Flow meter calibration system and method based on Internet of Things

Abstract

The invention provides a flow meter calibration system and method based on the Internet of Things. The system comprises: a meter to be calibrated and a standard meter arranged on a calibration pipeline, the standard meter providing a standard flow corresponding to each calibration point for the meter to be calibrated; each standard meter corresponds to a plurality of meters to be calibrated of the same type; the standard meter and the meter to be calibrated are connected by a serial port server to collect corresponding standard flow data; a calibration control system is used to adjust the calibration environment of the meter to be calibrated on the calibration pipeline until it is the same as the calibration environment of each calibration point preset in the standard meter; after the calibration environment is adjusted, the standard flow data of each meter to be calibrated is fitted to complete the calibration of each meter to be calibrated, the calibration environment of each calibration point preset in the meter to be calibrated and the standard meter is adjusted to make the two completely consistent, the calibration error is reduced by adjusting the accuracy and stability of the calibration environment, and the calibration accuracy of the calibration equipment and the flow meter is also improved; unmanned calibration is realized, and the calibration intelligence and efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of instrument testing, and in particular to a flow meter calibration system and method based on the Internet of Things. Background Art

[0002] With the rapid development of my country's economy, the market demand for flow meter products continues to increase. In order to ensure the reliability of flow meters, it is necessary to calibrate the flow meters before leaving the factory. The calibration of flow meters is a very time-consuming and labor-intensive task. For a long time, the existing technology has adopted manual or semi-automatic calibration methods. For example, a calibration takes more than two hours, which is inefficient. For example, based on the calibration experience passed down by word of mouth, each calibration point is manually adjusted. During calibration, a computer terminal is used to communicate with the instrument, and the mark points are recorded to calibrate the flow meter.

[0003] In the related technology, manual calibration is adopted. On the one hand, the workload is large and time-consuming. On the other hand, affected by the accuracy of the calibration system equipment, it cannot meet the calibration of high-precision flow meters and the calibration error is large. This leads to low calibration accuracy and low calibration efficiency, which is not conducive to the production and growth of the instrument. Summary of the invention

[0004] In view of the above-mentioned shortcomings of the prior art, an object of the present invention is to provide a flow meter calibration system and method based on the Internet of Things, which are used to solve the problem that batch flow meters cannot be calibrated automatically in the prior art.

[0005] To achieve the above objectives and other related objectives, the present invention provides a flow meter calibration system based on the Internet of Things, comprising:

[0006] The meter to be calibrated and the standard meter are arranged on the calibration pipeline, wherein the standard meter provides the standard flow corresponding to each calibration point for the meter to be calibrated;

[0007] Each of the standard tables corresponds to a plurality of tables to be calibrated of the same type; the standard table and the table to be calibrated are connected to each other via a serial port server to collect corresponding standard flow data;

[0008] A calibration control system is connected to the serial port server and is used to adjust the calibration environment of the meter to be calibrated on the calibration pipeline until it is the same as the calibration environment of each calibration point preset in the standard table, wherein the calibration environment at least includes calibration flow, temperature parameters, field pressure and valve switch status; and is also used to fit the standard flow data of each meter to be calibrated after the calibration environment is adjusted to complete the calibration of each meter to be calibrated.

[0009] In one embodiment of the present invention, it also includes: a cloud server, which is respectively connected to the serial port server and the calibration control system, and the cloud server is used to classify and process the received standard flow data of the meter to be calibrated according to the type of the meter to be calibrated, compare the classified meter to be calibrated and the corresponding standard meter at each calibration point, calibrate each meter to be calibrated according to the comparison result, and generate a calibration record for each meter to be calibrated.

[0010] In one embodiment of the present invention, the cloud server is embedded with an expert knowledge base for calculating the error value and linear characteristics of the standard flow data of the current meter to be calibrated at each calibration point, and determining whether correction compensation should be performed on the current meter to be calibrated based on the error value and linear characteristics according to preset expert experience.

[0011] In one embodiment of the present invention, the calibration pipeline is installed with a standard meter and a meter to be calibrated having the same calibrated specifications on the same calibration pipeline according to different calibrated specifications. There are multiple meters to be calibrated, wherein the standard meter and the meter to be calibrated are connected by a serial port server to form an Internet of Things, and the Internet of Things network is connected to the calibration control system.

[0012] In one embodiment of the present invention, a calibration visualization data cockpit is provided, and the calibration visualization data cockpit network is connected to a cloud server, and is used to receive calibration records and standard flow data of each meter to be calibrated, and to visually display the calibration records and standard flow data; it is also used to generate corresponding management requests according to the corresponding management authority of the user, respond using the type of the management request, and display the corresponding response results.

[0013] In one embodiment of the present invention, it also includes: a smart terminal, which is connected to the cloud server through a network and is used to manage the calibration matters of the meter to be calibrated on the current calibration pipeline according to the user's authority when the logged-in user meets the user's authority.

[0014] In one embodiment of the present invention, it also includes: a product management system, which is connected to a cloud server and is used to determine the corresponding table to be calibrated in the product contract based on the identification information of the product contract, and call the calibration records corresponding to each table to be calibrated during calibration to generate a calibration certificate for the product.

[0015] In one embodiment of the present invention, it further includes:

[0016] Storing the calibration record of the meter to be calibrated, wherein the calibration record includes the historical standard flow data corresponding to each calibration point of the meter to be calibrated;

[0017] The standard flow data of the meter to be calibrated is obtained, and the standard flow data of each calibration point corresponding to the standard table is referred to, and the standard flow data corresponding to each calibration point of the meter to be calibrated is fitted to complete the calibration of the meter to be calibrated.

[0018] In one embodiment of the present invention, it also includes: obtaining the calibration environment corresponding to the standard table and the table to be calibrated; adjusting the calibration environment in the table to be calibrated according to the calibration environment of the standard table until the calibration environment of the standard table is the same as the calibration environment in the table to be calibrated, and determining that the calibration environment adjustment is completed.

[0019] Another object of the present invention is to provide a flow meter calibration method based on the Internet of Things, comprising:

[0020] The table to be calibrated and the standard table are arranged on the calibration pipeline, providing a standard environment corresponding to each calibration point for the standard table and the table to be calibrated;

[0021] Each of the standard tables corresponds to a plurality of tables to be calibrated of the same type; the standard table and the table to be calibrated are connected to each other via a serial port server to collect corresponding standard flow data;

[0022] Adjust the calibration environment of the meter to be calibrated on the calibration pipeline until it is the same as the calibration environment of each calibration point preset in the standard meter, wherein the calibration environment at least includes calibration flow, temperature parameters, on-site pressure and valve switch status;

[0023] After the calibration environment is adjusted, the standard flow data of each meter to be calibrated is fitted to complete the calibration of each meter to be calibrated.

[0024] As described above, the flow meter calibration system and method based on the Internet of Things of the present invention have the following beneficial effects:

[0025] The meter to be calibrated and the standard meter on the calibration pipeline are connected through the serial port server. Before calibration, the calibration environment of each calibration point preset on the meter to be calibrated and the standard meter is adjusted to make the two completely consistent, meeting the requirements of accuracy and stability, reducing calibration errors, and improving the calibration accuracy of calibration equipment and flow meters; by remotely controlling the calibration process of the flow meter in the cloud, unmanned control of the calibration of the meter to be calibrated on the calibration pipeline is achieved, shortening the calibration time and calibration workload, and realizing intelligent calibration; at the same time, batch calibration of the same type of meters to be calibrated also improves calibration efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 Shown is a schematic diagram of the structure of a flow meter calibration system based on the Internet of Things provided by the present invention;

[0027] Figure 2Shown is a schematic diagram of the principle of a flow meter calibration system based on the Internet of Things provided by the present invention;

[0028] Figure 3 Shown is a flow chart of a flow meter calibration method based on the Internet of Things provided by the present invention. DETAILED DESCRIPTION

[0029] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0030] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0031] See also Figure 1 , which is a schematic diagram of the structure of a flow meter calibration system based on the Internet of Things provided by the present invention, is described in detail as follows:

[0032] The meter to be calibrated and the standard meter are arranged on the calibration pipeline, wherein the standard meter provides the standard flow corresponding to each calibration point for the meter to be calibrated;

[0033] It should be noted that the meters to be calibrated include but are not limited to electromagnetic flowmeters, vortex flowmeters, water meter electromagnetic flowmeters, Toshiba flowmeters, differential pressure flowmeters, Lixin electromagnetic flowmeters, Canadian flowmeters, etc. The standard meter is a flow meter that matches the type of meter to be calibrated, and is not limited here.

[0034] For example, the meter to be calibrated can be a flow meter of various calibers, DN15-DN2000 domestic electromagnetic flowmeter, DN15-DN600 vortex flowmeter, DN40-DN800 water meter electromagnetic flowmeter, DN15-DN2000 Toshiba flowmeter, DN50-DN300 differential pressure flowmeter, DN15-DN2000 Lixin electromagnetic flowmeter, DN15-DN2000 Canadian flowmeter, etc.

[0035] It should also be noted that the calibration pipeline includes fluid pumps connected in series through pipelines, and the fluid pumps are used to provide a flow rate that meets the corresponding requirements for the standard meter. Multiple meters of the same type to be calibrated can be installed on each calibration pipeline for calibration at the same time, that is, one standard meter can calibrate multiple meters to be calibrated on the calibration pipeline at the same time. For example, one standard meter corresponds to five meters to be calibrated on the calibration pipeline, thereby improving the efficiency of calibration.

[0036] Each of the standard tables corresponds to a plurality of tables to be calibrated of the same type; the standard table and the table to be calibrated are connected to each other via a serial port server to collect corresponding standard flow data;

[0037] Specifically, the standard meter and the meter to be calibrated are connected through a serial port server to collect standard flow data of the standard meter and the meter to be calibrated; it should be noted that the standard meter, the meter to be calibrated, the calibration environment equipment, the calibration-related management personnel, etc. form an Internet of Things with information interconnection through the network to complete the full life cycle management of automatic calibration.

[0038] For example, a serial port server is used to integrate the communication lines of each pipeline instrument on site to solve the problem of many and messy lines on site. The serial port server synchronizes data to the back end (cloud server) via Ethernet to facilitate remote unmanned calibration. Ethernet connection is used between each pipeline and the cloud server to ensure communication speed, reduce communication lines, and make the on-site pipelines tidy.

[0039] A calibration control system is connected to the serial port server and is used to adjust the calibration environment of the meter to be calibrated on the calibration pipeline until it is the same as the calibration environment of the standard meter, wherein the calibration environment at least includes calibration flow, temperature parameters, field pressure and valve switch status; and is also used to fit the standard flow data of each meter to be calibrated after the calibration environment is adjusted to complete the calibration of each meter to be calibrated.

[0040] Specifically, the calibration control system can be implemented on the local side, on the remote side (cloud server), or by the local side and the remote side system working together to implement the calibration control system.

[0041] Among them, the calibration environments corresponding to the standard table and the table to be calibrated are obtained; the calibration environment in the table to be calibrated is adjusted according to the calibration environment of the standard table, until the calibration environment is the same as the calibration environment of each calibration point preset in the standard table, and it is determined that the calibration environment adjustment is completed.

[0042] For example, through the calibration environment adjustment method, the meters to be calibrated on each calibration pipeline are adjusted so that the calibration environment of each meter to be calibrated on the fixed pipeline is the same as the calibration environment of each calibration point preset in the standard table. The adjusted calibration environment parameters include but are not limited to calibration flow, temperature parameters, field pressure and valve switch status. According to the different types of calibration environment parameters, they are adjusted one by one until all calibration environment parameters are adjusted to be the same. Among them, the collected parameters of the corresponding type are compared with the parameters of the same type preset in the standard table. If it is detected that the parameters of a certain type of the meter to be tested are different from the parameters of the same type preset in the standard table, the parameters of a certain type corresponding to the meter to be tested are adjusted according to the parameters of the same type preset in the standard table.

[0043] In this embodiment, when calibrating the flow meter based on the Internet of Things, since the calibration environments corresponding to the standard meter and the meter to be measured have been adjusted to be exactly the same, it is only necessary to collect the standard flow data corresponding to the meter to be calibrated and the standard meter under the current calibration environment, and fit the standard flow data of each meter to be calibrated according to the standard table to complete the calibration of each meter to be calibrated, thereby reducing the calibration error and improving the calibration accuracy of the calibration equipment and the flow meter.

[0044] It should also be noted that the flow meter calibration system based on the Internet of Things in this embodiment is applicable to calibration methods, standard meter method, volumetric method; it is also applicable to flow meters with 232, 484, and HART communications.

[0045] In other embodiments, it also includes: a cloud server, which is respectively connected to the serial port server and the calibration control system, and the cloud server is used to classify the received standard flow data of the meter to be calibrated according to the type of the meter to be calibrated, compare the classified meter to be calibrated and the corresponding standard meter at each calibration point, calibrate each meter to be calibrated according to the comparison result, and generate a calibration record for each meter to be calibrated.

[0046] Among them, the cloud server uses the forwarding function of the serial port server to obtain the standard flow data of the meter to be calibrated, and classifies the standard flow data. According to the unique identification information of each meter to be calibrated, the standard flow data corresponding to each calibration point is sorted. For example, at the 20% range calibration point, the standard flow data of each meter to be calibrated at the current calibration point is counted. Similarly, the standard flow data of each meter to be calibrated is classified and sorted according to the identification information. According to the standard flow data after the classification information is processed, the standard flow data corresponding to each meter to be calibrated at each calibration point is unified, and the standard flow data of the meter to be calibrated and the standard meter at the same calibration point are compared, thereby generating calibration records corresponding to each meter to be calibrated at each calibration point.

[0047] In this embodiment, by using a cloud server for unmanned calibration, automatic calibration is achieved, the single calibration time is reduced, and unmanned control of the calibration of the meters to be calibrated on the calibration pipeline is achieved, which shortens the calibration time and calibration workload and realizes intelligent calibration.

[0048] For example, after the calibrated meter is clamped, the calibration process is completed at one time without manual intervention, which greatly improves production efficiency. On-site measurements have shown that the calibration process was reduced from the original 120 minutes to 40 minutes, increasing the calibration efficiency by more than 3 times and also saving production costs.

[0049] Specifically, the calibration records of the meter to be calibrated are stored, and the calibration records include the historical standard flow data corresponding to each calibration point of the meter to be calibrated; the standard flow data of the meter to be calibrated is obtained, and the standard flow data corresponding to each calibration point of the standard table is referred to, and the standard flow data corresponding to each calibration point of the meter to be calibrated is fitted to complete the calibration of the meter to be calibrated.

[0050] For example, the calibration process is automatically controlled by the cloud server, which compensates for the errors of the calibration system equipment, improves the calibration accuracy, reduces the measurement verification error, and automatically detects and processes the calibration data to avoid human operation errors. The calibration results are automatically generated with high accuracy, good consistency, and accurate and reliable data.

[0051] Specifically, compared with the prior art, the existing calibration method uses manual or semi-automatic methods for calibration, which is labor-intensive and time-consuming; at the same time, due to the large number of existing product specifications, different communication methods, different communication protocols, different wiring methods, different specifications and lines, it does not meet the requirements of safe and civilized production, and has great safety hazards; the same batch of calibration instruments are affected by the difference in the calibration environment, the calibration error is large, and the work efficiency is reduced, which is not conducive to the normal production of the enterprise. For example, according to the calibration experience passed down by word of mouth, each calibration point is manually adjusted, and the instrument is communicated with through the computer super terminal at the calibration point, and each data is manually recorded, that is, the semi-automatic method of the instrument is manually combined, and the data of each calibration point is manually adjusted according to experience, manually entered into EXCEL to record the data, and the "calibration certificate" and "calibration original record" are manually edited and printed, and the "verifier" and "calibrator" are manually signed.

[0052] In this embodiment, cloud computing is used to calibrate the flow meter, making the calibration process fully automated without human involvement, greatly shortening the calibration time, improving production capacity, and saving production costs. Figure 2 , which is a schematic diagram of the principle of a flow meter calibration system based on the Internet of Things provided by the present invention, is described in detail as follows:

[0053] The calibration site uses Ethernet to connect calibration hardware, software, network equipment and other calibration resources, unify related resources, connect "pipelines", "calibration process control systems", "company management networks" and send data to "mobile terminal users (users outside the calibration room)". End customers must log in to browse data based on role-based authority management, ensuring system security. Standard meters, calibrated meters, calibration environment equipment, calibration-related management personnel, etc., through the network, constitute the Internet of Things where information between people, machines and objects is interconnected. The Internet of Things realizes all functions of data collection, calculation, storage, processing, sharing and data visualization, and realizes the full life cycle management process of automatic calibration of flow meters.

[0054] For example, a "serial port server" is used to integrate various communication lines on site. The integrated "calibrated meter" and "standard meter" communicate with the edge computing module in real time through Ethernet and exchange relevant data, solving the problem of many and messy lines on site for flow meter calibration.

[0055] For another example, the "calibration process control system" is composed of a PLC system and corresponding cloud computing control algorithms to complete the generation and stabilization of the environment for each calibration point. According to the cloud computing control algorithm, it stabilizes the flow rate and other related parameters at the corresponding calibration points, allowing the calibration pipeline to reach the calibration environment of each meter to be calibrated, thereby realizing the calibration process of the flow meter.

[0056] For another example, the automatic calibration control algorithm is included in the "cloud platform". The artificial intelligence calibration algorithm and the corresponding control algorithm are the core part of the calibration. It contains an intelligent expert knowledge base and is the crystallization and upgrade of many years of flow meter calibration experience of calibration personnel and field engineers, such as: experience and methods for handling various problems in the calibration process, automatic organization and comprehensive analysis of calibration data, and automatic handling solutions for operating defects of related control equipment. It can perform basic error and repeatability calculations to ensure that the entire calibration process meets relevant requirements; the control algorithm compensates for the errors of the calibration system equipment (such as the "flow characteristics", "hysteresis" and "dead zone" of the control valve), and the system meets the calibration environment requirements for high-precision flow meters.

[0057] For another example, the automatic collection and preservation of calibration data is achieved through edge computing of the "cloud platform". The cloud platform is a "comprehensive computing platform that takes into account both data storage and processing". The processing algorithm of calibration data realizes the "calibration record" and data visualization of the mobile terminal. It is the basis for the calibration data record and traceability. It is stored in the database to solve the problem of tracing historical records, and pushes alarm information to the mobile terminal human-computer interconnection, realizing the full life cycle management process of automatic calibration of flow meters.

[0058] For example, the automatic calculation and correction algorithm of the flow meter B51 and B52 parameters is also implemented on the cloud platform. The built-in control algorithm monitors the real-time communication between the calibrated flow meter and the edge computing module, and collects relevant data of the calibration process at each calibration point and pre-stores it in the edge computing module. The algorithm module analyzes and calculates the original collected calibration process data, and corrects the parameters of the flow meter storage unit "B51, B52" to make the meter meet the relevant factory technical requirements, and saves it to the database as the final result for easy query.

[0059] Internet users (external networks outside the calibration room) adopt B / S structure design, based on role-based permission management, authorized to browse calibration site data, users can log in to the cloud through IE browser, enter the system for operation management, with historical operation records to ensure the security of site data;

[0060] In other embodiments, the cloud server is embedded with an expert knowledge base for calculating the error value and linear characteristics of the standard flow data of the current meter to be calibrated at each calibration point, and determining whether correction compensation should be performed on the current meter to be calibrated based on the error value and linear characteristics according to preset expert experience.

[0061] Specifically, it is the crystallization and upgrade of the calibration personnel and field engineers' many years of flow meter calibration experience, such as: experience and methods for handling various problems in the calibration process, automatic organization and comprehensive analysis of calibration data, and automatic handling of related control equipment operating defects. It can perform basic error and repeatability calculations to ensure that the entire calibration process meets relevant requirements; the control algorithm compensates for the errors of the calibration system equipment (such as the "flow characteristics", "hysteresis", "dead zone", etc. of the control valve), and the system meets the calibration environment requirements for high-precision flow meters.

[0062] In other embodiments, the calibration pipeline installs a standard meter and a meter to be calibrated with the same calibrated specifications on the same calibration pipeline according to different calibrated specifications. There are multiple meters to be calibrated, wherein the standard meter and the meter to be calibrated are connected by a serial port server to form an Internet of Things, and the Internet of Things network is connected to the calibration control system.

[0063] For example, network integration technology is used to realize the conversion of different communication protocols of instruments, reduce hard wiring, and integrate on-site network communications through serial port servers to ensure accurate and smooth data. At the same time, the site is clean and standardized to avoid unnecessary safety hazards. In addition, standard meters, calibrated meters, calibration environment equipment, calibration-related management personnel, etc. form an information-interconnected Internet of Things through the network, realizing all the functions of data collection, calculation, storage, processing, sharing, and connecting calibration-related personnel, realizing the full life cycle management process of automatic calibration of flow meters, achieving full automation of the calibration process, and improving production capacity.

[0064] In other embodiments, a calibration visualization data cockpit is provided, and the calibration visualization data cockpit network is connected to a cloud server, and is used to receive calibration records and standard flow data of each meter to be calibrated, and to visually display the calibration records and standard flow data; it is also used to generate corresponding management requests according to the corresponding management authority of the user, respond using the type of the management request, and display the corresponding response results.

[0065] Specifically, the calibration visualization data cockpit uses data visualization technology to help calibration personnel and related managers control the real-time status of flow meter calibration production and display key indicators of the calibration process and results; different visualized data can be obtained through mouse operations, making more accurate decisions and promoting production development.

[0066] For example, the visual data cockpit can be set and calibrated at the local or remote end, and the remote human-computer interaction function can be realized through the calibration of the visual data cockpit, so that the staff can observe the current calibration work of the flow meter through the calibration of the visual data cockpit.

[0067] In other embodiments, it also includes: a smart terminal, which is connected to the cloud server through a network and is used to manage the calibration matters of the meters to be calibrated on the current calibration pipeline according to the user's authority when the logged-in user meets the user's authority.

[0068] Specifically, the public cloud - cloud server corresponding to the cloud server is accessed through smart terminals such as computers, notebooks, mobile phones, and tablets. When accessing the cloud server, based on the user permissions corresponding to the cloud server logged in by each smart terminal, when it is detected that the user permissions corresponding to the terminal meet the corresponding user permissions, the calibration work matters are managed according to the management request instructions corresponding to the current user permissions. For example, the management request instructions include but are not limited to certain query requests, calibration requests, display requests, etc.

[0069] Through the above method, it is fundamentally eliminated that the staff is bound to the site to perform the calibration work of the flow meter, and it is convenient for the staff to manage the current calibration work of the flow meter at any time and any place, thereby greatly improving the supervision and management efficiency of the calibration work, and also improving the calibration efficiency of the flow meter.

[0070] In other embodiments, it also includes: a product management system, which is connected to a cloud server and is used to determine the corresponding table to be calibrated in the product contract based on the identification information of the product contract, and call the calibration records corresponding to each table to be calibrated during calibration to generate a calibration certificate for the product.

[0071] Among them, the product management system (company management system network) is connected through Figure 2The company management system network including firewalls, network printers, MIS (management information system), local cloud, database servers and disk arrays determines the corresponding table to be calibrated in the product contract according to the identification information corresponding to the product contract provided by the company management system network, and then calls the calibration records corresponding to each table to be calibrated, fills each calibration record into the corresponding template to generate the calibration certificate required for product verification, and the automatic calibration formed can automatically generate calibration certificates according to actual conditions, such as: "Flow calibration special report", "Calibration data table", "Calibration original record", "Chinese (English) version of calibration certificate", etc. At the same time, the "verifier" and "calibrator" automatically sign on the corresponding certificate and automatically save it in the database, which simplifies the product management of the company management system network and improves the management efficiency of various products.

[0072] Specifically, the above calibration process complies with the provisions of the national calibration regulations and the standard requirements, and the calibration results are reliable. For example, it can realize automatic calibration of "large diameter / medium diameter / small diameter / independent calibration / differential pressure / water meter" flow meters, and the calibration parameters meet the relevant technical requirements. A calibration certificate will be automatically generated after the calibration is completed.

[0073] See also Figure 3 , which is a flow chart of a flow meter calibration method based on the Internet of Things provided by the present invention, including:

[0074] Step S1, setting a table to be calibrated and a standard table on a calibration pipeline, providing a standard environment corresponding to each calibration point for the standard table and the table to be calibrated;

[0075] Step S2, each of the standard tables corresponds to a plurality of tables to be calibrated of the same type; the standard table and the table to be calibrated are connected to each other via a serial port server to collect corresponding standard flow data;

[0076] Step S3, adjusting the calibration environment of the meter to be calibrated on the calibration pipeline until it is the same as the calibration environment of each calibration point preset in the standard meter, wherein the calibration environment at least includes calibration flow, temperature parameters, field pressure and valve switch status;

[0077] Step S4, after the calibration environment is adjusted, the standard flow data of each meter to be calibrated is fitted to complete the calibration of each meter to be calibrated.

[0078] Among them, the flow meter calibration method based on the Internet of Things and the flow meter calibration system based on the Internet of Things correspond to each other, and their corresponding technical details, technical contents and even technical solutions and technical effects are all corresponding to the flow meter calibration system based on the Internet of Things, and will not be repeated here.

[0079] In summary, the present invention connects the table to be calibrated and the standard table on the calibration pipeline through a serial port server. Before calibration, the calibration environment of each calibration point preset in the table to be calibrated and the standard table is adjusted to make the two completely consistent, thereby reducing the calibration error and improving the calibration accuracy of the calibration equipment and the flow meter. The calibration process of the flow meter is remotely controlled in the cloud, and the calibration of the table to be calibrated on the calibration pipeline is unmanned, which shortens the calibration time and workload, and realizes intelligent calibration. At the same time, the calibration of the same type of tables to be calibrated is carried out in batches, which also improves the calibration efficiency. Therefore, the present invention effectively overcomes the various shortcomings in the prior art and has a high industrial utilization value.

[0080] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by a person of ordinary skill in the art without departing from the spirit and technical concept disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A flow meter calibration system based on the Internet of Things, It is characterized in that include: The meter to be calibrated and the standard meter are arranged on the calibration pipeline, wherein the standard meter provides the standard flow corresponding to each calibration point for the meter to be calibrated; Each of the standard tables corresponds to a plurality of tables to be calibrated of the same type; The standard meter and the meter to be calibrated are connected via a serial port server to collect corresponding standard flow data; A calibration control system, connected to the serial port server, is used to obtain the calibration environment corresponding to the standard table and the table to be calibrated, wherein the calibration environment at least includes calibration flow, temperature parameters, field pressure and valve switch status, and adjusts the calibration environment in the table to be calibrated according to the calibration environment of each calibration point preset in the standard table, until the calibration environment of each calibration point preset in the standard table is the same as the calibration environment in the table to be calibrated, and it is determined that the calibration environment adjustment is completed; and is also used to fit the standard flow data of each table to be calibrated after the calibration environment adjustment is completed, so as to complete the calibration of each table to be calibrated; The cloud server is connected to the serial port server and the calibration control system respectively, and is used to classify the received standard flow data of the meter to be calibrated according to the type of the meter to be calibrated, compare the classified standard flow data corresponding to each calibration point of the meter to be calibrated and the corresponding standard table, calibrate each meter to be calibrated according to the comparison result, and generate a calibration record for each meter to be calibrated; The cloud server is embedded with an expert knowledge base for calculating the error value and linear characteristics of the standard flow data of the current meter to be calibrated at each calibration point, and determining whether the current meter to be calibrated should be corrected and compensated according to the error value and linear characteristics and preset expert experience.

2. According to the flow meter calibration system based on the Internet of Things according to claim 1, It is characterized in that The calibration pipeline is installed with a standard meter and a meter to be calibrated of the same calibrated specification on the same calibration pipeline according to different calibrated specifications. There are multiple meters to be calibrated, wherein the standard meter and the meter to be calibrated are connected by a serial port server to form an Internet of Things, and the Internet of Things network is connected to the calibration control system.

3. According to the flow meter calibration system based on the Internet of Things as claimed in claim 2, It is characterized in that Also includes: The calibration visualization data cockpit is network-connected to the cloud server, and is used to receive the calibration records and standard flow data of each meter to be calibrated, and to visually display the calibration records and standard flow data; it is also used to generate corresponding management requests according to the corresponding management authority of the user, respond using the type of the management request, and display the corresponding response results.

4. The flow meter calibration system based on the Internet of Things according to claim 1 or 2, It is characterized in that Also includes: The smart terminal is connected to the cloud server through a network and is used to manage the calibration of the meters to be calibrated on the current calibration pipeline according to the user's authority when the logged-in user meets the user's authority.

5. The flow meter calibration system based on the Internet of Things according to claim 1 or 2, It is characterized in that Also includes: The product management system is connected to the cloud server and is used to determine the corresponding table to be calibrated in the product contract according to the identification information of the product contract, and call the calibration records corresponding to each table to be calibrated during calibration to generate a calibration certificate for the product.

6. The flow meter calibration system based on the Internet of Things according to claim 1, It is characterized in that Also includes: Storing the calibration record of the meter to be calibrated, wherein the calibration record includes the historical standard flow data corresponding to each calibration point of the meter to be calibrated; The standard flow data of the meter to be calibrated is obtained, and the standard flow data of each calibration point corresponding to the standard table is referred to, and the standard flow data corresponding to each calibration point of the meter to be calibrated is fitted to complete the calibration of the meter to be calibrated.

7. A flow meter calibration method based on the Internet of Things, It is characterized in that include: The table to be calibrated and the standard table are arranged on the calibration pipeline, providing a standard environment corresponding to each calibration point for the standard table and the table to be calibrated; Each of the standard tables corresponds to a plurality of tables to be calibrated of the same type; the standard table and the table to be calibrated are connected to each other via a serial port server to collect corresponding standard flow data; Obtaining calibration environments corresponding to the standard table and the table to be calibrated, the calibration environment at least including calibration flow, temperature parameters, field pressure and valve switch status, and adjusting the calibration environment in the table to be calibrated according to the calibration environment of each calibration point preset in the standard table, until the calibration environment of each calibration point preset in the standard table is the same as the calibration environment in the table to be calibrated, and determining that the calibration environment adjustment is completed; After the calibration environment is adjusted, the standard flow data of each meter to be calibrated is fitted to complete the calibration of each meter to be calibrated; wherein the received standard flow data of the meter to be calibrated is classified according to the type of the meter to be calibrated, and the standard flow data corresponding to each calibration point of the classified meter to be calibrated and the corresponding standard meter are compared, and each meter to be calibrated is calibrated according to the comparison result, and a calibration record of each meter to be calibrated is generated; Calculate the error value and linearity characteristic of the standard flow data of the current meter to be calibrated at each calibration point, and determine whether to perform correction compensation on the current meter to be calibrated according to the error value and linearity characteristic according to preset expert experience.

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