CN116464629A - Intelligent oil pump on-line monitoring system - Google Patents
Intelligent oil pump on-line monitoring system Download PDFInfo
- Publication number
- CN116464629A CN116464629A CN202310722801.8A CN202310722801A CN116464629A CN 116464629 A CN116464629 A CN 116464629A CN 202310722801 A CN202310722801 A CN 202310722801A CN 116464629 A CN116464629 A CN 116464629A
- Authority
- CN
- China
- Prior art keywords
- oil pump
- signal
- pressing
- alarm
- fault
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 84
- 238000012423 maintenance Methods 0.000 claims abstract description 47
- 238000007726 management method Methods 0.000 claims abstract description 33
- 230000007246 mechanism Effects 0.000 claims abstract description 33
- 238000012545 processing Methods 0.000 claims abstract description 20
- 238000005086 pumping Methods 0.000 claims abstract description 15
- 238000013500 data storage Methods 0.000 claims abstract description 9
- 238000003825 pressing Methods 0.000 claims description 79
- 230000009471 action Effects 0.000 claims description 25
- 230000008859 change Effects 0.000 claims description 14
- 238000000034 method Methods 0.000 claims description 8
- 239000011159 matrix material Substances 0.000 claims description 7
- 230000001105 regulatory effect Effects 0.000 claims description 7
- 230000008569 process Effects 0.000 claims description 5
- 230000007257 malfunction Effects 0.000 claims description 4
- 238000010606 normalization Methods 0.000 claims description 3
- 230000009466 transformation Effects 0.000 abstract description 6
- 238000007689 inspection Methods 0.000 abstract description 4
- 238000001514 detection method Methods 0.000 description 6
- 230000005540 biological transmission Effects 0.000 description 5
- 230000006870 function Effects 0.000 description 5
- 230000036541 health Effects 0.000 description 5
- 238000012806 monitoring device Methods 0.000 description 4
- 230000000007 visual effect Effects 0.000 description 4
- 230000005856 abnormality Effects 0.000 description 3
- 230000008901 benefit Effects 0.000 description 3
- 238000013461 design Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000003860 storage Methods 0.000 description 3
- 238000005728 strengthening Methods 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 230000006866 deterioration Effects 0.000 description 2
- 239000004973 liquid crystal related substance Substances 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 239000013589 supplement Substances 0.000 description 2
- 238000013518 transcription Methods 0.000 description 2
- 230000035897 transcription Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 239000000470 constituent Substances 0.000 description 1
- 230000006378 damage Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000013021 overheating Methods 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000004904 shortening Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000013598 vector Substances 0.000 description 1
Classifications
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04B—POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS
- F04B51/00—Testing machines, pumps, or pumping installations
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F15—FLUID-PRESSURE ACTUATORS; HYDRAULICS OR PNEUMATICS IN GENERAL
- F15B—SYSTEMS ACTING BY MEANS OF FLUIDS IN GENERAL; FLUID-PRESSURE ACTUATORS, e.g. SERVOMOTORS; DETAILS OF FLUID-PRESSURE SYSTEMS, NOT OTHERWISE PROVIDED FOR
- F15B19/00—Testing; Calibrating; Fault detection or monitoring; Simulation or modelling of fluid-pressure systems or apparatus not otherwise provided for
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F15—FLUID-PRESSURE ACTUATORS; HYDRAULICS OR PNEUMATICS IN GENERAL
- F15B—SYSTEMS ACTING BY MEANS OF FLUIDS IN GENERAL; FLUID-PRESSURE ACTUATORS, e.g. SERVOMOTORS; DETAILS OF FLUID-PRESSURE SYSTEMS, NOT OTHERWISE PROVIDED FOR
- F15B20/00—Safety arrangements for fluid actuator systems; Applications of safety devices in fluid actuator systems; Emergency measures for fluid actuator systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
- G06F18/232—Non-hierarchical techniques
- G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
- G06F18/23213—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Engineering & Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Theoretical Computer Science (AREA)
- Mechanical Engineering (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Biology (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Fluid Mechanics (AREA)
- Probability & Statistics with Applications (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Fluid-Pressure Circuits (AREA)
Abstract
The invention provides an intelligent oil pump online monitoring system which comprises an acquisition system, a data storage system, an online monitoring system, an alarm system and a management and maintenance system. The online monitoring system provided by the invention is connected in parallel with the existing hydraulic mechanism, when the oil pump acts, the related switching value signals of the hydraulic mechanism are collected, and the related information is counted, so that the online monitoring of the pumping pressure of the oil pump can be realized, and the transformer operation and maintenance personnel can visually check during daily inspection without additional operation. In addition, the invention integrates the existing data, and the database stores the data by adopting a structure conforming to the daily workflow of the power transformation operation, thereby facilitating the maintenance and the searching of the data. By adopting the management and maintenance system, when the fault occurs again, the system can automatically match the fault condition with the most similar condition for reference of processing personnel. So that the personnel can quickly find the fault. Meanwhile, recorded accident data is convenient for people to learn and browse and grow rapidly.
Description
Technical Field
The invention belongs to the technical field of monitoring of a high-voltage circuit breaker hydraulic mechanism of a transformer substation, and particularly relates to an intelligent oil pump on-line monitoring system.
Background
The opening and closing operation of the circuit breaker is performed through an operating mechanism, and the working performance and the quality of the operating mechanism have great influence on the working performance and the reliability of the circuit breaker. The hydraulic mechanism is widely applied to the operation control of the high-voltage circuit breaker due to the advantages of compact structure, high transmission power, reliable and stable operation and the like. However, hydraulic operating mechanisms often exhibit hydraulic system leaks that result in pressure drops due to poor materials and manufacturing processes used or excessive operation. The oil pump is started to supplement the pressure once the pressure of the hydraulic mechanism cannot be maintained within the operation required range. When the hydraulic system fault continuously exists, the oil pump can be continuously started, and frequent pressing phenomenon is generated. If the oil pump is frequently pressurized, not caused by the control loop fault, but caused by the abnormality of the hydraulic system, the pressure of the mechanism continuously drops, and finally the circuit breaker is blocked and cannot normally act. This may result in an unplanned power outage or an increase in the equipment fault range due to the inability of the circuit breaker to trip again, jeopardizing safe operation of the equipment and the power grid.
At present, an implementation scheme for solving the leakage problem of a high-voltage circuit breaker hydraulic system of 110kV and above of a transformer substation is an intelligent transformer substation. In the scheme, an online monitoring device is added in the design and construction stage of the transformer substation, so that the hydraulic condition can be monitored in real time. However, this solution does not allow a technical retrofit of existing equipment. If the health condition of the hydraulic system is clearly judged through the pressing data recorded by the operating personnel at present in each month, hidden danger can be found in time by shortening the transcription period under the condition of not carrying out technical transformation, but the operation and maintenance workload can be obviously increased.
Disclosure of Invention
In view of the above, the invention aims to solve the problems that when the system of the high-voltage circuit breaker of the transformer substation leaks, the scheme of the existing intelligent transformer substation cannot be applied and the manual operation and maintenance mode can increase the operation and maintenance workload.
In order to solve the technical problems, the invention provides the following technical scheme:
an intelligent oil pump on-line monitoring system, comprising: the system comprises an acquisition system, a data storage system, an online monitoring system, an alarm system and a management maintenance system;
the acquisition system is used for acquiring a switching value signal of the hydraulic mechanism;
the data storage system is provided with a database, a data structure unit is generated in the database for each oil pump monitoring object, basic information and operation information of the oil pump monitoring object are stored in the data structure unit, and the operation information is obtained based on the acquired switching value signal record;
the on-line monitoring system is used for judging according to the operation information of each oil pump monitoring object, determining whether the operation state of each oil pump monitoring object meets the rated condition, if not, generating corresponding fault information and sending out an alarm signal, wherein the rated condition is correspondingly determined by the basic information of each oil pump monitoring object, and the fault information comprises the operation information of the oil pump monitoring object which does not meet the rated condition;
the alarm system is used for sending out corresponding fault alarms according to the alarm signals;
the management maintenance system is used for matching the fault type and the corresponding processing scheme according to the fault information and generating an accident event record.
Further, the switching value signal of the hydraulic mechanism specifically includes:
the motor starting signal, the pressing overtime signal, the closing locking signal, the opening locking signal, the oil pump starting locking signal, the oil pump pressure value, the temperature and the pressing pulse signal.
Further, the operation information comprises the number of times of pumping in 24 hours, and the online monitoring system compares the number of times of pumping in 24 hours with a pumping threshold value, so that judgment is achieved, wherein the online monitoring system adjusts the magnitude of the pumping threshold value through an adjusting coefficient obtained from the management maintenance system so as to adapt to the change of the number of times of normal pumping of the oil pump under different temperature conditions.
Further, the management and maintenance system adjusts the adjustment coefficient in a self-tuning mode based on the temperature, and the self-tuning process of the adjustment coefficient specifically comprises the following steps:
at the current temperature, if fault alarm occurs, the oil pump action alarm is correct, or the oil pump action is not alarm, other alarm actions are false alarm, and the value of the adjusting coefficient is not changed; if the oil pump action alarms and malfunctions, the value of the adjusting coefficient is reduced; if the fault alarm occurs, the oil pump action is not alarmed, and if other alarm actions are correct, the value of the regulating coefficient is increased.
Further, the operation information further includes hydraulic pressure low, hydraulic pressure slope, closing lock, opening lock, pressing timeout and oil pump start lock, based on the operation information, the on-line monitoring system is specifically used for:
comparing the hydraulic pressure with the hydraulic pressure low rated value, if the hydraulic pressure is smaller than the hydraulic pressure low rated value, generating corresponding fault information and sending out an alarm signal;
comparing the hydraulic slope with a hydraulic slope rated value, if the hydraulic slope is not smaller than the hydraulic slope rated value, generating corresponding fault information and sending an alarm signal;
comparing the number of times of pressing with a pressing threshold value, if the number of times of pressing is not smaller than the pressing threshold value, generating corresponding fault information and sending out an alarm signal, wherein the pressing threshold value is the sum of a rated value of the number of times of pressing and an adjusting coefficient;
and comparing the reset time of closing lock, opening lock, pressing overtime and oil pump starting lock with corresponding rated values, and if the corresponding rated values are exceeded, generating corresponding fault information and sending an alarm signal.
Further, the motor starting signal, the pressing timeout signal, the closing locking signal, the opening locking signal and the oil pump starting locking signal record the time information of signal sending and resetting in the database, the oil pump pressure value and the temperature record numerical value information and corresponding time information in the database, and the pressing pulse signal records the time information of pressing pulse sending in the database.
Further, the basic information includes equipment manufacturer, model, operation period, equipment parameters, related work records and accident records.
Further, each data structure unit of the oil pump monitoring object has a corresponding index structure in the database, and the index structure is specifically:
operation and inspection center, transformer substation, voltage class, hydraulic mechanism and data.
Further, the management and maintenance system obtains a plurality of types of typical fault types by adopting a K-mean algorithm based on the historical operation information recorded by the database, and the plurality of types of typical fault types and the corresponding fault treatment schemes are stored in the database.
Further, in the management and maintenance system, before adopting the K-mean algorithm, the historical operation information is processed and converted into a numerical matrix which can be calculated by a computer, specifically:
for the historical operation information recorded by the signal without specific value, the values are set to 0 and 1, when the fault occurs, the signal is set to 1 if the fault occurs, and otherwise, the signal is set to 0;
for the historical operation information recorded by the numerical signal, adopting normalization processing to map all signal values to between [0,1 ];
creating new values according to historical operation information, wherein the new values comprise motor starting, pressing overtime, closing locking, opening locking, oil pump starting locking, pressing times, hydraulic change trend values before 2 hours, motor starting, pressing overtime, closing locking, opening locking, oil pump starting locking, pressing times and hydraulic change trend values before 8 hours, and normalizing;
and adding the processed various numerical values into a numerical matrix to be used as the input of a K-mean algorithm.
In summary, the invention provides an intelligent oil pump online monitoring system which comprises an acquisition system, a data storage system, an online monitoring system, an alarm system and a management and maintenance system. The online monitoring system provided by the invention is connected in parallel with the existing hydraulic mechanism, when the oil pump acts, the related switching value signals of the hydraulic mechanism are collected, and the related information is counted, so that the online monitoring of the pumping pressure of the oil pump can be realized, and the transformer operation and maintenance personnel can visually check during daily inspection without additional operation. In addition, the invention integrates the existing data, and the database stores the data by adopting a structure conforming to the daily workflow of the power transformation operation, thereby facilitating the maintenance and the searching of the data. By adopting the management and maintenance system, when the fault occurs again, the system can automatically match the fault condition with the most similar condition for reference of processing personnel. So that the personnel can quickly find the fault. Meanwhile, recorded accident data is convenient for people to learn and browse and grow rapidly.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a block diagram of an intelligent oil pump on-line monitoring system according to an embodiment of the present invention;
FIG. 2 is a flow chart of adjusting coefficient self-tuning according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating the structure of a data structure unit according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of alarm logic provided in an embodiment of the present invention;
fig. 5 is a flowchart of alarm judgment provided in an embodiment of the present invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is apparent that the embodiments described below are only some embodiments of the present invention, not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the prior art, hydraulic operating mechanisms often exhibit hydraulic system leaks that result in pressure drops due to poor materials and manufacturing processes used or excessive operation. The oil pump is started to supplement the pressure once the pressure of the hydraulic mechanism cannot be maintained within the operation required range. When the hydraulic system fault continuously exists, the oil pump can be continuously started, and frequent pressing phenomenon is generated. In contrast, frequent oil pump start-up can also reflect the potential for anomalies or malfunctions in the hydraulic system.
Consequences that may result from failure of the oil pump include overheating of the motor and even damage. If the oil pump is frequently pressurized, not caused by the control loop fault, but caused by the abnormality of the hydraulic system, the pressure of the mechanism continuously drops, and finally the circuit breaker is blocked and cannot normally act. This may result in an unplanned power outage or an increase in the equipment fault range due to the inability of the circuit breaker to trip again, jeopardizing safe operation of the equipment and the power grid.
However, in the prior art, only slight pressure leakage is usually generated at the initial stage of the hydraulic system failure, and the oil pump is started slightly more than normal, but no obvious phenomenon or alarm signal exists. In addition, because the transformer substation only records the number of times of pressing the breaker mechanism once a month, the operation and maintenance personnel are difficult to discover the abnormality of the hydraulic system in time.
For faults which occur frequently and repeatedly or are processed, alarm information and fault processing information when the faults are not reserved, new personnel want to process the faults and have no thread, and the faults need to be restarted to start searching, so that time and labor are wasted.
Therefore, on the premise of not increasing the workload of the operation and maintenance of the transformer, the invention aims to provide the intelligent oil pump on-line monitoring system which realizes the detection of the intelligent oil pump system with lower equipment transformation cost and risk. Meanwhile, through collecting and analyzing data, the running condition of the hydraulic system can be judged in advance, and the abnormal condition of the hydraulic system can be found and processed in time. The invention can also give out the preliminary judgment of the faults and assist the staff to quickly find the defects, thereby reducing the influence of the faults on equipment and a power grid.
Referring to fig. 1, an embodiment of the present invention provides an intelligent oil pump online monitoring system, including: the system comprises an acquisition system, a data storage system, an online monitoring system, an alarm system and a management and maintenance system.
The following describes each constituent unit of the online monitoring system provided in this embodiment in detail.
In this embodiment, the acquisition system is used to acquire the switching value signal of the hydraulic mechanism.
For monitoring of a high-voltage breaker hydraulic system of a transformer substation, an intelligent transformer substation is added with an online monitoring device in the design and construction stage, so that the hydraulic condition is monitored in real time. This solution does not allow a technical modification of existing equipment. Therefore, in this embodiment, the acquisition system should acquire the switching value information of the hydraulic mechanism in at least one mode of connecting in parallel to the corresponding position of the hydraulic mechanism, and transmit the data to other parts, so as to provide a data source for the subsequent system to perform state detection and diagnosis.
In this embodiment, the data storage system is provided with a database, in which a data structure unit is generated for each oil pump monitoring object, and basic information and operation information of the oil pump monitoring object are stored in the data structure unit, and the operation information is recorded based on the collected switching value signals.
It should be noted that, for the traditional method of clearly judging the health condition of the hydraulic system by the pressing data recorded by the operator at present in each month, in this way, in order to accurately find the fault in time, the transcription period needs to be shortened, which clearly increases the operation and maintenance workload. In this embodiment, the collecting system can obtain relevant information of the hydraulic system in real time or according to requirements, and on the basis, the online monitoring system provided by the embodiment further establishes a database for storing various recorded information so as to realize omnibearing long-term monitoring on the oil pump. The database receives the data from the acquisition system and transmits the data to the on-line monitoring module for real-time display and processing. The management and maintenance system generates new incident record data by inputting or calculating and stores the data in the database. The storage technology used by the database may be Microsoft Access or MySQL.
The database establishes a corresponding data structure unit for each monitored oil pump, and is used for storing some basic information of the oil pump and operation information recorded according to the collected switching value signals.
In this embodiment, the online monitoring system is configured to determine, according to operation information of each oil pump monitoring object, whether an operation state of each oil pump monitoring object meets a rated condition, and if not, generate corresponding fault information and send an alarm signal, where the rated condition is determined by basic information of each oil pump monitoring object, and the fault information includes operation information of the oil pump monitoring object that does not meet the rated condition.
As an important unit for realizing intelligent monitoring of the intelligent oil pump on-line monitoring system provided by the embodiment, the main function of the on-line monitoring system is to judge whether the hydraulic system is normal or not based on the current collected signal condition. It can be understood that the operation information recorded in the database at least includes non-numerical information and numerical information, and based on these information, the online monitoring system can determine whether the number of actions or the change trend of the oil pump satisfies the rated condition, so as to reflect the condition of the hydraulic system.
In this embodiment, the alarm system is configured to send out a corresponding fault alarm according to the alarm signal.
In this embodiment, the management and maintenance system is configured to match the fault type and the corresponding processing scheme according to the fault information, and generate an incident event record.
It should be noted that the management and maintenance system is another important unit for realizing intelligent monitoring for the intelligent oil pump on-line monitoring system. The management and maintenance system receives faults monitored by the on-line monitoring system, various related operation data of the current hydraulic system are contained in the fault information, the management and maintenance system automatically searches similar faults according to the matching degree through the operation data, and according to built-in settings of the system, a possible fault and a processing scheme are provided, and the possible fault and the processing scheme are sent to the on-line monitoring system to be displayed, and meanwhile, a record of an accident event is generated. For staff, the fault can be rapidly positioned according to historical events and prompts of the system, the fault processing time is shortened, and the operation safety of the system is ensured.
The embodiment provides an intelligent oil pump on-line monitoring system, which comprises an acquisition system, a data storage system, an on-line monitoring system, an alarm system and a management maintenance system. The online monitoring system provided by the invention is connected in parallel with the existing hydraulic mechanism, when the oil pump acts, the related switching value signals of the hydraulic mechanism are collected, and the related information is counted, so that the online monitoring of the pumping pressure of the oil pump can be realized, and the transformer operation and maintenance personnel can visually check during daily inspection without additional operation. In addition, the invention integrates the existing data, and the database stores the data by adopting a structure conforming to the daily workflow of the power transformation operation, thereby facilitating the maintenance and the searching of the data. By adopting the management and maintenance system, when the fault occurs again, the system can automatically match the fault condition with the most similar condition for reference of processing personnel. So that the personnel can quickly find the fault. Meanwhile, recorded accident data is convenient for people to learn and browse and grow rapidly.
In one embodiment of the invention, the field switching value signals specifically collected by the collection system comprise information such as motor start, pressing timeout, closing lock, opening lock, oil pump start lock, oil pump pressure value, temperature, pressing pulse and the like. The data switching value information motor is started, the pressing overtime, the closing lock, the opening lock, the oil pump starting lock and the like are obtained through relays connected in corresponding loops. And the temperature, oil pump pressure values are obtained by means of sensors installed in the hydraulic system. The number of pressing times is obtained by connecting an existing hydraulic mechanism pressing time counter in parallel. When the oil pump is pressed, the action pulse is transmitted to the pressing frequency counter of the hydraulic mechanism, and meanwhile, the system also receives the action pulse and records the current time.
Based on the pressing pulse information acquired by the acquisition system, the on-line monitoring system obtains the pressing times of the oil pump in 24 hours by counting the pressing pulse information in a period of time to judge. It should be noted that the number of times the oil pump is pressed is sensitive to the change of temperature. For example, the number of pump strokes may increase significantly at cold air temperatures, especially during the night. Therefore, in order to keep the accuracy of the online monitoring system in judging the information of the pressing pulse, an input adjusting coefficient is added in the judgment, the adjusting coefficient is a temperature-related quantity, the values are different at different temperatures, the initial adjusting coefficient is manually set by an operator, and the initial adjusting coefficient is obtained through analysis of big data of the management and maintenance system in the later stage so as to adjust the pressing threshold value, and the false alarm times are reduced.
For adjustment of the adjustment coefficient, in one embodiment of the present invention, the management and maintenance system adjusts the magnitude of the adjustment coefficient in a self-tuning manner based on the temperature data. Specifically, the data adjustment coefficient output by the management and maintenance system is an array which changes according to the temperature, and the adjustment coefficient is self-set as follows, and the initial value of the adjustment coefficient is set according to the experience value of the operator. The following chart shows the condition that the adjustment coefficient is self-adjusted when fault alarm occurs at a certain temperature. When an alarm occurs, the oil pump pressing alarm action is correct, or the oil pump pressing alarm does not act, and other alarm actions are performed, but the oil pump pressing alarm is checked to be false alarm, and the adjustment coefficient does not need to be changed. If the oil pump action warning malfunction or failure is detected, but the oil pump action warning does not act, the value of the adjusting coefficient is correspondingly adjusted, so that the oil pump action warning is more accurate. And the action of false alarm or missing alarm of the oil pump action is reduced. The flow of the self-tuning of the tuning system is shown in fig. 2.
In one embodiment of the present invention, the operation information recorded in the database specifically includes information such as motor start, timeout of pressing, closing lock, opening lock, oil pump start lock, oil pump pressure value, temperature, pressing time, etc. Further, the motor is started, the pressing time-out, the closing and the opening and the closing are performed, and the oil pump is started and closed, and the time information of signal emission and reset is recorded in the database. The pressing time records the time information sent by the pressing pulse, the pressing is recorded once, and the pressing times in a certain period of time are obtained by counting the pressing times recorded in the certain period of time. In addition, the data structure unit of each oil pump detection object contains basic information of the oil pump equipment, including equipment manufacturer, model, operation period, equipment parameters, related work records and accident records. Wherein the operational years, work records, accident records and the years of collection are gradually increased with the increase of time, and the work records and the accident records are required to be manually input in the management system. The index structure of each unit in the database is shown in fig. 3, namely, the operation and inspection center, the transformer substation, the voltage class, the hydraulic mechanism and the data.
In a further embodiment of the invention, the on-line monitoring system monitors the running state of the oil pump system in real time based on the obtained data, and the key important information of the oil pump system is displayed in front of a user in real time through the processing of a computer. The method comprises the steps of temperature, oil pump pressure value, number of times of pumping in 24 hours, and trend of variation of the oil pump pressure value.
Specifically, the number of times the oil pump is pressurized within 24 hours can be obtained directly from the database. The basic decision is that the oil pump is allowed to start 10 times per day. And the alarm function is started after more than 10 times of strengthening monitoring and attention signals and after more than 20 times of strengthening monitoring and attention signals, at the moment, an audible and visual alarm is sent out on a display interface, and meanwhile, related personnel are notified to process through a short message, and the alarm signals must be manually reset by operating personnel. In cold air temperature, especially at night, the number of times of oil pump pressing may obviously increase, so the determination is added with an adjustment coefficient, the adjustment coefficient is a temperature-related quantity, at different temperatures, the numerical values are different, the initial adjustment coefficient is manually set by an operator, and the later time is obtained through analysis of big data of a management and maintenance system, so as to adjust the pressing threshold value and reduce the number of false alarms. It should be understood that the threshold used for the determination in this embodiment should be determined according to the actual situation, and this embodiment is merely for convenience of illustration.
The change trend of the oil pump pressure value is obtained through oil pump pressure value calculation, the calculated time interval is within the time range of oil pump pressing twice, and the change curvature of time is obtained through polynomial fitting of data. The health degree of the hydraulic mechanism in the current state can be reflected from the side surface by comparing the change trend of the oil pump pressure value of the breaker in the same type in the current state. The change trend of the oil pump pressure value is obviously accelerated, the slope is obviously increased, and when the slope is larger than a preset value, the current situation that the hydraulic mechanism possibly has leakage can be judged, and an alarm system is started immediately to inform relevant personnel of processing.
The on-line monitoring system can show the current running state of the hydraulic system through the graph and the curve. The system comprises all breaker data in operation, and personnel can directly observe various data of the oil pump information system and health conditions of different oil pump systems through visual display and comparison of the data. The system can automatically track the deterioration conditions of different indexes, give a prompt in advance for the condition of accelerating the deterioration of the indexes, facilitate the strengthening monitoring of operators, and simultaneously make preparations in advance, and once the early warning value is reached, the system immediately carries out overhaul on fault equipment. When the system detects a fault, the alarm device is started, and meanwhile, related information is sent to the management and maintenance system, and the management and maintenance system returns related judgment of an accident and generates a record of the accident event.
The logic for discriminating the accident by the system comprehensively adopts a plurality of signals to judge, the fault can be judged by overtime of the hydraulic pressure low and the number of times of pressing, the accident signals are closed, opened, closed and the like, and the alarm is started by adopting the condition that the number of times of pressing exceeds the rated value and is not reset, and the logic is shown in the figure 4.
In one embodiment of the invention, the fault detection report output by the management maintenance system module and the online processing scheme are input by a K-mean algorithm with feature matrix vectors as input. Before the K-mean algorithm is used, the data stored in the database is firstly processed and converted into a numerical matrix which can be calculated by a computer.
For the motor start, the fault signals such as the overtime of pressing, the closing and locking, the opening and locking, the oil pump start and locking and the like have no specific numerical values, the values are set to be 0 and 1, when the fault occurs, the signal is set to be 1, and otherwise, the signal is set to be 0.
Trend of variation in hydraulic pressureThe temperature, the number of pressing times in 24 hours and the like are numerical values, and the different numerical values have larger differenceAt these values, a normalization process is performed such that all data x are in the same reference frame. In the scheme, min-max standardization is adopted to map all data to [0,1]]In between the two,
wherein, the liquid crystal display device comprises a liquid crystal display device,，/>，/>respectively, the maximum value, the minimum value and the normalized value of the data.
According to the data in the database, new values are created, including motor start, time-out of pressing, closing lock, opening lock, oil pump start lock and pressing times in 2 hours, hydraulic change trend values before 2 hours, motor start, time-out of pressing, closing lock, opening lock, oil pump start lock and pressing times in 8 hours, hydraulic change trend values before 8 hours are normalized, and the values are added into the input matrix.
Then, K faults with different characterizations are manually selected according to the existing faults, and the values of the faults are taken as centers and recorded as，/>，/>，..........，/>。
Defining a loss function:wherein M is the total number of samples, +.>Represents the ith sample, +.>Is->The cluster to which the cluster belongs.
Next, the following procedure is repeated until J converges.
For each sampleAssign it to the closest center:
where t is the number of steps in the iteration.
For each class center k, the center of the class is recalculated:
；
when the J value converges, the center point and the class of sample division converge simultaneously. As a clustering algorithm, the selection of the initial K value is very important, and may affect the effect of subsequent machine learning, so that different fault samples with typical phenomena should be selected when the sample faults are manually selected for learning at the beginning, otherwise, the final result of the clustering algorithm may be affected.
The system is in one-to-one correspondence with the processing mode of a certain fault, the data are input into a database in advance, and when the most similar fault condition under the current condition is obtained according to the detection data, the system can automatically search out the history fault record which is the most similar to the current fault, and the processing method. The rapid positioning processing of faults is convenient for maintenance personnel.
In addition, the alarm system of the intelligent oil pump is mainly an audible and visual alarm device and a signal transmitting device which are connected to the upper computer. When a fault is received, the processor sends out an action instruction to trigger the loudspeaker to give out sound and alarm and the red light to give out light and alarm, and meanwhile, the GSM module sends an alarm short message to the mobile phone on duty. Therefore, the transformer operator can easily find the abnormal phenomenon of the hydraulic system when inspecting or receiving the short message, and immediately develop corresponding treatment. The audible and visual alarm of the alarm system must be manually reset by an operator to be eliminated. Based on the design, the flow of the intelligent oil pump on-line monitoring system for alarming judgment is shown in fig. 5.
The hardware system of the invention is composed of an acquisition system, transmission hardware, an upper computer, storage hardware and an alarm system. The acquisition system comprises a motor start for acquiring data, a pressing overtime, a closing lock, a separating lock, an oil pump start lock, a relay for pressing pulse data, a hydraulic sensor and a temperature sensor. The wired or wireless data transmission hardware can select GSM or ZigBee by laying cables and optical cables or adopting a wireless transmission mode to upload data to a background machine and a wireless transmission mode. The upper computer is a computer with the computing power of the display card not lower than GTX 950. The storage hardware is a mechanical hard disk. The alarm system comprises an indicator light, a loudspeaker and a GSM module with a short message receiving and transmitting function.
Compared with the prior art, the invention has the following advantages:
1. the intelligent oil pump on-line monitoring device is connected in parallel to the existing hydraulic mechanism pressing frequency counter. When the oil pump is pressurized, the action pulse is transmitted to the hydraulic mechanism pressurizing frequency counter, and meanwhile, the intelligent oil pump on-line monitoring device also receives the action pulse. The number of pressing times within 24 hours is counted, so that the oil pump pressing can be monitored on line, and the transformer operation and maintenance personnel can visually check the oil pump pressing during daily inspection without additional operation.
2. The existing data are integrated, the database stores the data by adopting a structure conforming to the daily workflow of the power transformation operation, and the maintenance and the searching of the data are convenient.
3. The alarm threshold is corrected through temperature, so that the frequent false alarm function caused by frequent pressing due to temperature reduction in winter and night is prevented, and the alarm threshold is adjusted through the automatic learning mode of a machine, so that false alarm and missing alarm are avoided.
4. Through the management maintenance system, the accident happening each time and the data uploaded by the accident hydraulic system at the time are recorded, and the fault condition is learned by using a machine learning mode. When the fault occurs again, the system can automatically match the fault condition with the most similar condition for reference of processing staff. So that the personnel can quickly find the fault. Meanwhile, recorded accident data is convenient for people to learn and browse and grow rapidly.
The intelligent oil pump on-line monitoring system provided by the invention can realize the detection of the pressing and the running health state of the oil pump, can learn and adjust the alarm threshold parameters, provides possible accident reasons and processing schemes of the current accident according to the alarm information when the alarm occurs, and stores records of accident events.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. An intelligent oil pump on-line monitoring system, which is characterized by comprising: the system comprises an acquisition system, a data storage system, an online monitoring system, an alarm system and a management maintenance system;
the acquisition system is used for acquiring a switching value signal of the hydraulic mechanism;
the data storage system is provided with a database, a data structure unit is generated in the database for each oil pump monitoring object, basic information and operation information of the oil pump monitoring object are stored in the data structure unit, and the operation information is obtained based on the acquired switching value signal record;
the on-line monitoring system is used for judging according to the operation information of each oil pump monitoring object, determining whether the operation state of each oil pump monitoring object meets a rated condition, if not, generating corresponding fault information and sending out an alarm signal, wherein the rated condition is correspondingly determined by the basic information of each oil pump monitoring object, and the fault information comprises the operation information of the oil pump monitoring object which does not meet the rated condition;
the alarm system is used for sending out corresponding fault alarms according to the alarm signals;
the management and maintenance system is used for matching the fault type and the corresponding processing scheme according to the fault information and generating an accident event record.
2. The intelligent oil pump on-line monitoring system according to claim 1, wherein the switching value signal of the hydraulic mechanism specifically comprises:
the motor starting signal, the pressing overtime signal, the closing locking signal, the opening locking signal, the oil pump starting locking signal, the oil pump pressure value, the temperature and the pressing pulse signal.
3. The intelligent oil pump online monitoring system according to claim 2, wherein the operation information comprises the number of times of pumping in 24 hours, and the online monitoring system compares the number of times of pumping in 24 hours with a pumping threshold value, so as to achieve judgment, wherein the online monitoring system adjusts the magnitude of the pumping threshold value through an adjustment coefficient obtained from the management maintenance system so as to adapt to the change of the number of times of normal pumping of the oil pump under different temperature conditions.
4. The intelligent oil pump on-line monitoring system according to claim 3, wherein the management and maintenance system adjusts the adjustment coefficient in a self-tuning manner based on temperature, and the adjustment coefficient self-tuning process specifically comprises:
at the current temperature, if the fault alarm occurs, the oil pump action alarm is correct, or the oil pump action is not alarm, other alarm actions are in false alarm, and the value of the regulating coefficient is not changed; if the oil pump action alarms and malfunctions, the value of the regulating coefficient is regulated down; if the fault alarm occurs, the oil pump action is not alarmed, and if other alarm actions are correct, the value of the regulating coefficient is regulated.
5. The intelligent oil pump on-line monitoring system of claim 3, wherein the operational information further comprises hydraulic pressure, hydraulic pressure slope, closing lock, opening lock, timeout of pumping, and oil pump start lock, based on the operational information, the on-line monitoring system is specifically configured to:
comparing the hydraulic pressure with a hydraulic pressure low rated value, if the hydraulic pressure is smaller than the hydraulic pressure low rated value, generating corresponding fault information and sending out an alarm signal;
comparing the hydraulic slope with a hydraulic slope rated value, and if the hydraulic slope is not smaller than the hydraulic slope rated value, generating corresponding fault information and sending an alarm signal;
comparing the number of times of pressing with the pressing threshold, if the number of times of pressing is not smaller than the pressing threshold, generating corresponding fault information and sending out an alarm signal, wherein the pressing threshold is the sum of the rated value of the number of times of pressing and the regulating coefficient;
and comparing the reset time of the closing lock, the opening lock, the pressing overtime and the oil pump starting lock with corresponding rated values, and if the reset time exceeds the corresponding rated values, generating corresponding fault information and sending an alarm signal.
6. The intelligent oil pump on-line monitoring system according to claim 2, wherein the motor start signal, the pressing timeout signal, the closing lock signal, the opening lock signal and the oil pump start lock signal record signal sending and resetting time information in the database, the oil pump pressure value and the temperature record numerical value information and corresponding time information in the database, and the pressing pulse signal records pressing pulse sending time information in the database.
7. The intelligent oil pump online monitoring system of claim 1, wherein the base information includes equipment manufacturer, model number, operational age, equipment parameters, related work records and accident records.
8. The intelligent oil pump online monitoring system according to claim 1, wherein the data structure unit of each oil pump monitoring object has a corresponding index structure in the database, and the index structure specifically is:
operation and inspection center, transformer substation, voltage class, hydraulic mechanism and data.
9. The intelligent oil pump online monitoring system according to claim 1, wherein the management and maintenance system obtains a plurality of types of typical fault types by using a K-mean algorithm based on historical operation information recorded by the database, and the plurality of types of typical fault types and corresponding fault handling schemes are stored in the database.
10. The intelligent oil pump on-line monitoring system according to claim 9, wherein in the management and maintenance system, before adopting a K-means algorithm, the historical operation information is processed and converted into a numerical matrix which can be calculated by a computer, specifically:
for the historical operation information recorded by the signal without specific value, the values are set to 0 and 1, when the fault occurs, the signal is set to 1 if the fault occurs, and otherwise, the signal is set to 0;
for the historical operation information recorded by the numerical signal, adopting normalization processing to map all signal values to between [0,1 ];
creating new values according to the historical operation information, wherein the new values comprise motor starting, pressing overtime, closing locking, opening locking, oil pump starting locking, pressing times, hydraulic change trend values before 2 hours, motor starting, pressing overtime, closing locking, opening locking, oil pump starting locking, pressing times and hydraulic change trend values before 8 hours, and normalizing;
and adding the processed various numerical values into a numerical matrix to serve as the input of the K-mean algorithm.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310722801.8A CN116464629B (en) | 2023-06-19 | 2023-06-19 | Intelligent oil pump on-line monitoring system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310722801.8A CN116464629B (en) | 2023-06-19 | 2023-06-19 | Intelligent oil pump on-line monitoring system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116464629A true CN116464629A (en) | 2023-07-21 |
| CN116464629B CN116464629B (en) | 2023-10-24 |
Family
ID=87179257
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310722801.8A Active CN116464629B (en) | 2023-06-19 | 2023-06-19 | Intelligent oil pump on-line monitoring system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116464629B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117536951A (en) * | 2024-01-09 | 2024-02-09 | 布劳宁(上海)液压气动有限公司 | Hydraulic lock operation quality evaluation system based on Internet of things |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111306051A (en) * | 2020-01-16 | 2020-06-19 | 中国石油大学(北京) | Probe type state monitoring and early warning method, device and system for oil transfer pump unit |
| CN115596653A (en) * | 2022-09-21 | 2023-01-13 | 南通阳鸿石化储运有限公司（Cn） | Intelligent management and control application technology for oil pump in chemical reservoir area |
-
2023
- 2023-06-19 CN CN202310722801.8A patent/CN116464629B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111306051A (en) * | 2020-01-16 | 2020-06-19 | 中国石油大学(北京) | Probe type state monitoring and early warning method, device and system for oil transfer pump unit |
| CN115596653A (en) * | 2022-09-21 | 2023-01-13 | 南通阳鸿石化储运有限公司（Cn） | Intelligent management and control application technology for oil pump in chemical reservoir area |
Non-Patent Citations (1)
| Title |
|---|
| 钟声等: ""基于专家系统的断路器液压机构监测"", 《四川电力技术》, vol. 30, no. 2, pages 62 - 64 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117536951A (en) * | 2024-01-09 | 2024-02-09 | 布劳宁(上海)液压气动有限公司 | Hydraulic lock operation quality evaluation system based on Internet of things |
| CN117536951B (en) * | 2024-01-09 | 2024-04-02 | 布劳宁(上海)液压气动有限公司 | Hydraulic lock operation quality evaluation system based on Internet of things |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116464629B (en) | 2023-10-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN116464629B (en) | Intelligent oil pump on-line monitoring system | |
| CN110941918B (en) | Intelligent substation fault analysis system | |
| CN116435634B (en) | Storage battery temperature state monitoring and management system | |
| CN112713649B (en) | Power equipment residual life prediction method based on extreme learning machine | |
| CN112561736A (en) | Fault diagnosis system and method for relay protection device of intelligent substation | |
| CN114721352B (en) | State monitoring and fault diagnosis method and system of DCS (distributed control system) | |
| CN112615436A (en) | Health diagnosis and monitoring system and method for integrated automation device of transformer substation | |
| CN116955091A (en) | Data center fault detection system based on machine learning | |
| CN112633614A (en) | Real-time fault degree diagnosis system and method based on feature extraction | |
| CN117289659A (en) | Intelligent automatic monitoring system for centralized control operation of power plant | |
| CN115728057A (en) | Vibration monitoring and fault diagnosis method for gearbox of wind generating set | |
| CN117477774A (en) | Intelligent early warning system and method for multifunctional power distribution cabinet | |
| CN117318310B (en) | Remote unmanned intelligent monitoring system for explosion-proof power distribution cabinet | |
| CN117318297A (en) | Alarm threshold setting method, system, equipment and medium based on state monitoring | |
| CN117331790A (en) | Machine room fault detection method and device for data center | |
| CN115901004A (en) | Health monitoring system and method for zinc pot induction heater of hot galvanizing production line | |
| CN115469594A (en) | Digital twin monitoring system | |
| CN115596653A (en) | Intelligent management and control application technology for oil pump in chemical reservoir area | |
| CN109889400A (en) | A kind of Enterprise Service Bus trouble analysis system and operation method | |
| CN111879363A (en) | Operation maintenance method and system for automatic environment monitoring device | |
| CN115542861A (en) | Intelligent auxiliary patrol early warning response method and device for nuclear power plant state parameters | |
| Tang et al. | Development of Predictive Maintenance System for Nuclear Power Turbine Unit | |
| CN112798047B (en) | Environmental data monitoring and collecting method and system for android device | |
| CN115616998A (en) | Auxiliary disc inspection system, application method of auxiliary disc inspection system and application system | |
| KR20240057866A (en) | Integrated facility monitoring system using wireless sensor and metaverse |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |