CN-121541557-B - Intelligent remote monitoring system and method based on stop valve

CN121541557BCN 121541557 BCN121541557 BCN 121541557BCN-121541557-B

Abstract

The invention relates to the technical field of stop valve monitoring and discloses an intelligent remote monitoring system and method based on a stop valve. The system comprises a parameter acquisition module, a valve core matching module, a condition initialization module, a flow rate matching and optimizing module, a control optimizing module and a remote monitoring module. The method comprises the steps of obtaining fluid characteristic parameters and operation requirement parameters of a stop valve by a parameter obtaining module, matching the type of the valve core by a valve core matching module by combining fluid component information and operation precision constraint, configuring a target valve core, initializing operation conditions by a condition initializing module according to the structural characteristics of the target valve core and a selection result, outputting initial control constraint comprising a pressure difference threshold value and a maximum allowable wear rate, optimizing flow control speed by a flow rate speed matching optimizing module by taking the initial constraint as a condition and combining flow volume and time constraint, analyzing the wear trend of the valve core by a control optimizing module and optimizing the control parameters, and intermittently and remotely monitoring the target valve core in operation by a remote monitoring module by adopting the control parameters.

Inventors

LI HUAGUI
YANG DINGCHENG
Gu Liaoyong
XIANG WEI
DONG HONGPING
WANG QIAOBO
XIAO DONGHAI

Assignees

浙江石化阀门有限公司
浙江东方职业技术学院

Dates

Publication Date: 20260508
Application Date: 20260120

Claims (9)

1. Based on intelligent remote monitering system of stop valve, characterized by includes: The system comprises a parameter acquisition module, a control module and a control module, wherein the parameter acquisition module is used for acquiring fluid characteristic parameters and operation requirement parameters of the stop valve, the fluid characteristic parameters comprise fluid component information and flow volume information, and the operation requirement parameters comprise operation time constraint and operation precision constraint; the valve core matching module is used for performing valve core type matching according to the fluid component information and the operation precision constraint, and obtaining a target valve core by performing valve core configuration of a stop valve based on the valve core selection after obtaining the valve core selection; The condition initializing module is used for acquiring the structural characteristics of the target valve core, initializing the operating conditions according to the structural characteristics and the valve core selection, and outputting initial operation control constraint, wherein the initial operation control constraint comprises a pressure difference threshold value and a maximum allowable wear rate; the flow speed matching optimization module is used for taking the initial operation control constraint as an optimization condition, executing flow speed matching optimization according to the flow volume information and the operation time constraint, and positioning the flow control speed; The control optimizing module is used for analyzing the abrasion trend of the target valve core according to the flow control speed, and executing control optimizing based on the abrasion trend analysis result to obtain control parameters; the remote monitoring module is used for carrying out intermittent remote monitoring on the target valve core by adopting the control parameters in the process that the stop valve is operated at the flow control speed; The flow rate matching and optimizing module comprises: Pre-constructing a flow correlation prediction model; Taking the reciprocal of the standard flow speed as a speed variation scale to update the data of the standard flow speed, and obtaining a first standby flow speed; Inputting the first standby flow rate into a flow associated prediction model to obtain a first wear rate time limit, a first pressure difference time limit and a first predicted operation efficiency; Calculating to obtain a first predicted operation time by adopting the flow volume information and a first predicted operation efficiency, if the first predicted operation time meets the operation time constraint, reserving the first standby flow speed, and adopting a first difference value of the first wear rate time limit and a first pressure difference time limit as a first control reliability coefficient of the first standby flow speed; And by analogy, continuously updating the standard flow speed, and carrying out updating result evaluation by adopting the flow correlation prediction model and the operation time constraint to obtain a plurality of standby flow speeds and a plurality of control reliability coefficients which meet the preset updating frequency; The plurality of control reliability coefficients are serialized and the flow control speed is located from the plurality of backup flow speeds based on the sequencing result.
2. The shutoff valve-based intelligent remote monitoring system of claim 1, wherein the spool matching module comprises: Disassembling the fluid component information based on fluid types to obtain a plurality of fluid particle size distribution characteristics for a plurality of fluid types; updating the plurality of fluid particle size distribution characteristics according to the operation precision constraint to obtain a plurality of operation particle size distribution characteristics; fusing the operation particle size distribution characteristics to obtain global particle size distribution characteristics; performing multi-stage valve core matching based on the global particle size distribution characteristics to obtain a multi-stage valve core element, wherein the multi-stage valve core element has a plurality of operation scales, valve layer thicknesses and valve layer material marks; And carrying out sequential assembly of the multi-layer valve core elements based on the operation scales to obtain the valve core selection.
3. The shutoff valve-based intelligent remote monitoring system of claim 2, wherein the condition initialization module includes: acquiring a plurality of element material information of the multilayer valve element; Calculating an operation area according to the structural characteristics to obtain an effective operation area; performing networking data call according to the material information of the elements and the effective operation area to obtain a plurality of operation simulation models, and obtaining a valve core model by fusing the operation simulation models; after local data call is carried out, standard flow speed is obtained, the standard flow speed is adopted to carry out fluid mechanics simulation of the valve core model, a structural pressure difference threshold value is output, the standard flow speed is adopted to carry out fluid mechanics simulation of the operation simulation models, and a plurality of single pressure difference threshold values are output; performing intersection solution on the structural pressure difference threshold and a plurality of monomer pressure difference thresholds to obtain the pressure difference threshold; And taking the maximum value of the pressure difference threshold as constraint, carrying out fluid mechanics simulation of the valve core model, and calling the maximum allowable wear rate on the valve core model based on a simulation result.
4. The shutoff valve-based intelligent remote monitoring system of claim 1, wherein the flow rate matching optimization module pre-constructs a flow rate correlation prediction model, comprising: calling constraint by taking the valve core selection and fluid component information as historical data, and calling to obtain historical flow related data, wherein the historical flow related data comprises a plurality of sample flow speeds, a plurality of sample operation efficiencies, a plurality of wear rate change speeds and a plurality of pressure difference change speeds; Calculating to obtain a plurality of pressure difference change time limits according to the pressure difference threshold value and a plurality of pressure difference change speeds; calculating to obtain a plurality of wear rate change time limits according to the maximum allowable wear rate and a plurality of wear rate change speeds; and taking the plurality of sample flow rates, the plurality of sample operation efficiencies, the plurality of pressure difference time periods and the plurality of wear rate change time periods as training construction, and training the flow correlation prediction model constructed based on the neural network.
5. The shutoff valve-based intelligent remote monitoring system of claim 1, wherein the control optimizing module comprises: the flow control speed is subjected to direction data calling to obtain a control wear rate time limit and a control pressure difference time limit; the time limit of the control wear rate and the time limit of the control pressure difference are compared to carry out smaller value calling to be used as a monitoring period; predefining an fitness weight configuration and constructing a fitness evaluation function based on the fitness weight configuration, wherein the fitness weight configuration comprises an energy consumption weight, a life loss weight, and a fluid consumption weight; Screening and calling the history control records by taking the initial operation control constraint as a data calling constraint to obtain a plurality of sample control records, wherein each sample control record comprises a sample control parameter and sample monitoring consumption; performing fitness evaluation on the plurality of sample control records by using the fitness evaluation function, and positioning initial control parameters based on evaluation results, wherein the initial control parameters comprise a monitoring water flow rate, a monitoring water time length, a monitoring air flow rate, a monitoring air time length and a comprehensive monitoring time length; and adding the monitoring period to the initial control parameter to obtain the control parameter.
6. The intelligent remote monitoring system based on a stop valve according to claim 5, wherein the sample control parameter is composed of a sample water flow rate, a sample water duration, a sample gas flow rate, a sample gas duration, and a sample integration duration.
7. The shut-off valve based intelligent remote monitoring system of claim 6, wherein the sample monitoring consumption is comprised of sample monitoring energy consumption, sample element life loss, and sample water consumption.
8. The intelligent remote monitoring system based on the stop valve according to claim 1, further comprising a safety pre-warning module for performing safety pre-warning based on the wear trend analysis result, obtaining pre-warning parameters, and transmitting the pre-warning parameters to a remote monitoring center.
9. An intelligent remote monitoring method based on a stop valve is characterized by comprising all modules and method flows of the intelligent remote monitoring system based on the stop valve according to any one of claims 1 to 8.

Description

Intelligent remote monitoring system and method based on stop valve Technical Field The invention relates to the technical field of stop valve monitoring, in particular to an intelligent remote monitoring system and method based on a stop valve. Background In the industrial production process, the stop valve is used as a key control component in a fluid conveying system and is widely applied to the fields of petroleum, chemical industry, water treatment and the like. The running state directly affects the safety, stability and economy of the whole production system. Currently, the traditional stop valve control and monitoring mode has obvious limitations generally, and is difficult to meet the requirements of the modern industry on high-precision and intelligent operation. The traditional stop valve operation is carried out by relying on manual experience to carry out valve core model selection and parameter setting, and the influence of the fluid component difference on valve core suitability is not fully considered. For example, when corrosive fluid is conveyed, if a common metal valve core is selected, the valve core is easy to be corroded rapidly due to mismatching of materials and fluid components, the service life of the valve core is shortened, potential safety hazards such as fluid leakage and the like can be possibly caused, and when high-viscosity fluid is conveyed, if the valve core is unreasonable in structural design, the fluid flow resistance can be increased, and the flow control precision is reduced. Meanwhile, in the manual model selection process, the operation time constraint and the operation precision constraint are often considered by cutting, and the cooperative optimization of the operation time constraint and the operation precision constraint cannot be realized, so that in the actual operation of the stop valve, the control precision is sacrificed for meeting the time requirement, or the operation period is prolonged for ensuring the precision, and the production efficiency is influenced. In the operation monitoring link of the stop valve, the traditional mode mostly adopts a mode of on-site regular inspection or single parameter local monitoring. This mode has the problems of untimely monitoring and incomplete data. The local monitoring usually only pays attention to few key parameters such as flow, pressure and the like, lacks dynamic analysis and prejudgment of the abrasion trend of the valve core, cannot take maintenance measures in advance, can only carry out maintenance and replacement after the occurrence of the fault, and increases the equipment maintenance cost and production risk. In addition, along with the expansion of industrial production scale and the improvement of automation level, the centralized management and remote control of a plurality of stop valves are difficult to realize in the traditional local monitoring mode, so that the intelligent scheduling and the collaborative operation of the whole production system are not facilitated. The limitations of the traditional stop valve control and monitoring modes become important factors for restricting the efficiency improvement and the safety guarantee of a production system, and an integrated system capable of realizing the precise valve core selection, the operation parameter optimization and the remote intelligent monitoring is needed to solve the problems in the prior art. Disclosure of Invention The invention aims to provide an intelligent remote monitoring system and method based on a stop valve, which are used for solving the problems in the background technology. In order to achieve the above object, the present invention provides an intelligent remote monitoring system based on a stop valve, the system comprising: The system comprises a parameter acquisition module, a control module and a control module, wherein the parameter acquisition module is used for acquiring fluid characteristic parameters and operation requirement parameters of the stop valve, the fluid characteristic parameters comprise fluid component information and flow volume information, and the operation requirement parameters comprise operation time constraint and operation precision constraint; the valve core matching module is used for performing valve core type matching according to the fluid component information and the operation precision constraint, and obtaining a target valve core by performing valve core configuration of a stop valve based on the valve core selection after obtaining the valve core selection; The condition initializing module is used for acquiring the structural characteristics of the target valve core, initializing the operating conditions according to the structural characteristics and the valve core selection, and outputting initial operation control constraint, wherein the initial operation control constraint comprises a pressure difference threshold value and a maximum allowable wear rate; the flow speed mat