Production early warning control method and system based on industrial data analysis

Abstract

The present invention discloses a production early warning control method and system based on industrial data analysis, which relates to the technical field of industrial production early warning control, and constructs a production equipment location node plane diagram and an operating parameter dynamic performance model; then, collects equipment operating parameters, and dynamically adjusts the model; counts the normal operating parameter change groups of the equipment under normal conditions; uses these normal operating parameter change groups to compare the current operating parameters of the equipment and marks the abnormal parameters; according to the order of abnormal marking, connects the abnormal parameters in the model with vector lines to form abnormal dynamic performance; constructs these abnormal dynamic performances into an abnormal dynamic performance set for real-time monitoring of the equipment operating status, and performs analysis and early warning. The above technical scheme of the present invention realizes intelligent early warning control of industrial production equipment and improves the safety and stability of the production process.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial production early warning control and management, and in particular to a production early warning control and management method and system based on industrial data analysis. Background Art

[0002] In today's industrial production environment, with the deep integration of industrialization and informatization, and the introduction of concepts such as Industry 4.0 and intelligent manufacturing, the industrial production process has become increasingly complex and changeable. Traditional production management methods often rely on manual experience judgment and fixed rule settings to carry out production monitoring and risk control. This method is incapable of meeting the needs of large-scale, highly complex and fast-changing industrial production environments.

[0003] Especially in some key production links, such as the operation of large industrial equipment, the control of chemical production processes, and the coordination of intelligent manufacturing systems, potential risk factors may exist at any time, and it is often difficult to timely discover and effectively control them through traditional methods. Once these risk factors evolve into actual accidents or failures, they may cause huge economic losses to the company and even endanger the lives of people. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system capable of performing production early warning control on industrial industries.

[0005] The present invention discloses a production early warning control method based on industrial data analysis, comprising:

[0006] According to the relative position of the production equipment on the site, a production equipment location node plane diagram is constructed, and a site production equipment node operation parameter dynamic performance model is constructed for each site production equipment;

[0007] Collecting several types of operating parameters of production equipment at the site, and dynamically adjusting the corresponding operating parameter dynamic performance model based on the operating parameters;

[0008] Collect and record several types of operating parameters of the site production equipment in the normal state, record the combination of several operating parameter changes collected at the same time as a normal operating parameter change group, and make statistics on several normal operating parameter change groups;

[0009] All normal operating parameter change groups are used to compare the operating parameters of the site production equipment. If there are operating parameters that do not conform to all normal operating parameter change groups, the operating parameter dynamic performance unit corresponding to the operating parameter is marked as abnormal, wherein the operating parameter dynamic performance unit belongs to the operating parameter dynamic performance model;

[0010] In a preset time period, based on the order of abnormal markings, the operating parameter dynamic performance units of the operating parameter dynamic performance model are connected by vector lines to obtain abnormal dynamic performance of the abnormal operating parameter dynamic performance model;

[0011] constructing abnormal dynamic performance of the abnormal operation parameter dynamic performance model as an abnormal dynamic performance set;

[0012] When issuing status warnings for site production equipment, the operating parameters of the site production equipment are monitored in real time, and the operating parameters are analyzed using abnormal dynamic performance sets. Based on the analysis results, status warnings are issued for site production equipment.

[0013] In some embodiments disclosed in the present invention, a method for dynamically adjusting a corresponding operating parameter dynamic representation model based on an operating parameter includes:

[0014] The same operating parameters are sorted according to the collection time relationship to form an operating parameter collection sequence. Based on each operating parameter in the operating parameter collection sequence, the operating parameter dynamic representation model is adjusted to obtain a dynamic representation frame of the operating parameter dynamic representation model. Based on the collection frequency of the operating parameters, the dynamic representation frames are coherently represented to obtain the dynamic representation of the operating parameter dynamic representation model.

[0015] In some embodiments disclosed in the present invention, a method for constructing a site production equipment node and constructing an operating parameter dynamic performance model for each site production equipment includes:

[0016] Determine different types of operating parameters of the production equipment at the site, and construct an operating parameter dynamic expression unit for each type of operating parameter, the operating parameter dynamic expression unit includes a dynamic expression circle, and the dynamic expression circle determines the diameter according to the corresponding operating parameter;

[0017] A vertical node reference line is constructed for each site production equipment node, and the dynamic performance circle is configured at different heights from the vertical node reference line. Based on the preset weight of the type of operating parameter, the height of the dynamic performance circle corresponding to the operating parameter on the vertical node reference line is determined.

[0018] In some embodiments disclosed in the present invention, a method for constructing an abnormal dynamic performance of an abnormal operating parameter dynamic performance model into an abnormal dynamic performance set includes:

[0019] Constructing a positioning space for the abnormal operation parameter dynamic performance model, and determining an abnormal dynamic performance circle in each abnormal dynamic performance frame of the abnormal dynamic performance, and abnormal vector lines between the abnormal dynamic performance circles;

[0020] The positioning space is divided into blocks to obtain a number of positioning space blocks, the positioning space blocks to which the abnormal dynamic performance circle represented by each abnormal dynamic frame is mapped are determined, and the mapped positioning space blocks are sorted to obtain a positioning space block sequence;

[0021] Taking the positioning space block sequence as the screening and classification condition, each abnormal dynamic performance is classified to obtain several initial abnormal dynamic performance sets;

[0022] The direction of each abnormal dynamic performance circle in the positioning space block relative to the block center point is determined, and the pointing information is recorded for the positioning space blocks in the positioning space block sequence. Based on the positioning space block sequence with the pointing information recorded, the abnormal dynamic performances in the initial abnormal dynamic performance set are screened and classified again to obtain a reference abnormal dynamic performance set.

[0023] In some embodiments disclosed in the present invention, a method for monitoring the operating parameters of a site production equipment in real time and analyzing the operating parameters using an abnormal dynamic performance set includes:

[0024] Based on the real-time collected operation parameters, the operation dynamic performance model is dynamically adjusted to obtain the real-time dynamic performance of the operation dynamic performance model, and the performance state of each dynamic performance circle in the real-time dynamic performance is determined;

[0025] Analyze each real-time collected operating parameter using the normal operating parameter change group judgment model, determine the abnormal dynamic performance circle appearing in the real-time dynamic performance, and determine the order of appearance of the abnormal dynamic performance circles and the positioning space blocks to which they belong, and sort the positioning space blocks according to the order of the corresponding abnormal dynamic performance circles to obtain a positioning space block sequence, and determine the relative pointing of each abnormal dynamic performance circle to the block center point of the positioning space block, and record and mark the pointing information on each positioning space block in the positioning space block sequence, and associate the positioning space block sequence with the real-time dynamic performance;

[0026] Compare the positioning space block sequence in the real-time dynamic performance with the positioning space block sequences of different reference abnormal dynamic performance sets, and calculate the similar parameters based on the comparison results, and determine the reference abnormal dynamic performance set to be called based on the similar parameters;

[0027] Each abnormal dynamic performance in the reference abnormal dynamic set is compared with the real-time dynamic performance in real time, and the degree of adaptation is determined based on the comparison result. If the degree of adaptation is greater than or equal to the preset value, the corresponding abnormal dynamic performance is selected for calling, and an early warning is issued based on the called abnormal dynamic performance.

[0028] In some embodiments disclosed in the present invention, based on the comparison results, the method for calculating the similar parameters includes:

[0029] Determine a first coincidence of each positioning space block between the positioning space block sequences, and if the positioning space blocks are consistent, determine a second coincidence of the directional information corresponding to the positioning space blocks, and determine the proximity parameters between the positioning space block sequences based on the first coincidence and the second coincidence; ;

[0030] in, is a close parameter, To match the adjustment factor, To match the situation, adjust the constant. To locate the first The matching judgment function of the positioning space block is If the positioning space blocks match, then Output 1, otherwise output 0. For the The matching judgment function of the pointing information of the positioning space block, if the pointing information matches, then Output 1, otherwise output 0. is the total number of blocks in the positioning space block sequence.

[0031] In some embodiments disclosed in the present invention, a method for comparing each abnormal dynamic performance in the reference abnormal dynamic set with the real-time dynamic performance and determining the degree of adaptation based on the comparison result includes:

[0032] Compare the total expression circle area difference of the dynamic expression circles of the abnormal dynamic expression and the real-time dynamic expression in different dynamic expression frames, and the vector line matching ratio of the abnormal vector lines in different dynamic expression frames. The method for determining the vector line matching ratio is to calculate the ratio of the number of matched abnormal vector lines to the number of all abnormal vector lines, which is recorded as the vector line matching ratio. The method for determining the total expression circle area difference includes calculating a first total expression circle area of ​​all dynamic expression circles of the same dynamic expression frame of the abnormal dynamic expression, and calculating a second total expression circle area of ​​all dynamic expression circles of the same dynamic expression frame of the real-time dynamic expression, and calculating the difference between the first total expression circle and the second total expression circle, which is recorded as the total expression circle area difference;

[0033] Based on the difference in the areas of the performance circles and the matching ratio of the vector lines, the degree of adaptation between the abnormal dynamic performance and the real-time dynamic performance is determined;

[0034] Among them, the expression for calculating the degree of adaptation is: ;

[0035] in, For the degree of adaptation, is the preset maximum total circle area difference. is the total difference in the area of ​​the circle, is the vector line fitting ratio, is the adjustment coefficient of the vector line matching ratio, Adjustment constant for vector line fitting scaling effect.

[0036] In some embodiments disclosed in the present invention, a production early warning control system based on industrial data analysis is also disclosed, including:

[0037] The first module is used to construct a production equipment location node plane diagram according to the relative position of the site production equipment, and to construct a site production equipment node construction operation parameter dynamic performance model for each site production equipment;

[0038] The second module is used to collect several types of operating parameters of the production equipment on the site, and dynamically adjust the corresponding operating parameter dynamic performance model based on the operating parameters;

[0039] The third module is used to collect and record several types of operating parameters of the site production equipment in the normal state, record the combination of several operating parameter changes collected at the same time as a normal operating parameter change group, and perform statistics on several normal operating parameter change groups;

[0040] The fourth module is used to compare the operating parameters of the site production equipment with all normal operating parameter change groups. If there are operating parameters that do not conform to all normal operating parameter change groups, the operating parameter dynamic performance unit corresponding to the operating parameter is marked as abnormal, wherein the operating parameter dynamic performance unit belongs to the operating parameter dynamic performance model;

[0041] The fifth module is used to connect the operating parameter dynamic performance units of the operating parameter dynamic performance model by vector lines based on the order of abnormal marks within a preset time period to obtain abnormal dynamic performance of the abnormal operating parameter dynamic performance model;

[0042] A sixth module is used to construct the abnormal dynamic performance of the abnormal operation parameter dynamic performance model into an abnormal dynamic performance set;

[0043] The seventh module is used to monitor the operating parameters of the site production equipment in real time when issuing status warnings to the site production equipment, analyze the operating parameters using the abnormal dynamic performance set, and issue status warnings to the site production equipment based on the analysis results.

[0044] The present invention discloses a production early warning control method and system based on industrial data analysis, which relates to the technical field of industrial production early warning control, and constructs a production equipment location node plane diagram and an operating parameter dynamic performance model; then, collects equipment operating parameters, and dynamically adjusts the model; counts the normal operating parameter change groups of the equipment under normal conditions; uses these normal operating parameter change groups to compare the current operating parameters of the equipment and marks the abnormal parameters; according to the order of abnormal marking, connects the abnormal parameters in the model with vector lines to form abnormal dynamic performance; constructs these abnormal dynamic performances into an abnormal dynamic performance set for real-time monitoring of the equipment operating status, and performs analysis and early warning. The above technical scheme of the present invention realizes intelligent early warning control of industrial production equipment and improves the safety and stability of the production process.

[0045] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is a method step diagram of a production early warning control method based on industrial data analysis disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The technical solution of the present invention is further described below through the accompanying drawings and embodiments.

[0048] The following will be combined with the accompanying drawings and specific embodiments to clearly and completely describe the technical solution of the present invention. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention and cannot be understood as limiting the scope of protection of the present invention. Those skilled in the art in this field can make some non-essential improvements and adjustments based on the content of the present invention described below. In the present invention, unless otherwise clearly specified and limited, the technical terms used in the present invention should be the common meanings understood by the technical personnel described in the present invention.

[0049] Example:

[0050] The present invention discloses a production early warning control method based on industrial data analysis, see Figure 1 ,include:

[0051] Step S100, constructing a production equipment location node plan view according to the relative positions of the site production equipment, and constructing a site production equipment node operation parameter dynamic expression model for each site production equipment.

[0052] The purpose of constructing the production equipment location node plan and the dynamic performance model of the operating parameters is to visualize the spatial layout and operating status of the production equipment in the site. By drawing the production equipment location node plan, the relative position relationship between the equipment can be clearly understood, providing a spatial reference for subsequent equipment management and status monitoring. At the same time, constructing a dynamic performance model of the operating parameters for each site's production equipment can display the changes in the equipment's operating parameters in real time, such as temperature, pressure, speed, etc., providing a basis for equipment status monitoring and fault warning.

[0053] Explanation of the production equipment location node plan: This is a graphical representation used to show the relative position relationship between the various production equipment in the site. By constructing such a plan, you can intuitively understand the layout of the production equipment and provide a spatial reference for the subsequent construction of the dynamic performance model of the operating parameters and status warning.

[0054] Explanation of the dynamic performance model of operating parameters: This is a dynamic model built for each site's production equipment to show how the equipment's operating parameters change over time. The model may include multiple dynamic performance units, such as dynamic performance circles, to intuitively show the dynamic changes in the equipment's operating status.

[0055] In some embodiments disclosed in the present invention, a method for constructing a site production equipment node and constructing an operating parameter dynamic performance model for each site production equipment includes:

[0056] Step S101, determining different types of operating parameters of site production equipment, and constructing an operating parameter dynamic expression unit for each type of operating parameter, the operating parameter dynamic expression unit including a dynamic expression circle, the dynamic expression circle determines the diameter according to the corresponding operating parameter.

[0057] First, perform step S101 to determine the operating parameters of different types of site production equipment. These operating parameters may include temperature, pressure, rotation speed, vibration frequency, current intensity, etc., which are key indicators reflecting the operating status of the equipment. For each type of operating parameter, an operating parameter dynamic performance unit is constructed. The core of this dynamic performance unit is a dynamic performance circle, whose diameter is determined according to the corresponding operating parameter value. For example, the larger the operating parameter value, the larger the diameter of the dynamic performance circle, so that the size or degree of change of the operating parameter can be intuitively reflected by the diameter of the circle.

[0058] Step S102, construct a vertical node reference line for each site production equipment node, and configure the dynamic performance circle at different heights from the vertical node reference line, and determine the height of the dynamic performance circle corresponding to the operating parameter on the vertical node reference line based on the preset weight of the type to which the operating parameter belongs.

[0059] A vertical node reference line is constructed for each site production equipment node. This reference line is a vertical ruler or axis used to visually organize and manage the dynamic performance units of different operating parameters. Then, the dynamic performance circles are configured at different heights of the vertical node reference line. The height here is not set arbitrarily, but is determined based on the preset weight of the type of operating parameter. The preset weight reflects the importance or influence of different types of operating parameters in the evaluation of equipment operating status. The greater the weight of the operating parameter, the higher the height of the corresponding dynamic performance circle on the vertical node reference line.

[0060] Step S200 , collecting several types of operating parameters of production equipment at the site, and dynamically adjusting the corresponding operating parameter dynamic performance model based on the operating parameters.

[0061] The purpose of collecting and adjusting operating parameters is to obtain real-time operating status information of the equipment. By collecting several types of operating parameters of the production equipment on site, such as vibration, noise, current, etc., we can fully understand the operating status of the equipment. Then, based on the collected operating parameters, the corresponding operating parameter dynamic performance model is dynamically adjusted so that the model can reflect the changes in the operating status of the equipment in real time, providing accurate data support for subsequent status analysis and fault warning.

[0062] Explanation of operating parameters: This refers to various data generated by production equipment during operation, such as temperature, pressure, speed, vibration, etc. These parameters are an important basis for evaluating the operating status of the equipment.

[0063] In some embodiments disclosed in the present invention, a method for dynamically adjusting a corresponding operating parameter dynamic representation model based on an operating parameter includes:

[0064] Step S201, sorting the same operating parameters according to the collection time relationship to form an operating parameter collection sequence, adjusting the operating parameter dynamic representation model based on each operating parameter in the operating parameter collection sequence to obtain a dynamic representation frame of the operating parameter dynamic representation model, and based on the collection frequency of the operating parameters, coherently representing the dynamic representation frame to obtain a dynamic representation of the operating parameter dynamic representation model.

[0065] Step S300, collecting and recording several types of operating parameters of the site production equipment in a normal state, recording a combination of several operating parameter changes collected simultaneously as a normal operating parameter change group, and performing statistics on several normal operating parameter change groups.

[0066] The purpose of statistically analyzing the normal operation parameter change groups is to establish the parameter range for normal operation of the equipment. Under normal conditions of the equipment, several types of operating parameters are collected and recorded, and the combination of several operating parameter changes collected at the same time is recorded as a normal operation parameter change group. By statistically analyzing these combinations, the parameter change rules and ranges of the equipment during normal operation can be obtained, providing a benchmark for subsequent abnormality detection and fault warning.

[0067] Normal operation parameter change group explanation: This is a combination of several operating parameter changes collected simultaneously under the normal state of the equipment. By counting these combinations, the parameter range for normal operation of the equipment can be established, providing a benchmark for subsequent abnormal detection and early warning.

[0068] Step S400, using all normal operating parameter change groups to compare the operating parameters of the site production equipment, if there are operating parameters that do not conform to all normal operating parameter change groups, the operating parameter dynamic performance unit corresponding to the operating parameter is marked as abnormal, wherein the operating parameter dynamic performance unit belongs to the operating parameter dynamic performance model.

[0069] Explanation of the operating parameter dynamic performance unit: This is the basic component unit of the operating parameter dynamic performance model, such as the dynamic performance circle, etc. Each unit represents a specific operating parameter of the equipment and reflects the operating status of the equipment through its dynamic changes.

[0070] Abnormal marking is to timely discover abnormal status of equipment. All normal operating parameter change groups are used to compare the operating parameters of the production equipment on site. If there are operating parameters that do not meet all normal operating parameter change groups, it means that the equipment may be in an abnormal state. At this time, the operating parameter dynamic performance unit corresponding to the operating parameter is marked abnormally, which can intuitively display the abnormal part and degree of the equipment, providing a basis for subsequent fault diagnosis and maintenance.

[0071] Comparing the operating parameters of the production equipment on site with all normal operating parameter change groups is a comprehensive process. First, it is necessary to collect and count the operating parameter data of the equipment under normal operating conditions to form a series of normal operating parameter change groups, which represent the parameter change range and law of the equipment during normal operation. Then, the current operating parameters of the production equipment on site are collected in real time, and the various operating indicators of the equipment are obtained through sensors and data acquisition systems. Next, the real-time collected data is preprocessed to ensure the accuracy and consistency of the data, and then the real-time parameters are compared one by one with all normal operating parameter change groups to detect whether the real-time parameter values ​​are in line with the range or pattern of the normal change group.

[0072] Step S500, within a preset time period, based on the order of abnormal marks, the operating parameter dynamic performance units of the operating parameter dynamic performance model are connected by vector lines to obtain the abnormal dynamic performance of the abnormal operating parameter dynamic performance model.

[0073] The purpose of generating abnormal dynamic performance is to more intuitively display the abnormal state changes of the equipment. Within the preset time period, based on the order of abnormal markings, the operating parameter dynamic performance units of the operating parameter dynamic performance model are connected by vector lines to obtain the abnormal dynamic performance of the abnormal operating parameter dynamic performance model. Through this graphical representation, the changing trend and evolution process of the abnormal state of the equipment can be clearly seen, providing strong support for subsequent fault analysis and processing.

[0074] Abnormal dynamic performance explanation: In the preset time period, based on the order of abnormal marking, the operating parameter dynamic performance units of the operating parameter dynamic performance model are connected by vector lines to form a graphical representation. It reflects the dynamic changes of the equipment under abnormal conditions.

[0075] Step S600: constructing the abnormal dynamic performance of the abnormal operation parameter dynamic performance model into an abnormal dynamic performance set.

[0076] The purpose of constructing an abnormal dynamic performance set is to classify and analyze the abnormal state of the equipment. By constructing the abnormal dynamic performance of the abnormal operation parameter dynamic performance model into an abnormal dynamic performance set, different types of abnormal states can be uniformly managed and analyzed. By comparing and analyzing the similarities and differences between different abnormal dynamic performances, we can have a deeper understanding of the failure mechanism and evolution law of the equipment, providing a scientific basis for equipment maintenance and management.

[0077] Abnormal dynamic performance set explanation: This is a set that summarizes all abnormal dynamic performances and is used for subsequent status warning and analysis.

[0078] In some embodiments disclosed in the present invention, a method for constructing an abnormal dynamic performance of an abnormal operating parameter dynamic performance model into an abnormal dynamic performance set includes:

[0079] Step S601 : constructing a positioning space for the abnormal operation parameter dynamic performance model, and determining the abnormal dynamic performance circle in each abnormal dynamic performance frame of the abnormal dynamic performance, and the abnormal vector lines between the abnormal dynamic performance circles.

[0080] Constructing positioning space: First, construct a three-dimensional or two-dimensional positioning space for the abnormal operation parameter dynamic performance model. This space will serve as a container for abnormal dynamic performance circles and abnormal vector lines to organize and display the change trajectory and correlation relationship of abnormal operation parameters.

[0081] Determine abnormal dynamic performance elements: In the positioning space, identify and determine the abnormal dynamic performance circles in each abnormal dynamic performance frame, as well as the abnormal vector lines between these circles. The abnormal dynamic performance circles represent the value or state of the abnormal operating parameters, while the abnormal vector lines connect the abnormal dynamic performance circles at different times or states, indicating the change trend or association of the abnormal parameters.

[0082] Positioning space interpretation: This is a space constructed for the purpose of classifying and analyzing abnormal dynamic performance. By determining the abnormal dynamic performance circles in the abnormal dynamic performance frame and the abnormal vector lines between them, block division and classification can be performed in the positioning space.

[0083] Step S602, divide the positioning space into blocks to obtain a plurality of positioning space blocks, determine the positioning space blocks mapped to the abnormal dynamic performance circle of each abnormal dynamic frame, and sort the mapped positioning space blocks to obtain a positioning space block sequence.

[0084] Block division: The positioning space is divided into blocks to obtain several positioning space blocks. These blocks can be divided according to factors such as space size, shape, importance, etc., so as to better organize and display abnormal dynamic performance.

[0085] Determine the mapping blocks and sorting: Determine which positioning space block the abnormal dynamic performance circle of each abnormal dynamic frame is mapped to. Then, sort these mapped positioning space blocks according to the time sequence, spatial position or other relevant factors to obtain the positioning space block sequence. This sequence will serve as the basis for subsequent screening and classification.

[0086] Explanation of positioning space block sequence: This is the sequence obtained by sorting the blocks according to the mapping of the abnormal dynamic performance circle in the abnormal dynamic performance frame after the positioning space is divided into blocks. It is used for subsequent abnormal dynamic performance classification and screening.

[0087] Step S603 , classifying each abnormal dynamic performance by taking the positioning space block sequence as a screening and classification condition, and obtaining a plurality of initial abnormal dynamic performance sets.

[0088] Classification processing: Using the location space block sequence as the screening and classification condition, classify each abnormal dynamic performance. That is, classify the abnormal dynamic performances with similar characteristics or associations into the same category to form several initial abnormal dynamic performance sets. These sets preliminarily reflect the different categories or modes of abnormal operation parameters.

[0089] Step S604, determining the direction of each abnormal dynamic performance circle in the positioning space block relative to the block center point, and recording the pointing information for the positioning space block in the positioning space block sequence, and based on the positioning space block sequence with the pointing information recorded, re-screening and classifying the abnormal dynamic performances in the initial abnormal dynamic performance set to obtain a reference abnormal dynamic performance set.

[0090] Determine the direction information: Determine the direction of each abnormal dynamic performance circle in the positioning space block relative to the center point of the block. This direction information reflects the position and direction of the abnormal dynamic performance circle in space, which helps to further understand the changing trend and correlation of abnormal operation parameters.

[0091] Recording and re-screening and classification: Record the pointing information into the positioning space block sequence, and then re-screen and classify the abnormal dynamic performance in the initial abnormal dynamic performance set based on this sequence of recorded pointing information. This classification will be more detailed and accurate, and can better reveal the essential characteristics and correlation patterns of abnormal operating parameters. Finally, a reference abnormal dynamic performance set is obtained, which provides strong support for subsequent fault analysis, early warning and maintenance decisions.

[0092] Reference to the explanation of abnormal dynamic performance set: This is a set of abnormal dynamic performance obtained after classification and screening, which is used for comparison and analysis with real-time dynamic performance.

[0093] Step S700, when issuing a status warning to the site production equipment, the operating parameters of the site production equipment are monitored in real time, and the operating parameters are analyzed using an abnormal dynamic performance set, and based on the analysis result, a status warning is issued to the site production equipment.

[0094] Status warning is to timely discover and deal with equipment failures. When issuing status warnings for site production equipment, the operating parameters of site production equipment are monitored in real time, and the operating parameters are analyzed using abnormal dynamic performance sets. Once abnormal changes in operating parameters are found, and they meet a certain abnormal pattern in the abnormal dynamic performance set, status warnings are immediately issued to site production equipment to remind relevant personnel to take timely measures to ensure the normal operation of equipment and safe and stable production.

[0095] In some embodiments disclosed in the present invention, a method for monitoring the operating parameters of a site production equipment in real time and analyzing the operating parameters using an abnormal dynamic performance set includes:

[0096] Step S701 , dynamically adjust the operation dynamic performance model based on the operation parameters collected in real time, obtain the real-time dynamic performance of the operation dynamic performance model, and determine the performance state of each dynamic performance circle in the real-time dynamic performance.

[0097] In this step, the operation dynamic performance model is first dynamically adjusted based on the real-time collected operation parameters. This means that the model will update its display content in real time according to the current actual operation data of the equipment to ensure that the model can accurately reflect the operation status of the equipment. Through the adjusted model, the real-time dynamic performance of the operation dynamic performance model is obtained, which includes the real-time status information of each dynamic performance circle in the model. Subsequently, the performance status of these dynamic performance circles is analyzed to determine whether they are within the normal range or whether there are any abnormalities. The purpose of this step is to promptly discover abnormal changes in equipment operation and provide a basis for subsequent abnormal analysis and processing.

[0098] Step S702, using the normal operating parameter change group judgment model to analyze each real-time collected operating parameter, determine the abnormal dynamic performance circles that appear in the real-time dynamic performance, and determine the order of appearance of the abnormal dynamic performance circles and the positioning space blocks to which they belong, and sort the positioning space blocks according to the order of the corresponding abnormal dynamic performance circles to obtain a positioning space block sequence, and determine the relative pointing of each abnormal dynamic performance circle to the block center point of the positioning space block, and record the pointing information on each positioning space block in the positioning space block sequence, and associate the positioning space block sequence with the real-time dynamic performance.

[0099] Next, the normal operating parameter change group judgment model is used to conduct an in-depth analysis of each real-time collected operating parameter. By comparing the range of change of real-time parameters and normal operating parameters, it is possible to identify which parameters deviate from the normal range, and then determine the abnormal dynamic performance circle that appears in the real-time dynamic performance. At the same time, the order in which these abnormal dynamic performance circles appear, as well as the positioning space blocks to which they belong, are recorded, which helps to track the occurrence and development of abnormalities. In order to more intuitively display the position and trend of the abnormal dynamic performance circle, the positioning space blocks are sorted according to the order of the corresponding abnormal dynamic performance circles to obtain the positioning space block sequence. In addition, the relative orientation of each abnormal dynamic performance circle in the block center point in the positioning space block is determined, and this orientation information is recorded and marked on each positioning space block in the positioning space block sequence. Finally, the positioning space block sequence is associated with the real-time dynamic performance, which facilitates subsequent comparison and analysis.

[0100] Step S703, compare the positioning space block sequence in the real-time dynamic performance with the positioning space block sequences of different reference abnormal dynamic performance sets, calculate similar parameters based on the comparison results, and determine the reference abnormal dynamic performance set to be called based on the similar parameters.

[0101] After obtaining the positioning space block sequence in the real-time dynamic performance, it is compared with the positioning space block sequence of different reference abnormal dynamic performance sets. The purpose of this step is to find the historical abnormal dynamic performance set that is most similar to the current abnormality. In order to quantify this similarity, the close parameter is calculated, which reflects the similarity between the current abnormality and the historical abnormality. Based on the calculation results of the close parameter, the reference abnormal dynamic performance set that needs to be called is determined. This set contains the historical abnormal dynamic performance that is most similar to the current abnormality, which provides a strong reference for subsequent abnormality analysis and processing.

[0102] Proximity parameter explanation: This is a parameter used to measure the similarity between two positioning space block sequences. By calculating the proximity parameter, the reference abnormal dynamic performance set to be called can be determined.

[0103] In some embodiments disclosed in the present invention, based on the comparison results, the method for calculating the similar parameters includes:

[0104] Step S7031, determine the first matching situation of each positioning space block between the positioning space block sequences. If the positioning space blocks match, determine the second matching situation of the directional information corresponding to the positioning space blocks. Based on the first matching situation and the second matching situation, determine the similar parameters between the positioning space block sequences. .

[0105] in, is a close parameter, To match the adjustment factor, To match the situation, adjust the constant. To locate the first The matching judgment function of the positioning space block is If the positioning space blocks match, then Output 1, otherwise output 0. For the The matching judgment function of the pointing information of the positioning space block, if the pointing information matches, then Output 1, otherwise output 0. is the total number of blocks in the positioning space block sequence.

[0106] Step S704, compare each abnormal dynamic performance in the reference abnormal dynamic set with the real-time dynamic performance in real time, and determine the degree of adaptation based on the comparison result. If the degree of adaptation is greater than or equal to a preset value, select the corresponding abnormal dynamic performance for calling, and issue an early warning based on the called abnormal dynamic performance.

[0107] Compare each abnormal dynamic performance in the selected reference abnormal dynamic set with the real-time dynamic performance in real time. Through this comparison process, the similarity between the current abnormality and the historical abnormality can be further verified, and their degree of adaptation can be determined. If the degree of adaptation is greater than or equal to the preset threshold, the corresponding abnormal dynamic performance is selected for calling, and the early warning mechanism is triggered based on this abnormal dynamic performance. The purpose of this step is to promptly discover and handle the abnormal operating status of the equipment, prevent the occurrence of potential failures, and ensure the stable operation of the equipment.

[0108] In some embodiments disclosed in the present invention, a method for comparing each abnormal dynamic performance in the reference abnormal dynamic set with the real-time dynamic performance and determining the degree of adaptation based on the comparison result includes:

[0109] Step S7041, compare the total expression circle area difference of the dynamic expression circles of the abnormal dynamic expression and the real-time dynamic expression in different dynamic expression frames, and the vector line matching ratio of the abnormal vector lines in different dynamic expression frames, the method for determining the vector line matching ratio is to calculate the ratio of the number of matched abnormal vector lines to the number of all abnormal vector lines, recorded as the vector line matching ratio, the method for determining the total expression circle area difference includes calculating a first total expression circle area of ​​all dynamic expression circles of the same dynamic expression frame of the abnormal dynamic expression, and calculating a second total expression circle area of ​​all dynamic expression circles of the real-time dynamic expression in the same dynamic expression frame, and calculating the difference between the first total expression circle and the second total expression circle, which is recorded as the total expression circle area difference.

[0110] Step S7042, based on the difference in the areas of the performance circles and the matching ratio of the vector lines, the degree of adaptation between the abnormal dynamic performance and the real-time dynamic performance is determined.

[0111] Explanation of the degree of adaptation: This is a parameter used to measure the similarity between the abnormal dynamic performance in the reference abnormal dynamic performance set and the real-time dynamic performance. By calculating the degree of adaptation, the abnormal dynamic performance used for early warning can be selected.

[0112] Among them, the expression for calculating the degree of adaptation is: .

[0113] in, For the degree of adaptation, is the preset maximum total circle area difference. is the total difference in the area of ​​the circle, is the vector line fitting ratio, is the adjustment coefficient of the vector line matching ratio, Adjustment constant for vector line fitting scaling effect.

[0114] In some embodiments disclosed in the present invention, a production early warning control system based on industrial data analysis is also disclosed, including:

[0115] The first module is used to construct a production equipment location node plane diagram according to the relative position of the site production equipment, and to construct a site production equipment node construction operation parameter dynamic performance model for each site production equipment;

[0116] The second module is used to collect several types of operating parameters of the production equipment on the site, and dynamically adjust the corresponding operating parameter dynamic performance model based on the operating parameters;

[0117] The third module is used to collect and record several types of operating parameters of the site production equipment in the normal state, record the combination of several operating parameter changes collected at the same time as a normal operating parameter change group, and perform statistics on several normal operating parameter change groups;

[0118] The fourth module is used to compare the operating parameters of the site production equipment with all normal operating parameter change groups. If there are operating parameters that do not conform to all normal operating parameter change groups, the operating parameter dynamic performance unit corresponding to the operating parameter is marked as abnormal, wherein the operating parameter dynamic performance unit belongs to the operating parameter dynamic performance model;

[0119] The fifth module is used to connect the operating parameter dynamic performance units of the operating parameter dynamic performance model by vector lines based on the order of abnormal marks within a preset time period to obtain abnormal dynamic performance of the abnormal operating parameter dynamic performance model;

[0120] A sixth module is used to construct the abnormal dynamic performance of the abnormal operation parameter dynamic performance model into an abnormal dynamic performance set;

[0121] The seventh module is used to monitor the operating parameters of the site production equipment in real time when issuing status warnings to the site production equipment, analyze the operating parameters using the abnormal dynamic performance set, and issue status warnings to the site production equipment based on the analysis results.

[0122] The present invention discloses a production early warning control method and system based on industrial data analysis, which relates to the technical field of industrial production early warning control, and constructs a production equipment location node plane diagram and an operating parameter dynamic performance model; then, collects equipment operating parameters, and dynamically adjusts the model; counts the normal operating parameter change groups of the equipment under normal conditions; uses these normal operating parameter change groups to compare the current operating parameters of the equipment and marks the abnormal parameters; according to the order of abnormal marking, connects the abnormal parameters in the model with vector lines to form abnormal dynamic performance; constructs these abnormal dynamic performances into an abnormal dynamic performance set for real-time monitoring of the equipment operating status, and performs analysis and early warning. The above technical scheme of the present invention realizes intelligent early warning control of industrial production equipment and improves the safety and stability of the production process.

[0123] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present invention can be implemented by hardware, or by software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each implementation scenario of the present invention.

[0124] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A production early warning control method based on industrial data analysis, characterized in that: include: According to the relative position of the production equipment on the site, a production equipment location node plane diagram is constructed, and a site production equipment node operation parameter dynamic performance model is constructed for each site production equipment; Collecting several types of operating parameters of production equipment at the site, and dynamically adjusting the corresponding operating parameter dynamic performance model based on the operating parameters; Collect and record several types of operating parameters of the site production equipment in the normal state, record the combination of several operating parameter changes collected at the same time as a normal operating parameter change group, and make statistics on several normal operating parameter change groups; All normal operating parameter change groups are used to compare the operating parameters of the site production equipment. If there are operating parameters that do not conform to all normal operating parameter change groups, the operating parameter dynamic performance unit corresponding to the operating parameter is marked as abnormal, wherein the operating parameter dynamic performance unit belongs to the operating parameter dynamic performance model; In a preset time period, based on the order of abnormal markings, the operating parameter dynamic performance units of the operating parameter dynamic performance model are connected by vector lines to obtain abnormal dynamic performance of the abnormal operating parameter dynamic performance model; constructing abnormal dynamic performance of the abnormal operation parameter dynamic performance model as an abnormal dynamic performance set; When issuing status warnings for site production equipment, the operating parameters of the site production equipment are monitored in real time, and the operating parameters are analyzed using abnormal dynamic performance sets. Based on the analysis results, status warnings are issued for site production equipment; The method for constructing a site production equipment node and constructing an operating parameter dynamic performance model for each site production equipment includes: Determine different types of operating parameters of the production equipment at the site, and construct an operating parameter dynamic expression unit for each type of operating parameter, the operating parameter dynamic expression unit includes a dynamic expression circle, and the dynamic expression circle determines the diameter according to the corresponding operating parameter; A vertical node reference line is constructed for each site production equipment node, and the dynamic performance circle is configured at different heights from the vertical node reference line. Based on the preset weight of the type of operating parameter, the height of the dynamic performance circle corresponding to the operating parameter on the vertical node reference line is determined.

2. The production early warning control method based on industrial data analysis according to claim 1 is characterized in that: Based on the operating parameters, the method for dynamically adjusting the corresponding operating parameter dynamic performance model includes: The same operating parameters are sorted according to the collection time relationship to form an operating parameter collection sequence. Based on each operating parameter in the operating parameter collection sequence, the operating parameter dynamic representation model is adjusted to obtain a dynamic representation frame of the operating parameter dynamic representation model. Based on the collection frequency of the operating parameters, the dynamic representation frames are coherently represented to obtain the dynamic representation of the operating parameter dynamic representation model.

3. The production early warning control method based on industrial data analysis according to claim 1 is characterized in that: The method of constructing the abnormal dynamic performance of the abnormal operation parameter dynamic performance model into an abnormal dynamic performance set includes: Constructing a positioning space for the abnormal operation parameter dynamic performance model, and determining an abnormal dynamic performance circle in each abnormal dynamic performance frame of the abnormal dynamic performance, and abnormal vector lines between the abnormal dynamic performance circles; The positioning space is divided into blocks to obtain a number of positioning space blocks, the positioning space blocks to which the abnormal dynamic performance circle represented by each abnormal dynamic frame is mapped are determined, and the mapped positioning space blocks are sorted to obtain a positioning space block sequence; Taking the positioning space block sequence as the screening and classification condition, each abnormal dynamic performance is classified to obtain several initial abnormal dynamic performance sets; The direction of each abnormal dynamic performance circle in the positioning space block relative to the block center point is determined, and the pointing information is recorded for the positioning space blocks in the positioning space block sequence. Based on the positioning space block sequence with the pointing information recorded, the abnormal dynamic performances in the initial abnormal dynamic performance set are screened and classified again to obtain a reference abnormal dynamic performance set.

4. The production early warning control method based on industrial data analysis according to claim 3 is characterized in that: The method of monitoring the operating parameters of the production equipment in the field in real time and analyzing the operating parameters by using the abnormal dynamic performance set includes: Based on the real-time collected operation parameters, the operation dynamic performance model is dynamically adjusted to obtain the real-time dynamic performance of the operation dynamic performance model, and the performance state of each dynamic performance circle in the real-time dynamic performance is determined; Analyze each real-time collected operating parameter using the normal operating parameter change group judgment model, determine the abnormal dynamic performance circle appearing in the real-time dynamic performance, determine the order of the abnormal dynamic performance circles and the positioning space blocks to which they belong, sort the positioning space blocks according to the order of the corresponding abnormal dynamic performance circles, obtain the positioning space block sequence, determine the relative direction of the block center point of each abnormal dynamic performance circle in the positioning space block, record and mark the pointing information on each positioning space block in the positioning space block sequence, and associate the positioning space block sequence with the real-time dynamic performance; Compare the positioning space block sequence in the real-time dynamic performance with the positioning space block sequences of different reference abnormal dynamic performance sets, and calculate the similar parameters based on the comparison results, and determine the reference abnormal dynamic performance set to be called based on the similar parameters; Each abnormal dynamic performance in the reference abnormal dynamic set is compared with the real-time dynamic performance in real time, and the degree of adaptation is determined based on the comparison result. If the degree of adaptation is greater than or equal to the preset value, the corresponding abnormal dynamic performance is selected for calling, and an early warning is issued based on the called abnormal dynamic performance.

5. The production early warning control method based on industrial data analysis according to claim 4 is characterized in that: Based on the comparison results, the methods for calculating the similar parameters include: Determine a first coincidence of each positioning space block between the positioning space block sequences, and if the positioning space blocks are consistent, determine a second coincidence of the directional information corresponding to the positioning space blocks, and determine the proximity parameters between the positioning space block sequences based on the first coincidence and the second coincidence; ； in, is a close parameter, To match the adjustment factor, To match the situation, adjust the constant. To locate the first The matching judgment function of the positioning space block is If the positioning space blocks match, then Output 1, otherwise output 0. For the The matching judgment function of the pointing information of the positioning space block, if the pointing information matches, then Output 1, otherwise output 0. is the total number of blocks in the positioning space block sequence.

6. The production early warning control method based on industrial data analysis according to claim 4 is characterized in that: The method of comparing each abnormal dynamic performance in the reference abnormal dynamic set with the real-time dynamic performance and determining the degree of adaptation based on the comparison result includes: Compare the total expression circle area difference of the dynamic expression circles of the abnormal dynamic expression and the real-time dynamic expression in different dynamic expression frames, and the vector line matching ratio of the abnormal vector lines in different dynamic expression frames. The method for determining the vector line matching ratio is to calculate the ratio of the number of matched abnormal vector lines to the number of all abnormal vector lines, which is recorded as the vector line matching ratio. The method for determining the total expression circle area difference includes calculating a first total expression circle area of ​​all dynamic expression circles of the same dynamic expression frame of the abnormal dynamic expression, and calculating a second total expression circle area of ​​all dynamic expression circles of the same dynamic expression frame of the real-time dynamic expression, and calculating the difference between the first total expression circle and the second total expression circle, which is recorded as the total expression circle area difference; Based on the difference in the areas of the performance circles and the matching ratio of the vector lines, the degree of adaptation between the abnormal dynamic performance and the real-time dynamic performance is determined; Among them, the expression for calculating the degree of adaptation is: ; in, For the degree of adaptation, is the preset maximum total circle area difference. is the total difference in the area of ​​the circle, is the vector line fitting ratio, is the adjustment coefficient of the vector line matching ratio, Adjustment constant for vector line fitting scaling effect.

7. The production early warning control system based on industrial data analysis is characterized by: A production early warning control method based on industrial data analysis for executing any one of claims 1-6, comprising: The first module is used to construct a production equipment location node plane diagram based on the relative positions of the site production equipment, and to construct a site production equipment node construction operation parameter dynamic performance model for each site production equipment; The second module is used to collect several types of operating parameters of the production equipment on the site, and dynamically adjust the corresponding operating parameter dynamic performance model based on the operating parameters; The third module is used to collect and record several types of operating parameters of the site production equipment in the normal state, record the combination of several operating parameter changes collected at the same time as a normal operating parameter change group, and perform statistics on several normal operating parameter change groups; The fourth module is used to compare the operating parameters of the site production equipment with all normal operating parameter change groups. If there are operating parameters that do not conform to all normal operating parameter change groups, the operating parameter dynamic performance unit corresponding to the operating parameter is marked as abnormal, wherein the operating parameter dynamic performance unit belongs to the operating parameter dynamic performance model; The fifth module is used to connect the operating parameter dynamic performance units of the operating parameter dynamic performance model by vector lines based on the order of abnormal marks within a preset time period to obtain abnormal dynamic performance of the abnormal operating parameter dynamic performance model; A sixth module is used to construct the abnormal dynamic performance of the abnormal operation parameter dynamic performance model into an abnormal dynamic performance set; The seventh module is used to monitor the operating parameters of the site production equipment in real time when issuing status warnings to the site production equipment, analyze the operating parameters using abnormal dynamic performance sets, and issue status warnings to the site production equipment based on the analysis results.

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