CN117329135B - Method for monitoring running state of slurry pump based on data analysis - Google Patents
Method for monitoring running state of slurry pump based on data analysis Download PDFInfo
- Publication number
- CN117329135B CN117329135B CN202311329338.7A CN202311329338A CN117329135B CN 117329135 B CN117329135 B CN 117329135B CN 202311329338 A CN202311329338 A CN 202311329338A CN 117329135 B CN117329135 B CN 117329135B
- Authority
- CN
- China
- Prior art keywords
- pump
- slurry pump
- monitoring time
- slurry
- module
- 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.)
- Active
Links
- 239000002002 slurry Substances 0.000 title claims abstract description 206
- 238000012544 monitoring process Methods 0.000 title claims abstract description 152
- 238000007405 data analysis Methods 0.000 title claims abstract description 33
- 238000000034 method Methods 0.000 title claims abstract description 16
- 230000002159 abnormal effect Effects 0.000 claims abstract description 44
- 238000004364 calculation method Methods 0.000 claims description 51
- 230000005856 abnormality Effects 0.000 claims description 34
- 238000003745 diagnosis Methods 0.000 claims description 25
- 238000011156 evaluation Methods 0.000 claims description 21
- 238000013178 mathematical model Methods 0.000 claims description 18
- 238000004458 analytical method Methods 0.000 claims description 16
- 239000007788 liquid Substances 0.000 claims description 10
- 238000005457 optimization Methods 0.000 claims description 6
- 230000005540 biological transmission Effects 0.000 claims description 4
- 239000000284 extract Substances 0.000 claims description 3
- 238000012423 maintenance Methods 0.000 abstract description 8
- 238000004519 manufacturing process Methods 0.000 abstract description 7
- 230000008901 benefit Effects 0.000 abstract description 5
- 230000002035 prolonged effect Effects 0.000 abstract description 4
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000004576 sand Substances 0.000 description 1
- 239000010865 sewage 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
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D7/00—Pumps adapted for handling specific fluids, e.g. by selection of specific materials for pumps or pump parts
- F04D7/02—Pumps adapted for handling specific fluids, e.g. by selection of specific materials for pumps or pump parts of centrifugal type
- F04D7/04—Pumps adapted for handling specific fluids, e.g. by selection of specific materials for pumps or pump parts of centrifugal type the fluids being viscous or non-homogenous
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D15/00—Control, e.g. regulation, of pumps, pumping installations or systems
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D15/00—Control, e.g. regulation, of pumps, pumping installations or systems
- F04D15/0088—Testing machines
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D15/00—Control, e.g. regulation, of pumps, pumping installations or systems
- F04D15/02—Stopping of pumps, or operating valves, on occurrence of unwanted conditions
- F04D15/0245—Stopping of pumps, or operating valves, on occurrence of unwanted conditions responsive to a condition of the pump
-
- 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]
Abstract
The invention discloses a method for monitoring the running state of a slurry pump based on data analysis, and particularly relates to the field of data analysis. According to the invention, through collecting and analyzing the running state data of the slurry pump, abnormal conditions of the running state of the slurry pump can be timely found, equipment damage and production accidents are avoided, when abnormal conditions occur, early warning signals can be automatically sent out and monitoring personnel are informed to perform timely intervention, the downtime and maintenance cost of the slurry pump can be reduced, the running efficiency and production benefit of the slurry pump are improved, through early warning of the running state of the slurry pump, replacement and maintenance of the slurry pump can be early warned, the service life of the slurry pump is prolonged, and the safety of the slurry pump in the running process is improved.
Description
Technical Field
The invention relates to the technical field of data analysis, in particular to a method for monitoring the running state of a slurry pump based on data analysis.
Background
The slurry pump is a mechanical device widely applied to various projects, and is mainly used for conveying and mixing various kinds of slurry, sewage and other types of liquid, and various types of slurry pumps such as a single-stage slurry pump, a double-stage slurry pump, a sand slurry pump and the like are adopted according to different purposes and working environments.
At present, the monitoring of the running state of the slurry pump mainly uses a sensor to collect temperature and noise and oil sample information when the slurry pump runs at fixed time intervals, collected data are stored in a system, the collected data are compared with a preset value of system data when monitoring personnel monitor the operation state of the slurry pump, and the monitoring personnel analyze and maintain the running state of the slurry pump after finding that the running state of the slurry pump is abnormal.
It still has some drawbacks in practical use, such as:
the existing monitoring system for the running state of the slurry pump is not comprehensive enough in collection of the running data of the slurry pump, the running state data of the slurry pump is analyzed in a manual mode, accuracy is lacking, early warning signals cannot be sent to monitoring personnel automatically, maintenance time of the slurry pump is prolonged, damage to the slurry pump is aggravated, time cost and labor cost for maintenance of the slurry pump are increased, and running efficiency and production benefit of the slurry pump are reduced.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, embodiments of the present invention provide a method for monitoring an operation state of a slurry pump based on data analysis, which solves the problems set forth in the above-mentioned background art by adopting the following scheme.
In order to achieve the above purpose, the present invention provides the following technical solutions: the method for monitoring the running state of the slurry pump based on data analysis comprises the following steps:
the mud pump monitoring time dividing module: the system is used for acquiring the running state parameters of each slurry pump, dividing the running state parameters into each monitoring time according to a time division mode, monitoring the slurry pump in each monitoring time, and numbering 1,2 and 3 … … n.
The mud pump data acquisition module: the device is used for collecting the flow speed, pump body slurry ratio, pump shaft vibration change frequency, pump shaft vibration change amplitude, rotating shaft oil liquid ratio, pump shaft inclination and lift of the slurry pump at each monitoring time, and is respectively marked as、/>、/>、/>、/>、/>And->Where i=1, 2 … … n, i is denoted as the i-th monitoring time.
A mud pump data analysis module: the system comprises a flow change coefficient calculation unit, a pressure change coefficient calculation unit, a vibration change coefficient calculation unit and a rotation speed change coefficient calculation unit, wherein the flow change coefficient calculation unit, the pressure change coefficient calculation unit, the vibration change coefficient calculation unit and the rotation speed change coefficient calculation unit are used for analyzing data transmitted by a mud pump data acquisition module and transmitting the data obtained by analysis to a mud pump abnormality index calculation module.
The slurry pump abnormality index calculation module: the system comprises a slurry pump data analysis module, a slurry pump abnormality index calculation unit, a slurry pump operation state evaluation and diagnosis module and a slurry pump operation state analysis and diagnosis module.
The slurry pump running state evaluation and diagnosis module: the system comprises a slurry pump abnormality index calculation module, a slurry pump abnormality index diagnosis module, a pre-warning and intervention module, a slurry pump operation state analysis module and a slurry pump operation state analysis module.
Early warning and intervention module: the monitoring time number and the abnormal data of the running state of the slurry pump, which are used for receiving the running state evaluation and diagnosis transmission of the running state of the slurry pump, are used for achieving early warning and intervention of the running state of the slurry pump through analysis and recording of the abnormal data of the running state of the slurry pump.
Preferably, the mud pump data acquisition module acquires the mud pump running state information of each monitoring time through the sensor and the camera, acquires the mud pump running state information in real time, converts the acquired information into digital signals, and classifies the acquired data and transmits the acquired data to the mud pump data analysis module.
Preferably, the data analysis module analyzes the data transmitted by the data acquisition module of the slurry pump through a mathematical model, integrates the data acquired by the sensor and the camera, and extracts the characteristics related to the running state of the slurry pump.
Preferably, the mathematical model used by the flow rate change coefficient calculation unit is:，/>mud pump flow coefficient of variation representing the ith monitoring time,/->Mud pump flow rate indicating the ith monitoring time, +.>Mud pump flow rate indicating the i-1 th monitoring time,/->Pump body mud ratio of mud pump representing ith monitoring time, +.>Other influencing factors representing the flow coefficient, +.>The time difference representing the i-th monitoring time and the i-1-th monitoring time is shown.
The mathematical model used by the pressure change coefficient calculation unit is as follows:，/>a mud pump pressure variation coefficient representing the ith monitoring time,/->Indicating a preset pressure value of the mud pump, +.>Represents the cross-sectional area of the pump body of the slurry pump->Represents the cross-sectional area of the piston pull rod of the slurry pump, +.>Mud pump piston stroke indicating the ith monitoring time, +.>Other influencing factors representing the pressure change coefficient, +.>The time difference representing the i-th monitoring time and the i-1-th monitoring time is shown.
The mathematical model used by the vibration change coefficient calculation unit is as follows:，/>a mud pump vibration change coefficient indicating the ith monitoring time,/->Pump shaft vibration change frequency of mud pump representing ith monitoring time, +.>Pump shaft vibration variation amplitude of mud pump for indicating ith monitoring time, +.>Representing the ith monitorTime measurement of pump shaft inclination of mud pump +.>Other influencing factors representing the vibration variation coefficient.
The mathematical model used by the rotation speed change coefficient calculation unit is as follows:，a rotation speed change coefficient of the slurry pump representing the ith monitoring time,/->The oil liquid ratio of the rotating shaft of the slurry pump representing the ith monitoring time, +.>Indicating the oil liquid ratio of the rotary shaft of the slurry pump at the ith-1 monitoring time>Mud pump head indicating the ith monitoring time, +.>Pump lift of mud pump representing the i-1 th monitoring time,/, for example>Other influencing factors representing the rotational speed variation coefficient,the time difference representing the i-th monitoring time and the i-1-th monitoring time is shown.
Preferably, the mathematical model used by the slurry pump abnormality index calculation unit is:，/>mud pump abnormality index indicating the ith monitoring time, +.>Mud pump flow coefficient of variation representing the ith monitoring time,/->A mud pump pressure variation coefficient representing the ith monitoring time,/->A mud pump vibration change coefficient indicating the ith monitoring time,/->A rotation speed change coefficient of the slurry pump representing the ith monitoring time,/->Other anomaly factors representing mud pump anomaly indices.
Preferably, the slurry pump abnormality indexWhen the operation state of the slurry pump indicating the ith monitoring time is an abnormal state, the monitoring time number of the abnormal operation state of the slurry pump and the abnormal data of the operation state of the slurry pump are transmitted to the early warning and intervention module, and the abnormal index of the slurry pump is->And when the operation state of the slurry pump at the ith monitoring time is a non-abnormal state, the real-time monitoring of the operation state of the slurry pump at the ith monitoring time is maintained.
Preferably, the early warning and intervention module generates an abnormal report of the running state of the slurry pump by analyzing abnormal data of the running state of the slurry pump, generates a corresponding optimization scheme according to the running state evaluation and diagnosis module transmission result of the slurry pump, and sends the optimization scheme to a monitoring person closest to the abnormal monitoring time of the running state of the slurry pump to early warn and intervene the running state of the slurry pump.
The invention has the technical effects and advantages that:
according to the invention, through collecting and analyzing the running state data of the slurry pump, abnormal conditions of the running state of the slurry pump can be found in time, equipment damage and production accidents are avoided, through monitoring the running state of the slurry pump, when abnormal conditions occur, early warning signals can be automatically sent out and monitoring personnel are informed to intervene in time, the downtime and maintenance cost of the slurry pump can be reduced, the running efficiency and production benefit of the slurry pump are improved, through early warning of the running state of the slurry pump, the replacement and maintenance of the slurry pump can be early warned, the service life of the slurry pump is prolonged, and the safety of the slurry pump in the running process is improved.
Drawings
Fig. 1 is a schematic diagram of the overall structure of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. 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.
The method for monitoring the running state of the slurry pump based on the data analysis shown in the reference figure 1 comprises a slurry pump monitoring time dividing module, a slurry pump data acquisition module, a slurry pump data analysis module, a slurry pump abnormality index calculation module, a slurry pump running state evaluation and diagnosis module and an early warning and intervention module.
The slurry pump monitoring time dividing module is used for obtaining the running state parameters of each slurry pump, dividing the running state parameters into monitoring times according to a time dividing mode, monitoring the slurry pump in each monitoring time, and numbering 1,2 and 3 … … n.
The mud pump data acquisition module acquires the mud pump running state information of each monitoring time through the sensor and the camera, acquires the mud pump running state information in real time, converts the acquired information into digital signals, and classifies the acquired data and transmits the acquired data to the mud pump data analysis module.
The mud pump data acquisition module is used for acquiring the flow speed, pump body mud ratio, pump shaft vibration change frequency, pump shaft vibration change amplitude, rotating shaft oil liquid ratio, pump shaft inclination and lift of the mud pump at each monitoring time, and is respectively marked as、/>、/>、/>、/>、/>And->Where i=1, 2 … … n, i is denoted as the i-th monitoring time.
The mud pump data analysis module comprises a flow change coefficient calculation unit, a pressure change coefficient calculation unit, a vibration change coefficient calculation unit and a rotation speed change coefficient calculation unit, and is used for analyzing the data transmitted by the mud pump data acquisition module and transmitting the data obtained by analysis to the mud pump abnormality index calculation module.
The mud pump data analysis module analyzes the data transmitted by the mud pump data acquisition module through a mathematical model, integrates the data acquired by the sensor and the camera, extracts the characteristics related to the running state of the mud pump, and determines the accuracy and the credibility of the data.
The mathematical model used by the flow change coefficient calculation unit is as follows:，mud pump flow coefficient of variation representing the ith monitoring time,/->Mud pump flow rate indicating the ith monitoring time, +.>Mud pump flow rate indicating the i-1 th monitoring time,/->Pump body mud ratio of mud pump representing ith monitoring time, +.>Other influencing factors representing the flow coefficient, +.>The time difference representing the i-th monitoring time and the i-1-th monitoring time is shown.
The mathematical model used by the pressure change coefficient calculation unit is as follows:，/>a mud pump pressure variation coefficient representing the ith monitoring time,/->Indicating a preset pressure value of the mud pump, +.>Represents the cross-sectional area of the pump body of the slurry pump->Represents the cross-sectional area of the piston pull rod of the slurry pump, +.>Mud pump piston stroke indicating the ith monitoring time, +.>Other influencing factors representing the pressure change coefficient, +.>The time difference representing the i-th monitoring time and the i-1-th monitoring time is shown.
The mathematical model used by the vibration change coefficient calculation unit is as follows:，/>a mud pump vibration change coefficient indicating the ith monitoring time,/->Pump shaft vibration change frequency of mud pump representing ith monitoring time, +.>Pump shaft vibration variation amplitude of mud pump for indicating ith monitoring time, +.>Pump shaft inclination of mud pump indicating the ith monitoring time, +.>Other influencing factors representing the vibration variation coefficient.
The mathematical model used by the rotation speed change coefficient calculation unit is as follows:，a rotation speed change coefficient of the slurry pump representing the ith monitoring time,/->The oil liquid ratio of the rotating shaft of the slurry pump representing the ith monitoring time, +.>Indicating the oil liquid ratio of the rotary shaft of the slurry pump at the ith-1 monitoring time>Mud pump head indicating the ith monitoring time, +.>Pump lift of mud pump representing the i-1 th monitoring time,/, for example>Other influencing factors representing the rotational speed variation coefficient,the time difference representing the i-th monitoring time and the i-1-th monitoring time is shown.
The slurry pump abnormality index calculation module is used for receiving all data integrated by the slurry pump data analysis module, calculating all data integrated by the slurry pump data analysis module through the slurry pump abnormality index calculation unit to obtain a slurry pump abnormality index, and transmitting the slurry pump abnormality index to the slurry pump running state evaluation and diagnosis module.
The mathematical model used by the slurry pump abnormality index calculation unit is as follows:，/>mud pump abnormality index indicating the ith monitoring time, +.>Mud pump flow coefficient of variation representing the ith monitoring time,/->A mud pump pressure variation coefficient representing the ith monitoring time,/->The mud pump vibration change coefficient indicating the ith monitoring time,a rotation speed change coefficient of the slurry pump representing the ith monitoring time,/->Other anomaly factors representing mud pump anomaly indices.
The slurry pump running state evaluation and diagnosis module is used for receiving the slurry pump abnormality index transmitted by the slurry pump abnormality index calculation module, evaluating and diagnosing the slurry pump running state through the slurry pump abnormality index, and transmitting the evaluation and diagnosis result to the early warning and intervention module.
Abnormality index of the slurry pumpWhen the operation state of the slurry pump indicating the ith monitoring time is an abnormal state, the monitoring time number of the abnormal operation state of the slurry pump and the abnormal data of the operation state of the slurry pump are transmitted to the early warning and intervention module, and the abnormal index of the slurry pump is->And when the operation state of the slurry pump at the ith monitoring time is a non-abnormal state, the real-time monitoring of the operation state of the slurry pump at the ith monitoring time is maintained.
The early warning and intervention module is used for receiving monitoring time numbers of the running state abnormality of the slurry pump, which are transmitted by the running state evaluation and diagnosis of the slurry pump, and abnormal data of the running state of the slurry pump, and achieving early warning and intervention of the running state of the slurry pump through analysis and recording of the abnormal data of the running state of the slurry pump.
The early warning and intervention module generates an abnormal running state report of the slurry pump by analyzing abnormal running state data of the slurry pump, generates a corresponding optimization scheme according to the running state evaluation and diagnosis module transmission result of the slurry pump, and sends the optimization scheme to a monitoring person closest to abnormal running state monitoring time of the slurry pump to early warn and intervene the running state of the slurry pump.
According to the invention, the time division and numbering are carried out on the slurry pump through the slurry pump monitoring time division module, the slurry pump operation state data acquisition is convenient, the slurry pump operation state information of each monitoring time is acquired through the slurry pump data acquisition module by using a sensor and a camera, the data are transmitted to the slurry pump data analysis module, the slurry pump operation state information of each monitoring time is integrated and classified through the slurry pump data analysis module, each parameter of the integrated and classified is transmitted to the slurry pump abnormal index calculation module, each parameter of the integrated and classified is calculated to obtain the slurry pump abnormal index, the slurry pump abnormal index is transmitted to the slurry pump operation state evaluation and diagnosis module, the slurry pump operation state evaluation and diagnosis are carried out on the slurry pump abnormal index analysis through the slurry pump operation state evaluation and diagnosis module, the evaluation and diagnosis result is transmitted to the early warning and intervention module, the optimized scheme corresponding to the evaluation and diagnosis result is generated through the early warning and intervention module, and the optimized scheme is transmitted to the monitoring personnel closest to the slurry pump operation state abnormal monitoring time, and early warning and intervention are carried out on the slurry pump operation state.
According to the invention, through collecting and analyzing the running state data of the slurry pump, abnormal conditions of the running state of the slurry pump can be found in time, equipment damage and production accidents are avoided, through monitoring the running state of the slurry pump, when abnormal conditions occur, early warning signals can be automatically sent out and monitoring personnel are informed to intervene in time, the downtime and maintenance cost of the slurry pump can be reduced, the running efficiency and production benefit of the slurry pump are improved, through early warning of the running state of the slurry pump, the replacement and maintenance of the slurry pump can be early warned, the service life of the slurry pump is prolonged, and the safety of the slurry pump in the running process is improved.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (6)
1. The method for monitoring the running state of the slurry pump based on data analysis comprises the following steps:
the mud pump monitoring time dividing module: the system is used for acquiring the running state parameters of each slurry pump, dividing the running state parameters into monitoring time according to a time division mode, monitoring the slurry pump in each monitoring time period, and numbering 1,2 and 3 … … n;
the mud pump data acquisition module: the device is used for collecting the flow speed, pump body slurry ratio, pump shaft vibration change frequency, pump shaft vibration change amplitude, rotating shaft oil liquid ratio, pump shaft inclination and lift of the slurry pump at each monitoring time, and is respectively marked as、/>、/>、/>、/>、/>And->Where i=1, 2 … … n, i is denoted as the i-th monitoring time;
a mud pump data analysis module: the system comprises a flow change coefficient calculation unit, a pressure change coefficient calculation unit, a vibration change coefficient calculation unit and a rotation speed change coefficient calculation unit, wherein the flow change coefficient calculation unit, the pressure change coefficient calculation unit, the vibration change coefficient calculation unit and the rotation speed change coefficient calculation unit are used for analyzing data transmitted by a mud pump data acquisition module and transmitting the data obtained by analysis to a mud pump abnormality index calculation module;
the mathematical model used by the flow change coefficient calculation unit is as follows:，/>mud pump flow coefficient of variation representing the ith monitoring time,/->Mud pump flow rate indicating the ith monitoring time, +.>Mud pump flow rate indicating the i-1 th monitoring time,/->Pump body mud ratio of mud pump representing ith monitoring time, +.>Other influencing factors representing the flow coefficient, +.>Representing the time difference between the i-th monitoring time and the i-1 th monitoring time;
the mathematical model used by the pressure change coefficient calculation unit is as follows:，/>a mud pump pressure variation coefficient representing the ith monitoring time,/->Indicating a preset pressure value of the mud pump, +.>Represents the cross-sectional area of the pump body of the slurry pump->Represents the cross-sectional area of the piston pull rod of the slurry pump, +.>Mud pump piston stroke indicating the ith monitoring time, +.>Other influencing factors representing the pressure change coefficient, +.>Representing the time difference between the i-th monitoring time and the i-1 th monitoring time;
the mathematical model used by the vibration change coefficient calculation unit is as follows:，a mud pump vibration change coefficient indicating the ith monitoring time,/->Pump shaft vibration change frequency of mud pump representing ith monitoring time, +.>Pump shaft vibration variation amplitude of mud pump for indicating ith monitoring time, +.>Pump shaft inclination of mud pump indicating the ith monitoring time, +.>Other influencing factors representing the vibration variation coefficient;
the mathematical model used by the rotation speed change coefficient calculation unit is as follows:，/>a rotation speed change coefficient of the slurry pump representing the ith monitoring time,/->The oil liquid ratio of the rotating shaft of the slurry pump at the ith monitoring time is represented,indicating the oil liquid ratio of the rotary shaft of the slurry pump at the ith-1 monitoring time>The mud pump head representing the ith monitoring time,pump lift of mud pump representing the i-1 th monitoring time,/, for example>Other influencing factors representing the rotational speed change factor, +.>Representing the time difference between the i-th monitoring time and the i-1 th monitoring time;
the slurry pump abnormality index calculation module: the system comprises a slurry pump data analysis module, a slurry pump abnormality index calculation unit, a slurry pump operation state evaluation and diagnosis module, a slurry pump operation state analysis module, a slurry pump operation state diagnosis module and a slurry pump operation state analysis module, wherein the slurry pump operation state analysis module is used for receiving various data integrated by the slurry pump data analysis module, calculating various data integrated by the slurry pump data analysis module through the slurry pump abnormality index calculation unit to obtain a slurry pump abnormality index, and transmitting the slurry pump abnormality index to the slurry pump operation state evaluation and diagnosis module;
the slurry pump running state evaluation and diagnosis module: the system comprises a slurry pump abnormality index calculation module, a slurry pump abnormality index diagnosis module, a pre-warning and intervention module, a slurry pump operation state analysis module and a slurry pump operation state analysis module, wherein the slurry pump operation state analysis module is used for receiving the slurry pump abnormality index transmitted by the slurry pump abnormality index calculation module, and transmitting the evaluation and diagnosis result to the pre-warning and intervention module;
early warning and intervention module: the monitoring time number and the abnormal data of the running state of the slurry pump, which are transmitted by the running state evaluation and diagnosis module, are used for receiving the abnormal monitoring time number and the abnormal data of the running state of the slurry pump, and the early warning and the intervention of the running state of the slurry pump are achieved through the analysis and the recording of the abnormal data of the running state of the slurry pump.
2. The method for monitoring the operation state of a slurry pump based on data analysis according to claim 1, wherein: the mud pump data acquisition module acquires the mud pump running state information of each monitoring time through the sensor and the camera, acquires the mud pump running state information, converts the acquired information into digital signals, and classifies and transmits the acquired data to the mud pump data analysis module.
3. The method for monitoring the operation state of a slurry pump based on data analysis according to claim 1, wherein: the mud pump data analysis module analyzes the data transmitted by the mud pump data acquisition module through a mathematical model, integrates the data acquired by the sensor and the camera, and extracts the characteristics related to the running state of the mud pump.
4. The method for monitoring the operation state of a slurry pump based on data analysis according to claim 1, wherein: the mathematical model used by the slurry pump abnormality index calculation unit is as follows:，/>mud pump abnormality index indicating the ith monitoring time, +.>Mud pump flow coefficient of variation representing the ith monitoring time,/->A mud pump pressure variation coefficient representing the ith monitoring time,/->A mud pump vibration change coefficient indicating the ith monitoring time,/->A rotation speed change coefficient of the slurry pump representing the ith monitoring time,/->Other anomaly factors representing mud pump anomaly indices.
5. The method for monitoring the operation state of a slurry pump based on data analysis according to claim 1, wherein: abnormality index of the slurry pumpWhen the operation state of the slurry pump indicating the ith monitoring time is an abnormal state, the monitoring time number of the abnormal operation state of the slurry pump and the abnormal data of the operation state of the slurry pump are transmitted to the early warning and intervention module, and the abnormal index of the slurry pump is->And when the operation state of the slurry pump at the ith monitoring time is a non-abnormal state, the monitoring of the operation state of the slurry pump at the ith monitoring time is maintained.
6. The method for monitoring the operation state of a slurry pump based on data analysis according to claim 1, wherein: the early warning and intervention module generates an abnormal running state report of the slurry pump by analyzing abnormal running state data of the slurry pump, generates a corresponding optimization scheme according to the running state evaluation and diagnosis module transmission result of the slurry pump, and sends the optimization scheme to a monitoring person closest to abnormal running state monitoring time of the slurry pump to early warn and intervene the running state of the slurry pump.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311329338.7A CN117329135B (en) | 2023-10-13 | 2023-10-13 | Method for monitoring running state of slurry pump based on data analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311329338.7A CN117329135B (en) | 2023-10-13 | 2023-10-13 | Method for monitoring running state of slurry pump based on data analysis |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117329135A CN117329135A (en) | 2024-01-02 |
| CN117329135B true CN117329135B (en) | 2024-04-05 |
Family
ID=89282588
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311329338.7A Active CN117329135B (en) | 2023-10-13 | 2023-10-13 | Method for monitoring running state of slurry pump based on data analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117329135B (en) |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105570113A (en) * | 2016-03-02 | 2016-05-11 | 中国石油集团渤海钻探工程有限公司 | Remote online monitoring system for slurry pump |
| CN110490024A (en) * | 2018-04-09 | 2019-11-22 | 西南石油大学 | A kind of slush pump method for diagnosing faults and its device |
| CN111059042A (en) * | 2019-12-12 | 2020-04-24 | 广州南洋理工职业学院 | Slurry pump monitor |
| WO2022122635A1 (en) * | 2020-12-10 | 2022-06-16 | Abb Schweiz Ag | Monitoring industrial equipment with at least one rotating member |
| CN114674363A (en) * | 2022-03-01 | 2022-06-28 | 扬州华辉水泵有限公司 | Slurry pump flow velocity reliability prediction system based on industrial Internet of things |
| CN114707266A (en) * | 2022-03-31 | 2022-07-05 | 江苏苏华泵业有限公司 | Industrial centrifugal pump operation stability prediction system based on artificial intelligence |
| CN114934898A (en) * | 2022-07-25 | 2022-08-23 | 启东市申力高压油泵厂 | Hydraulic pump fault diagnosis analysis system based on multi-mode parameters |
| CN115168608A (en) * | 2022-07-12 | 2022-10-11 | 成都航天科工大数据研究院有限公司 | Mud pump fault diagnosis method based on multi-mode and deep semantic mining technology |
| CN115949599A (en) * | 2023-01-10 | 2023-04-11 | 浙江南元泵业有限公司 | Pump product intelligent diagnosis and control system based on performance curve |
| CN116066357A (en) * | 2021-11-03 | 2023-05-05 | 中石化石油工程技术服务有限公司 | System and method for diagnosing faults of slurry pump |
| CN116698414A (en) * | 2023-06-02 | 2023-09-05 | 西南石油大学 | Slurry pump bearing fault monitoring method based on multi-source data fusion |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7757562B2 (en) * | 2002-10-28 | 2010-07-20 | Mbh Data Source | Technique and apparatus for detecting and monitoring internal defect conditions of mud pumps |
| EP2440784B1 (en) * | 2009-06-12 | 2019-10-23 | Cidra Corporate Services, Inc. | Method and apparatus for predicting maintenance needs of a pump based at least partly on pump performance analysis |
-
2023
- 2023-10-13 CN CN202311329338.7A patent/CN117329135B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105570113A (en) * | 2016-03-02 | 2016-05-11 | 中国石油集团渤海钻探工程有限公司 | Remote online monitoring system for slurry pump |
| CN110490024A (en) * | 2018-04-09 | 2019-11-22 | 西南石油大学 | A kind of slush pump method for diagnosing faults and its device |
| CN111059042A (en) * | 2019-12-12 | 2020-04-24 | 广州南洋理工职业学院 | Slurry pump monitor |
| WO2022122635A1 (en) * | 2020-12-10 | 2022-06-16 | Abb Schweiz Ag | Monitoring industrial equipment with at least one rotating member |
| CN116066357A (en) * | 2021-11-03 | 2023-05-05 | 中石化石油工程技术服务有限公司 | System and method for diagnosing faults of slurry pump |
| CN114674363A (en) * | 2022-03-01 | 2022-06-28 | 扬州华辉水泵有限公司 | Slurry pump flow velocity reliability prediction system based on industrial Internet of things |
| CN114707266A (en) * | 2022-03-31 | 2022-07-05 | 江苏苏华泵业有限公司 | Industrial centrifugal pump operation stability prediction system based on artificial intelligence |
| CN115168608A (en) * | 2022-07-12 | 2022-10-11 | 成都航天科工大数据研究院有限公司 | Mud pump fault diagnosis method based on multi-mode and deep semantic mining technology |
| CN114934898A (en) * | 2022-07-25 | 2022-08-23 | 启东市申力高压油泵厂 | Hydraulic pump fault diagnosis analysis system based on multi-mode parameters |
| CN115949599A (en) * | 2023-01-10 | 2023-04-11 | 浙江南元泵业有限公司 | Pump product intelligent diagnosis and control system based on performance curve |
| CN116698414A (en) * | 2023-06-02 | 2023-09-05 | 西南石油大学 | Slurry pump bearing fault monitoring method based on multi-source data fusion |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117329135A (en) | 2024-01-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111043023B (en) | Fracturing pump on-line monitoring and fault diagnosis system | |
| CN106197996A (en) | Offshore crane Fault Diagnosis of Gear Case device and method based on multivariate data | |
| CN110701137B (en) | Intelligent online detection and diagnosis device and method for hydraulic system of heading machine | |
| CN102707037A (en) | On-line monitoring system for diesel lubrication oil | |
| CN111963415A (en) | Fault diagnosis method and system for hydraulic plunger pump | |
| CN110259433B (en) | Digital monitoring method for solid drilling machine | |
| CN106370556A (en) | Viscosity analysis-based lubricating oil life on-line monitoring system and method | |
| CN104807650A (en) | System and method for intelligently analyzing comprehensive performance of high-power engine | |
| CN117329135B (en) | Method for monitoring running state of slurry pump based on data analysis | |
| CN111412115A (en) | Novel wind power tower cylinder state online monitoring method and system | |
| JP2002073154A (en) | Equipment diagnostic system | |
| CN115159285A (en) | Elevator state monitoring method and elevator state monitoring device | |
| CN113418731A (en) | Online fault diagnosis method for cigarette making machine set | |
| CN112686279B (en) | Gear box fault diagnosis method based on K-means clustering and evidence fusion | |
| CN116877452B (en) | Non-positive-displacement water pump running state monitoring system based on Internet of things data | |
| CN202133662U (en) | Online oil monitoring system of large power reducer | |
| CN115510914B (en) | Intelligent diagnosis method and system for faults of gate and supporting running piece | |
| CN116661381A (en) | Intelligent production equipment remote monitoring system | |
| CN210293296U (en) | But electronic screw press based on thing networking remote monitoring | |
| CN211015603U (en) | Big data monitoring system of port crane transmission part | |
| CN109553006B (en) | Intelligent crane health diagnosis system and working method | |
| CN114508490A (en) | Intelligent split centrifugal pump, network fault point positioning method and readable storage module applied to centrifugal pump | |
| CN112562298A (en) | Remote online water quality monitoring system for sewage treatment | |
| CN112559584A (en) | Remote acquisition and regulation system based on detection and monitoring signal samples | |
| CN113091953A (en) | Temperature detection system based on servo motor |
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 |