Valve diagnosis method and device, electronic equipment and storage medium

Abstract

The invention provides a valve diagnosis method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining to-be-detected sensing data of a to-be-detected valve, inputting the to-be-detected sensing data into a valve digital twinborn model, carrying out the abnormal recognition, obtaining a diagnosis result, and carrying out the diagnosis display based on the to-be-detected sensing data, the valve digital twinborn model and the diagnosis result. And / or a preset protection instruction is sent to the to-be-detected valve based on the diagnosis result so as to perform action protection on the to-be-detected valve, and the valve digital twin model is obtained by training based on historical sensing data and a constructed valve geometric physical model; according to the method, the historical sensing data and the valve geometric physical model are combined for abnormal recognition, the influence of physical factors such as different working conditions and valve materials on valve fault judgment can be eliminated or reduced, the fault recognition accuracy is improved, diagnosis visual display is carried out through the valve digital twinborn model, the intuition of valve diagnosis is improved, and the valve fault diagnosis accuracy is improved. And troubleshooting is facilitated.

Description

Technical Field

[0001] The present application relates to the field of valve diagnosis technology, and in particular to a valve diagnosis method, device, electronic equipment and storage medium. Background Art

[0002] Valves are widely used in the field of fluid system control. Due to the influence of the environment in which the valves are used and the wear and aging of the valves themselves during use, valves will inevitably fail, such as the valve cannot be completely closed and the medium leaks. Therefore, it is necessary to monitor the valves in real time and perform fault diagnosis in a timely manner.

[0003] Valve fault diagnosis refers to analyzing the valve operation status data, determining the possible fault type corresponding to the abnormal valve status, and taking corresponding protective measures. In related technologies, valve fault diagnosis is mainly carried out by establishing a corresponding mathematical model for a certain fault mechanism to perform data analysis, thereby determining whether such a fault has occurred, but it is easy to cause misjudgment of the fault or misjudgment of the fault type. Summary of the invention

[0004] The present invention provides a valve diagnosis method, device, electronic equipment and storage medium to solve the technical problem of inaccurate fault judgment in the above-mentioned valve fault diagnosis.

[0005] In one embodiment of the present application, the present application provides a valve diagnosis method, including: obtaining sensor data to be inspected of the valve to be inspected; inputting the sensor data to be inspected into the valve digital twin model for abnormality identification to obtain a diagnosis result; performing a diagnosis display based on the sensor data to be inspected, the valve digital twin model and the diagnosis result, and / or sending a preset protection instruction to the valve to be inspected based on the diagnosis result to perform action protection on the valve to be inspected; wherein, the valve digital twin model is trained based on historical sensor data and a constructed valve geometric physical model.

[0006] In one embodiment of the present application, a diagnostic display is performed based on the sensor data to be inspected, the valve digital twin model and the diagnostic result, including: displaying the operating status of the valve to be inspected based on the sensor data to be inspected and the valve digital twin model; and / or, if the diagnostic result is abnormal, and the abnormality duration period is greater than a preset number of acquisition cycles, then a fault display is performed based on the fault type corresponding to the sensor data to be inspected, the valve digital twin model and the diagnostic result, so as to provide a fault warning.

[0007] In one embodiment of the present application, the method for determining the valve digital twin model includes: obtaining historical sensor data and physical characteristic data of the valve to be inspected; constructing a valve geometric physical model based on the physical characteristic data; mapping the historical sensor data to the valve geometric physical model to obtain the valve digital twin model.

[0008] In one embodiment of the present application, the historical sensor data is mapped to the valve geometric physical model to obtain a valve digital twin model, including: marking the historical sensor data to obtain normal sensor data and abnormal sensor data; performing iterative training based on the comparison results of normal sensor data and abnormal sensor data to obtain a model mapping relationship in the valve digital twin model; wherein the model mapping relationship includes a fault type mapping relationship and a sensor data prediction mapping relationship.

[0009] In one embodiment of the present application, a valve geometric physical model is constructed based on the physical characteristic data, including: constructing a three-dimensional valve model of the valve to be inspected; importing the working capacity parameters of the valve to be inspected, and the material, density, and thermal expansion coefficient of each valve component into the valve three-dimensional model to obtain a valve geometric physical model; wherein the physical characteristic data includes the working capacity parameters, and the material, density, and thermal expansion coefficient of multiple valve components.

[0010] In one embodiment of the present application, the sensor data to be tested is input into the valve digital twin model for abnormality identification to obtain a diagnosis result, including: predicting the valve state based on the historical sensor data and the valve digital twin model to obtain predicted sensor data; comparing the predicted sensor data with the sensor data to be tested according to the valve digital twin model to obtain a diagnosis result; wherein, the training of the valve digital twin model is completed based on a long short-term memory network.

[0011] In one embodiment of the present application, the acquisition of the sensor data to be tested includes at least one of the following: collecting the medium pressure at the valve inlet, the medium pressure at the valve outlet and the internal pressure of the cylinder respectively through multiple pressure sensors; collecting the valve body temperature, the valve seat temperature and the medium temperature respectively through multiple temperature sensors; collecting the instantaneous flow rate and the cumulative flow rate of the medium through a flow sensor; collecting the valve operating opening through a valve actuator displacement sensor; collecting the valve action time and valve action frequency of the valve to be tested from fully open to fully closed and from fully closed to fully open through a valve action data measurement sensor; collecting the valve operation amplitude through a valve vibration data measurement sensor.

[0012] In one embodiment of the present application, the present application provides a valve diagnosis device, including: an acquisition module, used to acquire sensor data to be inspected of the valve to be inspected; a diagnosis module, used to input the sensor data to be inspected into the valve digital twin model for abnormality identification to obtain a diagnosis result; a display and protection module, used to perform a diagnosis display based on the sensor data to be inspected, the valve digital twin model and the diagnosis result, and / or send a preset protection instruction to the valve to be inspected based on the diagnosis result to perform action protection on the valve to be inspected; wherein, the valve digital twin model is trained based on historical sensor data and a constructed valve geometric and physical model.

[0013] In one embodiment of the present application, the present application provides an electronic device, which includes: one or more processors; a storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the electronic device implements the valve diagnosis method as described in any of the above embodiments.

[0014] In one embodiment of the present application, the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor of a computer, the computer executes the valve diagnosis method described in any one of the above embodiments.

[0015] Beneficial effects of the embodiments of the present invention: The present invention provides a valve diagnosis method, device, electronic device and storage medium. The embodiments of the present invention obtain a valve digital twin model through training of historical sensor data and a constructed valve geometric physical model, which identifies the abnormalities of the sensor data to be tested, eliminates or reduces the influence of different working conditions and physical factors such as the valve's own material on the judgment of valve fault characteristics, and improves the accuracy of valve fault identification; and, through the valve digital twin model for diagnostic visualization display, the intuitiveness of the valve diagnosis process is improved to facilitate troubleshooting.

[0016] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0018] Figure 1 A schematic diagram showing an exemplary system architecture to which the technical solution of the embodiments of the present application can be applied;

[0019] Figure 2 A schematic flow chart of a valve diagnosis method according to an embodiment of the present application is shown;

[0020] Figure 3 A schematic diagram of constructing a valve digital twin model according to an embodiment of the present application is shown;

[0021] Figure 4 A schematic diagram of a flow chart for implementing valve fault diagnosis according to an embodiment of the present application is shown;

[0022] Figure 5 A block diagram of a valve fault diagnosis system according to an embodiment of the present application is shown;

[0023] Figure 6 A block diagram of a valve diagnostic device according to an embodiment of the present application is shown;

[0024] Figure 7 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0025] The following describes the embodiments of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0026] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present application, and thus the drawings only show components related to the present application rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed at will, and the component layout may also be more complicated.

[0027] In the following description, a large number of details are discussed to provide a more thorough explanation of the embodiments of the present application. However, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present application difficult to understand.

[0028] See also Figure 1 , Figure 1 A schematic diagram of an exemplary system architecture to which the technical solution of the embodiment of the present application can be applied is shown. Figure 1As shown, the system architecture may include a computer device 101, a valve to be inspected 102, and a valve sensor 103. The computer device 101 may be at least one of a general-purpose computer and a neural network computer, etc. The number of valve sensors 103 may be multiple, and the valve sensor is used to collect sensor data to be inspected when the valve to be inspected 102 is running, and transmit it to the computer device 101, so as to diagnose the valve to be inspected 102.

[0029] Exemplarily, the computer device 101 obtains the sensor data to be inspected of the valve to be inspected; the sensor data to be inspected is input into the valve digital twin model for abnormality identification to obtain a diagnosis result; if the diagnosis result is abnormal, and the abnormality duration period is greater than the preset number of acquisition cycles, a diagnosis display is performed based on the sensor data to be inspected, the valve digital twin model and the diagnosis result; wherein the valve digital twin model is trained based on historical sensor data and a constructed valve geometric physical model.

[0030] In the related art, valve fault analysis is performed through data analysis of mathematical models, which can easily lead to misjudgment of the fault or misjudgment of the fault type.

[0031] In order to solve the above technical problems, the present application provides a valve diagnosis method, device, electronic device and storage medium. The implementation details of the technical solution of the embodiment of the present application are elaborated in detail below.

[0032] See also Figure 2 , Figure 2 FIG. 2 shows a flow chart of a valve diagnosis method according to an embodiment of the present application. Figure 2 As shown, in an exemplary embodiment, the valve diagnosis method includes at least steps S210 to S230, which are described in detail as follows:

[0033] Step S210, obtaining sensor data of the valve to be inspected.

[0034] In one embodiment of the present application, the acquisition of the sensor data to be tested includes at least one of the following: collecting the medium pressure at the valve inlet, the medium pressure at the valve outlet and the internal pressure of the cylinder respectively through multiple pressure sensors; collecting the valve body temperature, the valve seat temperature and the medium temperature respectively through multiple temperature sensors; collecting the instantaneous flow rate and the cumulative flow rate of the medium through a flow sensor; collecting the valve operating opening through a valve actuator displacement sensor; collecting the valve action time and valve action frequency of the valve to be tested from fully open to fully closed and from fully closed to fully open through a valve action data measurement sensor; collecting the valve operation amplitude through a valve vibration data measurement sensor.

[0035] In one embodiment of the present application, types of valve sensors include pressure sensors, temperature sensors, flow sensors, valve actuator displacement sensors, valve motion data measurement sensors, and valve vibration data measurement sensors.

[0036] In one embodiment of the present application, the sensing data to be inspected is collected in real time from the physical valve to be inspected through valve sensing, that is, the dynamic operation data of the valve to be inspected is obtained.

[0037] In one embodiment of the present application, the medium pressure at the valve inlet will affect the valve sealing; the medium pressure at the valve outlet determines the pressure difference before and after the valve, and there are requirements for the pressure difference before and after the valve in specific applications; whether the internal pressure of the cylinder is normal will affect the valve control accuracy and stability.

[0038] In one embodiment of the present application, the valve body temperature of the valve to be inspected is different under different loads. If the heat dissipation is not up to standard, the valve body temperature will be too high, resulting in valve body damage; the valve seat temperature will affect the sealing performance of the seal; the medium temperature tests whether the valve to be inspected is suitable for the medium.

[0039] In one embodiment of the present application, the instantaneous flow rate of the medium and the cumulative flow rate of the medium can facilitate the statistics of the production plan.

[0040] In one embodiment of the present application, the vibration signal generated when the valve is in operation can also reflect the health status of the valve to be inspected.

[0041] In one embodiment of the present application, the sensor data to be inspected may also include data collected by other types of sensors or valve sensors located at other positions of the valve to be inspected.

[0042] Step S220: input the sensor data to be tested into the valve digital twin model for abnormality identification to obtain a diagnosis result.

[0043] Among them, the valve digital twin model is trained based on historical sensor data and the constructed valve geometric physical model.

[0044] In one embodiment of the present application, the method for determining the valve digital twin model includes: obtaining historical sensor data and physical characteristic data of the valve to be inspected; constructing a valve geometric physical model based on the physical characteristic data; mapping the historical sensor data into the valve geometric physical model to obtain the valve digital twin model.

[0045] In one embodiment of the present application, there is a corresponding relationship between the type of historical sensor data and the type of sensor data to be inspected, that is, historical sensor data is collected from the physical valve to be inspected through the valve sensor, that is, the valve dynamic operation data recorded in history is obtained.

[0046] In one embodiment of the present application, a valve geometric physical model is constructed based on physical characteristic data, including: constructing a three-dimensional valve model of the valve to be inspected; importing the working capacity parameters of the valve to be inspected, as well as the material, density, and thermal expansion coefficient of each valve component into the valve three-dimensional model to obtain a valve geometric physical model; wherein the physical characteristic data includes the working capacity parameters, and the material, density, and thermal expansion coefficient of multiple valve components.

[0047] In one embodiment of the present application, historical sensor data is mapped to a valve geometric physical model to obtain a valve digital twin model, including: marking the historical sensor data to obtain normal sensor data and abnormal sensor data; performing iterative training based on the comparison results of the normal sensor data and the abnormal sensor data to obtain a model mapping relationship in the valve digital twin model; wherein the model mapping relationship includes a fault type mapping relationship and a sensor data prediction mapping relationship.

[0048] In one embodiment of the present application, the fault type mapping relationship is used to characterize the determination of the fault type based on the difference between the predicted sensor data and the sensor data to be tested.

[0049] In one embodiment of the present application, the sensor data prediction mapping relationship is used to characterize the valve state prediction based on the historical sensor data to obtain the predicted sensor data.

[0050] In one embodiment of the present application, before iterative training is performed based on the comparison results of normal sensor data and abnormal sensor data, the method further includes: filtering the historical sensor data to remove spikes and noise interference.

[0051] In one embodiment of the present application, taking into account the generalization of model training and the temporal nature of valve dynamic operation data, a long short-term memory network (LSTM) algorithm is used to fuse dynamic data with a physical model.

[0052] In one embodiment of the present application, the parameters of the LSTM algorithm need to be set, such as the input dimension, the number of hidden layers, the number of neurons in each layer, the calculation formula of the loss function, the optimizer type, etc. The LSTM algorithm trains and iterates the valve dynamic operation data of multi-dimensional historical records to automatically capture the interrelationships in a large amount of data.

[0053] In one embodiment of the present application, see Figure 3 , Figure 3 FIG. 1 shows a schematic diagram of constructing a valve digital twin model according to an embodiment of the present application. Figure 3As shown, historical sensor data is collected from the physical valve to be inspected through various valve sensors, such as pressure sensors, temperature sensors, flow sensors, valve actuator displacement sensors, valve action data measurement sensors and valve vibration data measurement sensors; signal conditioning is to filter the collected data to achieve multi-dimensional data fusion; the fused data is mapped to the virtual valve geometric physical model to obtain the valve digital twin model.

[0054] In one embodiment of the present application, the sensor data to be tested is input into the valve digital twin model for abnormality identification to obtain a diagnosis result, including: predicting the valve state based on historical sensor data and the valve digital twin model to obtain predicted sensor data; comparing the predicted sensor data with the sensor data to be tested according to the valve digital twin model to obtain a diagnosis result; wherein, the training of the valve digital twin model is completed based on a long short-term memory network.

[0055] In one embodiment of the present application, after the model training is completed, the output of the LSTM can be compared with the valve dynamic operation data of the valve to be inspected that is actually detected to achieve fault judgment and early warning of the valve to be inspected.

[0056] Step S230, performing a diagnosis display based on the sensor data to be inspected, the valve digital twin model and the diagnosis result, and / or sending a preset protection instruction to the valve to be inspected based on the diagnosis result to perform action protection on the valve to be inspected.

[0057] In one embodiment of the present application, a diagnostic display is performed based on the sensor data to be inspected, the valve digital twin model and the diagnostic result, including: displaying the operating status of the valve to be inspected based on the sensor data to be inspected and the valve digital twin model; and / or, if the diagnostic result is abnormal, and the abnormality duration period is greater than a preset number of acquisition cycles, then a fault display is performed based on the fault type corresponding to the sensor data to be inspected, the valve digital twin model and the diagnostic result, so as to provide a fault warning.

[0058] In one embodiment of the present application, the operating status display can be realized by converting the sensor data to be detected into a two-dimensional graph.

[0059] In one embodiment of the present application, there is a corresponding relationship between the fault type and the fault position of the valve to be inspected so as to display the fault.

[0060] In one embodiment of the present application, after obtaining the diagnosis result, it also includes: if the diagnosis result is abnormal, and the abnormal duration period is greater than the preset number of acquisition cycles, a preset protection instruction is sent to the valve to be inspected based on the identified fault type, and fault warning information is generated; if the diagnosis result is normal, new sensor data to be inspected is continued to be obtained for abnormality identification.

[0061] In one embodiment of the present application, the preset number of acquisition cycles can be set to 3.

[0062] In one embodiment of the present application, if there is no abnormality, the real-time monitoring state is maintained; if the occurrence of abnormal data is identified, the abnormal data maintenance time is timed. If it does not exceed three acquisition cycles, it is considered to be an interference signal. If the collected abnormal data exceeds three acquisition cycles, it is considered that the valve is faulty, and a protection action instruction corresponding to the valve fault is issued, and a warning is issued to the relevant staff, and the fault status is sent to the visualization module for display. The process of delayed fault judgment on the collected abnormal data can further avoid misjudgment of faults.

[0063] In one embodiment of the present application, see Figure 4 , Figure 4 FIG. 2 shows a flow chart of implementing valve fault diagnosis according to an embodiment of the present application. Figure 4 As shown, feature mapping and multi-dimensional data fusion are performed through the collected historical sensor data and the constructed valve geometric physical model, so as to generate a valve digital twin model through the LSTM algorithm; the sensor data to be inspected is collected in real time through the valve sensor, and the operating status of the valve to be inspected is displayed in the visualization module based on the valve digital twin model; the sensor data to be inspected is identified for abnormalities through the valve digital twin model; if no abnormality is identified, new sensor data to be inspected is continued to be collected; if an abnormality is identified, the abnormal maintenance time is counted by a timer. If the abnormal maintenance time is greater than 3 acquisition cycles, the abnormal maintenance time is reset to zero, and a protection action instruction corresponding to the fault type is issued, and the fault is displayed in the visualization module, and fault warning information is generated to warn the staff; if the abnormal maintenance time is less than or equal to 3 acquisition cycles, new sensor data to be inspected is continued to be collected for abnormal identification. The present application can utilize supervised learning to combine the valve geometry physical model with the valve dynamic data, thereby eliminating or reducing the impact of different operating conditions and physical factors such as the valve's own material on the judgment of valve fault characteristics, thereby improving the accuracy of valve fault identification; and, in the process of processing abnormal data, by delaying judgment processing, it is possible to eliminate the phenomenon of fault misjudgment caused by abnormal data due to electromagnetic interference or long signal transmission distance, thereby improving the reliability of valve fault identification.

[0064] In one embodiment of the present application, the visualization module displays the operating status and faults based on the valve digital twin model.

[0065] In one embodiment of the present application, see Figure 5 , Figure 5 FIG. 1 is a block diagram of a valve fault diagnosis system according to an embodiment of the present application. Figure 5As shown, the valve fault diagnosis system includes a valve digital twin model, data storage, feedback control, a visualization module and a communication interface; the valve digital twin model includes valve operation data acquisition, a valve geometric physical model, and a valve fault diagnosis and early warning module; wherein, valve operation data acquisition is data acquisition through valve sensors, including historical sensor data and sensor data to be inspected; the communication interface is used for external communication with the valve fault diagnosis and early warning module, so that the parameters of the module can be manually modified, or the valve to be inspected can be manually intervened and controlled; the data storage function is used to store the historical sensor data, fault data and external information input by the communication interface of the valve to be inspected, so as to train and update the valve fault diagnosis and early warning module; the feedback control unit is used to send a control signal when a valve fault is detected or predicted, so as to take protective action measures for the valve to be inspected; the visualization module displays the valve operation status and fault status on the screen in real time, and can also serve as a warning if a fault occurs.

[0066] See also Figure 6 , Figure 6 A block diagram of a valve diagnostic device according to an embodiment of the present application is shown. The device can be applied to Figure 1 The implementation environment shown in the figure is specifically configured in the computer device 101. The device can also be applied to other exemplary implementation environments and specifically configured in other devices. This embodiment does not limit the implementation environment to which the device is applied.

[0067] like Figure 6 As shown, a valve diagnosis device 600 according to an embodiment of the present application includes: an acquisition module 601 , a diagnosis module 602 and a display protection module 603 .

[0068] Wherein, the acquisition module 601 is used to acquire the sensor data to be inspected of the valve to be inspected;

[0069] The diagnostic module 602 is used to input the sensor data to be tested into the valve digital twin model for abnormality identification and obtain a diagnostic result;

[0070] A display protection module 603 is used to perform a diagnosis display based on the sensor data to be inspected, the valve digital twin model and the diagnosis result, and / or send a preset protection instruction to the valve to be inspected based on the diagnosis result to perform action protection on the valve to be inspected;

[0071] Among them, the valve digital twin model is trained based on historical sensor data and the constructed valve geometric physical model.

[0072] It should be noted that the valve diagnostic device provided in the above embodiment and the valve diagnostic method provided in the above embodiment belong to the same concept, wherein the specific manner in which each module and unit performs the operation has been described in detail in the method embodiment, and will not be repeated here. In practical applications, the valve diagnostic device provided in the above embodiment can allocate the above functions to different functional modules as needed, that is, divide the internal structure of the device into different functional modules to complete all or part of the functions described above, and this is not limited here.

[0073] An embodiment of the present application also provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, when the one or more programs are executed by one or more processors, the electronic device implements the valve diagnosis method provided in the above-mentioned embodiments.

[0074] See also Figure 7 , Figure 7 The structure diagram of the computer system suitable for implementing the electronic device of the embodiment of the present application is shown. It should be noted that: Figure 7 The computer system 700 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0075] like Figure 7 As shown, the computer system 700 includes a central processing unit (CPU) 701, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 702 or the program loaded from the storage part 708 to the random access memory (RAM) 703, such as executing the method in the above embodiment. In the RAM 703, various programs and data required for system operation are also stored. The CPU 701, the ROM 702 and the RAM 703 are connected to each other through the bus 704. The input / output (I / O) interface 705 is also connected to the bus 704.

[0076] The following components are connected to the I / O interface 705: an input section 706 including a keyboard, a mouse, etc.; an output section 707 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 710 as needed so that a computer program read therefrom is installed into the storage section 708 as needed.

[0077] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 709, and / or installed from a removable medium 711. When the computer program is executed by a central processing unit (CPU) 701, various functions defined in the system of the present application are executed.

[0078] It should be noted that the computer-readable medium shown in the embodiment of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, 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), a 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. 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, wherein a computer-readable computer program is carried. This propagated data signal can take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. A computer program contained on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0079] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0080] The units involved in the embodiments described in the present application can be implemented by software or by hardware, and the units described can also be set in a processor. Among them, the names of these units do not constitute a limitation on the units themselves under certain circumstances. Therefore, the technical solution according to the implementation mode of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including a number of instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute a method according to the implementation mode of the present application.

[0081] Another aspect of the present application provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor of a computer, the computer executes the valve diagnosis method provided in each of the above embodiments. The computer-readable storage medium may be included in the electronic device described in the above embodiments, or may exist independently without being assembled into the electronic device.

[0082] In the above embodiments, unless otherwise specified, by using serial numbers such as "first" and "second" to describe common objects, it only means that they refer to different instances of the same object, rather than indicating that the objects being described must adopt a given order, whether in time, space, sorting or any other way.

[0083] The above embodiments are merely illustrative of the principles and effects of the present application, and are not intended to limit the present application. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed in the present application shall still be covered by the claims of the present application.

Claims

1. A valve diagnosis method, characterized in that: The method comprises: Acquire the sensor data of the valve to be inspected; Inputting the sensor data to be inspected into the valve digital twin model for abnormality identification to obtain a diagnosis result; Performing a diagnostic display based on the sensor data to be inspected, the valve digital twin model and the diagnostic result, and / or sending a preset protection instruction to the valve to be inspected based on the diagnostic result to perform action protection on the valve to be inspected; Among them, the valve digital twin model is trained based on historical sensor data and a constructed valve geometric physical model.

2. The valve diagnosis method according to claim 1, characterized in that: Performing a diagnosis display based on the sensor data to be inspected, the valve digital twin model and the diagnosis result, including: Displaying the operating status of the valve to be inspected based on the sensor data to be inspected and the valve digital twin model; and / or, If the diagnosis result is abnormal, and the abnormal duration period is greater than the preset number of acquisition cycles, a fault display is performed based on the sensor data to be tested, the valve digital twin model and the fault type corresponding to the diagnosis result to provide a fault warning.

3. The valve diagnosis method according to claim 1, characterized in that: The method for determining the valve digital twin model includes: Obtain historical sensor data and physical characteristic data of the valve to be inspected; Constructing a valve geometric physical model according to the physical characteristic data; The historical sensor data is mapped to the valve geometric physical model to obtain a valve digital twin model.

4. The valve diagnosis method according to claim 3, characterized in that: Mapping the historical sensor data to the valve geometric physical model to obtain a valve digital twin model, including: Marking the historical sensor data to obtain normal sensor data and abnormal sensor data; Iterative training is performed based on the comparison results of normal sensor data and abnormal sensor data to obtain the model mapping relationship in the valve digital twin model; The model mapping relationship includes a fault type mapping relationship and a sensor data prediction mapping relationship.

5. The valve diagnosis method according to claim 3, characterized in that: Constructing a valve geometric physical model according to the physical characteristic data, including: Constructing a three-dimensional valve model of the valve to be inspected; Importing the working capacity parameters of the valve to be inspected, as well as the material, density, and thermal expansion coefficient of each valve component into the three-dimensional model of the valve to obtain a valve geometric physical model; The physical characteristic data include the working capacity parameters, and the material, density, and thermal expansion coefficient of multiple valve components.

6. The valve diagnosis method according to any one of claims 1 to 5, characterized in that: The sensor data to be tested is input into the valve digital twin model for abnormality identification to obtain a diagnosis result, including: Predicting a valve state based on the historical sensor data and the valve digital twin model to obtain predicted sensor data; Comparing the predicted sensor data with the sensor data to be tested according to the valve digital twin model to obtain a diagnosis result; Among them, the training of the valve digital twin model is completed based on the long short-term memory network.

7. The valve diagnosis method according to any one of claims 1 to 5, characterized in that: The acquisition of the sensor data to be inspected includes at least one of the following: The medium pressure at the valve inlet, the medium pressure at the valve outlet and the internal pressure of the cylinder are collected respectively through multiple pressure sensors; The valve body temperature, valve seat temperature and medium temperature are collected respectively through multiple temperature sensors; The instantaneous flow rate and the accumulated flow rate of the medium are collected through the flow sensor; The valve operating opening is collected through the valve actuator displacement sensor; The valve action data measurement sensor collects the valve action time and valve action frequency from fully open to fully closed and from fully closed to fully open of the valve to be inspected; The valve operation amplitude is collected through the valve vibration data measurement sensor.

8. A valve diagnostic device, characterized in that: The device comprises: An acquisition module, used for acquiring sensor data to be inspected of the valve to be inspected; A diagnostic module, used for inputting the sensor data to be tested into the valve digital twin model for abnormality identification to obtain a diagnostic result; A display protection module, used for performing a diagnosis display based on the sensor data to be inspected, the valve digital twin model and the diagnosis result, and / or sending a preset protection instruction to the valve to be inspected based on the diagnosis result, so as to perform action protection on the valve to be inspected; Among them, the valve digital twin model is trained based on historical sensor data and a constructed valve geometric physical model.

9. An electronic device, characterized in that: The electronic device comprises: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the electronic device to implement the valve diagnosis method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor of a computer, the computer is caused to execute the valve diagnosis method according to any one of claims 1 to 7.

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