Intelligent gas valve remote control and early warning system based on the Internet of Things

Abstract

The present invention discloses an Internet of Things-based intelligent gas valve remote control and early warning system, which relates to the field of valve monitoring technology. The system comprises: a valve processing module, which prepares an intelligent valve using 316N stainless steel that has undergone grain boundary treatment, and provides a sealing ring, a fiber grating array, and a QCM sensor on the intelligent valve; and an intelligent control module, which uses the fiber grating array and QCM sensor to obtain fiber grating strain and sulfide film data, and determine the lubricant release amount and current regulation density. The present invention monitors valve stem strain in real time using a fiber grating array to obtain segmented friction force, and automatically releases nano-lubricant based on the friction force, thereby reducing the friction coefficient and ensuring flexible valve opening and closing. The system also detects changes in sulfide film surface density using a QCM sensor and automatically triggers valve stem rotation for self-cleaning or electrolytic polishing based on the corrosion rate, effectively inhibiting corrosion development.

Description

Technical Field

[0001] The present invention relates to the field of valve monitoring technology, and in particular to an intelligent gas valve remote control and early warning system based on the Internet of Things. Background Art

[0002] With the accelerating pace of urbanization and the continuous improvement of people's living standards, natural gas has been widely used as a clean energy source in residential life, commercial activities, and industrial production. However, natural gas is flammable and explosive. Once leaked, it can easily cause serious safety accidents such as fires and explosions, posing a significant threat to people's lives and property. In recent years, gas accidents have occurred frequently due to factors such as aging pipelines, improper operation, and equipment failure.

[0003] Traditional gas management systems rely primarily on manual inspections, scheduled maintenance, and on-site manual valve closures. These systems lack real-time monitoring of gas usage, making it difficult to detect potential hazards and implement effective measures before an incident occurs. Furthermore, after an incident occurs, the gas supply cannot be quickly shut off, delaying emergency response and further exacerbating the impact of the disaster.

[0004] With the rapid development of the Internet of Things (IoT), big data, cloud computing, artificial intelligence, and wireless communication technologies, by combining sensor technology, edge computing, remote communication, and automatic control, it is possible to achieve real-time monitoring, abnormality warning, remote control, and data analysis of gas systems, thereby improving the safety and management efficiency of gas use.

[0005] Chinese invention patent publication number CN115683986A discloses a system for monitoring the effects of atmospheric corrosion on multi-metallic electrical equipment. The system includes a corrosion acquisition module, a corrosion analysis module, and a vapor-phase corrosion inhibition module. Prior to monitoring, the vapor-phase corrosion inhibition module applies a comprehensive corrosion protection spray coating to the electrical equipment's metal components and electrical elements using a multi-metal vapor-phase corrosion inhibitor, thereby maintaining the equipment in a first state. The disclosed system uses the corrosion acquisition module, the corrosion analysis module, and the vapor-phase corrosion inhibition module to perform corrosion protection and corrosion monitoring on the electrical equipment's structures, thereby ensuring the equipment's safe operation. Furthermore, the system utilizes a background management module to provide three-dimensional visualization of each electrical equipment structure for a more intuitive display. The system offers advantages such as intelligence, ease of use, and economical efficiency.

[0006] However, in special scenarios such as chemical parks, when monitoring gas safety, when the concentration of H2S is greater than 5ppm, it will electrochemically react with the metal parts of stainless steel valves and form a sulfide film with semiconductor properties, which will increase the resistivity of the stainless steel valve surface and induce the galvanic cell effect. -Under the synergistic effect of the above, chromium-carbon compound phases will precipitate at the grain boundaries, which will cause a sharp increase in valve stem friction and pitting of the sealing surface, which will lead to chain failures such as false alarms or mechanical jamming. Summary of the Invention

[0007] The purpose of the present invention is to provide an intelligent gas valve remote control and early warning system based on the Internet of Things to solve the problems raised in the above background technology.

[0008] To achieve the above objectives, the present invention provides the following technical solutions: an intelligent gas valve remote control and early warning system based on the Internet of Things, comprising:

[0009] Valve processing module: A smart valve is prepared by using 316N stainless steel with grain boundary treatment, and a sealing ring, a fiber grating array and a QCM sensor are set on the smart valve;

[0010] Intelligent control module: obtains the fiber Bragg grating strain size and sulfide film data through the fiber Bragg grating array and QCM sensor, and determines the lubricant release amount and current regulation density, including:

[0011] SB1: Friction compensation control: The friction force at different positions on the valve stem is obtained according to the strain of the fiber Bragg grating, and the nano-lubricant is released according to the friction force and a preset friction threshold;

[0012] SB2: Corrosion emergency response: Based on the sulfide film data, determine the change in the surface density of the sulfide film, and perform rotational self-cleaning or electrolytic polishing on the valve stem based on the change in the surface density of the sulfide film.

[0013] Furthermore, a sealing ring, a fiber grating array and a QCM sensor are provided on the prepared smart valve, including:

[0014] SA1: Preparation of valve body material: After heat treatment and grain boundary characterization treatment of the smart valve, the valve stem of the smart valve is plated and the sealing surface is surface treated by magnetron sputtering coating and cemented carbide inlay;

[0015] SA2: Setting up a monitoring system: setting an axial microgroove on the smart valve, installing a fiber Bragg grating inside the axial microgroove, and embedding a QCM sensor in the sealed cavity of the smart valve;

[0016] SA3: Sealing compensation setting: After the PTFE gasket is compressed, it is subjected to heat aging cycle treatment at a temperature of 25℃-200℃.

[0017] Furthermore, the valve stem of the smart valve is plated and the sealing surface is surface treated, including:

[0018] SA1.1: Matrix treatment: The valve body blank machined from 316N stainless steel is subjected to matrix treatment by solution treatment, aging treatment and stress relief annealing;

[0019] SA1.2: Coating treatment: After cleaning the sandblasted valve stem, a pre-treated valve stem is obtained, and a Cr transition layer and an M0-NC gradient layer are deposited on the surface of the valve stem;

[0020] SA1.3: Sealing surface treatment: Three layers of WC-10Co powder are clad on the sealing surface, and the clad sealing surface is cryogenically treated.

[0021] Furthermore, during the solution treatment process, the valve body blank is maintained at a temperature of 1050° C. for at least 1 hour and is quenched with deionized water to obtain a supersaturated solid solution;

[0022] During the aging treatment, the supersaturated solid solution is finely ground, maintained at a temperature of 750° C. for at least 4 hours, air-cooled to 300° C., and then slowly cooled with argon gas to obtain an aged structure containing nano-carbides;

[0023] During the stress relief annealing process, the aged structure containing nano-carbides is finely processed and maintained at a temperature of 550°C for at least 2 hours. At the same time, it is furnace cooled to 300°C and then air-cooled to room temperature to obtain a smart valve after preliminary processing.

[0024] Furthermore, the gold electrodes of the QCM sensor are subjected to plasma cleaning and Al2O3 deposition treatments, and a ceramic insulator is installed on the sealed cavity, and the electrodes of the QCM sensor are led out through the ceramic insulator.

[0025] Furthermore, the release of nano-lubricants includes:

[0026] SB1.1: Determine friction force: Divide the valve stem into equal intervals based on the spacing between two adjacent fiber Bragg gratings (FBGs). Determine the segmented friction force corresponding to each interval based on the wavelength offset of the FBGs. Specifically,

[0027] ;

[0028] in: is the segmented friction force in the ith interval, is the comprehensive conversion coefficient, is the wavelength offset of the fiber Bragg grating in the i-th interval, is the wavelength offset of the fiber Bragg grating in the i+1th interval, is the spacing between two adjacent fiber Bragg gratings;

[0029] SB1.2: Friction comparison: Determine the total friction force of the valve stem using the segmented friction force, compare the total friction force with a preset friction threshold, and release the nano-lubricant based on the comparison result, specifically:

[0030] When the total friction force is less than the preset friction threshold, the nano-lubricant is not released; otherwise, the next step SB1.3 is executed, and steps SB1.1 and SB1.2 are repeated until the total friction force is less than the preset friction threshold;

[0031] SB1.3: Determine the amount of lubrication: Determine the amount of nano-lubricant released based on the difference between the total friction force and the preset friction threshold, specifically:

[0032] ;

[0033] in: is the release volume of the nanolubricant, is the friction increment coefficient, is the total friction force, is the preset friction threshold.

[0034] Furthermore, the formula for obtaining the comprehensive conversion coefficient is specifically:

[0035] ;

[0036] in: is the comprehensive conversion coefficient, is the elastic modulus of the valve stem material, is the friction coefficient between the valve stem and the sealing surface, is the cross-sectional area of ​​the valve stem, is the initial center wavelength of the fiber Bragg grating, is the elastic-optical coefficient.

[0037] Furthermore, the release volume of the nano-lubricant is adjusted according to the actual working environment temperature of the smart valve to determine the release volume after temperature correction, specifically:

[0038] ;

[0039] in: is the release volume after adjustment of nanolubricant, is the release volume of the nanolubricant, is the working environment temperature of the valve, is the standard reference temperature.

[0040] Furthermore, the valve stem is subjected to rotational self-cleaning or electrolytic polishing treatment, including:

[0041] SB2.1: Determine the corrosion rate: Determine the corrosion rate of the sulfide film based on the surface density of the sulfide film. Compare the corrosion rate with the preset corrosion threshold range and determine the corrosion treatment method based on the comparison results. Specifically,

[0042] When the corrosion rate is less than the lower limit threshold of the preset corrosion threshold, no treatment is performed; when the corrosion rate is within the preset corrosion threshold range, step SB2.2 is executed to perform a rotational self-cleaning process until the corrosion rate is less than the lower limit threshold of the preset corrosion threshold; when the corrosion rate is greater than the upper limit threshold of the preset corrosion threshold, step SB2.3 is executed to perform an electrolytic polishing process until the corrosion rate is less than the lower limit threshold of the preset corrosion threshold;

[0043] SB2.2: Rotational self-cleaning: Connect the top of the valve stem to the harmonic reducer through a coupling, and connect the harmonic reducer to the servo motor. At the same time, adjust the motor current of the servo motor according to the torque fluctuation. Specifically:

[0044] ;

[0045] in: is the current adjustment amount, is the torque fluctuation, is the motor torque constant;

[0046] SB2.3: Electrolytic polishing: Mix citric acid, NaNO3, and deionized water to obtain an electrolyte solution. Set a three-dimensional flow channel on the smart valve and circulate the electrolyte solution in the three-dimensional flow channel. Connect the control valve of the electrolyte solution to the PLC controller and adjust the power supply output current according to the flow rate of the electrolyte solution. Specifically:

[0047] ;

[0048] in: is the effective current density, is the initial set current density, is the real-time electrolyte flow rate, is the standard reference flow rate.

[0049] Furthermore, during the electropolishing process, the potential of the working electrode is compared with a preset potential threshold, and the current density is adjusted in real time based on the comparison result, specifically:

[0050] When the potential is greater than a preset potential threshold and current fluctuation occurs, the working electrode is replaced; when the potential is greater than a preset potential threshold and no current fluctuation occurs, the current density is reduced through the PLC controller; conversely, when the potential is not greater than the preset potential threshold, the current density is not adjusted;

[0051] The current density is reduced through the PLC controller, specifically:

[0052] ;

[0053] in: is the adjusted current density, is the current density, is the proportional control coefficient, is the integral control coefficient, is the potential deviation, is the reference potential.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] First, the present invention uses a fiber grating array to monitor valve stem strain in real time, obtaining segmented friction. Based on the magnitude of the friction, the nano-lubricant is automatically released, thereby reducing the friction coefficient and ensuring flexible valve opening and closing. Simultaneously, the QCM sensor detects changes in the surface density of the sulfide film and, based on the corrosion rate, automatically triggers valve stem rotation for self-cleaning or electrolytic polishing, effectively inhibiting corrosion progression.

[0056] Second, the present invention can dynamically adjust the amount of nano-lubricant released according to the real-time ambient temperature, thereby ensuring the best lubrication effect under different working conditions;

[0057] Third: The present invention realizes remote control and early warning through real-time transmission of valve status data combined with PLC control algorithm, thereby significantly reducing the risk of gas leakage and explosion;

[0058] Fourthly, the present invention prepares a valve through a 316N stainless steel valve body with optimized grain boundaries, and performs Cr / Mo-NC gradient plating and WC-10Co cladding sealing surface on the valve surface, thereby improving the wear resistance and corrosion resistance of the valve and reducing maintenance frequency and cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 This is a system block diagram of the intelligent gas valve remote control and early warning system of the present invention;

[0060] Figure 2 This is the strain distribution diagram of the valve stem in the present invention;

[0061] Figure 3This is a diagram showing the corrosion rate of the sulfide film and the treatment effect in the present invention;

[0062] Figure 4 This is a diagram showing the temperature adaptive lubrication effect of the present invention. DETAILED DESCRIPTION

[0063] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0064] In special scenarios such as chemical parks, when monitoring gas safety, when the concentration of H2S is greater than 5ppm, it will react electrochemically with the metal parts of stainless steel valves and form a sulfide film with semiconductor properties, which will increase the resistivity of the stainless steel valve surface and induce the galvanic cell effect. - Under the synergistic effect of the chromium-carbon compound phase, the grain boundaries will precipitate chromium-carbon compound phases, which will cause a sharp increase in valve stem friction and pitting of the sealing surface, which will lead to chain failures such as false alarms or mechanical jamming. The technical solution of the present application prepares an intelligent valve through 316N stainless steel with grain boundary treatment, and integrates a sealing ring, a fiber grating array and a QCM sensor on the intelligent valve. At the same time, the valve stem strain is monitored in real time by the fiber grating to obtain the valve stem friction, and the nano-lubricant is automatically released according to the size of the valve stem friction. At the same time, the sulfide film corrosion data is detected by the QCM sensor, and the valve stem rotation self-cleaning or electrolytic polishing treatment is performed according to the corrosion rate. Therefore, through the remote transmission of valve status data, not only can the dynamic lubrication compensation, corrosion warning and adaptive maintenance of the gas valve be realized, but also the H2S and Cl in the chemical environment can be solved. - This causes valve stem sticking and sealing surface corrosion problems.

[0065] Example 1

[0066] refer to Figures 1-4 This embodiment provides an IoT-based intelligent gas valve remote control and early warning system. This intelligent gas valve remote control and early warning system includes a valve processing module and an intelligent control module. In this embodiment, the valve processing module uses grain boundary treated 316N stainless steel as the valve body material and fabricates an intelligent valve. The constructed intelligent valve also undergoes composite sealing and monitoring processes, specifically as follows:

[0067] Step SA1: Prepare the valve body material. A smart valve made of 316N stainless steel is subjected to heat treatment and grain boundary characterization to obtain the treated smart valve. Furthermore, the valve stem of the treated smart valve is coated using magnetron sputtering, and the sealing surface of the treated smart valve is surface treated by cemented carbide inlaying.

[0068] Step SA2: Setting up the monitoring system. Using a diamond tool on an ultra-precision CNC machine tool, axial microgrooves are machined into the smart valve pre-processed in Step SA1. These microgrooves are then electropolished. Polyimide-coated fiber gratings (FBGs) are then fixed to the interior of the microgrooves using high-temperature adhesive, thereby establishing a fiber grating array (FBG) within the valve stem. In this embodiment, eight axial microgrooves are provided, each with a depth of 0.5 mm.

[0069] Furthermore, a micro QCM sensor is embedded in the sealed cavity of the smart valve, which has undergone pretreatment in step SA1. Specifically, the gold electrode on the QCM sensor is plasma cleaned, and then 10nm of Al2O3 is deposited on the cleaned gold electrode surface using an ALD device. Simultaneously, a ceramic insulator is installed in the sealed cavity through high-temperature sintering, and the QCM sensor leads are led out through the ceramic insulator. Notably, a 0.2mm air gap is provided at the bottom of the blind hole in the sealed cavity to enhance vibration response.

[0070] Step SA3: Sealing compensation setting. After the PTFE gasket is compressed using a hydraulic compression mold, it is subjected to a heat aging treatment cycle at temperatures between 25°C and 200°C. Specifically, the compression process is divided into three compression stages for characterization. In the initial compression stage, the initial compression is performed at a pressure of 5 MPa and maintained at a temperature of 23°C for at least 5 minutes. In the final compression stage, the final compression is performed at a pressure of 15 MPa and maintained at a temperature of 80°C for at least 30 minutes. In the finalizing stage, the finalizing is performed at a pressure of 8 MPa and maintained at a temperature of 23°C for at least 240 minutes.

[0071] Furthermore, during the heat aging treatment, the compressed and shaped PTFE gasket is immersed in ASTMOiL No. 3 solution and subjected to cyclic temperature heating treatment within a temperature range of 25° C. to 200° C., and the cyclic heat treatment is performed at least 10 times.

[0072] In this embodiment, the intelligent control module is used to obtain the corresponding fiber Bragg grating (FBG) strain magnitude via the fiber Bragg grating (FBG) array provided in the valve processing module, and to obtain the corresponding sulfide film data via the micro QCM sensor provided in the valve processing module. Based on the obtained FBG strain and sulfide film data, the corresponding lubricant release amount and current regulation density are determined. The details are as follows:

[0073] Step SB1: Friction compensation control. This involves obtaining the corresponding friction force at different locations based on the acquired fiber Bragg grating strain, thereby determining the corresponding total friction force. Simultaneously, by comparing the total friction force with a preset friction threshold, WS2@ZrO2 nanolubricant is released into the valve body microchannels. The details are as follows:

[0074] Step SB1.1: Determine the friction force. This involves dividing the valve stem into equal intervals along its motion direction, based on the spacing between adjacent fiber Bragg gratings. In other words, eight fiber Bragg gratings are placed at equal intervals along the valve stem's motion direction, dividing the valve stem into multiple sections. The wavelength offset of the fiber Bragg gratings within each section is used to determine the corresponding segmented friction force for each section. Specifically,

[0075] ;

[0076] in: is the segmented friction force in the ith interval, is the comprehensive conversion coefficient, is the wavelength offset of the fiber Bragg grating in the i-th interval, is the wavelength offset of the fiber Bragg grating in the i+1th interval, is the spacing between two adjacent fiber Bragg gratings.

[0077] In the specific implementation process, the segmented friction force corresponding to each interval is shown in Table 1 below, specifically:

[0078] Table 1: Segmented friction force distribution

[0079]

[0080] Furthermore, the total friction force of the valve stem is determined based on the segmented friction force corresponding to each interval, specifically:

[0081] ;

[0082] in: is the total friction force, is the segmented friction force in the ith interval, is the total number of intervals, is the interval index.

[0083] During the specific implementation process, according to the segmented friction force corresponding to each interval, the total friction force of the valve stem as a whole is obtained to be 5.82N.

[0084] In this embodiment, the formula for obtaining the comprehensive conversion coefficient is specifically:

[0085] ;

[0086] in: is the comprehensive conversion coefficient, is the elastic modulus of the valve stem material, is the friction coefficient between the valve stem and the sealing surface, is the cross-sectional area of ​​the valve stem, is the initial center wavelength of the fiber Bragg grating, is the elastic-optical coefficient.

[0087] refer to Figure 2 , Figure 2 is the valve stem strain distribution diagram in this embodiment, Figure 2 It can be seen that the friction is greatest in the 20-40mm section of the valve stem, corresponding to the highest wavelength offset. This indicates that this area is most susceptible to H2S corrosion and requires more intensive lubrication. Meanwhile, friction is lower at both ends of the valve stem (0-10mm and 70-80mm), and the pressure distribution is similar to that of the sealing ring.

[0088] Step SB1.2: Friction comparison. The total friction force obtained in step SB1.1 is compared with the preset friction threshold, and the nano-lubricant is released based on the comparison result. Specifically:

[0089] When the total friction force obtained is less than the preset friction threshold, the nanolubricant is not released; conversely, when the total friction force obtained is not less than the preset friction threshold, the next step SB1.3 is executed, and the nanolubricant of corresponding size is released according to the difference between the total friction force and the preset friction threshold, and steps SB1.1 and SB1.2 are repeated at the same time until the total friction force obtained is less than the preset friction threshold.

[0090] Step SB1.3: Determine the lubrication amount. That is, the amount of nano-lubricant released is determined based on the difference between the total friction force and the preset friction threshold, specifically:

[0091] ;

[0092] in: is the release volume of the nanolubricant, is the friction increment coefficient, is the total friction force, is the preset friction threshold.

[0093] In other words, based on the determined release volume of the nanolubricant, a metering pump extracts the same volume of WS2@ZrO2 nanolubricant from the reservoir. Micro-nozzles are also installed in the axial direction of the valve stem and radial direction of the sealing surface of the smart valve. Through a distribution manifold, the WS2@ZrO2 nanolubricant is sprayed through the micro-nozzles onto the corresponding axial direction of the valve stem and radial direction of the sealing surface.

[0094] Specifically, the determined release volume of the nano-lubricant is adjusted in real time according to the actual working environment temperature of the smart valve to determine the release volume after temperature correction, specifically:

[0095] ;

[0096] in: is the release volume after adjustment of nanolubricant, is the release volume of the nanolubricant, is the working environment temperature of the valve, is the standard reference temperature.

[0097] refer to Figure 4 , Figure 4 This is the temperature adaptive lubrication effect diagram in this embodiment, Figure 4 It can be seen that at -10℃, the lubrication capacity of the nano-lubricant is reduced to At 80℃, the lubrication capacity of nano-lubricant increases to In other words, by dynamically adjusting the lubrication amount, it can ensure effectiveness under working conditions of -20℃~200℃.

[0098] Step SB2: Corrosion emergency response. This involves using a micro QCM sensor to obtain the surface density of the sulfide film. Based on the change in the surface density of the sulfide film, the valve stem of the smart valve is rotationally controlled or electropolished. The details are as follows:

[0099] Step SB2.1: Determine the corrosion rate. This involves using a micro QCM sensor to obtain the surface density of the sulfide film. The corrosion rate of the sulfide film is determined based on the surface density of the sulfide film obtained at different times. Specifically, the corrosion rate is:

[0100] ;

[0101] in: is the real-time corrosion rate, is the surface density of the sulfide film at time t, For the moment The surface density of the vulcanized film, is the time interval.

[0102] Furthermore, the determined real-time corrosion rate is compared with a preset corrosion threshold range, and a corresponding corrosion treatment method is determined based on the comparison result. Specifically:

[0103] When the real-time corrosion rate is less than the lower limit of the preset corrosion threshold, the currently generated sulfide film product is not processed. When the real-time corrosion rate is within the preset corrosion threshold, step SB2.2 is executed to perform self-cleaning by rotating the valve stem until the real-time corrosion rate is less than the lower limit of the preset corrosion threshold. When the real-time corrosion rate is greater than the upper limit of the preset corrosion threshold, step SB2.3 is executed to perform electrolytic polishing until the real-time corrosion rate is less than the lower limit of the preset corrosion threshold.

[0104] Step SB2.2: Rotational self-cleaning. The top of the valve stem is connected to a harmonic reducer via a coupling, which in turn is connected to a servo motor. This allows the servo motor to control the operating speed of the smart valve. Specifically, the servo motor's rotational control can strip the sulfide film from the valve stem thread surface and scrape the sulfide film from the sealing surface through the carbide sealing ring.

[0105] Furthermore, during the rotational self-cleaning process, the motor current of the servo motor can be adjusted in real time according to the magnitude of the torque fluctuation, specifically:

[0106] ;

[0107] in: is the current adjustment amount, is the torque fluctuation, is the motor torque constant.

[0108] During the specific implementation, the initial current is 1.2A, the initial torque is 190N.m, and further, the torque fluctuation is 0.1Nm, and the corresponding current adjustment is 0.33A, so the adjusted current is 1.53A.

[0109] Step SB2.3: Electrolytic polishing treatment. That is, citric acid, NaNO3 and deionized water with a concentration ratio of 5:3:92 are mixed to obtain the corresponding electrolyte solution. At the same time, a three-dimensional flow channel is set on the smart valve, including an annular distribution chamber, an axial microchannel, a radial injection hole and a spiral collection tank. Specifically, the obtained electrolyte solution is circulated on the smart valve through the three-dimensional flow channel. Furthermore, the working electrode, i.e., the titanium clamp of the valve body, is engaged with the valve stem conductive groove through a quick-release connector, the cathode mesh is fixed to the flange bolt hole of the valve through a retractable bracket, and the reference motor is magnetically installed on the inspection port.

[0110] In this embodiment, the smart valve is sandblasted with Al2O3 sand, ultrasonically cleaned with acetone, anhydrous ethanol, and deionized water for 10 minutes respectively, then immersed in a 10% H2SO4 solution for 30 seconds and rinsed with deionized water to obtain a pretreated smart valve.

[0111] Furthermore, the electrolyte solution control valve is connected to a PLC controller. This means that the PLC controller can adjust the electrolyte solution flow rate, thereby performing the electropolishing process. Specifically, the power supply output current is adjusted in real time based on the electrolyte solution flow rate, as follows: ;

[0112] in: is the effective current density, is the initial set current density, is the real-time electrolyte flow rate, is the standard reference flow rate.

[0113] In the specific implementation process, the initial current density is set to 2 mA / cm 2 The standard reference flow rate is 1.18 m / s, and the real-time electrolyte flow rate is 1.25 m / s, so the corresponding effective current density is 2.02 mA / cm 2 .

[0114] It is worth noting that during the electropolishing process, the potential of the working electrode is obtained and compared with the preset potential threshold, and the current density is adjusted in real time based on the comparison result. Specifically:

[0115] When the acquired potential is greater than a preset potential threshold, it is determined whether current fluctuation occurs. If current fluctuation occurs, the working electrode is replaced. If current fluctuation does not occur, the current density is reduced through the PLC controller. Conversely, when the acquired potential is not greater than the preset potential threshold, the current density is not adjusted.

[0116] In this embodiment, the current density is reduced by a PLC controller, specifically:

[0117] ;

[0118] in: is the adjusted current density, is the current density, is the proportional control coefficient, is the integral control coefficient, is the potential deviation, is the reference potential.

[0119] refer to Figure 3 , Figure 3 The corrosion rate and treatment effect of the sulfide film in this embodiment are shown in FIG. Figure 3 It can be seen that in the untreated stage, i.e., 0-5 hours, the corrosion rate of the sulfide film increases rapidly from 0 to 0.5 μg / cm 2 After 5-15 hours of rotary self-cleaning, the corrosion rate of the sulfide film decreased from 0.5μg / cm 2 .h dropped to 0.1μg / cm 2 .h, the reduction rate reached 80%, but it was still close to the lower limit threshold. After electrolytic polishing for 15 hours, the corrosion rate of the sulfide film decreased from 0.1μg / cm 2 .h dropped to 0.02μg / cm 2 .h.

[0120] Example 2

[0121] This embodiment provides an IoT-based intelligent gas valve remote control and early warning system. Its specific implementation method is the same as that of Example 1, except that, in step SA1, the intelligent valve is constructed from 316N stainless steel, and the valve stem and sealing surface of the intelligent valve are surface treated by magnetron sputtering coating and cemented carbide inlaying. The present invention is described below with reference to the specific implementation methods of this embodiment.

[0122] In this embodiment, the valve stem and sealing surface of the smart valve are surface treated by magnetron sputtering coating and cemented carbide inlay, as follows:

[0123] Step SA1.1: Matrix treatment. That is, the valve body blank machined from 316N stainless steel is subjected to matrix treatment through three treatment stages: solution treatment, aging treatment, and stress relief annealing. Specifically, the valve body blank is sandblasted, ultrasonically cleaned with acetone, and dried. The dried valve body blank is then hung vertically inside an atmosphere protection furnace and introduced with high-purity argon gas. At the same time, a temperature treatment is performed in the atmosphere protection furnace from room temperature to 1050°C, and maintained at 1050°C for at least 1 hour. The valve body blank after the temperature treatment is then placed in a deionized water tank and stirred to ensure uniform cooling to obtain a supersaturated solid solution.

[0124] Furthermore, the supersaturated solid solution is finely ground and then preheated in a salt bath furnace. In this embodiment, the salt bath in the salt bath furnace comprises BaCl2, NaCl, and KCl in a ratio of 5:3:2. It is worth noting that the salt bath in the salt bath furnace also contains 0.5% Na2CO3 to prevent oxidation of the supersaturated solid solution during the preheating process.

[0125] Specifically, during the preheat treatment, the temperature is raised from room temperature to 750°C and maintained at 750°C for at least 4 hours. The supersaturated solid solution after the preheat treatment is then air-cooled to 300°C and slowly cooled using argon gas to obtain an aged microstructure containing nanocarbides.

[0126] Furthermore, the obtained aged microstructure containing nanocarbides is finely processed to obtain a smart valve, and then maintained at a temperature of 550°C for at least 2 hours. After cooling to 300°C in a furnace, it is air-cooled to room temperature to obtain a preliminarily processed smart valve.

[0127] Step SA1.2: Coating treatment. The valve stem of the smart valve obtained in step SA1.1 is sandblasted using a pneumatic sandblaster. The sandblasted valve stem is then ultrasonically cleaned using acetone, anhydrous ethanol, and deionized water. The ultrasonically cleaned valve stem is then further ion-cleaned using a radio frequency plasma cleaner to obtain a pre-treated valve stem.

[0128] Furthermore, the pretreated valve stem was clamped in a rotating fixture and uniformly heated by infrared radiation at a rate of 10°C / min until it reached 300°C. Simultaneously, a 50nm thick Cr transition layer was deposited on the heated surface of the valve stem. A M0-NC gradient layer was then formed on the surface of the valve stem with the Cr transition layer deposited using a dual-target co-sputtering system.

[0129] Step SA1.3: Sealing Surface Treatment. This involves using a 500W fiber laser to deliver powder to the annular groove of the turned sealing surface, which has been ultrasonically cleaned with acetone. Three layers of cladding are then performed on the sealing surface. It is worth noting that the powder used in this example is WC-10Co powder vacuum-dried at 120°C for two hours, with a particle size of 15-45 μm.

[0130] Furthermore, the clad sealing surface is cryogenically treated in a liquid nitrogen cryogenic chamber, maintaining it at -196°C for at least two hours before naturally returning to room temperature to reduce the amount of retained austenite on the clad sealing surface. Simultaneously, the cryogenically treated sealing surface is ground on a CNC universal grinder, using a diamond grinding wheel and oil-based coolant for rough grinding, followed by fine grinding using a CBN grinding wheel and water-based nanofluid.

[0131] Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is limited by the accompanying embodiments and their equivalents.

Claims

1. An intelligent gas valve remote control and early warning system based on the Internet of Things, characterized in that: Includes: Valve processing module: A smart valve is prepared by using 316N stainless steel with grain boundary treatment, and a sealing ring, a fiber grating array and a QCM sensor are set on the smart valve; Intelligent control module: obtains the fiber Bragg grating strain size and sulfide film data through the fiber Bragg grating array and QCM sensor, and determines the lubricant release amount and current regulation density, including: SB1: Friction compensation control: According to the fiber Bragg grating strain, the friction force at different positions on the valve stem is obtained, and the nano-lubricant is released according to the friction force and the preset friction threshold, including: SB1.1: Determine friction force: Divide the valve stem into equal intervals based on the spacing between two adjacent fiber Bragg gratings (FBGs). Determine the segmented friction force corresponding to each interval based on the wavelength offset of the FBGs. Specifically, Among them: F i is the segmented friction force in the i-th interval, k is the comprehensive conversion coefficient, Δλ i is the wavelength offset of the fiber Bragg grating in the i-th interval, Δλ i+1 is the wavelength offset of the fiber Bragg grating in the i+1th interval, and Δz is the spacing between two adjacent fiber Bragg gratings; SB1.2: Friction comparison: Determine the total friction force of the valve stem using the segmented friction force, compare the total friction force with a preset friction threshold, and release the nano-lubricant based on the comparison result, specifically: When the total friction force is less than the preset friction threshold, the nano-lubricant is not released; otherwise, the next step SB1.3 is executed, and steps SB1.1 and SB1.2 are repeated until the total friction force is less than the preset friction threshold; SB1.3: Determine the amount of lubrication: Determine the amount of nano-lubricant released based on the difference between the total friction force and the preset friction threshold, specifically: V lub =0.1+α·(F tot -F0) Where: V lub is the release volume of the nanolubricant, ɑ is the friction increment coefficient, F tot is the total friction force, F0 is the preset friction threshold; SB2: Corrosion emergency response: Based on the sulfide film data, determine the change in the surface density of the sulfide film, and perform rotational self-cleaning or electrolytic polishing on the valve stem based on the change in the surface density of the sulfide film.

2. The intelligent gas valve remote control and early warning system based on the Internet of Things according to claim 1 is characterized in that: A sealing ring, a fiber grating array and a QCM sensor are arranged on the prepared intelligent valve, including: SA1: Preparation of valve body material: After heat treatment and grain boundary characterization treatment of the smart valve, the valve stem of the smart valve is plated and the sealing surface is surface treated by magnetron sputtering coating and cemented carbide inlay; SA2: Setting up a monitoring system: setting an axial microgroove on the smart valve, installing a fiber Bragg grating inside the axial microgroove, and embedding a QCM sensor in the sealed cavity of the smart valve; SA3: Sealing compensation setting: After the PTFE gasket is compressed, it is subjected to heat aging cycle treatment at a temperature of 25℃-200℃.

3. The intelligent gas valve remote control and early warning system based on the Internet of Things according to claim 2 is characterized in that: The valve stem of the smart valve is plated and the sealing surface is surface treated, including: SA1.1: Matrix treatment: The valve body blank machined from 316N stainless steel is subjected to matrix treatment by solution treatment, aging treatment and stress relief annealing; SA1.2: Coating treatment: After cleaning the sandblasted valve stem, a pre-treated valve stem is obtained, and a Cr transition layer and an M0-NC gradient layer are deposited on the surface of the valve stem; SA1.3: Sealing surface treatment: Three layers of WC-10Co powder are clad on the sealing surface, and the clad sealing surface is cryogenically treated.

4. The intelligent gas valve remote control and early warning system based on the Internet of Things according to claim 3 is characterized in that: During the solution treatment process, the valve body blank is kept at a temperature of 1050° C. for at least 1 hour and quenched with deionized water to obtain a supersaturated solid solution; During the aging treatment, the supersaturated solid solution is finely ground, maintained at a temperature of 750° C. for at least 4 hours, air-cooled to 300° C., and then slowly cooled with argon gas to obtain an aged structure containing nano-carbides; During the stress relief annealing process, the aged structure containing nano-carbides is finely processed and maintained at a temperature of 550°C for at least 2 hours. At the same time, it is furnace cooled to 300°C and then air-cooled to room temperature to obtain a smart valve after preliminary processing.

5. The intelligent gas valve remote control and early warning system based on the Internet of Things according to claim 2 is characterized in that: The gold electrodes of the QCM sensor are subjected to plasma cleaning and Al2O3 deposition treatments. Meanwhile, a ceramic insulator is installed on the sealed cavity, and the electrodes of the QCM sensor are led out through the ceramic insulator.

6. The intelligent gas valve remote control and early warning system based on the Internet of Things according to claim 1 is characterized in that: The formula for obtaining the comprehensive conversion coefficient is specifically: Where: k is the comprehensive conversion coefficient, E is the elastic modulus of the valve stem material, μ is the friction coefficient of the valve stem-sealing surface, A is the cross-sectional area of ​​the valve stem, λ0 is the initial center wavelength of the fiber Bragg grating, P e is the elastic-optical coefficient.

7. The intelligent gas valve remote control and early warning system based on the Internet of Things according to claim 1 is characterized in that: According to the actual working environment temperature of the smart valve, the release volume of the nano-lubricant is adjusted to determine the release volume after temperature correction, specifically: V act =V lub ×[1+0.05(T act -T0)] Where: V act is the release volume after nanolubricant adjustment, V lub is the release volume of the nanolubricant, T act is the working environment temperature of the valve, and T0 is the standard reference temperature.

8. The intelligent gas valve remote control and early warning system based on the Internet of Things according to claim 1 is characterized in that: The valve stem is subjected to rotary self-cleaning or electrolytic polishing treatment, including: SB2.1: Determine the corrosion rate: Determine the corrosion rate of the sulfide film based on the surface density of the sulfide film. Compare the corrosion rate with the preset corrosion threshold range and determine the corrosion treatment method based on the comparison results. Specifically, When the corrosion rate is less than the lower limit threshold of the preset corrosion threshold, no treatment is performed; when the corrosion rate is within the preset corrosion threshold range, step SB2.2 is executed to perform a rotational self-cleaning process until the corrosion rate is less than the lower limit threshold of the preset corrosion threshold; when the corrosion rate is greater than the upper limit threshold of the preset corrosion threshold, step SB2.3 is executed to perform an electrolytic polishing process until the corrosion rate is less than the lower limit threshold of the preset corrosion threshold; SB2.2: Rotational self-cleaning: Connect the top of the valve stem to the harmonic reducer through a coupling, and connect the harmonic reducer to the servo motor. At the same time, adjust the motor current of the servo motor according to the torque fluctuation. Specifically: Where: ΔI is the current adjustment, Δτ is the torque fluctuation, K t is the motor torque constant; SB2.3: Electrolytic polishing: Mix citric acid, NaNO3, and deionized water to obtain an electrolyte solution. Set a three-dimensional flow channel on the smart valve and circulate the electrolyte solution in the three-dimensional flow channel. Connect the control valve of the electrolyte solution to the PLC controller and adjust the power supply output current according to the flow rate of the electrolyte solution. Specifically: Among them: I eff is the effective current density, I0 is the initial set current density, v is the real-time electrolyte flow rate, and v0 is the standard reference flow rate.

9. The intelligent gas valve remote control and early warning system based on the Internet of Things according to claim 8 is characterized in that: During the electropolishing process, the potential of the working electrode is compared with a preset potential threshold, and the current density is adjusted in real time based on the comparison result, specifically: When the potential is greater than the preset potential threshold and current fluctuation occurs, the working electrode is replaced; when the potential is greater than the preset potential threshold and no current fluctuation occurs, the current density is reduced through the PLC controller; On the contrary, when the potential is not greater than the preset potential threshold, the current density is not adjusted; The current density is reduced through the PLC controller, specifically: Among them: I new is the adjusted current density, I prew is the current density, K p is the proportional control coefficient, K i is the integral control coefficient, ΔE is the potential deviation, and E0 is the reference potential.

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