Fault detection method and device for reciprocating plunger pump
By building a slider wear mechanism model and dynamic model, combining digital twin technology and real-time monitoring data, accurate fault detection and early warning of slide wear of reciprocating plunger pumps is achieved, and the problems of low accuracy and insufficient interpretability in the existing technology are solved.
Patent Information
- Application Number
- CN202411812657.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-10
- Publication Date
- 2025-03-28
AI Technical Summary
In the prior art, the fault detection of reciprocating plunger pumps completely relies on measurement data. The fault detection model cannot accurately describe the evolution of slider wear, has low accuracy, and the fault detection model is insufficiently interpretable.
A slide wear mechanism model of the reciprocating plunger pump slider and a dynamic model of the slider local wear expansion are constructed. Based on these models, a digital twin model that maps the wear of the slider throughout the life cycle is constructed, and the digital twin model is dynamically calibrated through real-time monitoring health status information to obtain a slider health monitoring model for fault detection and fault warning.
Through the correlation mapping of the real-time simulation slider wear mechanism model and the vibration monitoring data monitored in real-time, a slider health monitoring model driven by mechanism and data fusion is built, which can more comprehensively and accurately reflect the full life cycle wear process of the slider, improve the accuracy of fault detection, and provide more reasonable and accurate maintenance decisions.
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Figure CN119712525A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of fault detection of a reciprocating piston pump, and in particular to a method and device for fault detection of a reciprocating piston pump. Background Art
[0002] The reciprocating plunger pump is the core equipment in the hydraulic supply system of the fully-mechanized mining face. It provides hydraulic power for the hydraulic support of the working face and is the power source of the entire hydraulic system of the fully-mechanized mining face. Slider eccentric wear and ablation are typical failures of the plunger pump. If they are not discovered and handled in time, they will lead to unplanned downtime of the reciprocating plunger pump, affecting the safe and efficient production of the coal mine. Therefore, it is of great significance to monitor the state of the slider of the reciprocating plunger pump and diagnose the early warning of failures.
[0003] At present, the state monitoring and fault diagnosis of the slider mainly rely on the oil temperature data of the crankcase, or the vibration sensor installed on the surface of the crankcase for data collection. At the same time, the slider wear fault detection model will classify the slider wear degree into different levels such as slight, moderate, severe, and severe wear, and then classify it according to data analysis, and finally give the slider wear state. It can be seen that data is an important basis for establishing a slider wear fault detection model. In addition to collecting data under the normal state of the slider, it is also necessary to collect data under different wear states such as slight, moderate, severe, and severe. Based on these data, combined with signal analysis, artificial intelligence models, etc., the fault detection model is trained, and the trained model is deployed to realize the intelligent identification of slider wear faults.
[0004] However, the above technical solutions are completely dependent on measured data. On the one hand, although the data-driven fault detection model can accurately classify the wear faults of the slider, it lacks guidance on the fault mechanism and the model is not interpretable enough. On the other hand, since it is difficult to fully collect the status data of the slider throughout its life cycle, the data-driven fault detection model cannot accurately describe the working status of the slider and the complete performance degradation process from normal to slight wear and then to ablation. It cannot provide an intuitive and gradual evolution of the slider wear, which can provide equipment managers with a strong basis for maintenance. Summary of the invention
[0005] The present application aims to provide a reciprocating piston pump fault detection method and device to solve the technical problems in the prior art that the fault detection of the reciprocating piston pump completely relies on measurement data, the fault detection model cannot accurately describe the wear evolution process of the slider, the accuracy is low, and the fault detection model is insufficiently interpretable.
[0006] In order to solve the above technical problems, the present application provides a reciprocating piston pump fault detection method, comprising:
[0007] Construct a slider wear mechanism model for a reciprocating piston pump slider;
[0008] Construct a dynamic model of local wear extension of the slider;
[0009] Constructing a digital twin model that maps the wear of the slider throughout its life cycle based on the slider wear mechanism model and the dynamic model;
[0010] Dynamically calibrating the digital twin model through real-time monitored health status information of the slider to obtain a slider health monitoring model;
[0011] The slider health monitoring model is used to perform fault detection and fault warning on the slider wear of the reciprocating piston pump.
[0012] In some embodiments, constructing a slider wear mechanism model includes:
[0013] Conducting friction and wear tests on the sliding block friction pair material under different sliding speeds and loads to obtain the friction coefficient of the sliding block friction pair under different working conditions of the reciprocating piston pump;
[0014] According to the friction coefficient of the slider friction pair under the different working conditions, the slider wear mechanism model is constructed based on the Archard wear theory.
[0015] In some embodiments, the formula of the slider wear mechanism model is:
[0016]
[0017] Wherein, h is the wear depth; K is the friction coefficient, which is obtained through the friction and wear test of the slider friction pair; H is the material hardness; p is the contact pressure; v is the relative sliding velocity; m is the pressure index; and n is the velocity index.
[0018] In some embodiments, constructing a dynamic model of local wear extension of a slider includes:
[0019] The correlation between the wear of the slider and the vibration of the box is established based on the Hertz contact theory;
[0020] A dynamic model of local wear extension of the slider is constructed according to the correlation between the slider wear and the box vibration.
[0021] In some embodiments, in the correlation between the wear of the slider and the vibration of the box, the calculation formula of the slider deformation and the load is:
[0022] F=Kδ n
[0023] Where F is the Hertzian contact force; K is the total contact stiffness; δ is the contact deformation; and n is the load-deformation coefficient.
[0024] In some embodiments, the displacement excitation during the expansion process of the local wear of the slider is expressed as:
[0025]
[0026] In the formula, M represents the mass of the slider; C represents the damping ratio; K represents the stiffness; F represents the exciting force; y represents the displacement; represents the first derivative of displacement; represents the second derivative of displacement.
[0027] In some embodiments, a digital twin model mapping the wear of the slider throughout its life cycle is constructed based on the slider wear mechanism model and the dynamic model, including:
[0028] According to the working condition data of the reciprocating piston pump and the wear mechanism model of the slider, the correlation relationship between the wear depth and the load is obtained;
[0029] The load is input into the dynamic model, and the simulated vibration signal and its characteristic trend corresponding to the wear size of the slider throughout its life cycle are iteratively calculated;
[0030] The simulated vibration signal and its characteristic trend are processed by using a long short-term memory network to construct a mapping relationship model between slider wear and vibration characteristics.
[0031] In some embodiments, the digital twin model is dynamically calibrated by real-time monitoring of the health status information of the slider to obtain a slider health monitoring model, including:
[0032] Keeping consistent with the box position generating the simulated vibration signal in the dynamic model, the health status information of the slider is obtained in real time through a monitoring device arranged on the actual box;
[0033] The digital twin model is dynamically calibrated according to the health status information.
[0034] In some embodiments, dynamically calibrating the digital twin model according to the health status information includes:
[0035] Filter and remove noise from the acquired measured signal to obtain a vibration signal segment corresponding to the crankshaft phase;
[0036] extracting a first energy feature of the vibration signal segment;
[0037] Acquire state data of the slider at different wear levels, and extract a second energy feature from the state data;
[0038] The digital twin model is dynamically calibrated according to the first energy signature and the second energy signature.
[0039] The present application also provides a reciprocating piston pump fault detection device, comprising:
[0040] A first building module is configured to build a slider wear mechanism model of a reciprocating piston pump slider;
[0041] A second building module is configured to build a dynamic model of local wear extension of the slider;
[0042] A third construction module is configured to construct a digital twin model mapping the wear of the slider throughout its life cycle based on the slider wear mechanism model and the dynamic model;
[0043] A calibration module is configured to dynamically calibrate the digital twin model through real-time monitored health status information of the slider to obtain a slider health monitoring model;
[0044] The fault detection module is configured to perform fault detection and fault warning on the slider wear of the reciprocating piston pump through the slider health monitoring model.
[0045] An embodiment of the present application also provides an electronic device, comprising at least a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned reciprocating piston pump fault detection method when executing the computer program on the memory.
[0046] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned reciprocating piston pump fault detection method are implemented.
[0047] The fault detection method and device of the reciprocating piston pump provided in the embodiment of the present application construct a slider wear mechanism model of the slider of the reciprocating piston pump; construct a dynamic model of the local wear extension of the slider; construct a digital twin model that maps the wear of the slider throughout its life cycle based on the slider wear mechanism model and the dynamic model; dynamically calibrate the digital twin model through the real-time monitored slider health status information to obtain a slider health monitoring model; perform fault detection and fault warning on the slider wear of the reciprocating piston pump through the slider health monitoring model, and can correlate and map the real-time simulated slider wear mechanism model and the real-time monitored vibration monitoring data, A digital twin model of the slider of a reciprocating piston pump driven by mechanism and data fusion is constructed for slider wear fault detection. Compared with the existing fuzzy grading of slider wear degree, the constructed slider health monitoring model can more comprehensively and accurately reflect the wear process of the slider throughout its life cycle, and accurately quantify the wear degree of slider wear fault detection, providing quantitative and accurate result data for equipment management, improving the accuracy of fault detection, and thus providing more reasonable and accurate maintenance decisions; in addition, compared with the insufficient explainability of data-driven fault detection models, the slider health monitoring model constructed in this application is based on slider wear mechanism model, dynamic model, etc., and has good explainability. BRIEF DESCRIPTION OF THE DRAWINGS
[0048] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.
[0049] Figure 1 A flow chart of a fault detection method for a reciprocating piston pump according to an embodiment of the present application;
[0050] Figure 2 It is a schematic structural diagram of a fault detection device for a reciprocating piston pump according to an embodiment of the present application. DETAILED DESCRIPTION
[0051] Various aspects and features of the present application are described herein with reference to the accompanying drawings.
[0052] It should be understood that various modifications may be made to the embodiments of the present application. Therefore, the above description should not be considered as limiting, but only as an example of an embodiment. Other modifications within the scope and spirit of the present application will occur to those skilled in the art.
[0053] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the present application and, together with the general description of the present application given above and the detailed description of the embodiments given below, serve to explain the principles of the present application.
[0054] These and other characteristics of the present application will become apparent from the following description of a preferred form of embodiment given as a non-limiting example with reference to the accompanying drawings.
[0055] It should also be understood that, although the present application has been described with reference to some specific examples, those skilled in the art will be able to realize many other equivalent forms of the present application that have the features described in the claims and are therefore within the scope of protection defined thereby.
[0056] The above and other aspects, features and advantages of the present application will become more apparent in view of the following detailed description when taken in conjunction with the accompanying drawings.
[0057] Specific embodiments of the present application are described hereinafter with reference to the accompanying drawings; however, it should be understood that the embodiments applied for are merely examples of the present application, which may be implemented in a variety of ways. Well-known and / or repeated functions and structures are not described in detail to avoid unnecessary or redundant details that obscure the present application. Therefore, the specific structural and functional details applied for herein are not intended to be limiting, but merely serve as a basis and representative basis for the claims to teach those skilled in the art to use the present application in a variety of ways with substantially any suitable detailed structure.
[0058] This specification may use the phrases "in one embodiment," "in another embodiment," "in yet another embodiment," or "in other embodiments," all of which may refer to one or more of the same or different embodiments according to the present application.
[0059] Figure 1 FIG. 1 is a flow chart showing a method for detecting a fault of a reciprocating piston pump according to an embodiment of the present application. Figure 1 As shown, the first embodiment of the present application provides a fault detection method for a reciprocating piston pump, comprising:
[0060] S101: Construct a slider wear mechanism model for a reciprocating piston pump slider.
[0061] The reciprocating piston pump (reciprocating plunger pump) is an important device of the hydraulic system, which mainly includes a driving mechanism (such as a motor), a crankshaft connecting rod mechanism, a plunger and other components. The reciprocating plunger pump converts the rotational motion of the driving mechanism into the reciprocating motion of the plunger through the crankshaft connecting rod mechanism to achieve the suction and discharge of liquid. The crankshaft connecting rod mechanism includes a crankshaft, a connecting rod and a slider (crosshead). The slider is connected between the connecting rod and the plunger. The slider is an important component in the plunger pump. The rotation of the crankshaft pushes the plunger to perform linear reciprocating motion through the slider. Since the wear of the slider is a typical fault of the plunger pump, the reciprocating plunger pump is fault-detected by monitoring the slider status in this embodiment.
[0062] First, a friction and wear tester was used to conduct friction and wear tests on the slider friction pair material of the reciprocating piston pump slider under different sliding speeds and loads to obtain the friction coefficient of the slider friction pair under different working conditions of the reciprocating piston pump (referred to as the piston pump). Then, using the friction coefficient of the above slider friction pair, a mechanism model of slider wear was constructed based on Archard wear theory, and the formula is as follows:
[0063]
[0064] Where: h is the wear depth; K is the friction coefficient, which is obtained through the friction and wear test of the slider friction pair; H is the material hardness; p is the contact pressure; v is the relative sliding velocity; m is the pressure index; and n is the velocity index.
[0065] The slider wear mechanism model is a slider wear failure mechanism model (or slider damage mechanism model). When a slider fails, the degree of wear at different positions is different. Therefore, the position where the slider is most susceptible to wear and has the most severe wear is used as the key position for measuring the slider wear degree.
[0066] S102: Construct a dynamic model of local wear extension of the slider.
[0067] By building a dynamic model of the local wear extension of the slider, we can obtain the box vibration signal that characterizes the slider state. The box simulated vibration signal generated by the dynamic model has the same trend and volatility as the measured vibration signal. Therefore, the vibration characteristic curve corresponding to the slider wear of the plunger pump under different working conditions is constructed.
[0068] Step S102 specifically includes:
[0069] S1021: Establish the correlation between slider wear and box vibration based on Hertz contact theory;
[0070] S1022: Constructing a dynamic model of the local wear extension of the slider according to the correlation between the slider wear and the box vibration.
[0071] In this embodiment, the correlation between the wear of the slider and the vibration of the box is established based on the Hertz contact theory, and the deformation of the slider and the load can be calculated by the following formula:
[0072] F=Kδ n (2)
[0073] Where F is the Hertzian contact force; K is the total contact stiffness; δ is the contact deformation; and n is the load-deformation coefficient.
[0074] The dynamic model based on Hertz contact theory can more accurately reflect the expansion process of local wear of the slider. The displacement excitation during the expansion process can be expressed by a partition function, which is specifically expressed as follows:
[0075]
[0076] In the formula, M represents the mass of the slider; C represents the damping ratio; K represents the stiffness; F represents the exciting force; y represents the displacement, that is, the wear depth; represents the first derivative of displacement, i.e., wear velocity; Represents the second derivative of displacement, i.e. wear acceleration.
[0077] Based on the above formulas (2) and (3), the dynamic model of local wear extension of the slider can be derived.
[0078] It is understandable that the Hertz contact force in the above formula (2) corresponds to the exciting force in formula (3) and is used to represent the vibration of the box. S103: Construct a digital twin model that maps the wear of the slider throughout its life cycle based on the slider wear mechanism model and the dynamic model.
[0079] Digital twins make full use of data such as physical models, sensors, and operation history, integrate multi-disciplinary, multi-physical quantity, multi-scale, and multi-probability simulation processes, and complete mapping in virtual space, thereby reflecting the entire life cycle of the corresponding physical equipment. In this step, a digital twin model that maps the wear of the slider throughout its life cycle is constructed by combining the real-time operating data of the reciprocating piston pump, the real-time simulated slider wear mechanism model, and the dynamic model constructed in step S102 to obtain an initial slider health monitoring model. The digital twin model can be obtained by training a neural network. Step S103 specifically includes:
[0080] S1031: Obtaining a correlation between wear depth and load according to the working condition data of the reciprocating piston pump and the wear mechanism model of the slider;
[0081] S1032: inputting the load into the dynamic model, and iteratively calculating the simulated vibration signal and its characteristic trend corresponding to the wear size of the slider throughout its life cycle;
[0082] S1033: Using a long short-term memory network to process the simulated vibration signal and its characteristic trend, and construct a mapping relationship model between slider wear and vibration characteristics.
[0083] Specifically, the relative sliding speed of the slider can be calculated in real time through the rotation speed of the crankshaft of the plunger pump. Combining other parameters with the failure mechanism model of the slider wear, the correlation between the wear depth and the load can be obtained. Substituting the load into the dynamic model of the local wear extension of the slider obtained in step S102, the simulated vibration signal corresponding to the wear size of the slider throughout its life cycle (0-10mm, with an interval of 0.1mm) and its characteristic trend can be iteratively calculated.
[0084] The wear depth of the slider is an intuitive representation of the slider state. In this step, a long short-term memory network is used to establish a mapping relationship model between slider wear and vibration characteristics (slider wear-vibration characteristic mapping relationship model), thereby obtaining a relationship between the wear degree corresponding to the entire life cycle of the slider and the vibration characteristics of the box, and the correlation is continuous.
[0085] S104: Dynamically calibrate the digital twin model through real-time monitoring of the health status information of the slider to obtain a slider health monitoring model.
[0086] In this step, the initial slider health monitoring model obtained by using the slider wear mechanism model of real-time simulation (the data of the initial health monitoring model is the theoretical data obtained by simulation) can be associated and mapped with the health status information of the slider obtained by real-time monitoring (such as the actual vibration monitoring data), and the digital twin model constructed in step S103 can be dynamically calibrated to construct a slider health monitoring model driven by the fusion of mechanism and measured data.
[0087] Step S104 specifically includes:
[0088] S1041: Keeping the position of the box that generates the simulated vibration signal in the dynamic model consistent, obtaining the health status information of the slider in real time through a monitoring device arranged on the actual box;
[0089] S1042: Dynamically calibrate the digital twin model according to the health status information.
[0090] Specifically, a vibration acceleration sensor can be installed on the actual box to monitor the vibration signal of the box in real time, so as to obtain the health status information of the slider in real time. The health status information is the measured signal. Then the real-time monitored health status information is compared and integrated with the constructed initial slider health monitoring model to obtain a more accurate slider health monitoring model.
[0091] Step S1042 specifically includes:
[0092] S201: Acquire measured vibration state data of the slider under different wear degrees, and extract energy characteristics from the measured vibration state data;
[0093] S204: Dynamically calibrate the digital twin model according to the energy characteristics.
[0094] In this step, the state data of the slider under different wear degrees can be monitored in real time to obtain the measured vibration state data of the slider. For example, the measured vibration state data of the slider under different wear degrees such as mild, moderate, severe, and severe can be obtained. The slider wear-vibration characteristic mapping relationship model obtained in step S103 is a continuous curve or straight line. The slider wear depth corresponding to the measured vibration state data can be obtained from the slider wear-vibration characteristic mapping relationship model according to the measured vibration state data, and the slider wear depth in the model is compared with the slider wear degree corresponding to the measured vibration state data. If the slider wear depth in the model belongs to the slider wear degree range corresponding to the measured vibration state data or the slider wear depth in the model deviates closely from the slider wear degree corresponding to the measured vibration state data, the model is determined to be accurate and no calibration is required, or only fine-tuning calibration is required; when the slider wear depth in the model does not belong to the slider wear degree range corresponding to the measured vibration state data or the slider wear depth in the model deviates far from the slider wear degree corresponding to the measured vibration state data, the measured vibration state data is input into the digital twin model to perform dynamic calibration training on the digital twin model to obtain a more accurate slider health monitoring model that integrates the slider wear mechanism and the measured data.
[0095] Optionally, step S201 specifically includes:
[0096] S2011: filtering and denoising the acquired measured vibration state data to obtain a vibration signal segment corresponding to the crankshaft phase;
[0097] S2012: Extract the energy characteristics of the vibration signal segment. After filtering and denoising the measured signal, obtain the vibration signal segment corresponding to the crankshaft phase, obtain its energy characteristics, dynamically calibrate the digital twin model, and obtain a slider health monitoring model driven by data fusion and the mechanism that can characterize the wear of the slider throughout its life cycle.
[0098] As can be seen from the above, in this embodiment, through steps S101 to S103, a mechanism model of slider wear is constructed based on Archard wear theory, a correlation between slider wear and box vibration is established based on Hertz contact theory, and a mapping relationship model between slider wear and vibration characteristics is established using a long short-term memory network, thereby obtaining a relationship between the wear degree corresponding to the slider's entire life cycle and the box vibration characteristics, and obtaining an initial slider health monitoring model that characterizes the slider's entire life cycle wear; then, through step S104, a slider health monitoring model driven by a mechanism and data fusion that can characterize the slider's entire life cycle wear is obtained. In step S104, the wear-vibration characteristic mapping relationship model of the slider's entire life cycle is dynamically calibrated and updated using the actual measured data of the sensor, so that the model used for slider wear fault detection is more accurate.
[0099] It is understandable that in this embodiment, the health status information of the slider is the vibration data of the slider. In other embodiments, the health status information of the slider may also include the mass of the slider, the pressure, temperature and flow rate of the environment in which the slider is located, etc., so that the health status of the slider can be more comprehensively monitored. For example, when the temperature is high, the slider wears faster. Therefore, the digital twin model can be dynamically calibrated according to the measured vibration status data within the same temperature range to obtain a more accurate slider health monitoring model.
[0100] S105: Performing fault detection and fault detection on the slider wear of the reciprocating piston pump through the slider health monitoring model.
[0101] In this step, during the operation of the reciprocating piston pump, the health status information of the slider can be obtained in real time through the monitoring device such as the sensor set in the box, and the information can be input into the slider health monitoring model to monitor the slider wear in real time to determine whether a fault occurs, and to perform corresponding fault warning after the fault occurs. On the one hand, the slider wear mechanism model can be simulated in real time and dynamically combined with the working condition data of the reciprocating piston pump, and the mapping relationship model can be dynamically updated to match it with the current operating conditions to obtain a more accurate slider health monitoring model. On the other hand, the real-time monitored slider health status information is input into the slider health monitoring model, and the slider wear degree is calculated according to the real-time monitored vibration signal. The slider wear is monitored in real time, providing direct data support for the health management of the reciprocating piston pump. When the calculated slider wear reaches a certain level, a warning signal is issued to prompt the user to arrange maintenance work as soon as possible to avoid the piston pump from failing to work properly and avoid safety accidents.
[0102] The fault detection method for a reciprocating piston pump provided in an embodiment of the present application constructs a slider wear mechanism model of a reciprocating piston pump slider; constructs a dynamic model of local wear extension of the slider; constructs a digital twin model that maps the wear of the slider throughout its life cycle based on the slider wear mechanism model and the dynamic model; dynamically calibrates the digital twin model through real-time monitored slider health status information to obtain a slider health monitoring model; performs fault detection and fault warning on the slider wear of the reciprocating piston pump through the slider health monitoring model, and can correlate and map the real-time simulated slider wear mechanism model and the real-time monitored vibration monitoring data to construct a digital twin model. A digital twin model of the slider of a reciprocating piston pump driven by mechanism and data fusion is established for slider wear fault detection. Compared with the existing fuzzy grading of slider wear degree, the constructed slider health monitoring model can more comprehensively and accurately reflect the wear process of the slider throughout its life cycle, and accurately quantify the wear degree of slider wear fault detection, provide quantitative and accurate result data for equipment management, improve the accuracy of fault detection, and thus provide more reasonable and accurate maintenance decisions; in addition, compared with the insufficient explainability of data-driven fault detection models, the slider health monitoring model constructed in this application is based on slider wear mechanism model, dynamic model, etc., and has good explainability.
[0103] Figure 2 FIG. 2 is a schematic diagram showing the structure of a fault detection device for a reciprocating piston pump according to an embodiment of the present application. Figure 2 As shown, the second embodiment of the present application provides a fault detection device for a reciprocating piston pump, comprising:
[0104] A first building module 10 is configured to build a slider wear mechanism model of a reciprocating piston pump slider;
[0105] A second construction module 20 is configured to construct a dynamic model of local wear extension of the slider;
[0106] A third construction module 30 is configured to construct a digital twin model mapping the wear of the slider throughout its life cycle according to the slider wear mechanism model and the dynamic model;
[0107] A calibration module 40 is configured to dynamically calibrate the digital twin model through real-time monitored health status information of the slider to obtain a slider health monitoring model;
[0108] The fault detection module 50 is configured to perform fault detection and fault warning on the slider wear of the reciprocating piston pump through the slider health monitoring model.
[0109] In some embodiments, the first building block 10 is further configured to:
[0110] Conducting friction and wear tests on the sliding block friction pair material under different sliding speeds and loads to obtain the friction coefficient of the sliding block friction pair under different working conditions of the reciprocating piston pump;
[0111] According to the friction coefficient of the slider friction pair under the different working conditions, the slider wear mechanism model is constructed based on the Archard wear theory.
[0112] In some embodiments, the formula of the slider wear mechanism model is:
[0113]
[0114] Wherein, h is the wear depth; K is the friction coefficient, which is obtained through the friction and wear test of the slider friction pair; H is the material hardness; p is the contact pressure; v is the relative sliding velocity; m is the pressure index; and n is the velocity index.
[0115] In some embodiments, the second building block 20 is further configured to:
[0116] The correlation between the wear of the slider and the vibration of the box is established based on the Hertz contact theory;
[0117] A dynamic model of local wear extension of the slider is constructed according to the correlation between the slider wear and the box vibration.
[0118] In some embodiments, in the correlation between the wear of the slider and the vibration of the box, the calculation formula of the slider deformation and the load is:
[0119] F=Kδ n
[0120] Where F is the Hertzian contact force; K is the total contact stiffness; δ is the contact deformation; and n is the load-deformation coefficient.
[0121] In some embodiments, the displacement excitation during the expansion process of the local wear of the slider is expressed as:
[0122]
[0123] In the formula, M represents the mass of the slider; C represents the damping ratio; K represents the stiffness; F represents the exciting force; y represents the displacement; represents the first derivative of displacement; represents the second derivative of displacement.
[0124] In some embodiments, the third building block 30 is further configured to:
[0125] According to the working condition data of the reciprocating piston pump and the wear mechanism model of the slider, the correlation relationship between the wear depth and the load is obtained;
[0126] The load is input into the dynamic model, and the simulated vibration signal and its characteristic trend corresponding to the wear size of the slider throughout its life cycle are iteratively calculated;
[0127] The simulated vibration signal and its characteristic trend are processed by using a long short-term memory network to construct a mapping relationship model between slider wear and vibration characteristics.
[0128] In some embodiments, the calibration module 40 is further configured to:
[0129] Keeping consistent with the box position generating the simulated vibration signal in the dynamic model, the health status information of the slider is obtained in real time through a monitoring device arranged on the actual box;
[0130] The digital twin model is dynamically calibrated according to the health status information.
[0131] In some embodiments, the calibration module 40 is further configured to:
[0132] Acquire measured vibration state data of the slider under different wear degrees, and extract energy characteristics from the measured vibration state data;
[0133] The digital twin model is dynamically calibrated according to the energy characteristics.
[0134] The above-mentioned reciprocating piston pump fault detection device corresponds to the reciprocating piston pump fault detection method in the above-mentioned embodiment. Therefore, based on the above-mentioned reciprocating piston pump fault detection method, a person skilled in the art can understand the specific implementation of the reciprocating piston pump fault detection device in the embodiment of the present application and its various variations. The reciprocating piston pump fault detection device will not be introduced in detail here. As long as a person skilled in the art implements the reciprocating piston pump fault detection method in the embodiment of the present application, the reciprocating piston pump fault detection device belongs to the scope of protection of the present application.
[0135] A third embodiment of the present application provides an electronic device, comprising at least a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned reciprocating piston pump fault detection method when executing the computer program on the memory.
[0136] In some embodiments, the processor executing the computer program may be a processing device including one or more general-purpose processing devices, such as a microprocessor, a central processing unit (CPU), a graphics processing unit (GPU), etc. More specifically, the processor may be a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a processor running other instruction sets, or a processor running a combination of instruction sets. The processor may also be one or more special-purpose processing devices, such as an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), a system on a chip (SoC), etc.
[0137] The memory may be a read-only memory (ROM), a random access memory (RAM), a phase-change random access memory (PRAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), an electrically erasable programmable read-only memory (EEPROM), other types of random access memory (RAM), a flash disk or other form of flash memory, a cache, a register, a static memory, a compact disk read-only memory (CD-ROM), a digital versatile disk (DVD) or other optical storage, a cassette or other magnetic storage device, or any other possible non-temporary medium used to store information or instructions that can be accessed by a computer device.
[0138] The electronic devices of the embodiments of the present application may include but are not limited to fixed terminal devices such as servers, desktop computers, digital TVs, etc., and mobile terminal devices such as vehicle-mounted devices (such as head-up display devices), handheld devices (such as mobile phones, tablet computers, etc.), wearable devices (such as smart watches, smart bracelets, etc.), etc.
[0139] The electronic device may include more or fewer components, for example, may further include a wireless communication interface, etc., or may combine certain components, or arrange the components differently.
[0140] A fourth embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned reciprocating piston pump fault detection method are implemented.
[0141] The computer-readable storage medium of the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.
[0142] In the embodiment of the present application, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any storage medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in combination with an instruction execution system, device or device. The program code contained on the storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.
[0143] The computer program of the embodiment of the present application can be organized into one or more computer executable components or modules. Any number and combination of such components or modules can be used to implement the various aspects of the present application. For example, the various aspects of the present application are not limited to the specific computer executable instructions or specific components or modules shown in the drawings and described herein. Other embodiments may include different computer executable instructions or components with more or less functions than those shown and described herein.
[0144] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.
[0145] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example of the energy acquisition device described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.
[0146] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.
[0147] In addition, the features of the embodiments shown in the drawings of the present application or the various embodiments mentioned in this specification are not necessarily understood as independent embodiments. Instead, each feature described in one example of an embodiment can be combined with one or more other desired features from other embodiments to produce other embodiments not described in words or with reference to the drawings.
[0148] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other to form a technical solution.
Claims
1. A method for detecting a fault of a reciprocating piston pump, characterized in that: include: Construct a slider wear mechanism model for a reciprocating piston pump slider; Construct a dynamic model of local wear extension of the slider; Constructing a digital twin model that maps the wear of the slider throughout its life cycle based on the slider wear mechanism model and the dynamic model; Dynamically calibrating the digital twin model through real-time monitored health status information of the slider to obtain a slider health monitoring model; The slider health monitoring model is used to perform fault detection and fault warning on the slider wear of the reciprocating piston pump.
2. The method according to claim 1, characterized in that Construct a slider wear mechanism model for a reciprocating piston pump slider, including: Conducting friction and wear tests on the sliding block friction pair material under different sliding speeds and loads to obtain the friction coefficient of the sliding block friction pair under different working conditions of the reciprocating piston pump; According to the friction coefficient of the slider friction pair under the different working conditions, the slider wear mechanism model is constructed based on the Archard wear theory.
3. The method according to claim 2, characterized in that The formula of the slider wear mechanism model is: Wherein, h is the wear depth; K is the friction coefficient, which is obtained through the friction and wear test of the slider friction pair; H is the material hardness; p is the contact pressure; v is the relative sliding velocity; m is the pressure index; and n is the velocity index.
4. The method according to claim 1, characterized in that: Construct a dynamic model of local wear extension of the slider, including: The correlation between the wear of the slider and the vibration of the box is established based on the Hertz contact theory; A dynamic model of local wear extension of the slider is constructed according to the correlation between the slider wear and the box vibration.
5. The method according to claim 4, characterized in that In the correlation between the wear of the slider and the vibration of the box, the calculation formula of the slider deformation and the load is: F=Kδ n Where F is the Hertzian contact force; K is the total contact stiffness; δ is the contact deformation; and n is the load-deformation coefficient.
6. The method according to claim 4, characterized in that The displacement excitation during the expansion of the local wear of the slider is expressed as: In the formula, M represents the mass of the slider; C represents the damping ratio; K represents the stiffness; F represents the exciting force; y represents the displacement; represents the first derivative of displacement; represents the second derivative of displacement.
7. The method according to claim 1, characterized in that A digital twin model for mapping the wear of the slider throughout its life cycle is constructed based on the slider wear mechanism model and the dynamic model, including: According to the working condition data of the reciprocating piston pump and the wear mechanism model of the slider, the correlation relationship between the wear depth and the load is obtained; The load is input into the dynamic model, and the simulated vibration signal and its characteristic trend corresponding to the wear size of the slider throughout its life cycle are iteratively calculated; The simulated vibration signal and its characteristic trend are processed by using a long short-term memory network to construct a mapping relationship model between slider wear and vibration characteristics.
8. The method according to claim 1, characterized in that The digital twin model is dynamically calibrated through the real-time monitored health status information of the slider to obtain a slider health monitoring model, including: Keeping consistent with the box position generating the simulated vibration signal in the dynamic model, the health status information of the slider is obtained in real time through a monitoring device arranged on the actual box; The digital twin model is dynamically calibrated according to the health status information.
9. The method according to claim 8, characterized in that Dynamically calibrating the digital twin model according to the health status information includes: Acquire measured vibration state data of the slider under different wear degrees, and extract energy characteristics from the measured vibration state data; The digital twin model is dynamically calibrated according to the energy characteristics.
10. A fault detection device for a reciprocating piston pump, characterized in that: include: A first building module is configured to build a slider wear mechanism model of a reciprocating piston pump slider; A second building module is configured to build a dynamic model of local wear extension of the slider; A third construction module is configured to construct a digital twin model mapping the wear of the slider throughout its life cycle based on the slider wear mechanism model and the dynamic model; A calibration module is configured to dynamically calibrate the digital twin model through real-time monitored health status information of the slider to obtain a slider health monitoring model; The fault detection module is configured to perform fault detection and fault warning on the slider wear of the reciprocating piston pump through the slider health monitoring model.