Valve flow prediction method and system based on valve pressure difference

Abstract

The invention discloses a valve flow prediction method based on valve pressure difference. The method comprises the following steps: S1, valve state monitoring and data acquisition; s2, flow prediction; s3, performing real-time health assessment and adjustment; s4, performing anomaly detection and early warning; and S5, data recording and feedback optimization. According to the method, the valve abrasion and aging are introduced into the algorithm to serve as influence factors, the flow is predicted, the flow prediction model can be adjusted under the valve abrasion and aging condition, flow prediction is more accurate, and adjustment errors or system faults caused by prediction errors are reduced. Meanwhile, by introducing a valve health monitoring and flow prediction model and an anomaly detection and early warning mechanism, the flow prediction model can be adjusted under the condition that the valve is abraded or aged, so that flow prediction is more accurate, and adjustment errors or system faults caused by prediction errors are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of valves, and in particular to a valve flow prediction method based on valve pressure difference and a system thereof. Background Art

[0002] As a key device in fluid control systems, valves are widely used in industries such as petroleum, natural gas, chemical industry, and electric power. They are responsible for regulating and controlling important parameters such as fluid flow, pressure, and temperature in pipelines. The performance of valves directly affects the operating efficiency, safety, and energy consumption of the system. Therefore, accurately predicting the flow changes and working conditions of valves is an important means to ensure equipment reliability and stable system operation.

[0003] Traditional valve flow prediction methods are usually based on sensor data such as flow, pressure difference, temperature, etc., and are calculated through mathematical models. These methods mostly rely on current operating parameters and ignore the aging and wear effects of valves during long-term use, resulting in low accuracy of prediction results when the valves are aged or worn severely, making it difficult to meet the long-term stability and accuracy requirements in actual applications. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] In a first aspect, an embodiment of the present invention provides a valve flow prediction method based on valve pressure difference, comprising:

[0007] S1. Valve status monitoring and data collection: 1.1. Install multiple sensors on the valve to monitor the working status of the valve and related working condition data in real time; 1.2. Collect valve data in real time and store it in the database;

[0008] S2. Flow prediction: Flow prediction is performed through a flow prediction model based on valve pressure difference, flow rate, and valve aging and wear;

[0009] S3. Real-time health assessment and adjustment: 3.1. Evaluate the aging and wear of the valve by real-time monitoring of the working status of the valve; 3.2. Dynamically adjust the parameters of the prediction model based on the real-time health assessment results;

[0010] S4. Abnormal detection and early warning: 4.1. Set the tolerance range of valve flow and pressure difference, and detect abnormal conditions in flow prediction by comparing real-time monitoring with predicted values; 4.2. If abnormalities are found, trigger the early warning mechanism, immediately sound an alarm and send a warning signal to the operator;

[0011] S5. Data recording and feedback optimization: The deviation between each prediction and actual flow is recorded to provide data support for subsequent algorithm optimization.

[0012] As a preferred solution of the valve flow prediction method based on valve pressure difference described in the present invention, the flow prediction model algorithm is specifically as follows:

[0013]

[0014] Among them: F flow (t) represents the basic part of flow calculation, including the influence of pressure difference, aging wear degree and flow state; F wear (t) represents the long-term influence of the accumulated effect of wear over time on flow changes; ∈(t) is the external disturbance factor, which represents the impact of environmental changes on the fluid.

[0015] As a preferred solution of the valve flow prediction method based on valve pressure difference described in the present invention, wherein: low (t) The specific calculation formula is as follows:

[0016] F flow (t)=μ·ΔP(t)·σ(ω(t))·f1(ΔP(t),t)

[0017] Where: μ is a fluid-related constant; ΔP(t) is the valve pressure difference at the current moment; σ(ω(t)) is the wear coefficient, which reflects the impact of valve wear on flow and changes with the increase of wear degree ω(t); f1(ΔP(t), t) is a nonlinear function that describes the change of valve flow, taking into account the complex relationship between pressure difference and time.

[0018] As a preferred solution of the valve flow prediction method based on valve pressure difference described in the present invention,

[0019] Where: F wear (t) The specific calculation formula is as follows:

[0020]

[0021] Where: αe -β(t-τ) Used to describe the attenuation effect of wear, where α is the initial coefficient of wear rate and β represents the rate of wear attenuation; It is used to describe the influence of wear degree on flow rate, γ is the sensitivity of wear to flow rate, and ω(τ) is the wear degree at historical moment τ.

[0022] As a preferred solution of the valve flow prediction method based on valve pressure difference described in the present invention, the mathematical formula of the early warning mechanism is specifically expressed as follows:

[0023]

[0024] Where: Alert(t) indicates whether the warning is triggered at time t, 1 for triggering and 0 for not triggering; E(t) is the flow error; E threshold It is the preset error threshold. If it exceeds this value, an early warning will be triggered.

[0025] As a preferred solution of the valve flow prediction method based on valve pressure difference described in the present invention, the specific calculation formula of E(t) is as follows:

[0026] E(t=|Q actual (t)-Q(t)|

[0027] Where: Q actual (t) is the actual traffic collected in real time.

[0028] As a preferred solution of the valve flow prediction method based on valve pressure difference described in the present invention, the early warning mechanism can be directly triggered when detecting the following situations:

[0029]

[0030] σ(ω(t))>σ threshold

[0031] Where: ΔP min is the minimum preset value of the pressure difference; ΔP max is the maximum preset value of the pressure difference; σ threshold The preset value for the aging wear coefficient.

[0032] In a second aspect, an embodiment of the present invention provides a valve flow prediction system based on valve pressure difference, comprising:

[0033] Data acquisition module: The data collected by each sensor is transmitted to the data acquisition module through the interface for real-time processing and caching. After the data format is standardized, it is sent to downstream processing;

[0034] Data transmission and storage module: including: data transmission unit: responsible for transmitting data from each sensor to the central database; data storage unit: storing the collected data and historical information;

[0035] Analysis and prediction module: including: flow prediction unit: predicts flow changes under different working conditions through data input; health assessment unit: evaluates valve wear and aging according to the working status of the valve; algorithm optimization unit: optimizes the algorithm according to the evaluation of the health assessment unit;

[0036] Abnormal warning module: including: abnormal detection unit: real-time monitoring, detecting abnormalities by comparing with predicted values; warning unit: once the abnormal detection unit finds that the valve state is abnormal and the deviation in flow prediction exceeds the set threshold, it will send a warning message.

[0037] In a third aspect, an embodiment of the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of a valve flow prediction method based on valve pressure difference as described in the first aspect of the present invention is implemented.

[0038] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of a valve flow prediction method based on valve pressure difference as described in the first aspect of the present invention is implemented.

[0039] Beneficial effects of the present invention:

[0040] The present invention predicts the flow rate by introducing valve wear and aging as an influencing factor in the algorithm, and can adjust the flow prediction model when the valve is worn and aged, so that the flow prediction is more accurate, and the adjustment error or system failure caused by the prediction error is reduced. At the same time, by introducing valve health monitoring, flow prediction model and abnormal detection and early warning mechanism, the flow prediction model can be adjusted when the valve is worn or aged, so that the flow prediction is more accurate, and the adjustment error or system failure caused by the prediction error is reduced. The high accuracy and long-term stability of the flow prediction are achieved, the safety and reliability of the valve operation are improved, and an intelligent equipment monitoring and early warning system is provided. The equipment maintenance and management efficiency is optimized, and reliable support is provided for the industrial production system. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0042] Figure 1 A method flow chart of a valve flow prediction method based on valve pressure difference proposed by the present invention;

[0043] Figure 2 This is a system architecture diagram of a valve flow prediction system based on valve pressure difference proposed by the present invention. DETAILED DESCRIPTION

[0044] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0045] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0046] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0047] Reference Figure 1-2 The present invention provides a valve flow prediction method based on valve pressure difference, comprising:

[0048] S1. Valve status monitoring and data collection: 1.1. Install multiple sensors on the valve to monitor the working status of the valve and related working condition data in real time. The sensors include differential pressure sensor, temperature sensor, and flow sensor; 1.2. Collect valve data in real time, including differential pressure, flow, temperature, working time, etc., and store them in the database for subsequent analysis;

[0049] S2. Flow prediction: Flow prediction is performed through a flow prediction model based on valve pressure difference, flow rate, and valve aging and wear;

[0050] S3. Real-time health assessment and adjustment: 3.1. Evaluate the aging and wear of the valve by real-time monitoring of the working status of the valve; 3.2. Dynamically adjust the parameters of the prediction model based on the real-time health assessment results;

[0051] S4. Abnormal detection and early warning: 4.1. Set the tolerance range of valve flow and pressure difference, and detect abnormal conditions in flow prediction by comparing real-time monitoring with predicted values; 4.2. If abnormalities are found, trigger the early warning mechanism, immediately sound an alarm and send a warning signal to the operator;

[0052] S5. Data recording and feedback optimization: The deviation between each prediction and actual flow is recorded to provide data support for subsequent algorithm optimization.

[0053] The traffic prediction model algorithm is as follows:

[0054]

[0055] Among them: F flow (t) represents the basic part of flow calculation, including the influence of pressure difference, aging wear degree and flow state; F wear (t) represents the long-term impact of the accumulated effect of wear over time on flow changes; ∈(t) is the external disturbance factor, which represents the impact of environmental changes on the fluid, such as temperature and fluid density. This formula comprehensively considers multiple factors such as valve aging wear effect, pressure difference, flow rate and external environmental factors, and can more accurately reflect the impact of valve wear on flow prediction.

[0056] Furthermore, F flow (t) The specific calculation formula is as follows:

[0057] F flow (t)=μ·ΔP(t)·σ(ω(t))·f1(ΔP(t),t)

[0058] Where: μ is a fluid-related constant; ΔP(t) is the valve pressure difference at the current moment; σ(ω(t)) is the wear coefficient, which reflects the impact of valve wear on flow, and changes with the increase of wear degree ω(t), and the value range of ω(t) is 0 to 1; f1(ΔP(t), t) is a nonlinear function that describes the change of valve flow, considering the complex relationship between pressure difference and time. This formula is used for the basic part of flow calculation and is affected by pressure difference and aging wear degree.

[0059] Furthermore, F wear (t) The specific calculation formula is as follows:

[0060]

[0061] Where: αe -β(t-τ) Used to describe the attenuation effect of wear, where α is the initial coefficient of wear rate and β represents the rate of wear attenuation; It is used to describe the impact of wear on flow. γ is the sensitivity of wear to flow. ω(τ) is the wear at the historical moment τ. This part is used to represent the cumulative effect of wear over time and its long-term impact on flow.

[0062] Furthermore, the mathematical formula of the early warning mechanism is expressed as follows:

[0063]

[0064] Where: Alert(t) indicates whether the warning is triggered at time t, 1 for triggering and 0 for not triggering; E(t) is the flow error; E threshold It is a preset error threshold. If it exceeds this value, an early warning will be triggered. The traffic flow is monitored in real time through this early warning mechanism, and the early warning mechanism can be triggered in time when an abnormality occurs.

[0065] Furthermore, the specific calculation formula of E(t) is as follows:

[0066] E(t=|Q actual (t)-Q(t)|

[0067] Where: Q actual (t) is the actual flow collected in real time. By calculating the difference between the actual flow and the predicted flow, it is determined whether it exceeds the predetermined threshold and whether it is abnormal.

[0068] Furthermore, the early warning mechanism can be directly triggered when it detects the following situations:

[0069]

[0070] σ(ω(t))>σ threshold

[0071] Where: ΔP min is the minimum preset value of the pressure difference; ΔP max is the maximum preset value of the pressure difference; σ threshold It is the preset value of the aging wear coefficient. When the pressure difference suddenly becomes abnormal, for example, it is far beyond the expected range, even if the wear coefficient and other factors have not changed significantly, the early warning mechanism will be triggered. When the wear degree increases sharply and exceeds the preset value, it indicates that the valve is excessively worn, which will also trigger the early warning mechanism.

[0072] This embodiment also provides a valve flow prediction system based on valve pressure difference, including:

[0073] Data acquisition module: The data collected by each sensor is transmitted to the data acquisition module through the interface for real-time processing and caching. After the data format is standardized, it is sent to downstream processing;

[0074] Data transmission and storage module: including: data transmission unit: responsible for transmitting data from each sensor to the central database; data storage unit: storing the collected data and historical information;

[0075] Analysis and prediction module: including: flow prediction unit: predict the flow change under different working conditions through data input; health assessment unit: evaluate the wear and aging of the valve according to the working status of the valve; algorithm optimization unit: optimize the algorithm according to the evaluation of the health assessment unit;

[0076] Abnormal warning module: including: abnormal detection unit: real-time monitoring, detecting abnormalities by comparing with predicted values; warning unit: once the abnormal detection unit finds that the valve state is abnormal and the deviation in flow prediction exceeds the set threshold, it will send a warning message.

[0077] This embodiment also provides a computer device, which is suitable for a valve flow prediction method based on valve pressure difference, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement a valve flow prediction method based on valve pressure difference as proposed in the above embodiment.

[0078] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0079] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, a valve flow prediction method based on valve pressure difference as proposed in the above embodiment is implemented; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0080] In summary, the present invention predicts the flow rate by introducing valve wear and aging as an influencing factor in the algorithm, and can adjust the flow prediction model when the valve is worn and aged, so that the flow prediction is more accurate, and the adjustment error or system failure caused by the prediction error is reduced. At the same time, by introducing valve health monitoring, flow prediction model and abnormal detection and early warning mechanism, the flow prediction model can be adjusted when the valve is worn or aged, so that the flow prediction is more accurate, and the adjustment error or system failure caused by the prediction error is reduced. The high accuracy and long-term stability of the flow prediction are achieved, the safety and reliability of the valve operation are improved, and an intelligent equipment monitoring and early warning system is provided. The equipment maintenance and management efficiency is optimized, and reliable support is provided for the industrial production system.

[0081] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A valve flow prediction method based on valve pressure difference, characterized in that: include: S1. Valve status monitoring and data collection: 1.

1. Install multiple sensors on the valve to monitor the working status of the valve and related working condition data in real time; 1.

2. Collect valve data in real time and store it in the database; S2. Flow prediction: Flow prediction is performed through a flow prediction model based on valve pressure difference, flow rate, and valve aging and wear; S3. Real-time health assessment and adjustment: 3.

1. Evaluate the aging and wear of the valve by real-time monitoring of the working status of the valve; 3.

2. Dynamically adjust the parameters of the prediction model based on the real-time health assessment results; S4. Abnormal detection and early warning: 4.

1. Set the tolerance range of valve flow and pressure difference, and detect abnormal conditions in flow prediction by comparing real-time monitoring with predicted values; 4.

2. If abnormalities are found, trigger the early warning mechanism, immediately sound an alarm and send a warning signal to the operator; S5. Data recording and feedback optimization: The deviation between each prediction and actual flow is recorded to provide data support for subsequent algorithm optimization.

2. A valve flow prediction method based on valve pressure difference according to claim 1, characterized in that: The traffic prediction model algorithm is specifically as follows: Among them: F flow (t) represents the basic part of flow calculation, including the influence of pressure difference, aging wear degree and flow state; F wear (t) represents the long-term influence of the accumulated effect of wear over time on flow changes; ∈(t) is the external disturbance factor, which represents the impact of environmental changes on the fluid.

3. A valve flow prediction method based on valve pressure difference according to claim 2, characterized in that: The F flow (t) The specific calculation formula is as follows: F flow (t)=μ·ΔP(t)·σ(ω(t))·f1(ΔP(t),t) Where: μ is a fluid-related constant; ΔP(t) is the valve pressure difference at the current moment; σ(ω(t)) is the wear coefficient, which reflects the effect of valve wear on flow and changes with the increase of wear degree ω(t); f1(ΔP(t), t) is a nonlinear function that describes the change of valve flow, taking into account the complex relationship between pressure difference and time.

4. The valve flow prediction method based on valve pressure difference according to claim 3 is characterized in that: The F wear (t) The specific calculation formula is as follows: Where: αe -β(t-τ) Used to describe the attenuation effect of wear, where α is the initial coefficient of wear rate and β represents the rate of wear attenuation; It is used to describe the influence of wear degree on flow rate, γ is the sensitivity of wear to flow rate, and ω(τ) is the wear degree at historical moment τ.

5. The valve flow prediction method based on valve pressure difference according to claim 4 is characterized in that: The mathematical formula of the early warning mechanism is specifically expressed as follows: Where: Alert(t) indicates whether the warning is triggered at time t, 1 for triggering and 0 for not triggering; E(t) is the flow error; E th resh old It is the preset error threshold. If it exceeds this value, an early warning will be triggered.

6. The valve flow prediction method based on valve pressure difference according to claim 5, characterized in that: The specific calculation formula of E(t) is as follows: E(t)=|Q actual (t)-Q(t)| Where: Q actual (t) is the actual traffic collected in real time.

7. The valve flow prediction method based on valve pressure difference according to claim 6, characterized in that: The early warning mechanism can be directly triggered when it detects the following situations: σ(ω(t))>σ th resh old Where: ΔP min is the minimum preset value of the pressure difference; ΔP max is the maximum preset value of the pressure difference; σ th resh old The preset value for the aging wear coefficient.

8. A valve flow prediction system based on valve pressure difference, based on a valve flow prediction method based on valve pressure difference according to any one of claims 1 to 7, characterized in that: include: Data acquisition module: The data collected by each sensor is transmitted to the data acquisition module through the interface for real-time processing and caching. After the data format is standardized, it is sent to downstream processing; Data transmission and storage module: including: data transmission unit: responsible for transmitting data from each sensor to the central database; data storage unit: storing the collected data and historical information; Analysis and prediction module: including: flow prediction unit: predict the flow change under different working conditions through data input; health assessment unit: evaluate the wear and aging of the valve according to the working status of the valve; algorithm optimization unit: optimize the algorithm according to the evaluation of the health assessment unit; Abnormal warning module: including: abnormal detection unit: real-time monitoring, detecting abnormalities by comparing with predicted values; warning unit: once the abnormal detection unit finds that the valve state is abnormal and the deviation in flow prediction exceeds the set threshold, it will send a warning message.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of a valve flow prediction method based on valve pressure difference as described in any one of claims 1-7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a valve flow prediction method based on valve pressure difference described in any one of claims 1 to 7 are implemented.

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