risk assessment value of the target production process at the current moment; Indicates the first Risk assessment value of other production processes at the current moment; Indicates the number of other production processes adjacent to the target production process; Represents the normalization function, used for normalization processing.

[0115] If the warning level coefficient is less than the preset first threshold, a first-level risk warning is issued; if the warning level coefficient is not less than the preset first threshold and less than the preset second threshold, a second-level risk warning is issued; if the warning level coefficient is not less than the preset second threshold, a third-level risk warning is issued, wherein the severity of the first-level risk warning, the second-level risk warning and the third-level risk warning gradually increases. In one embodiment of the present invention, indicator lights of different colors can be used to represent warning information of different levels.

[0116] The value range of the preset first threshold is , the value range of the preset first threshold is In one embodiment of the present invention, the preset first threshold is set to 0.3, and the preset second threshold is set to 0.7. The specific values of the preset first threshold and the preset second threshold can also be set by the implementer according to the specific implementation scenario and are not limited here.

[0117] The same method as above can be used to provide early warning of the temperature of each production process in chemical production.

[0118] One embodiment of the present invention provides a digital chemical production information data management platform, please refer to Figure 2 , which shows a framework diagram of a digital chemical production information data management platform provided by one embodiment of the present invention. The management platform includes:

[0119] The data acquisition module is used to obtain the actual temperature data of each production process at each historical moment in a preset time period before the current moment;

[0120] The temperature prediction module is used to take any production process as the target production process, and predict the target production process's temperature data at historical moments and the current moment based on the target production process's actual temperature data at each historical moment; based on the difference between the target production process's actual temperature data at historical moments and the predicted temperature data, adjust the target production process's predicted temperature data at the current moment to obtain the adjusted predicted temperature of the target production process at the current moment;

[0121] The risk assessment module is used to treat other production processes that are adjacent to and subsequent to the target production process as subsequent production processes of the target production process, and obtain the early warning sensitivity of the target production process at the current moment based on the difference in the adjusted predicted temperature between the target production process and each subsequent production process at the current moment, as well as the position of the target production process among all production processes; based on the early warning sensitivity, the standard temperature range of the target production process is adjusted, and combined with the adjusted predicted temperature of the target production process at the current moment, the risk assessment value of the target production process at the current moment is obtained;

[0122] The temperature warning module is used to issue risk warnings for the temperature of each production process at the current moment based on the risk assessment value.

[0123] See also Figure 3-Figure 5 , Figure 3 A schematic diagram comparing the temperature prediction effects of a catalytic reaction process provided by one embodiment of the present invention; Figure 4 A schematic diagram of correlation analysis between sensitivity and temperature deviation provided by one embodiment of the present invention; Figure 5 A schematic diagram of the relationship between the dynamic threshold interval and the risk level provided by an embodiment of the present invention; Figure 3-Figure 5 As evidenced by the relevant content, this application can effectively realize the early warning effect of the temperature of each production process of chemical production in the temperature prediction module and risk assessment module.

[0124] One embodiment of the present invention provides a digital chemical production information data management system, which includes a memory, a processor and a computer program, wherein the memory is used to store the corresponding computer program, and the processor is used to run the corresponding computer program. When the computer program runs in the processor, it can implement the method described in steps S1 to S4.

[0125] 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.

[0126] 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 digital chemical production information data management method, characterized in that: The method comprises: Obtain the actual temperature data of each production process at each historical moment within a preset time period before the current moment; Taking any production process as the target production process, based on the actual temperature data of the target production process at each historical moment, predict the predicted temperature data of the target production process at the historical moment and the current moment; based on the difference between the actual temperature data of the target production process at the historical moment and the predicted temperature data, adjust the predicted temperature data of the target production process at the current moment to obtain the adjusted predicted temperature of the target production process at the current moment; Other production processes that are adjacent to and follow the target production process are regarded as successor production processes of the target production process. Based on the difference in the adjusted predicted temperature between the target production process and each successor production process at the current moment, and the position of the target production process among all production processes, the early warning sensitivity of the target production process at the current moment is obtained; based on the early warning sensitivity, the standard temperature range of the target production process is adjusted, and combined with the adjusted predicted temperature of the target production process at the current moment, the risk assessment value of the target production process at the current moment is obtained; Based on the risk assessment value, a risk warning is issued for the temperature of the target production process at the current moment; The obtaining of the early warning sensitivity of the target production process at the current moment includes: Performing negative correlation mapping on the absolute value of the difference between the target production process and each subsequent production process at the current moment, to obtain the temperature similarity between the target production process and each subsequent production process at the current moment; The average value of the temperature similarities between the target production process and all subsequent production processes at the current moment is used as the temperature importance of the target production process at the current moment; The number of all other production processes after the target production process is used as the numerator, the number of all other production processes before the target production process and the sum of the preset adjustment parameters are used as the denominator, and the ratio is used as the position parameter of the target production process; The temperature importance and the position parameter are integrated and normalized to obtain the early warning sensitivity of the target production process at the current moment.

2. A digital chemical production information data management method according to claim 1, characterized in that: The predicted temperature data of the target production process at the historical moment and the current moment include: In the preset time period, other historical moments except the previous preset number of historical moments are used as the historical moments to be predicted; The current moment or any historical moment to be predicted is used as the target moment to be predicted, and curve fitting is performed on the actual temperature data of the target production process at all moments before the target moment to be predicted to obtain a fitting function of the target production process at the target moment to be predicted. The target moment to be predicted is input into the fitting function, and the predicted temperature data of the target production process at the target moment to be predicted is output.

3. A digital chemical production information data management method according to claim 2, characterized in that: The step of obtaining the adjusted predicted temperature of the target production process at the current moment includes: The difference between the actual temperature data and the predicted temperature data of the target production process at each historical moment to be predicted is used as the temperature prediction deviation value of the target production process at each historical moment to be predicted; The serial number value corresponding to each historical moment to be predicted is used as the numerator, the cumulative value of the serial number values corresponding to all historical moments to be predicted is used as the denominator, and the ratio is used as the reference weight of each historical moment to be predicted; Using the reference weights of the historical moments to be predicted, weighted summation is performed on the temperature prediction deviation values of the target production process at the historical moments to be predicted to obtain the temperature adjustment value of the target production process at the current moment; The sum of the predicted temperature data and the temperature adjustment amount of the target production process at the current moment is used as the adjusted predicted temperature of the target production process at the current moment.

4. A digital chemical production information data management method according to claim 1, characterized in that: Obtaining the risk assessment value of the target production process at the current moment includes: Narrowing the standard temperature range of the target production process according to the warning sensitivity of the target production process at the current moment to obtain an adjusted temperature range of the target production process at the current moment; When the adjusted predicted temperature of the target production process at the current moment falls within the adjusted temperature range, the risk assessment value of the target production process at the current moment is set to 0; When the adjusted predicted temperature of the target production process at the current moment is greater than the upper limit of the adjusted temperature range, a risk assessment value of the target production process at the current moment is obtained based on the difference between the adjusted predicted temperature of the target production process at the current moment and the upper limit of the adjusted temperature range; When the adjusted predicted temperature of the target production process at the current moment is less than the lower limit value of the adjusted temperature range, the risk assessment value of the target production process at the current moment is obtained based on the difference between the adjusted predicted temperature of the target production process at the current moment and the lower limit value of the adjusted temperature range.

5. A digital chemical production information data management method according to claim 4, characterized in that: The step of obtaining the adjustment temperature range of the target production process at the current moment includes: half of the product of the warning sensitivity of the target production process at the current moment and the length of the standard temperature range of the target production process is used as the endpoint adjustment amount of the standard temperature range of the target production process at the current moment; Obtain the adjustment temperature range of the target production process at the current moment, the lower limit value of the adjustment temperature range is equal to the sum of the lower limit value of the standard temperature range of the target production process and the endpoint adjustment amount, and the upper limit value of the adjustment temperature range is equal to the difference between the upper limit value of the standard temperature range of the target production process and the endpoint adjustment amount.

6. A digital chemical production information data management method according to claim 1, characterized in that: The risk warning of the temperature of the target production process at the current moment includes: If the risk assessment value of the target production process at the current moment is equal to 0, no risk warning will be issued; If the risk assessment value of the target production process at the current moment is greater than 0, different levels of risk warnings will be issued to the target production process based on other production processes adjacent to the target production process and the risk assessment value of the target production process at the current moment.

7. A digital chemical production information data management method according to claim 6, characterized in that: The risk warnings of different levels issued for the target production process include: Normalizing the average of the risk assessment values of all other production processes adjacent to the target production process and the target production process at the current moment to obtain the warning level coefficient of the target production process at the current moment; If the warning level coefficient is less than the preset first threshold, a first-level risk warning is issued; if the warning level coefficient is not less than the preset first threshold and less than the preset second threshold, a second-level risk warning is issued; if the warning level coefficient is not less than the preset second threshold, a third-level risk warning is issued, wherein the severity of the first-level risk warning, the second-level risk warning and the third-level risk warning gradually increases.

8. A digital chemical production information data management platform, characterized by: The management platform includes: The data acquisition module is used to obtain the actual temperature data of each production process at each historical moment in a preset time period before the current moment; The temperature prediction module is used to take any production process as the target production process, and predict the predicted temperature data of the target production process at the historical moment and the current moment based on the actual temperature data of the target production process at each historical moment; based on the difference between the actual temperature data of the target production process at the historical moment and the predicted temperature data, adjust the predicted temperature data of the target production process at the current moment to obtain the adjusted predicted temperature of the target production process at the current moment; a risk assessment module for treating other production processes adjacent to and following a target production process as subsequent production processes of the target production process, and obtaining the early warning sensitivity of the target production process at the current moment based on the difference in the adjusted predicted temperature between the target production process and each subsequent production process at the current moment, as well as the position of the target production process among all production processes; adjusting the standard temperature range of the target production process based on the early warning sensitivity, and obtaining a risk assessment value of the target production process at the current moment in combination with the adjusted predicted temperature of the target production process at the current moment; A temperature warning module is used to issue a risk warning for the temperature of each production process at the current moment based on the risk assessment value; The obtaining of the early warning sensitivity of the target production process at the current moment includes: Performing negative correlation mapping on the absolute value of the difference between the target production process and each subsequent production process at the current moment, to obtain the temperature similarity between the target production process and each subsequent production process at the current moment; The average value of the temperature similarities between the target production process and all subsequent production processes at the current moment is used as the temperature importance of the target production process at the current moment; The number of all other production processes after the target production process is used as the numerator, the number of all other production processes before the target production process and the sum of the preset adjustment parameters are used as the denominator, and the ratio is used as the position parameter of the target production process; The temperature importance and the position parameter are integrated and normalized to obtain the early warning sensitivity of the target production process at the current moment.

9. A digital chemical production information data management system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

Images