CN115407712A - Intelligent maintenance system for hydraulic station of steel mill and working process - Google Patents
Intelligent maintenance system for hydraulic station of steel mill and working process Download PDFInfo
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- CN115407712A CN115407712A CN202210930286.8A CN202210930286A CN115407712A CN 115407712 A CN115407712 A CN 115407712A CN 202210930286 A CN202210930286 A CN 202210930286A CN 115407712 A CN115407712 A CN 115407712A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/05—Programmable logic controllers, e.g. simulating logic interconnections of signals according to ladder diagrams or function charts
- G05B19/058—Safety, monitoring
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- G—PHYSICS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
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Abstract
The invention discloses an intelligent maintenance system and an intelligent maintenance work flow for a hydraulic station of a steel mill, and relates to a maintenance system and a work flow for the hydraulic station. The intelligent maintenance system for the steel mill hydraulic station intelligently realizes regular maintenance reminding and maintenance planning of equipment, can show the progress of maintenance on the equipment under maintenance, and intelligently updates information to a database after maintenance at each stage. The intelligent maintenance system can effectively improve the intelligent level of the maintenance scheme at the present stage, reduce the fault outage rate and the hidden trouble of improper maintenance, improve the economic benefit of the production line of the hydraulic station, and has important significance for the intelligent development of future maintenance and industrial control industries and the construction of unmanned operation and maintenance platforms in China.
Description
Technical Field
The invention relates to a hydraulic station maintenance system and a hydraulic station maintenance process, in particular to an intelligent maintenance system and an intelligent maintenance process for a hydraulic station of a steel mill.
Background
A large number of hydraulic systems exist in metallurgical steel plants, are important power sources and generally comprise a hydraulic pump set, an oil tank, a filter, a temperature control assembly and the like, and the quality of hydraulic oil is directly related to the reliability and the service life of steel plant equipment. The hydraulic oil is forbidden to be mixed with different grades of hydraulic oil for use, and the working temperature is in the temperature range required by the process. The oil mixing can cause the oil performance to be reduced, precipitates are generated, the oil aging and deterioration failure is accelerated due to the overhigh oil temperature, and therefore, the oil change is required periodically. At present, hydraulic faults of steel plants are mostly concentrated on the aspects of oil leakage, pump jumping, sudden oil temperature change, sudden liquid level change and the like. The main factors are that the oil pollution causes improper valve action, oil degradation, unstable pump output pressure, daily slow leakage and the like, and the oil leakage also causes greasy and dirty; in the surrounding environment of the hydraulic station, and is easy to cause fire, explosion and other dangers. Because hydraulic oil belongs to the consumptive material, and the price is higher, the ubiquitous oil mixing phenomenon of steel mill at present still adopts the point inspection to repair to hydraulic equipment's management mostly, adds how much oil, refuels when and all rely on the experience of maintenance workman, has very big potential safety hazard and non-normative. Meanwhile, historical data, particularly data reference and maintenance expert system guidance during fault are lacked, so that fault reasons are slow to investigate, the maintenance efficiency is low, and the construction period is long. At present, the maintenance is fault maintenance and regular maintenance, and no preventive maintenance is carried out. In other words, regular maintenance is physical examination, trouble-shooting maintenance is to find doctors after illness, and preventive maintenance is to get a preventive treatment. Regular maintenance of health examination is definitely important, but data when no fault occurs does not play a great role in fault type judgment and maintenance; the fault maintenance for finding doctors after getting ill is the fault problem, the fact of stopping the vehicle and production is caused, the maintenance is the sheep death and reinforcement, and the loss is reduced as the maintenance is faster. Preventive maintenance for preventive treatment is based on data fault prediction, early warning and prior prevention, potential risks are discovered early by data analysis, the probability of faults is avoided and reduced, and the method is the development direction of modern maintenance. Therefore, the intelligent maintenance system for the hydraulic station of the steel mill is designed, parameters such as the pollution degree, viscosity, oil level and oil temperature of hydraulic oil are monitored in real time on line, a state early warning model is arranged on a system platform to carry out trend prejudgment on faults, parameters such as the oil temperature are accurately analyzed according to an artificial intelligence algorithm, the faults can be prejudged on the operation state in advance, and the purpose of preventive maintenance is achieved.
Disclosure of Invention
The invention aims to provide an intelligent maintenance system for a hydraulic station of a steel mill and a working process. The decision system is characterized in that an intelligent decision platform is built by combining an intelligent algorithm, a big data technology and the like, a system fault model is formed by utilizing oil analysis data according to a machine learning linear regression algorithm, and the system fault is predicted by utilizing the model. The maintenance system is a database management system integrating user management, equipment management, maintenance work order management and operation log management, and realizes maintenance and maintenance recording, order dispatching, management and the like of the hydraulic station equipment.
The purpose of the invention is realized by the following technical scheme:
an intelligent maintenance system for a hydraulic station of a steel mill comprises a data acquisition monitoring system, a decision-making system and a maintenance system; the data acquisition monitoring system consists of a PLC control system, a sensor and a monitoring interface; the pollution degree, viscosity, oil level and oil temperature parameters of hydraulic oil in the system are collected by a sensor and transmitted to a PLC (programmable logic controller), so that real-time display and control on a monitoring interface of an upper computer are realized; the decision system is used for constructing an intelligent decision platform by combining an intelligent algorithm, a big data technology and the like, analyzing data acquired by the PLC, forming a system fault model, and judging the fault type by using a prediction system; the maintenance system is a database management system integrating user management, equipment management and work order management; the maintenance and maintenance records, the work order dispatching and the query management of maintenance personnel and hydraulic station equipment are realized.
The utility model provides a steel mill hydraulic pressure station wisdom maintenance system work flow, system work flow includes following step: the temperature, pressure, liquid level, flow and granularity sensors collect and upload parameters of the hydraulic oil such as temperature, pressure, oil level, flow, pollution degree and viscosity to the PLC, and the PLC system judges whether the parameters exceed the process allowable range; if the parameters exceed the standard, the upper computer monitors and immediately alarms, and simultaneously starts the maintenance system and issues a maintenance command; the system judges the fault type according to the standard exceeding parameter characteristics, and determines a maintenance scheme until the maintenance is finished; if the PLC judges that the data parameters do not exceed the process allowable range, a prediction system in the decision-making system works, judges whether the current data is in a dangerous state or not according to the prediction model, and judges whether the system breaks down or not; if the fault is judged according to the prediction system model, the upper computer immediately alarms, and simultaneously starts the maintenance system to realize emergency treatment and maintenance in the crisis state; if the prediction system model judges that no fault exists, the system is stable and far away from danger, and the system works normally.
According to the intelligent maintenance system and the working process for the steel mill hydraulic station, the upper computer monitoring interface of the intelligent maintenance system for the steel mill hydraulic station displays and records data of each sensor of the hydraulic station in real time, and inquires historical data and trends; the historical data provides training samples for the decision-making system, and the analysis and the evaluation of the overall condition of the hydraulic station are facilitated; the monitoring interface supports accessing a maintenance system and comprises a user login interface and an equipment management and maintenance interface; the fault information, maintenance times and progress of each device, maintenance personnel information and the like establish a ledger, so that the inquiry and access are facilitated; the host computer interface sets up the warning interface, can pop out the trouble suggestion when the trouble, and has the pilot lamp scintillation to in time discover unusually and participate in the maintenance for the maintenance personnel.
The intelligent maintenance system for the steel mill hydraulic station is provided with an artificial neural network model architecture, the hydraulic system collects data such as flow, pressure, temperature and the like through a sensor and transmits the data to a PLC, a decision system of an upper computer analyzes the data, and a set of parameter prediction system is established; the prediction system trains a model on the basis of a large amount of data by utilizing a neural network technology, so that the model has better generalization; the trained model is used for evaluating the fault probability of the hydraulic station; the method comprises the following steps of (1) collecting data by 16 hydraulic stations in total, such as pressure, temperature, flow, oil level, pollution degree, viscosity and the like, and using the data as an input layer; the output layer uses 5 different neurons to respectively represent different risk levels, the fault occurrence probability is defined as a risk, and the very high risk considers that the fault occurrence probability is very high; the risk is high, and the fault occurrence probability is high; the risk is medium, and the fault occurrence probability is medium; the risk is low, and the fault occurrence probability is low; the risk is very low, and the fault occurrence probability is very low; in the artificial neural network model, parameters such as pollution degree, viscosity, oil level, oil temperature, pressure, flow and the like are weighted to calculate the fault occurrence probability of the hydraulic station.
The invention has the advantages and effects that:
the intelligent maintenance system and the working process of the hydraulic station of the steel mill are designed and developed, oil product data are monitored in real time, early warning is carried out on dangerous states, trend prejudgment is carried out on faults in advance, and the purpose of preventive maintenance is achieved. The intelligent maintenance system for the steel mill hydraulic station intelligently realizes regular maintenance reminding and maintenance planning of equipment, can show the progress of maintenance on the equipment under maintenance, and intelligently updates information to a database after maintenance at each stage. The intelligent maintenance system can effectively improve the intelligent level of the maintenance scheme at the present stage, reduce the failure outage rate and the hidden trouble of improper maintenance, improve the economic benefit of the production line of the hydraulic station, and has important significance for the intelligent development of future maintenance and industrial control industries and the construction of unmanned operation and maintenance platforms in China.
Drawings
FIG. 1 is a schematic diagram of an intelligent maintenance system for a hydraulic station of a steel mill according to the present invention;
FIG. 2 is a flow chart of the system operation of the present invention;
FIG. 3 is an interface diagram of a monitoring system of the present invention;
FIG. 4 is a diagram of the neural network model architecture of the present invention.
Detailed Description
The present invention will be described in detail with reference to the embodiments shown in the drawings.
The intelligent maintenance system for the steel mill hydraulic station comprises a data acquisition monitoring system, a decision-making system and a maintenance system.
As shown in FIG. 1, the intelligent maintenance system for the hydraulic station of the steel mill of the present invention comprises: 1. a data acquisition monitoring system 2, a decision system 3 and a maintenance system. The data acquisition monitoring system consists of a PLC control system, a sensor and a monitoring interface. Parameters such as the pollution degree, viscosity, oil level and oil temperature of the hydraulic oil are collected by the sensors and transmitted to the PLC, and real-time display, control and the like of an upper computer monitoring interface are realized. The decision system is used for building an intelligent decision platform by combining an intelligent algorithm, a big data technology and the like, analyzing data collected by the PLC, forming a system fault model, and judging the fault type by using a prediction system. The maintenance system is a database management system integrating user management, equipment management and work order management. The maintenance and maintenance records, the work order dispatching, the query management and the like of maintenance personnel and hydraulic station equipment are realized.
Referring to fig. 2, the intelligent maintenance system of the steel mill hydraulic station has a working process. The method comprises the specific steps that the sensors for temperature, pressure, liquid level, flow, granularity and the like collect and upload parameters for temperature, pressure, oil level, flow, pollution degree, viscosity and the like of hydraulic oil to a PLC, and the PLC system judges whether the parameters exceed the process allowable range. If the parameters exceed the standard, the upper computer monitors and immediately alarms, and simultaneously starts the maintenance system to issue a maintenance command. And judging the fault type by the system according to the standard exceeding parameter characteristics, and determining a maintenance scheme until the maintenance is finished. And if the PLC judges that the data parameters do not exceed the process allowable range, a prediction system in the decision-making system works, judges whether the current data is in a dangerous state or not according to the prediction model, and judges whether the system has a fault or not. If the fault is judged according to the prediction system model, the upper computer immediately gives an alarm, and meanwhile, the maintenance system is started, so that emergency treatment and maintenance in a crisis state are achieved. If the prediction system model judges that no fault exists, the system is stable and far away from danger, and the system works normally.
Referring to fig. 3, the invention relates to an upper computer monitoring interface of an intelligent maintenance system of a hydraulic station of a steel mill. The interface displays and records data of each sensor of the hydraulic station in real time, and historical data and trends can be inquired. The historical data provides training samples for the decision-making system, and the analysis and the evaluation of the overall condition of the hydraulic station are facilitated. The monitoring interface supports access to the maintenance system and comprises a user login interface and an equipment management and maintenance interface. The machine account is established for the fault information, maintenance times and progress of each device, maintenance personnel information and the like, and query and access are facilitated. The host computer interface sets up the warning interface, can pop out the trouble suggestion when the trouble, and has the pilot lamp scintillation to in time discover unusually and participate in the maintenance for the maintenance personnel.
Referring to fig. 4, the invention relates to an artificial neural network model architecture of an intelligent maintenance system of a hydraulic station of a steel mill. The hydraulic system collects data such as flow, pressure, temperature and the like through a sensor and transmits the data to the PLC, and a decision system of the upper computer analyzes the data to establish a set of parameter prediction system. The prediction system trains a model on the basis of a large amount of data by utilizing a neural network technology, so that the model has better generalization. And (4) evaluating the fault probability of the hydraulic station by using the trained model. The pressure, the temperature, the flow, the oil level, the dirt degree, the viscosity and the like are calculated to acquire data of 16 hydraulic stations as input layers. The output layer uses 5 different neurons to respectively represent different risk levels, the fault occurrence probability is defined as a risk, and the very high risk considers that the fault occurrence probability is very high; the risk is high, and the fault occurrence probability is high; the risk is medium, the failure occurrence probability is medium; the risk is low, and the fault occurrence probability is low; the very low risk considers that the probability of failure is very low. In the artificial neural network model, parameters such as pollution degree, viscosity, oil level, oil temperature, pressure, flow and the like are weighted to calculate the fault occurrence probability of the hydraulic station.
Claims (4)
1. An intelligent maintenance system for a hydraulic station of a steel mill is characterized by comprising a data acquisition monitoring system, a decision-making system and a maintenance system; the data acquisition monitoring system consists of a PLC control system, a sensor and a monitoring interface; the parameters of the pollution degree, viscosity, oil level and oil temperature of hydraulic oil in the system are collected by a sensor and transmitted to a PLC (programmable logic controller), so that real-time display and control on a monitoring interface of an upper computer are realized; the decision system is used for constructing an intelligent decision platform by combining an intelligent algorithm, a big data technology and the like, analyzing data acquired by the PLC, forming a system fault model, and judging the fault type by using a prediction system; the maintenance system is a database management system integrating user management, equipment management and work order management; the maintenance and maintenance records, the work order dispatching and the query management of maintenance personnel and hydraulic station equipment are realized.
2. The utility model provides a steel mill hydraulic pressure station wisdom maintenance system work flow which characterized in that, system work flow includes following step: the temperature, pressure, liquid level, flow and granularity sensors collect and upload parameters of the hydraulic oil such as temperature, pressure, oil level, flow, pollution degree and viscosity to the PLC, and the PLC system judges whether the parameters exceed the process allowable range; if the parameters exceed the standard, the upper computer monitors and immediately alarms, and simultaneously starts the maintenance system and issues a maintenance command; the system judges the fault type according to the standard exceeding parameter characteristics, and determines a maintenance scheme until the maintenance is finished; if the PLC judges that the data parameters do not exceed the process allowable range, a prediction system in the decision-making system works, judges whether the current data is in a dangerous state or not according to the prediction model, and judges whether the system breaks down or not; if the fault is judged according to the prediction system model, the upper computer immediately gives an alarm, and simultaneously starts a maintenance system to realize emergency treatment and maintenance in a crisis state; if the prediction system model judges that no fault exists, the system is stable and far away from danger, and the system works normally.
3. The intelligent maintenance system and the work flow of the steel mill hydraulic station according to claim 1 or 2, wherein an upper computer monitoring interface of the intelligent maintenance system of the steel mill hydraulic station displays and records data of each sensor of the hydraulic station in real time, and inquires historical data and trends; the historical data provides training samples for the decision-making system, and the analysis and the evaluation of the overall condition of the hydraulic station are facilitated; the monitoring interface supports accessing a maintenance system and comprises a user login interface and an equipment management and maintenance interface; the fault information, maintenance times and progress of each device, maintenance personnel information and the like establish a ledger, so that the inquiry and access are facilitated; the host computer interface sets up the warning interface, can pop out the trouble suggestion when the trouble, and has the pilot lamp scintillation to in time discover unusually and participate in the maintenance for the maintenance personnel.
4. The intelligent maintenance system and the work flow of the steel mill hydraulic station according to claim 1 or 2, wherein the intelligent maintenance system is provided with an artificial neural network model architecture, the hydraulic system collects data such as flow, pressure, temperature and the like through a sensor and transmits the data to a PLC, and a decision system of an upper computer performs data analysis to establish a set of parameter prediction system; the prediction system trains a model on the basis of a large amount of data by utilizing a neural network technology, so that the model has better generalization; the trained model is used for evaluating the fault probability of the hydraulic station; the method comprises the following steps of (1) collecting data by 16 hydraulic stations in total, such as pressure, temperature, flow, oil level, pollution degree, viscosity and the like, and using the data as an input layer; the output layer uses 5 different neurons to respectively represent different risk levels, the fault occurrence probability is defined as a risk, and the very high risk considers that the fault occurrence probability is very high; the risk is high, and the fault occurrence probability is high; the risk is medium, the failure occurrence probability is medium; the risk is low, and the fault occurrence probability is low; the risk is very low, and the fault occurrence probability is very low; in the artificial neural network model, parameters such as pollution degree, viscosity, oil level, oil temperature, pressure, flow and the like are weighted to calculate the fault occurrence probability of the hydraulic station.
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| CN202210930286.8A CN115407712A (en) | 2022-08-04 | 2022-08-04 | Intelligent maintenance system for hydraulic station of steel mill and working process |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116664100A (en) * | 2023-05-09 | 2023-08-29 | 江苏盛达智慧科技信息有限公司 | BIM+AI-based intelligent operation and maintenance management system |
| CN116976862A (en) * | 2023-09-20 | 2023-10-31 | 山东国研自动化有限公司 | Factory equipment informatization management system and method |
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2022
- 2022-08-04 CN CN202210930286.8A patent/CN115407712A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116664100A (en) * | 2023-05-09 | 2023-08-29 | 江苏盛达智慧科技信息有限公司 | BIM+AI-based intelligent operation and maintenance management system |
| CN116976862A (en) * | 2023-09-20 | 2023-10-31 | 山东国研自动化有限公司 | Factory equipment informatization management system and method |
| CN116976862B (en) * | 2023-09-20 | 2024-01-02 | 山东国研自动化有限公司 | Factory equipment informatization management system and method |
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