Distributed intelligent lubrication on-line monitoring control system

Abstract

The invention relates to the technical field of industrial equipment lubrication, and discloses a distributed intelligent lubrication on-line monitoring control system, a hardware configuration part comprises a monitoring master station and a plurality of monitoring substations, the monitoring master station adopts a high-performance server or an industrial personal computer as a hardware platform, and is equipped with a high-performance CPU, a large-capacity memory and a high-speed hard disk; the monitoring substation is provided with a wireless communication module and is used for performing wireless communication with the monitoring substation and the looped network, and the monitoring substation is used for acquiring flow, liquid level, viscosity and granularity data of the lubricating liquid in real time through a sensor and transmitting the acquired data to the monitoring master station through the wireless communication module. Key parameters (such as flow, liquid level, viscosity and granularity) of the lubricating liquid are collected in real time through the sensor, calculation and analysis of the parameters of the lubricating liquid are achieved through the edge calculation engine, manual intervention or off-line sampling is not needed, and the real-time performance and efficiency of the monitoring process are greatly improved.

Description

Technical Field

[0001] The invention relates to the technical field of industrial equipment lubrication, and in particular to a distributed intelligent lubrication online monitoring and control system. Background Art

[0002] Lubricating fluid plays a vital role in mechanical equipment. Its main functions are to reduce friction, reduce wear, dissipate heat and prevent corrosion. It is widely used in various industrial equipment, such as bearings, gearboxes, hydraulic systems, etc. By forming a lubricating film between moving parts, lubricating fluid can significantly improve the operating efficiency and service life of the equipment. Therefore, as an important lubricating and cooling medium for mechanical equipment, the stability and health of its performance are directly related to the operating efficiency and life of the equipment. In order to ensure that the lubricating fluid always maintains good performance during the operation of the equipment, an online monitoring and control system is introduced. The system monitors various parameters of the lubricating fluid in real time, detects abnormal conditions in time, and predicts potential faults through data analysis. The online monitoring and control system usually includes sensors, data processing units and communication modules, which can realize automatic data acquisition, transmission and analysis.

[0003] Although the existing online lubrication monitoring system has improved the maintenance efficiency of equipment to a certain extent, it still has some shortcomings. For example, traditional systems mostly adopt a centralized architecture and rely on wired communication for data transmission, resulting in high wiring costs, difficult maintenance, and susceptibility to environmental factors. At the same time, many systems require manual intervention or offline sampling to detect lubricant parameters, which not only reduces the real-time and efficiency of monitoring, but also increases the risk of human errors. At the same time, it fails to fully monitor the core parameters of the lubricant such as flow and liquid level, limiting the full analysis and prediction of the equipment operation status. Summary of the invention

[0004] In view of the deficiencies of the prior art, the present invention provides a distributed intelligent lubrication online monitoring and control system, which solves the problems mentioned in the above background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a distributed intelligent lubrication online monitoring and control system, the hardware configuration part includes a monitoring main station and multiple monitoring substations, the monitoring main station uses a high-performance server or industrial computer as a hardware platform, is equipped with a high-performance CPU, a large-capacity memory and a high-speed hard disk, and is configured with a wireless communication module for wireless communication with the monitoring substations and the ring network; The monitoring substation collects the flow, level, viscosity and particle size data of the lubricating fluid in real time through sensors, and transmits the collected data to the monitoring main station through a wireless communication module; The monitoring main station processes, analyzes and stores the collected lubricating fluid data in real time to provide support for the operating status of the lubrication system.

[0006] Preferably, the software system part includes a data acquisition interface, an edge computing engine, a data display interface and a data upload module; The data acquisition interface is responsible for receiving the lubricating fluid parameter data transmitted by each monitoring substation; The edge computing engine is used to calculate and analyze lubricating fluid parameters, including lubricating fluid flow calculation and lubricating fluid parameter anomaly detection: The calculation formula of lubricating fluid flow is: ,in, is the volume flow rate, is the cross-sectional area of ​​the lubricating fluid channel, is the flow rate, Abnormal lubricant parameter detection: Use algorithms to analyze data in real time to detect whether the viscosity and particle size parameters of the lubricant are abnormal. The formula is: ,in, is the parameter value currently measured (viscosity or particle size), is the historical average value of the parameter, It is the standard deviation of the historical data of the parameter. When (EI) exceeds the set threshold, the parameter is judged to be abnormal; The data display interface is used to display lubricating fluid parameter data and test results in real time; The data upload module is responsible for uploading the calculation and analysis results to the ring network for use by other systems or managers.

[0007] Preferably, the edge computing engine cooperates with the monitoring main station to automatically perform the following control operations according to whether the detected lubricating fluid parameters are abnormal: When the viscosity or particle size parameters of the lubricating fluid are detected to be abnormal, an alarm signal is sent to the monitoring main station; Dynamically adjust the lubricant supply according to the type of abnormality, including automatically increasing or decreasing the lubricant flow rate; When a serious anomaly is detected (such as granularity exceeding the maximum safety range), the emergency shutdown protection device is triggered; Abnormal conditions are stored in the master station database for further analysis and optimization of system operating parameters.

[0008] Preferably, the monitoring main station communicates with the monitoring substation via wireless signals, and adopts an adaptive routing algorithm to ensure the stability and reliability of communication in a complex environment. The formula is: ,in, is the total score for a particular path, is the total number of links in the path, It is Quality indicators of a link, based on signal strength, error rate, latency, etc. is the weighting factor applied to the quality of each link.

[0009] Preferably, the various monitoring substations communicate with each other via wireless signals, support multiple communication protocols and encryption algorithms, and ensure the security and integrity of data transmission.

[0010] Preferably, the monitoring substation collects oil data in real time through sensors, and sends the data to the monitoring main station through a wireless communication module. The data transmission adopts a data encryption and verification mechanism, and the monitoring substation has a data storage function.

[0011] Preferably, the system has automatic diagnosis and fault warning functions, can detect and report system faults in a timely manner, and at the same time, provides a remote maintenance and upgrade interface to facilitate management personnel to maintain and upgrade the system.

[0012] Preferably, the system adopts multi-level security protection measures, including data encryption, access control, and firewalls to ensure the security of data transmission and storage. At the same time, redundant backup of key system components is performed to improve the reliability and fault tolerance of the system.

[0013] The present invention provides a distributed intelligent lubrication online monitoring and control system. It has the following beneficial effects: 1. The present invention adopts a distributed architecture. The system consists of a monitoring main station and multiple monitoring substations. It is suitable for equipment groups of various sizes and layouts. The substations can communicate with each other to improve the flexibility and reliability of data transmission. The wireless communication module of the system supports multiple communication protocols and encryption algorithms to ensure the security and integrity of data transmission, while reducing wiring costs and maintenance difficulties.

[0014] 2. The present invention collects key parameters of the lubricating fluid (such as flow rate, liquid level, viscosity and particle size) in real time through sensors, and uses the edge computing engine to calculate and analyze the lubricating fluid parameters without manual intervention or offline sampling, which greatly improves the real-time and efficiency of the monitoring process. The highly automated system architecture covers the entire process from data collection, anomaly detection to result output, significantly reducing errors caused by human operations.

[0015] 3. The present invention can not only detect abnormalities in lubricating fluid data in real time, but also predict potential equipment failures and achieve predictive maintenance by monitoring the main station based on comprehensive analysis of historical data and real-time data. When it is detected that the lubricating fluid parameters exceed the set threshold, the system will automatically trigger corresponding control measures, including adjusting the lubricating fluid supply or issuing an alarm, or even triggering equipment protection mechanisms (such as emergency shutdown), thereby avoiding unplanned shutdown of equipment due to lubrication failure and reducing operation and maintenance costs and production risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a partial flow chart of the system software of the present invention; Figure 2 It is a schematic diagram of the system hardware part of the present invention; Figure 3 It is a schematic diagram of the control method of the present invention. DETAILED DESCRIPTION

[0017] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Embodiment 1: Please see attached Figure 1 -Attached Figure 3 , the embodiment of the present invention provides a distributed intelligent lubrication online monitoring and control system, the hardware configuration part includes a monitoring main station and multiple monitoring substations, characterized in that the monitoring main station uses a high-performance server or industrial computer as a hardware platform, is equipped with a high-performance CPU, a large-capacity memory and a high-speed hard disk, and is configured with a wireless communication module for wireless communication with the monitoring substation and the ring network; The monitoring substation collects the flow, level, viscosity and particle size data of the lubricating fluid in real time through sensors, and transmits the collected data to the monitoring main station through the wireless communication module; The monitoring master station processes, analyzes and stores the collected lubricating fluid data in real time to provide support for the operating status of the lubrication system.

[0019] Through advanced communication and edge computing technologies, the security and continuity of data transmission are guaranteed, while supporting rapid response in complex industrial environments. The monitoring master station processes, analyzes and stores the collected lubricating fluid data in real time, which can dynamically reflect the operating status of the lubrication system and provide accurate data support and decision-making basis for equipment operation and maintenance, thereby significantly improving the operating efficiency and reliability of the system and reducing equipment downtime and maintenance costs caused by lubrication failures.

[0020] The software system part includes data acquisition interface, edge computing engine, data display interface and data upload module; The data acquisition interface is responsible for receiving the lubricating fluid parameter data transmitted by each monitoring substation; The edge computing engine is used to calculate and analyze lubricant parameters, including lubricant flow calculation and lubricant parameter anomaly detection: The calculation formula of lubricating fluid flow is: ,in, is the volume flow rate, is the cross-sectional area of ​​the lubricating fluid channel, is the flow rate, Abnormal lubricant parameter detection: Use algorithms to analyze data in real time to detect whether the viscosity and particle size parameters of the lubricant are abnormal. The formula is: ,in, is the parameter value currently measured (viscosity or particle size), is the historical average value of the parameter, It is the standard deviation of the historical data of the parameter. When (EI) exceeds the set threshold, the parameter is judged to be abnormal; The data display interface is used to display lubricating fluid parameter data and test results in real time; The data upload module is responsible for uploading the calculation and analysis results to the ring network for use by other systems or managers.

[0021] The edge computing engine collaborates with the monitoring master station to automatically perform the following control operations based on whether the lubricating fluid parameters detected are abnormal: When the viscosity or particle size parameters of the lubricating fluid are detected to be abnormal, an alarm signal is sent to the monitoring main station; Dynamically adjust the lubricant supply according to the type of abnormality, including automatically increasing or decreasing the lubricant flow rate; When a serious anomaly is detected (such as granularity exceeding the maximum safety range), the emergency shutdown protection device is triggered; Abnormal conditions are stored in the master station database for further analysis and optimization of system operating parameters.

[0022] The software system consists of a data acquisition interface, an edge computing engine, a data display interface, and a data upload module. The modules work together to form a complete functional chain of data acquisition, analysis, display, and upload. The data acquisition interface efficiently receives the lubricant parameter data transmitted by the monitoring substation, including key indicators such as flow, level, viscosity, and particle size, ensuring the integrity and real-time nature of data transmission, and providing a reliable data basis for subsequent analysis. The edge computing engine uses efficient computing power to analyze lubricant parameters in real time, accurately calculates the volume flow of the lubricant through the flow calculation formula, and performs anomaly detection based on historical data and standard deviation calculations to quickly determine whether the lubricant viscosity or particle size parameters exceed the safety range. The data display interface provides intuitive equipment status visualization support for operation and maintenance personnel, while the data upload module synchronizes the analysis and detection results to the ring network, supports remote access and management, further improves the system's collaboration and information sharing capabilities, and when the monitoring master station detects an abnormality, it can automatically trigger an alarm, dynamically adjust the lubricant supply, and even perform emergency shutdown operations in severe cases, thereby protecting the equipment from damage caused by lubrication abnormalities to the greatest extent, improving monitoring efficiency and fault response speed, reducing the risk of manual operation and errors, and providing important guarantees for the long-term and stable operation of the equipment.

[0023] The monitoring main station communicates with the monitoring substations through wireless signals and adopts an adaptive routing algorithm to ensure the stability and reliability of communication in complex environments. The formula is: ,in, is the total score for a particular path, is the total number of links in the path, It is Quality indicators of a link, based on signal strength, error rate, latency, etc. It is a weight factor applied to the quality of each link. The monitoring master station gives priority to communicating with its nearest monitoring substation. When the communication quality is poor, it can automatically switch to other monitoring substations or communicate directly with the monitoring master station.

[0024] The monitoring master station communicates with the monitoring substations through wireless signals, and uses an adaptive routing algorithm to optimize the communication path. The algorithm evaluates the quality of each link based on indicators such as signal strength, error rate, and delay, and calculates the total score of a specific path to determine the optimal communication path. This adaptive communication strategy can ensure the stability and reliability of communication in complex environments. When the communication quality between the monitoring master station and a monitoring substation is poor, the system can automatically switch to other monitoring substations or communicate directly with the monitoring master station. This flexible communication mechanism ensures the continuity and real-time nature of data transmission and avoids monitoring blind spots caused by communication problems. In summary, the monitoring master station uses an adaptive routing algorithm to communicate wirelessly with the monitoring substations, ensuring the stability and reliability of communication in complex industrial environments. This intelligent communication mechanism enables the system to automatically select the optimal communication path. When the communication quality is poor, it can flexibly switch to other monitoring substations or communicate directly with the monitoring master station, thereby ensuring real-time data transmission and monitoring continuity, which not only improves monitoring efficiency, but also reduces communication costs, providing strong support for the stable operation of industrial equipment.

[0025] Each monitoring substation communicates with each other through wireless signals, supports multiple communication protocols and encryption algorithms, and ensures the security and integrity of data transmission. When necessary, the monitoring substations can forward data to each other to improve the flexibility and reliability of data transmission.

[0026] Each monitoring substation communicates with each other through wireless signals. This design supports multiple communication protocols and encryption algorithms to ensure the security and integrity of data transmission. This interconnectivity between monitoring substations enables them to forward data to each other as needed, thereby improving the flexibility and reliability of data transmission. In practical applications, if the direct communication between a monitoring substation and the monitoring main station is blocked, it can use other monitoring substations as relays to safely transmit the data to the destination. This multi-hop transmission mechanism greatly improves the adaptability and robustness of the system in complex industrial environments. In summary, this design not only enhances the communication capability of the system in complex industrial environments, but also ensures the real-time and accuracy of monitoring data, providing strong support for the stable operation of industrial equipment.

[0027] The monitoring substation collects lubricating fluid data in real time through sensors and sends the data to the monitoring main station through wireless communication modules. Data transmission uses data encryption and verification mechanisms, and the monitoring substation has data storage functions. This improves the system's adaptability and safety performance in complex industrial environments, and effectively improves the real-time data transmission efficiency and system stability, providing reliable data support for lubricating fluid status monitoring and fault analysis. The system has automatic diagnosis and fault warning functions, which can detect and report system faults in time. At the same time, it provides remote maintenance and upgrade interfaces to facilitate management personnel to maintain and upgrade the system, and adopts multi-level security protection measures, including data encryption, access control, and firewalls to ensure the security of data transmission and storage. At the same time, redundant backups are made for key components of the system to improve the reliability and fault tolerance of the system. Potential system faults can be discovered and reported in time through real-time analysis of monitoring data. It reduces the reliance on manual inspections, improves the speed and efficiency of fault response, and provides remote maintenance and upgrade interfaces, so that management personnel can easily maintain and upgrade the system without having to go to the site in person. This not only reduces maintenance costs, but also improves the maintainability of the system. To ensure the security of data transmission and storage, the system adopts multi-level security protection measures, including data encryption, access control, and firewalls. Data encryption ensures the security of data during transmission and prevents data from being accessed or tampered with by unauthorized users. Access control limits access to system resources to ensure that only authorized users can access sensitive data. Firewalls prevent external attacks and protect the system from network threats. In addition, the system has redundant backups for key components to improve the reliability and fault tolerance of the system. Even when some components fail, the system can maintain normal operation to ensure the continuity of monitoring tasks. Automatic diagnosis and fault warning functions are used to report faults in a timely manner; remote maintenance and upgrade interfaces are provided to facilitate management personnel to maintain and upgrade the system; multi-level security protection measures are adopted to ensure the security of data transmission and storage; and redundant backup of key components is performed to improve the reliability and fault tolerance of the system. These features work together to make the system more intelligent, safe and reliable.

[0028] Embodiment 2: An intelligent lubrication online monitoring and control method comprises the following steps: Data collection: The key parameter data of lubricants are collected in real time through various sensors in the perception layer, including but not limited to viscosity, acid value, moisture, particle count, oxidation degree and wear metal content.

[0029] Data preprocessing: Clean, process outliers and normalize the collected data to facilitate subsequent analysis.

[0030] Calculate scores: Assign scores to each key parameter based on preset scoring criteria, where a higher score indicates better performance for that parameter.

[0031] Draw a radar chart: The scores of key parameters are represented on the radar chart. Each vertex represents a parameter, and the distance between the vertex and the center corresponds to the score of the parameter.

[0032] Analyze the radar chart: Observe the shape and size of the radar chart to evaluate the overall performance and health of the lubricant; irregular patterns or abnormal sizes indicate possible problems.

[0033] Develop maintenance strategies: Based on the analysis results of the radar chart, develop and implement maintenance strategies, such as changing gear oil or adjusting lubrication system parameters.

[0034] Continuous Monitoring: Key parameter data is regularly updated, radar charts are redrawn and analyzed to continuously monitor the condition of the gear oil.

[0035] Through the above steps, the method can realize real-time online monitoring of the lubricating fluid status, timely discover potential problems, and take corresponding maintenance measures to ensure the reliability and efficiency of equipment operation.

[0036] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A distributed intelligent lubrication online monitoring and control system, the hardware configuration part includes a monitoring main station and multiple monitoring substations, characterized in that: The monitoring master station uses a high-performance server or industrial computer as a hardware platform, equipped with a high-performance CPU, large-capacity memory and high-speed hard disk, and is configured with a wireless communication module for wireless communication with the monitoring substation and the ring network; The monitoring substation collects the flow, level, viscosity and particle size data of the lubricating fluid in real time through sensors, and transmits the collected data to the monitoring main station through a wireless communication module; The monitoring main station processes, analyzes and stores the collected lubricating fluid data in real time to provide support for the operating status of the lubrication system.

2. A distributed intelligent lubrication online monitoring and control system according to claim 1, characterized in that: The software system part includes data acquisition interface, edge computing engine, data display interface and data upload module; The data acquisition interface is responsible for receiving the lubricating fluid parameter data transmitted by each monitoring substation; The edge computing engine is used to calculate and analyze lubricating fluid parameters, including lubricating fluid flow calculation and lubricating fluid parameter anomaly detection: The calculation formula of lubricating fluid flow is: ,in, is the volume flow rate, is the cross-sectional area of ​​the lubricating fluid channel, is the flow rate, Abnormal lubricant parameter detection: Use algorithms to analyze data in real time to detect whether the viscosity and particle size parameters of the lubricant are abnormal. The formula is: ,in, is the parameter value currently being measured: viscosity or particle size, is the historical average value of the parameter, is the standard deviation of the historical data of the parameter. When the set threshold is exceeded, the parameter is judged to be abnormal; The data display interface is used to display lubricating fluid parameter data and test results in real time; The data upload module is responsible for uploading the calculation and analysis results to the ring network for use by other systems or managers.

3. A distributed intelligent lubrication online monitoring and control system according to claim 1, characterized in that: The edge computing engine cooperates with the monitoring main station to automatically perform the following control operations according to whether the detected lubricating fluid parameters are abnormal: When the viscosity or particle size parameters of the lubricating fluid are detected to be abnormal, an alarm signal is sent to the monitoring main station; Dynamically adjust the lubricant supply according to the type of abnormality, including automatically increasing or decreasing the lubricant flow rate; When a serious anomaly is detected: such as the granularity exceeds the maximum safety range, the emergency shutdown protection device is triggered; Abnormal conditions are stored in the master station database for analysis and optimization of system operating parameters.

4. A distributed intelligent lubrication online monitoring and control system according to claim 1, characterized in that: The monitoring main station communicates with the monitoring substation via wireless signals and adopts an adaptive routing algorithm to ensure the stability and reliability of communication in complex environments. The formula is: ,in, is the total score for a particular path, is the total number of links in the path, It is link quality indicators based on signal strength, error rate, latency, is the weighting factor applied to the quality of each link.

5. A distributed intelligent lubrication online monitoring and control system according to claim 1, characterized in that: The various monitoring substations communicate with each other through wireless signals, support multiple communication protocols and encryption algorithms, and ensure the security and integrity of data transmission.

6. A distributed intelligent lubrication online monitoring and control system according to claim 1, characterized in that: The monitoring substation collects lubricating fluid data in real time through sensors, and sends the data to the monitoring main station through a wireless communication module. The data transmission adopts a data encryption and verification mechanism, and the monitoring substation has a data storage function.

7. A distributed intelligent lubrication online monitoring and control system according to claim 2, characterized in that: The system has automatic diagnosis and fault warning functions, can detect and report system faults in a timely manner, and at the same time, provides a remote maintenance and upgrade interface to facilitate management personnel to maintain and upgrade the system.

8. A distributed intelligent lubrication online monitoring and control system according to claim 2, characterized in that: The system adopts multi-level security protection measures, including data encryption, access control, and firewalls to ensure the security of data transmission and storage. At the same time, redundant backup of key system components is performed to improve the reliability and fault tolerance of the system.

Images