Material data processing method and device based on oil refining and chemical engineering, equipment and medium

Abstract

The invention provides a material data processing method and device based on oil refining and chemical engineering, equipment and a medium. The method comprises the steps of obtaining material data of oil refining and chemical engineering nodes; the oil refining and chemical engineering node represents a device for processing materials in the oil refining and chemical engineering process, and the material data comprises feeding quality and discharging quality of the materials in the oil refining and chemical engineering node; if it is determined that the to-be-verified data exists in the discharging mass of the oil refining and chemical engineering node, the discharging mass of an adjacent node of the oil refining and chemical engineering node is obtained; the to-be-verified data is an abnormal value or a missing value, and the adjacent node represents a device for receiving the to-be-verified data generated by the oil refining and chemical engineering node in the oil refining and chemical engineering process; according to the discharging quality of the adjacent nodes and the feeding quality of the oil refining and chemical engineering nodes, the to-be-verified data are adjusted, and the adjusted discharging quality of the oil refining and chemical engineering nodes is obtained. By means of the method, the abnormal value or the missing value of discharging of the device can be adjusted, the data precision is improved, and balance analysis of the materials is achieved.

Description

Technical Field

[0001] This application relates to big data technology, and in particular to a method, apparatus, equipment and medium for processing material data based on oil refining and chemical industry. Background Technology

[0002] In the early stages of the oil refining and chemical industry, material processing mainly involved simple physical separation and preliminary chemical conversion. During this process, tracking and balancing material quality relied primarily on manual measurement and simple recording.

[0003] However, data read manually from instruments may contain outliers or missing values, resulting in low data accuracy. This leads to a lack of precise quantitative analysis of the trajectory of various components in crude oil during processing, affecting the effectiveness of material processing. Summary of the Invention

[0004] This application provides a method, apparatus, equipment, and medium for processing material data based on oil refining and chemical engineering, in order to improve the accuracy of material data.

[0005] Firstly, this application provides a method for processing material data based on oil refining and chemical engineering, including:

[0006] Acquire material data for refining and chemical processing nodes; wherein, the refining and chemical processing node represents a device that processes materials in the refining and chemical process, and the material data includes the feed quality and discharge quality of the materials in the refining and chemical processing node;

[0007] If it is determined that there is data to be verified in the output quality of the refining and chemical node, then the output quality of the neighboring node of the refining and chemical node is obtained; wherein, the data to be verified is an outlier or a missing value, and the neighboring node represents a device that receives the data to be verified produced by the refining and chemical node in the refining and chemical process.

[0008] Based on the discharge quality of the neighboring nodes and the feed quality of the refining and chemical node, the data to be verified is adjusted to obtain the adjusted discharge quality of the refining and chemical node.

[0009] Secondly, this application provides a processing apparatus for material data based on oil refining and chemical engineering, comprising:

[0010] The first acquisition unit is used to acquire material data of the refining and chemical node; wherein, the refining and chemical node represents a device for material processing in the refining and chemical process, and the material data includes the feed quality and discharge quality of the material in the refining and chemical node.

[0011] The second acquisition unit is used to acquire the output quality of neighboring nodes of the refining and chemical node if it is determined that there is data to be verified in the output quality of the refining and chemical node; wherein, the data to be verified is an outlier or a missing value, and the neighboring node represents a device that receives the data to be verified produced by the refining and chemical node in the refining and chemical process.

[0012] The data adjustment unit is used to adjust the data to be verified based on the discharge quality of the neighboring nodes and the feed quality of the refining and chemical node, so as to obtain the adjusted discharge quality of the refining and chemical node.

[0013] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0014] The memory stores computer-executed instructions;

[0015] The processor executes computer execution instructions stored in the memory to implement the method as described in the first aspect.

[0016] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method described in the first aspect.

[0017] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect.

[0018] This application provides a method, apparatus, equipment, and medium for processing material data in oil refining and chemical engineering. By acquiring material data from oil refining and chemical engineering nodes, it determines the feed quality and discharge quality of the units in the oil refining and chemical engineering process. It checks for outliers or missing values ​​in the discharge quality data to ensure timely monitoring of discharge quality and avoid storing erroneous data. If no outliers or missing values ​​are found, the data is considered correct; if outliers or missing values ​​are found, the discharge quality of neighboring nodes is acquired to determine the discharge quality of the next stage unit. Based on the discharge quality of neighboring nodes and the feed quality of the oil refining and chemical engineering node, outliers and missing values ​​are adjusted to obtain the correct discharge quality. By combining the discharge quality of neighboring nodes, the data to be verified for the current oil refining and chemical engineering node is corrected, avoiding data deviations throughout the entire process caused by considering only a single node's data, thus improving the accuracy of material data. Data correction provides a basis for calculating material losses and balances, facilitating effective management of material processing and improving processing efficiency and accuracy. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0020] Figure 1 A flowchart illustrating a method for processing material data based on oil refining and chemical engineering, provided for an embodiment of this application;

[0021] Figure 2 A model diagram of a refining and chemical process provided in the embodiments of this application;

[0022] Figure 3 A flowchart illustrating a method for processing material data based on oil refining and chemical engineering, provided for an embodiment of this application;

[0023] Figure 4 A schematic diagram of the interface for outliers provided in the embodiments of this application;

[0024] Figure 5 A flowchart illustrating a method for processing material data based on oil refining and chemical engineering, provided for an embodiment of this application;

[0025] Figure 6 A structural block diagram of a material data processing device based on oil refining and chemical industry provided for embodiments of this application;

[0026] Figure 7 A structural block diagram of a material data processing device based on oil refining and chemical industry provided for embodiments of this application;

[0027] Figure 8 A structural block diagram of an electronic device provided in an embodiment of this application;

[0028] Figure 9 This is a structural block diagram of an electronic device provided in an embodiment of this application.

[0029] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0031] It should be understood that the described embodiments are merely some, not all, of the embodiments in this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0032] In the following description, when referring to the accompanying drawings, the same numbers in different drawings denote the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0033] In the description of this application, it should be understood that the terms "first," "second," "third," etc., are used only to distinguish similar objects and are not necessarily used to describe a specific order or sequence, nor should they be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances. Furthermore, in the description of this application, unless otherwise stated, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0034] It should be noted that, due to space limitations, this application specification does not exhaustively list all possible implementation methods. Those skilled in the art, after reading this application specification, should be able to deduce that, as long as the technical features do not contradict each other, any combination of technical features can constitute an optional implementation method. The following provides a detailed description of each embodiment.

[0035] In the early stages of the refining and chemical industry, material handling and processing were primarily based on simple physical separation and preliminary chemical conversion. Tracking and balancing materials during processing relied mainly on manual measurement and simple recording methods. For example, in crude oil distillation, estimating the output of different fractions solely through manual reading of instrument data wasted significant manpower and time, and lacked precise and efficient quantitative analysis of the trajectory of various components in the crude oil during processing. Furthermore, data from various instruments could be abnormal or incomplete, further affecting the accuracy of material data.

[0036] The development of computer systems has made large-scale data processing possible. Refining and chemical companies have begun to develop specialized material balance calculation software capable of rapidly processing material data from various production stages. Through this software, materials throughout the entire refining and chemical process can be monitored and balanced in real time, allowing for timely correction of inaccurate material data and the detection of material losses or imbalances.

[0037] This application provides a method, apparatus, equipment, and medium for processing material data based on oil refining and chemical engineering, aiming to solve the above-mentioned technical problems in the prior art.

[0038] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0039] Figure 1 This is a flowchart illustrating a method for processing material data based on oil refining and chemical engineering, according to an embodiment of this application. This method can be executed by a material data processing device based on oil refining and chemical engineering. Figure 1 As shown, the method includes the following steps:

[0040] S101. Obtain material data for the refining and chemical processing node; wherein, the refining and chemical processing node represents the device that processes materials in the refining and chemical process, and the material data includes the feed quality and discharge quality of the material in the refining and chemical processing node.

[0041] For example, a complete oil refining and chemical process may contain multiple refining and chemical nodes, each of which can represent a device for material processing. In the oil refining and chemical process, there are many processing units, which may be located in different stages. For example, the units in the oil refining and chemical process may include atmospheric and vacuum distillation units, heavy oil catalytic cracking units, diesel hydrotreating units, etc. Materials can be transported between different units. For example, unit A can supply its output to unit B, and unit B, after processing, will then supply its output to unit C, forming a complete processing cycle.

[0042] Material data from each unit can be recorded in real time or periodically. This data characterizes the material processing status of each unit; for example, it may include the feed quality and output quality. Feed quality refers to the mass of the material input into the unit, while output quality refers to the mass of the material produced after processing. Material data for each unit can be acquired after completing a refining and chemical process. A unit can produce multiple materials; that is, for a single refining and chemical node, multiple output qualities can be obtained, each representing the mass of one specific material produced by the unit.

[0043] For quality-related data such as feed quality and discharge quality, the unit can be tons in this embodiment. Material data can be collected using flow meters in various pipes within the device. For example, mass flow meters, volumetric flow meters, etc., can be used to obtain material data.

[0044] In this embodiment, various data from different refining and chemical nodes can be obtained from different dimensions. For example, at the unit level, flow meter data from various pipelines in the unit can be collected, including mass flow meters, volumetric flow meters, temperature, pressure, and laboratory data. At the tank farm level, inventory data, movement data, and laboratory data of the tanks can be calculated through the level gauges of the tank farm tanks. At the inbound and outbound level, settlement data and laboratory data of certificates of conformity can be obtained through the integrated metering system. At the plant-wide level, data from various units can be summarized, including feed rate, discharge rate, intermediate product output, by-product output, and material composition information.

[0045] S102. If it is determined that there is data to be verified in the output quality of the refining and chemical node, then obtain the output quality of the neighboring nodes of the refining and chemical node; wherein, the data to be verified is an outlier or missing value, and the neighboring node represents the device that receives the data to be verified produced by the refining and chemical node in the refining and chemical process.

[0046] For example, for each refining and chemical processing node, it is determined whether there is any data to be verified in the output quality of the node. Data to be verified refers to outliers or missing values; that is, it is determined whether there are outliers and / or missing values ​​in the output quality of the node. If it is determined that there are no outliers or missing values, the material data is considered correct, and the processing can be analyzed based on the material data. If it is determined that there are outliers and / or missing values, it indicates that there is data in the material data that needs further verification, i.e., data to be verified.

[0047] Constraints can be pre-set to judge the data to be verified. For example, constraints such as upper and lower limits of yield, sorting settings, data type, and data source can be set. If the output quality meets the preset constraints, it is considered that the output quality is not the data to be verified; if the output quality does not meet the preset constraints, it is considered that the output quality is the data to be verified. For example, the yield corresponding to the output quality can be calculated based on the output quality and the feed quality. It can be determined whether the yield is within the preset upper and lower limits of yield. If it is, the output quality is not an outlier; if not, the output quality is an outlier. Another example is to determine the pipe corresponding to the output quality and whether each pipe has its own output quality. If not, it is determined that the output quality of that pipe is missing. In this embodiment, the preset constraints are not specifically limited; different constraints can be set for different nodes.

[0048] After identifying data requiring verification in the output quality of a refining and chemical processing node, neighboring nodes can be determined based on the refining and chemical processing flow, and relevant data on the output quality of these neighboring nodes can be obtained. A neighboring node refers to the device in the refining and chemical processing flow that receives the data requiring verification from the node; that is, the material produced by the node can be sent to different devices, and the device that should receive the data requiring verification is a neighboring node. Since erroneous data will also cause problems in the processing of neighboring nodes, it is necessary to obtain relevant data from neighboring nodes to facilitate data correction.

[0049] Figure 2 This is a model diagram of an oil refining and chemical process. Figure 2 It includes multiple refining and chemical nodes, each representing a different unit. Nodes can be connected by edges, indicating the transport of materials between the corresponding units. For Figure 2 If no data to be verified exists at node one, the process continues to check node two for the data to be verified. Node two has two output pipes. If the output quality to node four is abnormal, then node four is a neighboring node of node two, and the output quality of node four is collected. After the data at node two is processed, the process continues to check nodes three and four, until the last node, node five, is reached.

[0050] By establishing a model of the oil refining and chemical process, it is possible to clearly understand the input, output, and transformation of materials in each production stage, clarify the flow and change patterns of materials in different units, and thus identify bottlenecks and inefficient links in the process for targeted optimization, thereby improving the efficiency of the entire production process. It also helps companies identify material loss points in the production process, enabling them to take measures to reduce material waste. Companies can rationally plan the procurement, storage, and use of materials, and adjust the feed ratio of different qualities of crude oil based on the material balance in the crude oil processing process, ensuring the most efficient allocation of various resources. By accurately grasping the flow and conversion efficiency of materials, companies can avoid unnecessary material procurement and storage costs, reveal material losses during production, and negotiate more reasonable procurement quantities and prices with suppliers, thereby reducing costs. This helps companies reduce inventory levels while ensuring normal production, assists in scheduling operations, achieves precise production, meets production needs, reduces material inventory costs, and improves the company's economic benefits. It can also track the whereabouts of materials during the production process, including which materials are converted into pollutants and emitted into the environment. It can calculate the amount of pollutants such as smoke and sulfur dioxide generated, thus providing a basis for formulating emission reduction measures.

[0051] S103. Adjust the data to be verified based on the discharge quality of neighboring nodes and the feed quality of refining and chemical nodes to obtain the adjusted discharge quality of refining and chemical nodes.

[0052] For example, the data to be verified for the refining and chemical processing node is corrected based on the discharge quality of neighboring nodes and the feed quality of the refining and chemical processing node itself. For instance, outliers can be adjusted to fall within the normal range based on the discharge quality of neighboring nodes and the feed quality of the refining and chemical processing node; or, missing values ​​can be filled in. The adjusted data to be verified, along with the unadjusted normal discharge quality, is used as the adjusted discharge quality of the refining and chemical processing node. The adjusted discharge quality is provided to staff to facilitate subsequent analysis of material loss and material balance.

[0053] Historical data from neighboring nodes and refining / chemical nodes can be obtained, such as the output and feed quality of the nodes within a historical time period. Based on the output and feed quality of neighboring nodes and the refining / chemical nodes, and referring to historical data, the deviation of the data to be verified is inferred, thus obtaining the adjusted output quality. For example, based on historical data, the normal losses during material processing at refining / chemical nodes and neighboring nodes can be determined. Based on the normal losses and feed quality of refining / chemical nodes, the possible normal value of the data to be verified is inferred; based on the normal losses and output quality of neighboring nodes, the feed quality of neighboring nodes, which is also the possible normal value of the data to be verified, is inferred. Combining the two possible normal values ​​yields the final normal value, which is the adjusted data to be verified. In this embodiment, the calculation process for data adjustment is not specifically limited.

[0054] In this embodiment, the method further includes: obtaining the by-product quality of the refining and chemical node; wherein the by-product quality represents the sum of the quality of intermediate products and by-products produced by the refining and chemical node; and determining the estimated loss of the refining and chemical node based on the by-product quality, feed quality, and adjusted discharge quality of the refining and chemical node; wherein the estimated loss represents the quality that the refining and chemical node may lose during processing.

[0055] Specifically, during the processing of materials, the refining and chemical node may also generate intermediate products and by-products. The quality of by-products at the refining and chemical node can be recorded in real time or at regular intervals. The quality of by-products can represent the sum of the quality of intermediate products and by-products produced by the refining and chemical node.

[0056] After adjusting the discharge quality, the estimated loss of the refining and chemical processing node can be determined based on the by-product quality, feed quality, and adjusted discharge quality. The estimated loss characterizes the potential quality loss during processing at the refining and chemical processing node; that is, it determines how much material is lost. The formula for calculating the estimated loss can be:

[0057] G l =Gt -G p -G h ;

[0058] Among them, G l Estimates of losses in all forms other than products, by-products, and recoveries, including pollutant emissions; G t G represents the total amount of material input, i.e., the mass of the input material; p G represents the total amount of products and by-products produced, i.e., the mass of by-products; h The total amount of material recovered, i.e., the adjusted output quality.

[0059] Different formulas for calculating loss estimates can be set for different units. For example, for a reforming unit, the reformed gasoline production can be calculated first, then the light oil yield, and finally the loss estimate. Here, reformed gasoline = reported unit production - extracted residual oil (non-aromatics), light oil yield = sum of oil products (excluding LPG), and loss estimate = feedstock - light oil yield - LPG. For a hydrotreating unit, the light oil yield can be calculated first = sum of oil products (excluding LPG), and then the loss estimate can be calculated = feedstock - light oil yield - LPG. For a gas separator, the product yield can be calculated first = product yield - LPG yield. The sum of the products (excluding C2) is used to calculate the estimated loss = the sum of feedstock and product - C2; for MTBE units, the MTBE product yield can be calculated first = product / (C4 + methanol), then the remaining C4 yield can be calculated = remaining C4 / (C4 + methanol), and then the estimated loss can be calculated = C4 feedstock + methanol - product (MTBE + remaining C4), where MTBE is methyl tert-butyl ether; for benzene extraction units, the product yield can be calculated first = the sum of products, then the estimated loss can be calculated = feedstock - product.

[0060] The advantage of this setup is that by adjusting the data to be verified, the estimated loss values ​​in each stage can be obtained, thus providing a forecast of material loss. This helps in developing corresponding measures to reduce material waste and save costs.

[0061] In this embodiment, the method further includes: obtaining the actual value of the loss of the oil refining and chemical node; if the difference between the estimated value of the loss and the actual value of the loss is within a preset difference threshold, then the adjusted output quality of the oil refining and chemical node is determined to be the actual output quality of the oil refining and chemical node.

[0062] Specifically, the actual losses at refining and chemical processing nodes can be collected in real time or periodically, i.e., the actual loss values. By comparing the estimated loss values ​​with the actual loss values, it is possible to determine whether the adjustment of the output quality is accurate, ensuring the data accuracy of the output quality.

[0063] The difference between the estimated loss and the actual loss can be determined. It can be judged whether the difference is within the preset difference threshold. If it is, the adjusted output quality is considered to be the actual output quality of the refining and chemical node, that is, the data adjustment is completed and subsequent analysis and processing can continue. If not, the adjusted output quality is considered not accurate enough and further adjustment is required.

[0064] The advantage of this setup is that the actual value of the loss can be obtained from the production statistics report. By comparing and verifying the calculated loss estimate with the production statistics report, the accuracy of the calculation results can be ensured and the data precision can be improved.

[0065] In this embodiment, the method further includes: if the difference between the estimated loss and the actual loss is not within a preset difference threshold, then acquiring the material data of the refining and chemical node within a preset historical time period, and determining preset constraints for the refining and chemical process based on the material data within the preset historical time period; wherein, the preset constraints are used to determine whether there is data to be verified in the discharge quality of the refining and chemical node; if it is determined according to the preset constraints that there is data to be verified in the discharge quality of the refining and chemical node, then acquiring the discharge quality of the neighboring nodes of the refining and chemical node; and readjusting the data to be verified based on the discharge quality of the neighboring nodes and the feed quality of the refining and chemical node to obtain the adjusted discharge quality of the refining and chemical node.

[0066] Specifically, a historical time period is preset. If the difference between the estimated loss and the actual loss is not within a preset threshold, material data for the refining and chemical processing node within that time period can be obtained. This data may include feed quality and discharge quality. Based on the material data within the preset historical time period, the corresponding constraints for the refining and chemical processing stage are adjusted. These constraints can be used to determine if there is any data to be verified in the discharge quality of the refining and chemical processing node. For example, historical constraints under the same process can be matched using historical data and used as the adjusted constraints. The adjusted constraints can also be calculated. For example, if the upper and lower limits of the yield need to be adjusted, the historical maximum yield, historical minimum yield, and historical average yield can be obtained. Based on these historical maximum, minimum, and average yields, the upper and lower limits of the yield can be calculated. The formulas for calculating the upper and lower limits of the yield can be:

[0067] Pt u =Pt max +(Pt max -Pt avg );

[0068] Pt l =Pt min -(Pt min -Pt avg );

[0069] Among them, Pt u Pt is the upper limit of the yield. l As the lower limit of yield, Pt max Pt achieved the highest historical yield. min Pt represents the lowest historical yield. avg This represents the historical average yield.

[0070] After obtaining the adjusted constraints, it is re-evaluated whether there is any data to be verified in the discharge quality of the refining and chemical node. If so, the discharge quality of the neighboring nodes of the refining and chemical node is obtained again. Based on the discharge quality of the neighboring nodes and the feed quality of the refining and chemical node, the data to be verified is readjusted to obtain the adjusted discharge quality of the refining and chemical node.

[0071] Based on the newly adjusted output quality, calculate the new estimated loss value and determine whether the difference between the new estimated loss value and the actual loss value is within the preset difference threshold. If so, the newly adjusted output quality is determined to be the accurate output quality; otherwise, the constraints need to be adjusted again until the difference between the estimated loss value and the actual loss value is within the preset difference threshold.

[0072] The advantage of this setup is that by adjusting the constraints, the final calculated loss value is consistent with the production statistical report data, ensuring the accuracy of the adjustment of the data to be verified and facilitating further analysis.

[0073] In this embodiment, material data from refining and chemical processing nodes is acquired to determine the feed and discharge quality of the unit during the refining and chemical processing process. The presence of outliers or missing values ​​in the discharge quality is assessed to identify data to be verified, enabling timely monitoring of the discharge quality and preventing the storage of erroneous data. If no outliers or missing values ​​are found, the data is considered correct; if they are found, the discharge quality of neighboring nodes is acquired to determine the discharge quality of the next stage unit. Based on the discharge quality of neighboring nodes and the feed quality of the refining and chemical processing node, outliers and missing values ​​are adjusted to obtain the correct discharge quality. Combining the discharge quality of neighboring nodes, the data to be verified for the current refining and chemical processing node is corrected to avoid data deviations throughout the entire process caused by considering only a single node's data, thus improving the accuracy of material data. Data correction provides a basis for calculating material losses and balances, facilitating effective management of material processing and improving its efficiency and accuracy.

[0074] Figure 3 This is a schematic flowchart of a material data processing method based on oil refining and chemical industry provided in an embodiment of the present invention. This embodiment is an optional embodiment based on the above embodiment.

[0075] In this embodiment, if it is determined that there is data to be verified in the output quality of the refining and chemical node, the output quality of the neighboring nodes of the refining and chemical node is obtained, including: obtaining the output quality of the refining and chemical node within a preset historical time period, which is historical quality data; if it is determined that the output quality of the refining and chemical node is data to be verified based on the historical quality data, the output quality of the neighboring nodes of the refining and chemical node is obtained; wherein, the data to be verified is an outlier.

[0076] like Figure 3 As shown, the method includes the following steps:

[0077] S301. Obtain material data for the refining and chemical processing node; wherein, the refining and chemical processing node represents the device that processes materials in the refining and chemical process, and the material data includes the feed quality and discharge quality of the material in the refining and chemical processing node.

[0078] For example, this step can refer to step S101 above, and will not be repeated here.

[0079] S302. Obtain the output quality of the refining and chemical nodes within a preset historical time period, which is historical quality data.

[0080] For example, a historical time period is preset, such as the past month. For each refining and chemical node, the output quality of that node within the preset historical time period is obtained. A refining and chemical node may have one or more pipelines for output, which can produce different types of materials. The output quality of various materials produced by the refining and chemical node within the preset historical time period can be obtained. The output quality of each material within the historical time period can be obtained, and the output materials and their corresponding qualities can be associated to determine the historical quality data of the refining and chemical node. Alternatively, the sum of the qualities of various materials produced can be used to determine the historical quality data of the refining and chemical node.

[0081] S303. If the discharge quality of the refining and chemical node is determined to be the data to be verified based on historical quality data, then obtain the discharge quality of the neighboring nodes of the refining and chemical node; wherein, the data to be verified is an outlier.

[0082] For example, historical quality data can be used to determine whether there is any data to be verified in the output quality of a refining and chemical processing node. In this embodiment, outliers can be used as data to be verified. Outliers are data whose values ​​are significantly different from the normal output quality. For example, the average output quality can be calculated based on historical quality data, and the current output quality can be compared with the calculated average value. If the output quality is greater than the average value, the output quality is considered to be an outlier.

[0083] If it is determined that the discharge quality of the refining and chemical node is not an outlier, then the discharge quality of the refining and chemical node is recorded and stored for subsequent material balance analysis. If it is determined that the discharge quality of the refining and chemical node is an outlier, then the neighboring nodes of the refining and chemical node are identified, and the current discharge quality of the neighboring nodes is obtained. Based on the discharge quality of the neighboring nodes, the outlier is corrected and adjusted to a normal value.

[0084] In this embodiment, determining the output quality of the refining and chemical node as the data to be verified based on historical quality data includes: determining the anomaly identification boundary based on historical quality data; wherein, the anomaly identification interface represents the data range of normal output quality; if the output quality of the refining and chemical node is not within the anomaly identification boundary, then the output quality of the refining and chemical node is determined as the data to be verified.

[0085] Specifically, based on historical quality data, the normal range of output quality values ​​can be determined. This normal range is then defined as the anomaly identification threshold; that is, the anomaly identification threshold characterizes the normal range of output quality data. For example, the minimum and maximum values ​​in historical quality data can be identified, and these minimum and maximum values ​​can be used as anomaly identification thresholds. The range between the minimum and maximum values ​​represents the normal range of output quality data.

[0086] The discharge quality of the refining and chemical node is compared with the anomaly identification threshold. If the discharge quality of the refining and chemical node is not within the anomaly identification threshold, it means that the discharge quality of the refining and chemical node exceeds the normal value range and the discharge quality is an anomaly value; if the discharge quality of the refining and chemical node is within the anomaly identification threshold, it means that the discharge quality of the refining and chemical node is not an anomaly value.

[0087] The advantage of this setup is that it determines the normal range of output quality based on historical output quality, enables automatic identification of outliers, saves manpower and time, improves the efficiency and accuracy of outlier identification, and thus improves the efficiency and accuracy of subsequent data processing.

[0088] In this embodiment, determining the anomaly identification boundary based on historical quality data includes: determining the lower quartile and upper quartile from historical quality data within a preset historical time period; determining the interquartile range based on the lower quartile and upper quartile; and determining the anomaly identification boundary based on the lower quartile, upper quartile, and interquartile range.

[0089] Specifically, the historical quality data within the historical time period is sorted, for example, in ascending order. From the sorted historical quality data, the lower quartile and upper quartile are determined. The lower quartile, also known as the first quartile (Q1), is calculated based on the position of the data after sorting. When the data volume is odd, Q1 is the (n+1) / 4th data point; when the data volume is even, Q1 is the average of the n / 4th and n / 4+1th data points, where n is the number of historical quality data points. The upper quartile is the third quartile (Q3), calculated similarly to Q1, based on the 75th percentile position. Based on the lower and upper quartiles, the interquartile range (ICM) is determined, calculated as follows:

[0090] IQR = Q3 - Q1;

[0091] Wherein, IQR stands for interquartile range.

[0092] The outlier thresholds are calculated based on the lower quartile, upper quartile, and interquartile range. Outlier thresholds can be defined using Q1 - 1.5IQR and Q3 + 1.5IQR as boundaries; data exceeding these ranges are considered outliers.

[0093] The advantage of this setup is that it determines the anomaly identification boundary based on a preset statistical method, such as a box plot algorithm, thereby improving the efficiency and accuracy of outlier identification.

[0094] In this embodiment, if the discharge quality of the refining and chemical node is not within the anomaly identification limit, then the discharge quality of the refining and chemical node is determined to be data to be verified. This includes: if the discharge quality of the refining and chemical node is not within the anomaly identification limit, then the discharge quality of the refining and chemical node is determined to be potential abnormal data; wherein, potential abnormal data represents potential abnormal values; obtaining a preset historical load value of the refining and chemical node; wherein, the preset historical load value is the material processing capacity of the unit represented by the refining and chemical node; determining the upper limit of the discharge quality based on the preset historical load value; if the potential abnormal data is greater than the upper limit, then the discharge quality of the refining and chemical node is determined to be data to be verified.

[0095] Specifically, it is determined whether the output quality of the refining and chemical node is within the anomaly identification threshold. If so, the output quality is determined to be a normal value; otherwise, the output quality is determined to be potential abnormal data. Potential abnormal data indicates that the output quality may be an abnormal value and further judgment is required.

[0096] Obtain the preset historical load value for the refining and chemical node. The preset historical load value is the historical maximum load, which can characterize the material processing capacity of the unit represented by the refining and chemical node. For example, the historical maximum load is ∑Y pBased on preset historical load values, the upper limit of the discharge quality can be determined; that is, the upper limit of the unit is set according to the unit's best operating condition. Potential abnormal data is compared with the upper limit. If the potential abnormal data is greater than the upper limit, the discharge quality of the refining and chemical node is determined to be abnormal; if the potential abnormal data is less than or equal to the upper limit, the discharge quality of the refining and chemical node is determined to be normal.

[0097] The formula for calculating the upper limit of mass can be:

[0098] M = ∑X p ×24×(∑Y p / 100);

[0099] Where M is the upper limit of mass, ∑X p This represents the maximum hourly pipeline flow rate of the unit, expressed in tons. Under continuous full-load conditions, the maximum daily processing time for the unit is 24 hours. The maximum capacity can be calculated based on historical maximum loads.

[0100] The advantage of this setting is that data exceeding the anomaly identification threshold is considered a potential outlier. From the potential outliers, the true outliers are identified, achieving a secondary screening of outliers and improving the accuracy of data processing.

[0101] In this embodiment, if it is determined that there is data to be verified in the output quality of the refining and chemical node, the output quality of the neighboring nodes of the refining and chemical node is obtained, including: if it is determined that the output quality of the refining and chemical node is less than or equal to a preset quality threshold, the output quality of the refining and chemical node is determined as data to be verified, and the output quality of the neighboring nodes of the refining and chemical node is obtained; wherein, the data to be verified is a missing value.

[0102] Specifically, the data to be verified can be outliers or missing values. Missing values ​​refer to data missing from the output quality. The presence of missing values ​​can be determined from the output quality before or after outlier identification. For example, missing value identification can be performed after outlier identification is completed.

[0103] Missing values ​​can be identified using data from instantaneous flow meters. Specifically, this involves monitoring all flow meters in the plant and recording instantaneous flow changes. For example, using side-line meters on the unit, record the corresponding values. The data reliability is 100%, and the collected data should be greater than 0. If the data is 0, it is considered missing; that is, a value of 0 is a missing value. Alternatively, daily laboratory data can be analyzed to identify missing values. Specifically, by analyzing the plant-wide laboratory results, identify that oil product analysis was performed on that day. The collected laboratory data should be greater than 0. Based on common sense, if the data is 0, it is considered missing; that is, a value of 0 is a missing value.

[0104] The advantage of this setting is that if the collected data is 0, it is a missing value, enabling rapid identification of missing values ​​and improving the efficiency of data processing.

[0105] Figure 4 This is a schematic diagram of the interface for outlier values. Figure 4 In the system, outliers can be identified for different devices, and the ID of each device corresponding to the outlier, the device type, name, date, error size, etc. can be displayed.

[0106] S304. Based on the discharge quality of neighboring nodes and the feed quality of refining and chemical nodes, adjust the data to be verified to obtain the adjusted discharge quality of refining and chemical nodes.

[0107] For example, this step can refer to step S103 above, and will not be repeated here.

[0108] In this embodiment, material data from refining and chemical processing nodes is acquired to determine the feed and discharge quality of the unit during the refining and chemical processing process. The presence of outliers or missing values ​​in the discharge quality is assessed to identify data to be verified, enabling timely monitoring of the discharge quality and preventing the storage of erroneous data. If no outliers or missing values ​​are found, the data is considered correct; if they are found, the discharge quality of neighboring nodes is acquired to determine the discharge quality of the next stage unit. Based on the discharge quality of neighboring nodes and the feed quality of the refining and chemical processing node, outliers and missing values ​​are adjusted to obtain the correct discharge quality. Combining the discharge quality of neighboring nodes, the data to be verified for the current refining and chemical processing node is corrected to avoid data deviations throughout the entire process caused by considering only a single node's data, thus improving the accuracy of material data. Data correction provides a basis for calculating material losses and balances, facilitating effective management of material processing and improving its efficiency and accuracy.

[0109] Figure 5 This is a schematic flowchart of a material data processing method based on oil refining and chemical industry provided in an embodiment of the present invention. This embodiment is an optional embodiment based on the above embodiment.

[0110] In this embodiment, the data to be verified is adjusted based on the discharge quality of neighboring nodes and the feed quality of the refining and chemical node to obtain the adjusted discharge quality of the refining and chemical node. This includes: determining the number of data to be verified in the discharge quality of neighboring nodes; determining the current operating condition of the refining and chemical node based on the number of data to be verified in the discharge quality of neighboring nodes; wherein, the current operating condition represents the current working state; and adjusting the data to be verified based on the current operating condition of the refining and chemical node and the feed quality of the refining and chemical node to obtain the adjusted discharge quality of the refining and chemical node.

[0111] like Figure 5 As shown, the method includes the following steps:

[0112] S501. Obtain material data for the refining and chemical processing node; wherein, the refining and chemical processing node represents the device that processes materials in the refining and chemical process, and the material data includes the feed quality and discharge quality of the material in the refining and chemical processing node.

[0113] For example, this step can refer to step S101 above, and will not be repeated here.

[0114] S502. If it is determined that there is data to be verified in the output quality of the refining and chemical node, then the output quality of the neighboring nodes of the refining and chemical node is obtained; wherein, the data to be verified is an outlier or missing value, and the neighboring node represents the device that receives the data to be verified produced by the refining and chemical node in the refining and chemical process.

[0115] For example, this step can refer to step S102 above, and will not be repeated here.

[0116] S503. Determine the number of data to be verified in the output quality of neighboring nodes.

[0117] For example, the discharge quality of neighboring nodes is obtained, and it is determined whether there is data to be verified in the discharge quality of neighboring nodes, that is, whether there are outliers and / or missing values ​​in the discharge quality of neighboring nodes. The method for identifying data to be verified from the discharge quality of neighboring nodes is consistent with the method for identifying data to be verified from the discharge quality of refining and chemical nodes.

[0118] Determine the number of data points to be verified in the output quality of neighboring nodes; that is, determine the sum of the number of outliers and missing values ​​in neighboring nodes. Neighboring nodes are the nodes that receive data points to be verified from the refining and chemical processing nodes. Therefore, when there are data points to be verified in the output quality of the refining and chemical processing nodes, there will also be data points to be verified in the output quality of neighboring nodes. In other words, the number of data points to be verified in the output quality of neighboring nodes is always greater than 0.

[0119] S504. Determine the current operating condition of the refining and chemical node based on the number of data to be verified in the output quality of neighboring nodes; where the current operating condition represents the current working status.

[0120] For example, multiple operating conditions can be preset, allowing the device to operate under different conditions. Under different operating conditions, the device can perform material processing to varying degrees. Based on the quantity of data to be verified in the output quality of neighboring nodes, the current operating condition of the refining and chemical node is determined, i.e., the current operating status of the device is determined.

[0121] For example, different correlations between quantities and operating conditions can be preset, and the operating condition corresponding to the quantity can be determined based on the quantity of data to be verified in the output quality of neighboring nodes, which can then be used as the current operating condition of the refining and chemical node.

[0122] In this embodiment, determining the current operating condition of the refining and chemical node based on the number of data to be verified in the output quality of neighboring nodes includes: if the number of data to be verified in the output quality of neighboring nodes is greater than a preset first quantity threshold, then acquiring the current environmental data of the refining and chemical node, the historical environmental data of the refining and chemical node, the current environmental data of neighboring nodes, and the historical environmental data of neighboring nodes; determining the similarity between the current environmental data and the historical environmental data of the refining and chemical node as a first similarity, and determining the similarity between the current environmental data and the historical environmental data of neighboring nodes as a second similarity; and determining the current operating condition of the refining and chemical node based on the first similarity and the second similarity.

[0123] Specifically, a first quantity threshold is preset. The number of data points to be verified in the output quality of neighboring nodes is compared with this first quantity threshold. If the number of data points to be verified in the output quality of neighboring nodes exceeds the first quantity threshold, then the current environmental data, historical environmental data, current environmental data, and historical environmental data of the refining and chemical node, as well as those of neighboring nodes, are acquired. Environmental data refers to environmentally related data monitored by the unit, excluding output quality. For example, environmental data may include temperature and pressure. Current environmental data refers to the environmental data currently collected, while historical environmental data refers to environmental data collected over a past period, such as environmental data within a preset historical time period.

[0124] The system acquires current and historical environmental data for the refining and chemical processing nodes, as well as current and historical environmental data for neighboring nodes. For each refining and chemical processing node, the similarity between its current and historical environmental data is calculated as a first similarity. For neighboring nodes, the similarity between their current and historical environmental data is calculated as a second similarity. The similarity score characterizes the degree of similarity between the current and historical operating states. In this embodiment, the calculation method for the similarity score is not specifically limited; for example, cosine similarity can be used.

[0125] By combining the first and second similarity scores, the current operating condition of the refining and chemical processing node is determined. For example, the first and second similarity scores are compared, and the larger value is selected. The historical operating condition corresponding to the larger value is then determined as the current operating condition of the refining and chemical processing node. If the first and second similarity scores are the same, a historical operating condition of the refining and chemical processing node can be randomly selected as its current operating condition, or a historical operating condition of a neighboring node can be selected. For example, if the first similarity score is greater than the second similarity score, the operating condition of the refining and chemical processing node corresponding to the historical environmental data is obtained as the current operating condition.

[0126] The beneficial effect of this setting is that if the number of data to be verified in the output quality of neighboring nodes is greater than the preset first quantity threshold, the corresponding working condition is determined by combining the two similar situations, thereby improving the determination accuracy of the current working condition and thus improving the accuracy of data processing.

[0127] In this embodiment, determining the current operating condition of a refining and chemical node based on the number of data to be verified in the output quality of neighboring nodes includes: if the number of data to be verified in the output quality of neighboring nodes is less than or equal to a preset first quantity threshold and greater than a preset second quantity threshold, then acquiring the current environmental data and historical environmental data of the refining and chemical node; determining the similarity between the current environmental data and the historical environmental data of the refining and chemical node as a first similarity; and determining the current operating condition of the refining and chemical node based on the first similarity.

[0128] Specifically, a second quantity threshold is preset, which is less than a first quantity threshold. When the number of data to be verified in the output quality of neighboring nodes is less than or equal to the preset first quantity threshold, it is determined whether the number of data to be verified in the output quality of neighboring nodes is greater than the preset second quantity threshold. If so, the current environmental data and historical environmental data of the refining and chemical node are obtained. The similarity between the current environmental data and historical environmental data of the refining and chemical node is calculated, i.e., the first similarity is obtained. Based on the first similarity, the current operating condition of the refining and chemical node is determined. For example, if the first similarity is greater than the preset similarity threshold, the operating condition corresponding to the historical environmental data is obtained, and this operating condition is determined as the current operating condition; if the first similarity is less than or equal to the preset similarity threshold, the preset default operating condition is obtained as the current operating condition.

[0129] The beneficial effect of this setting is that when the number of data to be verified in the output quality of neighboring nodes is between the first and second quantity thresholds, the current working condition is determined based on the first similarity, thereby enabling targeted determination of the working condition for different quantities and improving the accuracy of the current working condition determination.

[0130] In this embodiment, the current operating condition of the refining and chemical node is determined based on the number of data to be verified in the output quality of neighboring nodes, including: if the number of data to be verified in the output quality of neighboring nodes is less than or equal to a preset second quantity threshold, then the current environmental data and historical environmental data of the neighboring nodes are obtained; the similarity between the current environmental data and the historical environmental data of the neighboring nodes is determined as a second similarity; and the current operating condition of the refining and chemical node is determined based on the second similarity.

[0131] Specifically, if the number of data points to be verified in the output quality of neighboring nodes is less than or equal to a preset second threshold, then the current and historical environmental data of the neighboring nodes are directly acquired. The similarity between the current and historical environmental data of the neighboring nodes is calculated, i.e., the second similarity is obtained. Based on the second similarity, the current operating condition of the refining and chemical node is determined. For example, if the second similarity is greater than the preset similarity threshold, then the operating condition corresponding to the historical environmental data of the neighboring nodes is acquired, and this operating condition is determined as the current operating condition; if the second similarity is less than or equal to the preset similarity threshold, then the preset default operating condition is acquired as the current operating condition.

[0132] The advantage of this setup is that it divides the number of data to be verified in the output quality of neighboring nodes into three cases for comparison, thereby enabling a targeted determination of the current working condition, obtaining the current working condition that is closest to the actual situation, and improving the accuracy of subsequent data processing.

[0133] In this embodiment, the Pearson correlation coefficient can be used to calculate the first and second similarities. Whether calculating the first or second similarity, k historical environmental data points can be obtained first, and the Pearson correlation coefficient can be used to calculate the correlation between each current environmental data point and its corresponding historical environmental data. The correlation degree is denoted as r. j , j = 1, 2, ..., k.

[0134] The formula for summing the Pearson correlation coefficients of all environmental data is as follows:

[0135]

[0136] Where P represents the similarity score. When P > 0.9 × k, the historical operating conditions can be considered as the current operating conditions. For example, if P is the second similarity score and P > 0.9 × k, then the operating conditions of neighboring nodes within the historical time period are determined as the current operating conditions of the refining and chemical node.

[0137] S505. Based on the current operating conditions and feed quality of the refining and chemical processing node, adjust the data to be verified to obtain the adjusted output quality of the refining and chemical processing node.

[0138] For example, different operating conditions can correspond to different adjustment ranges. After determining the current operating condition, the adjustment range corresponding to the current operating condition can be found. Based on the adjustment range and the feed quality of the refining and chemical node, the data to be verified is adjusted to obtain the adjusted output quality of the refining and chemical node. For example, the data to be verified can be appropriately increased or decreased based on the adjustment range and the output quality to obtain the adjusted data to be verified.

[0139] In this embodiment, the data to be verified is adjusted based on the current operating conditions and feed quality of the refining and chemical node to obtain the adjusted output quality of the refining and chemical node. This includes: determining a material standard dataset corresponding to the current operating conditions; wherein the material standard dataset includes the allowable feed quality and output quality under the current operating conditions; and adjusting the data to be verified based on the feed quality and output quality in the material standard dataset and the feed quality of the refining and chemical node to obtain the adjusted output quality of the refining and chemical node.

[0140] Specifically, each operating condition corresponds to its own material standard dataset, which includes the allowable feed quality and discharge quality under the operating condition. The material standard dataset corresponding to the current operating condition is determined. For example, the material standard dataset can be represented as [(80,120)(100,150)(120,180)(150,220)(200,300)], that is, the material standard dataset can include h (X,Y) values, where X can represent the feed quality, Y can represent the discharge quality, and h is greater than or equal to 1.

[0141] Missing values ​​and outliers can be calculated using linear interpolation. The formula for linear interpolation is as follows:

[0142] Y , =a+bX , ;

[0143] Among them, Y , X is the data to be verified. , Given the current feed quality at the refining and chemical processing node, both 'a' and 'b' are parameters that need to be determined. Based on the material standard dataset corresponding to the current operating conditions, 'a' and 'b' can be calculated.

[0144] First, calculate the average value of X based on the material standard dataset. And calculate the average value of Y

[0145] According to X 均 and Y 均 Calculate a and b, where, a = Y 均 -bX 均We can find that b is approximately 1.2 and a is approximately 31.2. Therefore, we obtain Y. , =31.2 + 1.2X , Substituting the feed quality of the refining and chemical processing node into the above formula yields the adjusted data to be verified.

[0146] If there are multiple data points to be verified in a refining and chemical processing node, and each data point is transmitted to a different neighboring node, different current operating conditions can be determined based on the number of data points to be verified in the different neighboring nodes, thereby obtaining different values ​​of a and b, and enabling separate adjustments to each data point to be verified.

[0147] The advantage of this setup is that each operating condition corresponds to its own dataset, and targeted automatic adjustments are made based on the data in the dataset, improving the efficiency and accuracy of data adjustment and facilitating subsequent analysis of material loss and balance.

[0148] In this embodiment, material data from refining and chemical processing nodes is acquired to determine the feed and discharge quality of the unit during the refining and chemical processing process. The presence of outliers or missing values ​​in the discharge quality is assessed to identify data to be verified, enabling timely monitoring of the discharge quality and preventing the storage of erroneous data. If no outliers or missing values ​​are found, the data is considered correct; if they are found, the discharge quality of neighboring nodes is acquired to determine the discharge quality of the next stage unit. Based on the discharge quality of neighboring nodes and the feed quality of the refining and chemical processing node, outliers and missing values ​​are adjusted to obtain the correct discharge quality. Combining the discharge quality of neighboring nodes, the data to be verified for the current refining and chemical processing node is corrected to avoid data deviations throughout the entire process caused by considering only a single node's data, thus improving the accuracy of material data. Data correction provides a basis for calculating material losses and balances, facilitating effective management of material processing and improving its efficiency and accuracy.

[0149] Figure 6 This is a structural block diagram of a material data processing device based on oil refining and chemical engineering, provided as an embodiment of the present invention. For ease of explanation, only the parts relevant to the embodiments of this disclosure are shown. (Refer to...) Figure 6 The material data processing device 600 based on oil refining and chemical industry includes: a first acquisition unit 601, a second acquisition unit 602 and a data adjustment unit 603.

[0150] The first acquisition unit 601 is used to acquire material data of a refining and chemical node; wherein, the refining and chemical node represents a device for material processing in the refining and chemical process, and the material data includes the feed quality and discharge quality of the material in the refining and chemical node.

[0151] The second acquisition unit 602 is used to acquire the output quality of the neighboring nodes of the refining and chemical node if it is determined that there is data to be verified in the output quality of the refining and chemical node; wherein, the data to be verified is an outlier or missing value, and the neighboring node represents a device that receives the data to be verified produced by the refining and chemical node in the refining and chemical process.

[0152] The data adjustment unit 603 is used to adjust the data to be verified based on the discharge quality of the neighboring node and the feed quality of the refining and chemical node, so as to obtain the adjusted discharge quality of the refining and chemical node.

[0153] Figure 7 A structural block diagram of a material data processing device based on oil refining and chemical engineering provided in this disclosure embodiment is shown below. Figure 7 As shown, the material data processing device 700 based on oil refining and chemical industry includes a first acquisition unit 701, a second acquisition unit 702 and a data adjustment unit 703, wherein the second acquisition unit 702 includes a history acquisition module 7021 and a quality acquisition module 7022.

[0154] In one example, the quality acquisition module 7022 includes:

[0155] The boundary determination submodule is used to determine the anomaly identification boundary based on the historical quality data; wherein, the anomaly identification interface represents the data range of normal output quality.

[0156] The anomaly detection submodule is used to determine the output quality of the refining and chemical node as the data to be verified if the output quality of the refining and chemical node is not within the anomaly identification limit.

[0157] In one example, the boundary determination submodule is specifically used for:

[0158] The lower quartile and upper quartile are determined from the historical quality data within the preset historical time period;

[0159] The interquartile range is determined based on the lower quartile and the upper quartile.

[0160] The anomaly detection threshold is determined based on the lower quartile, the upper quartile, and the interquartile range.

[0161] In one example, the exception handling submodule is specifically used for:

[0162] If the discharge quality of the refining and chemical node is not within the anomaly identification limit, then the discharge quality of the refining and chemical node is determined to be potential abnormal data; wherein, the potential abnormal data represents potential outlier values;

[0163] Obtain the preset historical load value of the refining and chemical node; wherein, the preset historical load value is the material processing capacity of the unit represented by the refining and chemical node;

[0164] The upper limit of the output quality is determined based on the preset historical load value;

[0165] If the potential abnormal data is greater than the quality upper limit, then the output quality of the refining and chemical node is determined to be the data to be verified.

[0166] In one example, the second acquisition unit 702 includes:

[0167] The missing data determination module is used to determine the output quality of the refining and chemical node as data to be verified if it is determined that the output quality of the refining and chemical node is less than or equal to a preset quality threshold, and to obtain the output quality of the neighboring nodes of the refining and chemical node; wherein the data to be verified is a missing value.

[0168] In one example, the data adjustment unit 703 includes:

[0169] The quantity determination module is used to determine the quantity of data to be verified in the output quality of the neighboring nodes;

[0170] The operating condition determination module is used to determine the current operating condition of the refining and chemical node based on the number of data to be verified in the output quality of the neighboring nodes; wherein, the current operating condition represents the current working state.

[0171] The data adjustment module is used to adjust the data to be verified based on the current operating conditions and feed quality of the refining and chemical node, so as to obtain the adjusted output quality of the refining and chemical node.

[0172] In one example, the operating condition determination module is specifically used for:

[0173] If the number of data to be verified in the output quality of the neighboring node is greater than a preset first quantity threshold, then the current environmental data of the refining and chemical node, the historical environmental data of the refining and chemical node, the current environmental data of the neighboring node, and the historical environmental data of the neighboring node are obtained.

[0174] The similarity between the current environmental data of the refining and chemical node and the historical environmental data of the refining and chemical node is determined as the first similarity, and the similarity between the current environmental data of the neighboring node and the historical environmental data of the neighboring node is determined as the second similarity.

[0175] The current operating condition of the refining and chemical node is determined based on the first similarity and the second similarity.

[0176] In one example, the operating condition determination module is specifically used for:

[0177] If the number of data to be verified in the output quality of the neighboring node is less than or equal to a preset first quantity threshold and greater than a preset second quantity threshold, then the current environmental data and the historical environmental data of the refining and chemical node are obtained.

[0178] The similarity between the current environmental data of the oil refining and chemical node and the historical environmental data of the oil refining and chemical node is determined as the first similarity.

[0179] Based on the first similarity, the current operating condition of the refining and chemical node is determined.

[0180] In one example, the operating condition determination module is specifically used for:

[0181] If the number of data to be verified in the output quality of the neighboring node is less than or equal to a preset second quantity threshold, then the current environmental data and the historical environmental data of the neighboring node are obtained.

[0182] The similarity between the current environmental data of the neighboring nodes and the historical environmental data of the neighboring nodes is determined as the second similarity.

[0183] Based on the second similarity, the current operating condition of the refining and chemical node is determined.

[0184] In one example, the data adjustment module is specifically used for:

[0185] Determine the material standard dataset corresponding to the current operating condition; wherein the material standard dataset includes the allowable feed quality and discharge quality under the current operating condition;

[0186] Based on the feed quality and discharge quality in the material standard dataset, and the feed quality of the refining and chemical node, the data to be verified is adjusted to obtain the adjusted discharge quality of the refining and chemical node.

[0187] One example also includes:

[0188] A by-product determination unit is used to obtain the by-product quality of the refining and chemical node; wherein, the by-product quality represents the sum of the mass of intermediate products and by-products produced by the refining and chemical node;

[0189] The loss determination unit is used to determine the estimated loss of the refining and chemical node based on the by-product quality, feed quality, and adjusted discharge quality of the refining and chemical node; wherein the estimated loss characterizes the quality that the refining and chemical node may lose during processing.

[0190] One example also includes:

[0191] The actual value acquisition unit is used to acquire the actual value of the loss of the oil refining and chemical node.

[0192] The loss comparison unit is used to determine the adjusted discharge quality of the refining and chemical node as the actual discharge quality of the refining and chemical node if the difference between the estimated loss value and the actual loss value is within a preset difference threshold.

[0193] One example also includes:

[0194] The condition determination unit is used to obtain material data of the refining and chemical process node within a preset historical time period if the difference between the estimated loss value and the actual loss value is not within a preset difference threshold, and to determine preset constraints of the refining and chemical process node based on the material data within the preset historical time period; wherein, the preset constraints are used to determine whether there is data to be verified in the output quality of the refining and chemical process node.

[0195] The readjustment unit is used to obtain the output quality of the neighboring nodes of the refining and chemical node if it is determined that there is data to be verified in the output quality of the refining and chemical node according to the preset constraints; and readjust the data to be verified according to the output quality of the neighboring nodes and the feed quality of the refining and chemical node to obtain the adjusted output quality of the refining and chemical node.

[0196] Figure 8 A structural block diagram of an electronic device provided in an embodiment of this application, such as... Figure 8 As shown, the electronic device includes: a memory 81 and a processor 82; the memory 81 is a memory used to store instructions executable by the processor 82.

[0197] The processor 82 is configured to perform the methods provided in the above embodiments.

[0198] The electronic device also includes a receiver 83 and a transmitter 84. The receiver 83 is used to receive instructions and data sent by other devices, and the transmitter 84 is used to send instructions and data to external devices.

[0199] Figure 9 This is a block diagram illustrating a terminal device according to an exemplary embodiment. The device may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness device, personal digital assistant, etc.

[0200] The device 900 may include one or more of the following components: a processing component 902, a memory 904, a power supply component 906, a multimedia component 908, an audio component 910, an input / output (I / O) interface 912, a sensor component 914, and a communication component 916.

[0201] Processing component 902 typically controls the overall operation of device 900, such as operations associated with display, telephone calls, data communication, camera operation, and recording. Processing component 902 may include one or more processors 920 to execute instructions to perform all or part of the steps of the methods described above. Furthermore, processing component 902 may include one or more modules to facilitate interaction between processing component 902 and other components. For example, processing component 902 may include a multimedia module to facilitate interaction between multimedia component 908 and processing component 902.

[0202] Memory 904 is configured to store various types of data to support the operation of device 900. Examples of this data include instructions for any application or method operating on device 900, contact data, phonebook data, messages, pictures, videos, etc. Memory 904 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0203] Power supply component 906 provides power to various components of device 900. Power supply component 906 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power to device 900.

[0204] Multimedia component 908 includes a screen that provides an output interface between the device 900 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 908 includes a front-facing camera and / or a rear-facing camera. When the device 900 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0205] Audio component 910 is configured to output and / or input audio signals. For example, audio component 910 includes a microphone (MIC) configured to receive external audio signals when device 900 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 904 or transmitted via communication component 916. In some embodiments, audio component 910 also includes a speaker for outputting audio signals.

[0206] I / O interface 912 provides an interface between processing component 902 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0207] Sensor assembly 914 includes one or more sensors for providing status assessments of various aspects of device 900. For example, sensor assembly 914 may detect the on / off state of device 900, the relative positioning of components such as the display and keypad of device 900, changes in position of device 900 or a component of device 900, the presence or absence of user contact with device 900, orientation or acceleration / deceleration of device 900, and temperature changes of device 900. Sensor assembly 914 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 914 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 914 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0208] Communication component 916 is configured to facilitate wired or wireless communication between device 900 and other devices. Device 900 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 916 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 916 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0209] In an exemplary embodiment, the apparatus 900 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0210] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 904 including instructions, which can be executed by a processor 920 of the device 900 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0211] A non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by the processor of a terminal device, enables the terminal device to perform the aforementioned method for processing material data based on oil refining and chemical engineering.

[0212] This application also discloses a computer program product, including a computer program that, when executed by a processor, implements the method described in this embodiment.

[0213] Various embodiments of the systems and technologies described above in this application can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0214] The program code used to implement the methods of this application may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or electronic device.

[0215] In the context of this application, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0216] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0217] The systems and technologies described herein can be implemented in computing systems that include back-end components (e.g., as data electronic devices), or computing systems that include middleware components (e.g., application electronic devices), or computing systems that include front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0218] Computer systems can include client and electronic devices. Clients and electronic devices are generally geographically separated and typically interact via communication networks. The client-electronic device relationship is created by computer programs running on the respective computers and having a client-electronic device relationship with each other. The electronic device can be a cloud electronic device, also known as a cloud computing electronic device or cloud host, a host product within the cloud computing service system, addressing the shortcomings of traditional physical hosts and VPS services ("Virtual Private Server," or simply "VPS") in terms of management difficulty and weak business scalability. The electronic device can also be an electronic device in a distributed system or an electronic device incorporating blockchain technology. It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this application is achieved, and this is not limited herein.

[0219] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0220] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for processing material data based on oil refining and chemical engineering, characterized in that, include: Acquire material data for refining and chemical processing nodes; wherein, the refining and chemical processing node represents a device that processes materials in the refining and chemical process, and the material data includes the feed quality and discharge quality of the materials in the refining and chemical processing node; If it is determined that there is data to be verified in the output quality of the refining and chemical node, then the output quality of the neighboring node of the refining and chemical node is obtained; wherein, the data to be verified is an outlier or a missing value, and the neighboring node represents a device that receives the data to be verified produced by the refining and chemical node in the refining and chemical process. Based on the discharge quality of the neighboring nodes and the feed quality of the refining and chemical node, the data to be verified is adjusted to obtain the adjusted discharge quality of the refining and chemical node.

2. The method according to claim 1, characterized in that, If it is determined that there is data to be verified in the discharge quality of the refinery and chemical node, then the discharge quality of the neighboring nodes of the refinery and chemical node is obtained, including: The output quality of the oil refining and chemical node within a preset historical time period is obtained as historical quality data. If the discharge quality of the refining and chemical node is determined to be the data to be verified based on the historical quality data, then the discharge quality of the neighboring nodes of the refining and chemical node is obtained; wherein, the data to be verified is an outlier.

3. The method according to claim 2, characterized in that, The discharge quality of the refining and chemical processing node is determined based on the historical quality data as the data to be verified, including: Based on the historical quality data, anomaly identification limits are determined; wherein, the anomaly identification interface represents the data range of normal output quality. If the output quality of the refining and chemical processing node is not within the anomaly identification limit, then the output quality of the refining and chemical processing node is determined to be the data to be verified.

4. The method according to claim 3, characterized in that, Based on the historical quality data, anomaly identification boundaries are determined, including: The lower quartile and upper quartile are determined from the historical quality data within the preset historical time period; The interquartile range is determined based on the lower quartile and the upper quartile. The anomaly detection threshold is determined based on the lower quartile, the upper quartile, and the interquartile range.

5. The method according to claim 3, characterized in that, If the discharge quality of the refining and chemical processing node is not within the anomaly identification threshold, then the discharge quality of the refining and chemical processing node is determined to be the data to be verified, including: If the discharge quality of the refining and chemical node is not within the anomaly identification limit, then the discharge quality of the refining and chemical node is determined to be potential abnormal data; wherein, the potential abnormal data represents potential outlier values; Obtain the preset historical load value of the refining and chemical node; wherein, the preset historical load value is the material processing capacity of the unit represented by the refining and chemical node; The upper limit of the output quality is determined based on the preset historical load value; If the potential abnormal data is greater than the quality upper limit, then the output quality of the refining and chemical node is determined to be the data to be verified.

6. The method according to claim 1, characterized in that, If it is determined that there is data to be verified in the discharge quality of the refinery and chemical node, then the discharge quality of the neighboring nodes of the refinery and chemical node is obtained, including: If it is determined that the discharge quality of the refining and chemical node is less than or equal to a preset quality threshold, then the discharge quality of the refining and chemical node is determined as data to be verified, and the discharge quality of the neighboring nodes of the refining and chemical node is obtained; wherein, the data to be verified is a missing value.

7. The method according to claim 1, characterized in that, Based on the discharge quality of the neighboring nodes and the feed quality of the refining and chemical processing node, the data to be verified is adjusted to obtain the adjusted discharge quality of the refining and chemical processing node, including: Determine the number of data to be verified in the output quality of the neighboring nodes; The current operating condition of the refining and chemical node is determined based on the number of data to be verified in the output quality of the neighboring nodes; wherein, the current operating condition represents the current working status. Based on the current operating conditions and feed quality of the refining and chemical processing node, the data to be verified is adjusted to obtain the adjusted output quality of the refining and chemical processing node.

8. The method according to claim 7, characterized in that, The current operating condition of the refining and chemical processing node is determined based on the number of data to be verified in the output quality of the neighboring nodes, including: If the number of data to be verified in the output quality of the neighboring node is greater than a preset first quantity threshold, then the current environmental data of the refining and chemical node, the historical environmental data of the refining and chemical node, the current environmental data of the neighboring node, and the historical environmental data of the neighboring node are obtained. The similarity between the current environmental data of the refining and chemical node and the historical environmental data of the refining and chemical node is determined as the first similarity, and the similarity between the current environmental data of the neighboring node and the historical environmental data of the neighboring node is determined as the second similarity. The current operating condition of the refining and chemical node is determined based on the first similarity and the second similarity.

9. The method according to claim 8, characterized in that, The current operating condition of the refining and chemical processing node is determined based on the number of data to be verified in the output quality of the neighboring nodes, including: If the number of data to be verified in the output quality of the neighboring node is less than or equal to a preset first quantity threshold and greater than a preset second quantity threshold, then the current environmental data and the historical environmental data of the refining and chemical node are obtained. The similarity between the current environmental data of the oil refining and chemical node and the historical environmental data of the oil refining and chemical node is determined as the first similarity. Based on the first similarity, the current operating condition of the refining and chemical node is determined.

10. The method according to claim 9, characterized in that, The current operating condition of the refining and chemical processing node is determined based on the number of data to be verified in the output quality of the neighboring nodes, including: If the number of data to be verified in the output quality of the neighboring node is less than or equal to a preset second quantity threshold, then the current environmental data and the historical environmental data of the neighboring node are obtained. The similarity between the current environmental data of the neighboring nodes and the historical environmental data of the neighboring nodes is determined as the second similarity. Based on the second similarity, the current operating condition of the refining and chemical node is determined.

11. The method according to claim 7, characterized in that, Based on the current operating conditions and feed quality of the refining and chemical processing node, the data to be verified is adjusted to obtain the adjusted output quality of the refining and chemical processing node, including: Determine the material standard dataset corresponding to the current operating condition; wherein the material standard dataset includes the allowable feed quality and discharge quality under the current operating condition; Based on the feed quality and discharge quality in the material standard dataset, and the feed quality of the refining and chemical node, the data to be verified is adjusted to obtain the adjusted discharge quality of the refining and chemical node.

12. The method according to any one of claims 1-11, characterized in that, Also includes: Obtain the by-product quality of the refining and chemical processing node; wherein, the by-product quality represents the sum of the mass of intermediate products and by-products produced by the refining and chemical processing node; Based on the by-product quality, feed quality, and adjusted discharge quality of the refining and chemical node, the estimated loss of the refining and chemical node is determined; wherein the estimated loss represents the quality that the refining and chemical node may lose during processing.

13. The method according to claim 12, characterized in that, Also includes: Obtain the actual value of the loss at the aforementioned refining and chemical nodes; If the difference between the estimated loss and the actual loss is within a preset difference threshold, then the adjusted discharge quality of the refining and chemical node is determined to be the actual discharge quality of the refining and chemical node.

14. The method according to claim 13, characterized in that, Also includes: If the difference between the estimated loss and the actual loss is not within a preset difference threshold, then the material data of the refining and chemical node within a preset historical time period is obtained, and the preset constraints of the refining and chemical process are determined based on the material data within the preset historical time period; wherein, the preset constraints are used to determine whether there is any data to be verified in the output quality of the refining and chemical node. If, according to the preset constraints, it is determined that there is data to be verified in the discharge quality of the refining and chemical node, then the discharge quality of the neighboring nodes of the refining and chemical node is obtained; based on the discharge quality of the neighboring nodes and the feed quality of the refining and chemical node, the data to be verified is readjusted to obtain the adjusted discharge quality of the refining and chemical node.

15. A processing device for material data based on oil refining and chemical engineering, characterized in that, include: The first acquisition unit is used to acquire material data of the refining and chemical node; wherein, the refining and chemical node represents a device for material processing in the refining and chemical process, and the material data includes the feed quality and discharge quality of the material in the refining and chemical node. The second acquisition unit is used to acquire the output quality of neighboring nodes of the refining and chemical node if it is determined that there is data to be verified in the output quality of the refining and chemical node; wherein, the data to be verified is an outlier or a missing value, and the neighboring node represents a device that receives the data to be verified produced by the refining and chemical node in the refining and chemical process. The data adjustment unit is used to adjust the data to be verified based on the discharge quality of the neighboring nodes and the feed quality of the refining and chemical node, so as to obtain the adjusted discharge quality of the refining and chemical node.

16. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-14.

17. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-14.

18. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method of any one of claims 1-14.

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