Intelligent response lubricating system based on molybdenum-bismuth self-repairing molecules and control method thereof

Abstract

The invention discloses an intelligent response lubricating system based on molybdenum-bismuth self-repairing molecules and a control method of the intelligent response lubricating system, and belongs to the technical field of intelligent control of lubricating systems.The intelligent response lubricating system comprises an acquisition module, a processing module and a control module, and the processing module is used for acquiring topological information, constructing a lubrication analysis link based on the online oil monitoring data and the topological information, and acquiring shape data and size data of the current machined part and a link information template. According to the method, feature optimization is performed on the lubrication analysis link by fusing the shape data of the machined part, high customization and accuracy of lubrication state analysis are realized, and compared with an analysis method adopting a general model, the method has the advantages that the optimization of the lubrication state can be realized according to geometric features such as a special-shaped surface of the specific machined part; abnormality detection and risk assessment are more suitable for actual working conditions, so that the accuracy of fault diagnosis is remarkably improved, and misjudgment or missed judgment caused by model mismatching is avoided.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of intelligent control of lubricating systems, and particularly relates to an intelligent response lubricating system based on molybdenum-bismuth self-repairing molecules and a control method thereof. BACKGROUND

[0002] Modern high-end equipment needs to run reliably for a long time under complex and severe working conditions such as variable load, variable speed and wide temperature range, and lubrication is a key technical means to protect equipment performance, slow down wear and prolong service life. With the development of equipment towards intelligence and long service life, the traditional static lubrication strategy has been difficult to meet the demand, therefore, the development of advanced lubrication technology capable of dynamic sensing and intelligent decision-making has become an important research direction in this field.

[0003] In the prior art, in order to realize dynamic regulation and control of lubrication, multiple sensors are usually deployed in the lubricating system to monitor the temperature, viscosity, particulate matter and other parameters of the oil online. Some systems trigger alarms or simple control actions by setting fixed thresholds. In terms of data acquisition, some solutions tend to perform full-coverage data acquisition on equipment in order to obtain comprehensive operation information. In addition, in terms of lubricant technology, intelligent lubricating oil containing self-repairing active molecules has also appeared, which can release active substances to repair the worn surface under the triggering of certain physical or chemical conditions.

[0004] The prior art solutions still have several deficiencies. The full-coverage data acquisition method results in high data redundancy and heavy processing burden, and the response speed of the system is limited, which is difficult to meet the demand of real-time control. The judgment method based on fixed thresholds has poor adaptability to complex and variable working conditions, and lacks consideration of the correlation of the overall structure of the equipment, resulting in low accuracy of the analysis results. The existing technology often ignores the decisive influence of the specific geometric shape of the workpiece on the wear distribution, so that the control strategy lacks pertinence. Even if intelligent lubricating oil is used, the release of active molecules is often passive and non-targeted, and it is difficult to achieve timely and accurate repair of key wear parts. SUMMARY

[0005] The purpose of the present application is to solve the problem of inaccurate evaluation of lubrication state, and an intelligent response lubricating system based on molybdenum-bismuth self-repairing molecules and a control method thereof are proposed.

[0006] In order to achieve the above-mentioned purpose, the present application adopts the following technical solutions: The application discloses an intelligent response lubricating system based on molybdenum-bismuth self-repairing molecules, which comprises a collection module, a processing module and a control module, the collection module is used for acquiring online oil monitoring data, the processing module is used for acquiring topological information, constructing a lubricating analysis link based on the online oil monitoring data and the topological information, acquiring shape data and size data of a current workpiece and a link information template, optimizing features of the lubricating analysis link to generate an optimized lubricating analysis link, and optimizing the lubricating analysis link to analyze the online oil monitoring data to generate a risk grade evaluation result; The control module controls a release unit to dynamically release molybdenum-bismuth active molecules according to the risk grade evaluation result.

[0007] The application discloses an intelligent response lubricating system based on molybdenum-bismuth self-repairing molecules, which comprises a collection module, a processing module and a control module, the collection module is used for acquiring online oil monitoring data, the processing module is used for acquiring topological information, constructing a lubricating analysis link based on the online oil monitoring data and the topological information, acquiring shape data and size data of a current workpiece and a link information template, optimizing features of the lubricating analysis link to generate an optimized lubricating analysis link, and optimizing the lubricating analysis link to analyze the online oil monitoring data to generate a risk grade evaluation result; S1: acquiring online oil monitoring data collected by a plurality of collection modules; S2: acquiring topological information describing connection relationships of components of equipment, and constructing a lubricating analysis link based on the online oil monitoring data and the topological information; S3: acquiring shape data and size data of a current workpiece; S4: acquiring database content in which a link information template is stored; S5: matching the shape data with the link information template, optimizing features of the lubricating analysis link in combination with the size data, and generating an optimized lubricating analysis link; S6: generating a risk grade evaluation result based on the optimized lubricating analysis link and the online oil monitoring data; S7: controlling a release unit to dynamically release molybdenum-bismuth active molecules according to the risk grade evaluation result.

[0008] As a further description of the above technical solutions: Three-dimensional model data of the current workpiece are acquired, and then a special-shaped surface area is recognized, special-shaped surface identification information is generated, and collection parameters of the plurality of collection modules are adjusted to focus on collection, so that optimized collection data sets are generated as the online oil monitoring data.

[0009] As a further description of the above technical solutions: Features of the lubricating analysis link are optimized, similarity between the shape data and the link information template is calculated, a shape matching degree score is generated, parameters in the lubricating analysis link are adjusted according to the size data, a parameter optimized link is generated, and the shape matching degree score and the parameter optimized link are fused to calculate a link priority order, and the link priority order constitutes the optimized lubricating analysis link.

[0010] As a further description of the above technical solutions: The online oil monitoring data is analyzed, key monitoring point data is extracted from the online oil monitoring data according to the priority in the optimized lubrication analysis link, a key data set is generated, a wear index value is calculated after trend analysis on the key data set, a risk level division model is obtained, the wear index value is compared with the risk level division model, and a risk level evaluation result is determined.

[0011] As a further description of the above technical solution: The risk level evaluation result is analyzed by the control release unit, a release control instruction containing a release dose is generated, spatial distribution information is extracted from the optimized lubrication analysis link, a high-risk friction surface area is located, the release control instruction is combined with the high-risk friction surface area, and the jetting parameters of the release unit are adjusted to realize targeted release.

[0012] As a further description of the above technical solution: The profiled surface area is identified, surface feature points are extracted from three-dimensional model data, a curvature threshold for defining the bending degree of the surface is obtained, profiled surface boundary information is generated after the surface feature points are screened based on the curvature threshold, and the profiled surface boundary information is used to generate profiled surface identification information.

[0013] As a further description of the above technical solution: The lubrication analysis link is constructed, abnormal data points are extracted from the online oil monitoring data, an abnormal feature vector is generated, a device structure diagram containing device component nodes and connection relationships is obtained, the abnormal feature vector is mapped to the corresponding node in the device structure diagram, and traversal is performed along the connection relationship to construct a preliminary lubrication analysis link as the lubrication analysis link.

[0014] As a further description of the above technical solution: The preliminary lubrication analysis link is constructed, load distribution data describing the load distribution of the device under different working conditions is obtained, the correlation strength between nodes in the device structure diagram is calculated based on the load distribution data, and a directed link is constructed according to the correlation strength to generate the preliminary lubrication analysis link.

[0015] As a further description of the above technical solution: The link priority order is calculated, the link information template is sorted according to the shape matching degree score to generate a template priority list, an engineering scaling model for modifying model parameters is obtained, and the link is scaled and adjusted according to the size data and the engineering scaling model to generate an adaptive link sequence as the optimized lubrication analysis link.

[0016] As described above, due to the adoption of the above technical solution, the beneficial effects of the present application are: 1. In this invention, the shape data of the processed parts are integrated to optimize the lubrication analysis link, which realizes a high degree of customization and accuracy in the lubrication state analysis. Compared with the analysis method using a general model, this invention can dynamically adjust the focus and path of the analysis according to the geometric features such as the irregular surface of the specific processed parts, so that the anomaly detection and risk assessment are more in line with the actual working conditions, thereby significantly improving the accuracy of fault diagnosis and avoiding misjudgment or omission due to model mismatch.

[0017] 2. In this invention, by focusing on key areas for data collection and using an optimized lubrication analysis link for calculation, the data processing burden and analysis delay of the system are reduced, enabling the system to react quickly to instantaneous changes in equipment status. This ensures that the release of self-healing molecules can closely follow the occurrence of wear events, thereby improving the real-time performance and effectiveness of the entire lubrication control system.

[0018] 3. This invention organically combines multiple technical aspects such as data acquisition, topology analysis, shape matching, and dynamic control to form a synergistic and efficient intelligent closed-loop system. The various technical features support and enhance each other. Shape matching improves the effect of link optimization, and the optimized link guides the focus of data acquisition and the target of molecule release. Deep technical integration achieves overall performance improvement, making the system's intelligence level and control effect surpass the sum of the individual applications. Detailed Implementation

[0019] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0020] This invention provides a technical solution: an intelligent responsive lubrication system based on molybdenum-bismuth self-healing molecules, comprising a data acquisition module, a processing module, and a control module. The data acquisition module acquires online oil monitoring data; the processing module acquires topology information and constructs a lubrication analysis link based on the online oil monitoring data and topology information; acquires the shape and size data of the current workpiece and a link information template; optimizes the lubrication analysis link to generate an optimized lubrication analysis link; and further optimizes the lubrication analysis link by analyzing online oil monitoring data to generate a risk level assessment result. Based on the risk level assessment results, the control module controls the release unit to dynamically release molybdenum-bismuth active molecules.

[0021] A control method of an intelligent response lubrication system based on a molybdenum-bismuth self-repairing molecule, characterized in that it comprises the following steps: S1: obtaining online oil monitoring data collected by a plurality of collection modules; Obtain the three-dimensional model data of the current workpiece, identify the irregular surface area, generate irregular surface identification information, and adjust the collection parameters of the plurality of collection modules to focus on collection, generate an optimized collection data set as online oil monitoring data; Identify the irregular surface area from the three-dimensional model data to extract the curved surface feature points, obtain the curvature threshold for defining the bending degree of the surface, generate the irregular surface boundary information based on the curvature threshold after filtering the curved surface feature points, and the irregular surface boundary information is used to generate the irregular surface identification information; S2: Obtain the topological information describing the connection relationship of each component of the device, and based on the online oil monitoring data and the topological information, construct a lubrication analysis link; Optimize the features of the lubrication analysis link, calculate the similarity between the shape data and the link information template, generate a shape matching score, adjust the parameter weight in the lubrication analysis link according to the size data, generate a parameter optimized link, and fuse the shape matching score and the parameter optimized link to calculate the link priority order. The link priority order constitutes an optimized lubrication analysis link; S3: Obtain the shape data and size data of the current workpiece; Analyze the online oil monitoring data, extract key monitoring point data from the online oil monitoring data according to the priority in the optimized lubrication analysis link, and generate a key data set. After trend analysis of the key data set, the wear index value is calculated, the risk level division model is obtained, and the wear index value is compared with the risk level division model to determine the risk level evaluation result; S4: Obtain the database content storing the link information template; The construction of the lubrication analysis link extracts abnormal data points from the online oil monitoring data, generates an abnormal feature vector, obtains a device structure diagram containing nodes and connection relationships of each component of the device, maps the abnormal feature vector to the corresponding node in the device structure diagram, and traverses along the connection relationship to construct a preliminary lubrication analysis link as the lubrication analysis link; The construction of the preliminary lubrication analysis link obtains load distribution data describing the load distribution of the device under different working conditions, calculates the correlation strength between nodes in the device structure diagram based on the load distribution data, and constructs a directed link according to the correlation strength to generate a preliminary lubrication analysis link; S5: Based on the shape data and the link information template, the lubrication analysis link is optimized in combination with the size data to generate an optimized lubrication analysis link; The computing link priority order generates a template priority list by sorting the link information templates according to the shape matching degree score, obtains an engineering scaling model for correcting the model parameters, and scales and adjusts the link according to the size data and the engineering scaling model to generate an adaptive link sequence as an optimized lubrication analysis link. S6: generating a risk level evaluation result based on the optimized lubrication analysis link and the online oil monitoring data; S7: controlling the release unit to dynamically release the molybdenum-bismuth active molecules according to the risk level evaluation result; The release control unit analyzes the risk level evaluation result to generate a release control instruction containing a release dose, extracts spatial distribution information from the optimized lubrication analysis link, locates a high-risk friction surface area, combines the release control instruction with the high-risk friction surface area, and adjusts the spraying parameters of the release unit to achieve targeted release.

[0022] The above is only a preferred specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can make equivalent replacements or changes within the technical range disclosed by the present application according to the technical solution and inventive concept of the present application, which should be covered within the protection scope of the present application.

Claims

1. An intelligent responsive lubrication system based on molybdenum-bismuth self-healing molecules, comprising a data acquisition module, a processing module, and a control module, characterized in that, The acquisition module is used to acquire online oil monitoring data, and the processing module is used to acquire topology information and construct a lubrication analysis link based on the online oil monitoring data and topology information. It also acquires the shape and size data of the current workpiece and the link information template, and performs feature optimization on the lubrication analysis link to generate an optimized lubrication analysis link. Furthermore, it is used to optimize the lubrication analysis link to analyze online oil monitoring data in order to generate a risk level assessment result. Based on the risk level assessment results, the control module controls the release unit to dynamically release molybdenum-bismuth active molecules.

2. The control method for an intelligent responsive lubrication system based on molybdenum-bismuth self-healing molecules according to claim 1, characterized in that, Includes the following steps: S1: Acquire online oil monitoring data collected by multiple acquisition modules; S2: Obtain topology information describing the connection relationships of various components of the equipment, and construct a lubrication analysis link based on the online oil monitoring data and the topology information; S3: Obtain the shape and dimension data of the currently processed part; S4: Retrieve the database contents containing link information templates; S5: Match shape data with link information templates, combine size data to optimize the lubrication analysis link, and generate an optimized lubrication analysis link; S6: Based on the optimized lubrication analysis link and online oil monitoring data, generate risk level assessment results; S7: Based on the risk level assessment results, control the release unit to dynamically release molybdenum-bismuth active molecules.

3. The intelligent responsive lubrication system and its control method based on molybdenum-bismuth self-healing molecules according to claim 2, characterized in that, The system acquires the 3D model data of the current workpiece, identifies irregular surface areas, generates irregular surface identification information, adjusts the acquisition parameters of multiple acquisition modules to focus acquisition, and generates an optimized acquisition dataset as online oil monitoring data.

4. The control method for an intelligent responsive lubrication system based on molybdenum-bismuth self-healing molecules according to claim 2, characterized in that, The lubrication analysis link is feature optimized by calculating the similarity between shape data and link information template, generating a shape matching score, adjusting the parameter weights in the lubrication analysis link according to the size data, generating a parameter-optimized link, and calculating the link priority order after fusing the shape matching score and the parameter-optimized link. The link priority order constitutes the optimized lubrication analysis link.

5. The control method for an intelligent responsive lubrication system based on molybdenum-bismuth self-healing molecules according to claim 4, characterized in that, Analyze online oil monitoring data, extract key monitoring point data from the online oil monitoring data and generate key datasets based on the priority in the optimized lubrication analysis chain, perform trend analysis on the key datasets to calculate wear index values, obtain a risk level classification model, and compare the wear index values ​​with the risk level classification model to determine the risk level assessment results.

6. The control method for an intelligent responsive lubrication system based on molybdenum-bismuth self-healing molecules according to claim 2, characterized in that, The control release unit analyzes the risk level assessment results, generates a release control command containing the release dosage, extracts spatial distribution information from the optimized lubrication analysis link, locates high-risk friction surface areas, combines the release control command with the high-risk friction surface areas, and adjusts the injection parameters of the release unit to achieve targeted release.

7. The control method for an intelligent responsive lubrication system based on molybdenum-bismuth self-healing molecules according to claim 2, characterized in that, The irregular surface region is identified by extracting surface feature points from the 3D model data, obtaining a curvature threshold to define the degree of surface curvature, and generating irregular surface boundary information after filtering surface feature points based on the curvature threshold. The irregular surface boundary information is used to generate irregular surface identification information.

8. The control method for an intelligent responsive lubrication system based on molybdenum-bismuth self-healing molecules according to claim 2, characterized in that, The process of constructing a lubrication analysis link involves extracting abnormal data points from the online oil monitoring data, generating abnormal feature vectors, obtaining a device structure diagram containing the nodes and connections of each component of the equipment, mapping the abnormal feature vectors to the corresponding nodes in the device structure diagram, and traversing along the connections to construct a preliminary lubrication analysis link as the lubrication analysis link.

9. The control method for an intelligent responsive lubrication system based on molybdenum-bismuth self-healing molecules according to claim 2, characterized in that, The preliminary lubrication analysis link is constructed by acquiring load distribution data that describes the load distribution of the equipment under different operating conditions, calculating the correlation strength between nodes in the equipment structure diagram based on the load distribution data, and constructing a directed link based on the correlation strength to generate the preliminary lubrication analysis link.

10. The control method for an intelligent responsive lubrication system based on molybdenum-bismuth self-healing molecules according to claim 2, characterized in that, The calculation of link priority order involves sorting the link information templates according to the shape matching score to generate a template priority list, obtaining an engineering scaling model for correcting model parameters, and scaling and adjusting the links according to the size data and the engineering scaling model to generate an adaptive link sequence as the optimized lubrication analysis link.