Internet-of-things monitoring system and method for basic state of steam turbine generator

Abstract

The invention discloses an internet-of-things monitoring system and method for the basic state of a steam turbine generator. The system comprises an acquisition module which is arranged at each key part of a steam turbine generator foundation and is used for acquiring static and dynamic characteristic state data of each key part and sending the static and dynamic characteristic state data to a transmission module; the transmission module is used for uploading the static and dynamic characteristic state data to the cloud analysis module; the cloud analysis module is used for performing threshold analysis on the static and dynamic characteristic state data, generating corresponding early warning information or alarm information when a corresponding threshold is reached, and sending the early warning information or alarm information to the early warning and alarm module; and the early warning and alarm module is used for executing corresponding early warning operation or alarm operation according to the early warning information or the alarm information. According to the invention, an internet-of-things monitoring scheme covering the basic state of the steam turbine generator for internet-of-things acquisition and data transmission to the cloud monitoring platform is constructed, monitoring, early warning and alarming of each key part of the steam turbine generator foundation are realized, and improvement of the operation safety and reliability of the steam turbine generator is facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of information processing, and particularly to an Internet of Things monitoring system and method for the foundation state of a steam turbine generator. Background Art

[0002] The foundation of a nuclear power steam turbine generator is a structure that supports the stable operation of the steam turbine generator. When designing, it is necessary to consider bearing the weight of the steam turbine generator set, the dynamic load during operation, and the possible seismic load. Among them, the static and dynamic characteristics of the key parts of the steam turbine generator foundation structure (such as key parts like the bedplate and springs) are crucial for the normal operation of the unit. However, the existing technical means have certain limitations in comprehensively and real-time monitoring the state of the nuclear power steam turbine generator foundation, and it is difficult to comprehensively grasp and real-time monitor the operating conditions of the foundation structure. Therefore, developing more advanced and efficient monitoring technologies to achieve real-time monitoring and early warning of the state of the nuclear power steam turbine generator foundation is of great significance for ensuring the safe and stable operation of the steam turbine generator set. This not only helps to improve the operating efficiency of the nuclear power plant, but also can detect potential faults in time and take measures to avoid major accidents and ensure the safety of personnel and equipment. Summary of the Invention

[0003] The purpose of the present invention is to provide an Internet of Things monitoring system, method, device, computer device, and storage medium for the foundation state of a steam turbine generator, aiming to solve the problems of incomplete data collection, untimely analysis, and low intelligent level of equipment management in the existing monitoring of the foundation state of a nuclear power steam turbine generator.

[0004] In a first aspect, an embodiment of the present invention provides an Internet of Things monitoring system for the foundation state of a steam turbine generator, including: a collection module, a transmission module, a cloud analysis module, and an early warning and alarm module;

[0005] The collection module is set at each key part of the steam turbine generator foundation and is used to collect the static and dynamic characteristic state data of each key part and send it to the transmission module;

[0006] The transmission module is used to upload each static and dynamic characteristic state data to the cloud analysis module;

[0007] The cloud analysis module is used to perform threshold analysis on each static and dynamic characteristic state data, and generate corresponding early warning information or alarm information when the corresponding threshold is reached and send it to the early warning and alarm module;

[0008] The early warning and alarm module is used to perform corresponding early warning operations or alarm operations according to the early warning information or alarm information.

[0009] In a second aspect, an embodiment of the present invention provides an Internet of Things monitoring method for the foundation state of a steam turbine generator, including;

[0010] Collect the static and dynamic characteristic state data of each key part of the steam turbine generator foundation;

[0011] Conduct threshold analysis on the static and dynamic characteristic state data of each key part, and generate corresponding warning information or alarm information when the corresponding threshold is reached;

[0012] Execute corresponding warning operations or alarm operations according to the warning information or alarm information.

[0013] The beneficial effects of the embodiments of the present invention are as follows: An IoT monitoring solution for the state of the steam turbine generator foundation covering IoT collection and data transmission to the cloud monitoring platform is constructed. Through IoT collection technology, it is possible to accurately and timely capture the static and dynamic characteristic state data of each key part of the steam turbine generator foundation, ensuring the accuracy and timeliness of the data. At the same time, the powerful analysis ability of the cloud analysis module can quickly identify abnormal data and generate warning or alarm information, greatly enhancing the intelligent level of equipment management, enabling operation and maintenance personnel to respond quickly and take measures, effectively preventing possible failures, and improving the reliability and stability of the steam turbine generator. Description of the Drawings

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for description in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0015] Figure 1 It is the IoT solution diagram of the IoT monitoring system for the state of the steam turbine generator foundation provided by the embodiments of the present invention;

[0016] Figure 2 It is the architecture diagram of the IoT monitoring system for the state of the steam turbine generator foundation provided by the embodiments of the present invention;

[0017] Figure 3 It is the function organization diagram of the IoT monitoring system for the state of the steam turbine generator foundation provided by the embodiments of the present invention;

[0018] Figure 4 It is the flow schematic diagram of the IoT monitoring method for the state of the steam turbine generator foundation provided by the embodiments of the present invention;

[0019] Figure 5 It is the sub-flow schematic diagram of the IoT monitoring method for the state of the steam turbine generator foundation provided by the embodiments of the present invention;

[0020] Figure 6 It is another sub-flow schematic diagram of the IoT monitoring method for the state of the steam turbine generator foundation provided by the embodiments of the present invention.

[0021] Figure 7 This is another sub - process schematic diagram of the IoT monitoring method for the turbine generator foundation status provided by the embodiments of the present invention. Specific embodiments

[0022] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0023] It should be understood that when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0024] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in this specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms.

[0025] It should be further understood that the term "and / or" used in this specification of the present invention and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0026] Please refer to Figure 1 , Figure 1 This is the IoT solution diagram of the IoT monitoring system for the turbine generator foundation status provided by the embodiments of the present invention.

[0027] The embodiments of the present invention provide an IoT monitoring system for the turbine generator foundation status, including: a collection module, a transmission module, a cloud analysis module, and an early warning and alarm module;

[0028] The collection module is set at each key part of the turbine generator foundation and is used to collect the static and dynamic characteristic state data of each key part and send it to the transmission module;

[0029] The transmission module is used to upload each static and dynamic characteristic state data to the cloud analysis module;

[0030] The cloud analysis module is used to perform threshold analysis on each static and dynamic characteristic state data, and generate corresponding early warning information or alarm information when the corresponding threshold is reached and send it to the early warning and alarm module;

[0031] An early warning and alarm module, configured to perform corresponding early warning operations or alarm operations according to early warning information or alarm information.

[0032] In this embodiment, the present invention takes the Internet of Things architecture as the core to form a monitoring solution for the state of each key part of the turbine generator foundation structure from IoT collection, data transmission to the cloud monitoring platform. By monitoring and early warning the main state parameters of each key part, it is convenient for operation and maintenance personnel to master the real-time and historical operating states of each key part in the cloud, and realize early state warning and instant alarm when an event occurs by reasonably setting thresholds, so as to provide a basis for the evaluation of each key part of the turbine generator foundation.

[0033] Specifically, the overall structure of the IoT solution of the present invention includes a perception layer (edge side), a network layer, and an application layer (cloud); among them, the access of the acquisition module is realized in the perception layer to collect the static and dynamic characteristic state data of each key part of the turbine generator foundation, and it can also have a data protocol conversion function; the access of the acquisition module can use wired communication methods to realize the signal connection between the industrial site and the intelligent monitoring system; among them, the access of the transmission module is realized in the network layer, which is mainly used to transmit the static and dynamic characteristic state data collected by the acquisition module. The static and dynamic characteristic state data can be first converted into digital quantities through the I / O acquisition module and then transmitted; among them, the access of the cloud analysis module and the early warning and alarm module is realized in the application layer, which is mainly used to provide data query, analysis, storage, and management functions according to requirements. For example, threshold analysis is performed on each static and dynamic characteristic state data according to requirements, so as to realize early state warning of each key part and instant alarm when an event occurs.

[0034] In one embodiment, the acquisition module includes:

[0035] A vibration velocity sensor, disposed on the soleplate and / or the soleplate bearing seat and / or the spring of the turbine generator foundation and configured to detect corresponding vibration velocity data;

[0036] A static displacement sensor, disposed on the soleplate and / or the soleplate bearing seat of the turbine generator foundation and configured to detect corresponding static displacement data;

[0037] A settlement displacement sensor, disposed at a key position of the turbine generator foundation and configured to detect settlement displacement data generated in the vertical direction at the key position during the operation of the turbine generator; wherein, the key position refers to the point where settlement displacement may occur during the operation of the turbine generator.

[0038] LVDT sensors are used to detect the deformation data of the springs on the turbine generator foundation. Among them, the LVDT sensors determine the displacement of the springs by sensing the change in the position of the magnetic cores in the induction coils. When the springs deform, the positions of the magnetic cores of the LVDTs connected to them also change, and this change is converted into an electrical signal by the sensors, so that the degree of spring deformation can be accurately measured;

[0039] Thermal resistance RTD sensors are used to detect the ambient temperature data of the environment where the turbine generator foundation is located.

[0040] In this embodiment, the turbine generator foundation is usually fixed with a reinforced concrete base. A platen is built on the reinforced concrete, and multiple platen bearing seats are arranged on the platen to support the turbine generator. Springs need to be added for support at some special support positions to absorb part of the vibration generated during the operation of the turbine generator.

[0041] In this embodiment, the vibration velocity sensors, static displacement sensors, settlement displacement sensors, LVDT sensors, and thermal resistance RTD sensors transmit the data they detect to the acquisition module. The acquisition module then transmits this data to the transmission module in the network layer and further uploads it to the cloud analysis module in the application layer. The cloud analysis module will conduct in-depth analysis on this data. Once data anomalies are found, the early warning alarm module will be triggered to send out early warning or alarm signals in a timely manner. In this way, the staff can quickly understand the operating status of the turbine generator foundation, take measures in a timely manner, avoid accidents, and ensure the safe and stable operation of the turbine generator.

[0042] Furthermore, the transmission module is used to upload the respective static and dynamic characteristic state data to the cloud analysis module according to the type and monitoring requirements of the data at corresponding intervals. Specifically, the transmission module uploads the respective static and dynamic characteristic state data in the MQTT protocol format; specifically, the Modbus industrial communication protocol can be used to perform high-speed data transmission in the form of RJ45 network ports; the upload intervals of the respective static and dynamic characteristic state data vary according to the data type and monitoring requirements. For example, the upload interval of the vibration velocity data is once per hour, and the static displacement data, settlement displacement data, deformation data, and temperature-related data are once per minute. It should be noted that the specific upload intervals of the data in this embodiment are not limited and can be set according to the actual situation.

[0043] In one embodiment, the cloud analysis module includes a first analysis unit and a second analysis unit;

[0044] The first analysis unit is used to calculate the state change trend of each static and dynamic characteristic state data, and generate corresponding early warning information when the state change trend reaches the corresponding preset change trend;

[0045] The second analysis unit is used to monitor the current state values of the static and dynamic characteristic state data, and generate corresponding alarm information when the current state values reach the preset alarm values.

[0046] In this embodiment, for the technology of the state change trend performed by the first analysis unit, the STL time series decomposition method (Seasonal-Trend Decomposition using LOESS) can be used for implementation. The STL time series decomposition method is applicable to the extraction of long-term trends of univariate data;

[0047] The specific implementation process is as follows:

[0048] Data input: The time series data of each static and dynamic characteristic state data is used as input (such as the vibration speed data uploaded once per hour in the above example);

[0049] Decompose the time series: The time series data is decomposed into a trend term (Trend), a seasonal term (Seasonal), and a residual term (Residual), where the trend term can well reflect the state change trend of the time series data;

[0050] Extract the trend: Directly use the trend term as the core feature of the state change trend of each corresponding static and dynamic characteristic state data;

[0051] In this way, by comparing the core features of the state change trends of each static and dynamic characteristic state data with the features of the preset change trends, it can be determined whether the current static and dynamic characteristic state data is in an abnormal state. If the judgment result is yes, corresponding early warning information is generated, and the early warning information includes but is not limited to the name of the static and dynamic characteristic state data, the specific description of the abnormal state, and the recommended countermeasures, etc. In this way, real-time monitoring and early warning of the turbine generator foundation state can be realized, and the operation safety and reliability of the turbine generator can be improved.

[0052] In this embodiment, for the analysis and calculation of the second analysis unit, the preset alarm values corresponding to each static and dynamic characteristic state data are directly set, and corresponding alarm information is directly generated when the current state values of each static and dynamic characteristic state data reach the preset alarm values.

[0053] In one embodiment, the early warning and alarm module includes an early warning unit and an alarm unit;

[0054] The early warning unit is used to send out an early warning signal by using corresponding sound, light, and electrical prompts according to the early warning information;

[0055] The alarm unit is used to send out an alarm signal by using corresponding sound, light, and electrical prompts according to the alarm information, and control the corresponding key parts to perform corresponding safety actions.

[0056] In this embodiment, the early warning unit can be configured with multi-level sound and light warnings (such as yellow / blue flashing lights, gradual buzzing), and when triggered, the early warning location is synchronously pushed to the monitoring terminal;

[0057] In this embodiment, the alarm unit uses high-frequency red light flashing and rapid sirens. After activation, it will shut down the power supply in the dangerous area and start the emergency braking device (such as shutting down dangerous equipment, starting emergency lighting or starting evacuation instructions). At the same time, it will send alarm information to the person responsible for safety through the Internet of Things module, and record the response action log for retrospective analysis.

[0058] In this embodiment, graded warnings, equipment linkage, information push and log functions can be added to both the early warning unit and the alarm unit, which strengthens the early warning level and closed-loop disposal process without increasing the complexity of the hardware.

[0059] In one embodiment, the IoT monitoring system for the basic status of the steam turbine generator further includes:

[0060] A threshold setting unit is used to set corresponding thresholds of various static and dynamic characteristic state data of various key parts of the steam turbine generator foundation under different working conditions;

[0061] The query unit is used to perform data query, analysis, storage and management according to user instructions.

[0062] In this embodiment, the threshold setting unit has a built-in multi-operating condition parameterized modeling tool, which can set corresponding thresholds for each key part of the steam turbine generator foundation, and set up a threshold dynamic compensation mechanism (such as automatically correcting the insulation temperature rise limit based on ambient humidity), providing manual input, historical data learning, and ISO standard import. Three threshold configuration modes provide users with more flexible threshold setting options. The manual input mode allows users to directly set the thresholds of each key part according to specific needs; the historical data learning mode intelligently recommends a reasonable threshold range by analyzing the historical operating data of the steam turbine generator; the ISO standard import mode facilitates users to follow international standards and quickly set thresholds that meet the specifications to ensure the monitoring accuracy and reliability of the system. In addition, the threshold setting unit also supports the threshold warning function. When the monitoring data approaches or exceeds the preset threshold, the warning or alarm mechanism is triggered in time to effectively prevent potential failures and improve the operating safety of the steam turbine generator.

[0063] In this embodiment, a multi-level query architecture is constructed in the query unit. This multi-level query architecture can quickly locate the specific key parts of the steam turbine generator foundation and their related static and dynamic characteristic state data according to the query conditions input by the user. Each level corresponds to a different classification dimension, such as component type, working status, fault type, etc. By selecting or inputting step by step, the user can accurately obtain the required state data and its corresponding threshold information. This design not only improves the query efficiency, but also makes the management and retrieval of data more orderly and intuitive, providing great convenience for the operation and maintenance personnel. At the same time, the query unit also supports fuzzy query and intelligent recommendation functions, further enhancing the usability and intelligence level of the system.

[0064] The above embodiments are the core components and function descriptions of the Internet of Things monitoring system for the state of the steam turbine generator foundation of the present invention. From the perspective of Internet of Things technology, a system that can realize data monitoring and early warning management of key parts of the steam turbine generator foundation is constructed by using wired communication protocols, Internet of Things gateways, and cloud platforms. It has strong scalability and flexibility, can realize online management of the steam turbine generator foundation, helps to improve the intelligent control of the state of the steam turbine generator foundation, and saves the workload of regular inspections by operation personnel. The architecture for specifically implementing this system can adopt the B / S architecture, such as Figure 2 shown, the B / S architecture consists of a data source layer, an IaaS layer, a PaaS layer, and a SaaS layer; the data source layer includes industrial equipment acquisition, Internet of Things gateway protocol conversion, and integrated service transmission network data transfer; the PaaS layer includes data integration, computing integration, event integration, and visualization component integration; the SaaS layer is for equipment information query and management, Internet of Things monitoring and analysis of the state of the steam turbine generator foundation, and early warning and alarm management.

[0065] In one embodiment, as Figure 3 shown, the Internet of Things monitoring system for the state of the steam turbine generator foundation further includes:

[0066] A state data display unit for displaying 3D model information, real-time status, and real-time early warning and alarm information of the steam turbine generator foundation;

[0067] An equipment information display unit for displaying building information related to the steam turbine generator foundation and sensor information for collecting static and dynamic characteristic state data;

[0068] A state monitoring unit for real-time displaying the current values and historical records of various static and dynamic characteristic state data, and can present the measurement points and measurement results at the measurement points in the form of mounting measurement points on a 3D model according to user filtering;

[0069] An early warning and alarm management unit for managing the query, display, confirmation, and information download of early warning signals and alarm signals;

[0070] The system management unit is used to display the relevant thresholds of the static and dynamic characteristic state data of each part, manage the basic information of the device, and upload files.

[0071] More specifically, the device information display unit can be displayed in a list form; and can be linked with document information for querying and downloading; centrally display sensor information for editing.

[0072] More specifically, the status monitoring unit respectively displays the real-time and historical status of the foundation according to five categories: vibration monitoring, static displacement, foundation settlement, spring status, and ambient temperature, and has functions of filtering by unit, operation time period, and sensors (single or multiple can be selected); display monitoring data; be able to give the measuring point position in the form of hanging measuring points of a 3D model according to the filtering; be able to display the status information in a list form, including serial number, time, sensor, and monitoring value information; give the maximum value of the monitored quantity.

[0073] More specifically, the early warning and alarm management unit has functions of filtering by monitoring content, status, start time, end time, etc.; be able to list and display monitoring content, monitoring purpose, measuring point number, early warning / alarm start time, early warning / alarm end time, trigger value, and threshold according to the filtering; be able to confirm the early warning / alarm status; be able to download the early warning / alarm result.

[0074] More specifically, the system management unit includes functions of threshold display, device basic information management, and file upload. It can list and display sensor types, monitoring parameters, early warning thresholds, and alarm thresholds; can list and display the type of steam turbine generator, operating frequency, form of spring vibration isolator, number of columns, number of spring vibration isolators, and size of the foundation platen; supports uploading 2D drawings to the home page for display.

[0075] In one embodiment, the IoT monitoring system for the steam turbine generator foundation status further includes a maintenance unit; the maintenance unit is used to regularly analyze the historical static and dynamic characteristic state data of each key part, confirm the historical maintenance nodes of each key part and obtain the historical maintenance cycle between the historical maintenance nodes, and use an intelligent algorithm to predict the future maintenance node of the next maintenance based on the time law of the historical maintenance cycle.

[0076] The maintenance unit of this embodiment realizes a comprehensive assessment of the structural health status and accurate prediction of future maintenance nodes by regularly analyzing the historical static and dynamic characteristic state data of each key part of the steam turbine generator foundation; this process is realized by using a time series analysis algorithm.

[0077] Specifically, the time intervals of the historical maintenance nodes of each key part can be analyzed to extract the rules of the historical maintenance cycle. Then, based on the rules of the historical maintenance cycle, the ARIMA model is adopted. The ARIMA model can effectively process non-stationary time series by combining three parts: autoregressive (AR), differencing (I), and moving average (MA). In the monitoring of the basic state of a turbogenerator, the ARIMA model can be used to predict the degradation trend of key parts, thereby determining the future maintenance time nodes. In this way, the operator can be reminded to perform maintenance or replace components in time before the future maintenance time nodes, effectively extending the service life of the equipment and reducing the maintenance cost.

[0078] An embodiment of the present invention also provides an IoT monitoring method for the basic state of a turbogenerator, including:

[0079] As Figure 4 shown, this method includes steps S401 to S403.

[0080] S401. Collect the static and dynamic characteristic state data of each key part of the turbogenerator foundation;

[0081] S402. Conduct threshold analysis on the static and dynamic characteristic state data of each key part, and generate corresponding early warning information or alarm information when the corresponding threshold is reached;

[0082] S403. Perform corresponding early warning operations or alarm operations according to the early warning information or alarm information.

[0083] In this embodiment, by collecting the static and dynamic characteristic state data of each key part in real time, combining relevant threshold analysis and intelligent algorithms to identify potential fault risks in advance, and linking with the control system for early warning or alarm, a closed-loop management from monitoring to active protection is realized.

[0084] This method takes the IoT architecture as the core to form a monitoring solution for the state of each key part of the turbogenerator foundation from IoT data collection, data transmission to the cloud monitoring platform. By monitoring and early warning the main state parameters of each key part, it is convenient for operation and maintenance personnel to master the real-time and historical operation states of each key part in the cloud, and realize early state warning and instant alarm when an event occurs by reasonably setting thresholds, thereby providing a basis for the evaluation of each key part of the turbogenerator foundation.

[0085] In one embodiment, as Figure 5 shown, collecting the static and dynamic characteristic state data of each key part of the turbogenerator foundation includes:

[0086] S501. Detect the vibration velocity data of the soleplate and / or the soleplate bearing seat and / or the spring of the turbogenerator foundation;

[0087] S502. Detect the static displacement data of the soleplate and / or the soleplate bearing seat of the steam turbine generator foundation;

[0088] S503. Detect the settlement displacement data generated in the vertical direction at the key positions of the steam turbine generator foundation during the operation of the steam turbine generator set;

[0089] S504. Detect the deformation data of the springs on the steam turbine generator foundation;

[0090] S505. Detect the ambient temperature data of the environment where the steam turbine generator foundation is located.

[0091] In this embodiment, the vibration velocity sensor, static displacement sensor, settlement displacement sensor, LVDT sensor, and thermal resistance RTD sensor transmit the data they detect to the acquisition module. The acquisition module then transmits this data to the transmission module in the network layer and further uploads it to the cloud analysis module in the application layer. The cloud analysis module will deeply analyze this data. Once data anomalies are found, the early warning and alarm module will be triggered to send out early warning or alarm signals in a timely manner. In this way, the staff can quickly understand the operating status of the steam turbine generator foundation, take measures in a timely manner, avoid accidents, and ensure the safe and stable operation of the steam turbine generator.

[0092] In one embodiment, as Figure 6 shown, threshold analysis is performed on the static and dynamic characteristic state data of each key part, and corresponding early warning information or alarm information is generated when the corresponding threshold is reached, including:

[0093] S601. Obtain the current state value and state change trend of the static and dynamic characteristic state data of each key part;

[0094] S602. Generate corresponding early warning information when the state change trend of the corresponding static and dynamic characteristic state data reaches the corresponding preset trend;

[0095] S603. Generate corresponding alarm information when the current state value of the corresponding static and dynamic characteristic state data reaches the preset state value.

[0096] In this embodiment, by real-time monitoring the static and dynamic characteristic state data (current value and change trend) of the key parts, an early warning is triggered when the data trend reaches the preset trend (prompting potential risks in advance), and if the current value further exceeds the preset state value, it is upgraded to an alarm, realizing a hierarchical risk response mechanism, taking into account both early warning and emergency state handling.

[0097] In one embodiment, as Figure 7 shown, the IoT monitoring system for the steam turbine generator foundation state further includes:

[0098] S701. Display the 3D model information, real-time status, and real-time warning and alarm information of the steam turbine generator foundation through the status data display interface;

[0099] S702. Display the building information related to the steam turbine generator foundation and the sensor information for collecting static and dynamic characteristic status data through the equipment information display interface;

[0100] S703. Display the current values and historical records of each static and dynamic characteristic status data through the status monitoring unit interface, and according to user filtering, present the measurement point positions and the measurement results at the measurement point positions in the form of mounting measurement points on a 3D model;

[0101] S704. Display the functions of querying, displaying, confirming, and information downloading of warning signals and alarm signals through the warning and alarm management interface.

[0102] S705. Display the relevant thresholds of each static and dynamic characteristic status data, manage the basic information of the equipment, and the function of file uploading through the system management interface.

[0103] In this embodiment, based on steps S701 - S705, the comprehensive status monitoring and information management of the steam turbine generator foundation are realized. Users can quickly obtain the 3D model, real-time status data, and warning and alarm information of the steam turbine generator foundation through an intuitive interface, so as to respond and handle potential problems in a timely manner. At the same time, the equipment information display interface provides the building and sensor information related to the steam turbine generator foundation, which helps users understand the operating environment of the equipment more comprehensively. The status monitoring unit interface intuitively displays the measurement point positions and measurement results in the form of mounting measurement points on a 3D model, facilitating users to perform data analysis and fault troubleshooting. The warning and alarm management interface and the system management interface respectively provide the management functions of warning signals and alarm signals, as well as the functions of setting relevant thresholds for static and dynamic characteristic status data, managing the basic information of the equipment, and file uploading, further improving the practicality and convenience of the system.

[0104] In one embodiment, the IoT monitoring method for the status of the steam turbine generator foundation further includes:

[0105] Regularly analyze the historical static and dynamic characteristic status data of each key part, confirm the historical maintenance nodes of each key part, and obtain the historical maintenance cycles between the historical maintenance nodes; predict the future maintenance nodes of the next maintenance based on the time law of the historical maintenance cycle through an intelligent algorithm.

[0106] In this embodiment, by regularly analyzing the historical static and dynamic characteristic status data of each key part of the steam turbine generator foundation, a comprehensive assessment of the structural health status and an accurate prediction of future maintenance nodes are realized; this process is achieved by using a time series analysis algorithm. For the specific implementation method, reference can be made to the description of the above embodiment.

[0107] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working process of the IoT monitoring method for the steam turbine generator foundation status described above can refer to the corresponding process in the foregoing embodiments of the IoT monitoring system for the steam turbine generator foundation status, and will not be elaborated herein.

[0108] As described above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or substitutions within the technical scope disclosed by the present invention, and these modifications or substitutions should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. An IoT monitoring system for the basic status of a steam turbine generator, characterized in that: include: Acquisition module, transmission module, cloud analysis module and early warning alarm module; A collection module, which is arranged at each key part of the steam turbine generator foundation and is used to collect static and dynamic characteristic state data of each key part and send it to the transmission module; A transmission module, used for uploading various static and dynamic characteristic status data to the cloud analysis module; A cloud analysis module is used to perform threshold analysis on each static and dynamic characteristic state data, and generate corresponding early warning information or alarm information when the corresponding threshold is reached and send it to the early warning alarm module; The early warning and alarm module is used to perform corresponding early warning operations or alarm operations according to the early warning information or alarm information.

2. The IoT monitoring system for the basic status of a steam turbine generator according to claim 1 is characterized in that: The acquisition module includes: A vibration velocity sensor is arranged on the tabletop and / or the tabletop bearing seat and / or the spring of the steam turbine generator foundation and is used to detect corresponding vibration velocity data; A static displacement sensor is arranged on the bedplate and / or the bedplate bearing seat of the steam turbine generator foundation and is used to detect corresponding static displacement data; A settlement displacement sensor is arranged at a key position of the steam turbine generator foundation and is used to detect settlement displacement data of the key position generated in the vertical direction when the steam turbine generator set is in operation; An LVDT sensor, used to detect deformation data of a spring on the foundation of the steam turbine generator; The thermal resistor RTD sensor is used to detect the ambient temperature data of the environment in which the steam turbine generator foundation is located.

3. The IoT monitoring system for the basic status of a steam turbine generator according to claim 1 is characterized in that: The transmission module is used to upload each static and dynamic characteristic status data to the cloud analysis module according to the type and monitoring requirements of the data in a corresponding period.

4. The IoT monitoring system for the basic status of a steam turbine generator according to claim 1 is characterized in that: The cloud analysis module includes a first analysis unit and a second analysis unit; The first analysis unit is used to calculate the state change trend of each static and dynamic characteristic state data, and generate corresponding warning information when the state change trend reaches the corresponding preset change trend; The second analysis unit is used to monitor the current state value of each static and dynamic characteristic state data, and generate corresponding alarm information when the current state value reaches a preset alarm value.

5. The IoT monitoring system for the basic status of a steam turbine generator according to claim 1 is characterized in that: The early warning alarm module includes an early warning unit and an alarm unit; The warning unit is used to issue a warning signal according to the warning information using corresponding sound and light prompts; The alarm unit is used to send out an alarm signal according to the alarm information using corresponding sound and light prompts, and control corresponding key parts to perform corresponding safety actions.

6. The IoT monitoring system for the basic status of a steam turbine generator according to claim 1 is characterized in that: Also includes: A threshold setting unit, used to set corresponding thresholds of various static and dynamic characteristic state data of various key parts of the steam turbine generator foundation under different working conditions; The query unit is used to perform data query, analysis, storage and management according to user instructions.

7. The IoT monitoring system for the basic status of a steam turbine generator according to claim 1 is characterized in that: Also includes: A status data display unit, used to display the 3D model information, real-time status and real-time early warning alarm information of the steam turbine generator foundation; An equipment information display unit, used to display building information related to the steam turbine generator foundation and sensor information used to collect static and dynamic characteristic status data; The status monitoring unit is used to display the current value and historical records of each static and dynamic characteristic status data in real time, and can present the measurement point location and the measurement results at the measurement point location in the form of a 3D model mounted measurement point according to user screening; Early warning and alarm management unit, used to manage the query, display, confirmation and information download of early warning and alarm signals; The system management unit is used to display the relevant thresholds of each static and dynamic characteristic status data, manage basic equipment information and upload files.

8. The IoT monitoring system for the basic status of a steam turbine generator according to claim 2, characterized in that: Also includes: The maintenance unit is used to regularly analyze the historical static and dynamic characteristic status data of each key part, confirm the historical maintenance nodes of each key part and obtain the historical maintenance cycles between the historical maintenance nodes, and use intelligent algorithms to predict the future maintenance nodes of the next maintenance based on the time rules of the historical maintenance cycles.

9. A method for monitoring the basic status of a steam turbine generator through Internet of Things, characterized in that: include; Collect static and dynamic characteristic status data of key parts of the steam turbine generator foundation; Perform threshold analysis on the static and dynamic characteristic status data of each key part, and generate corresponding early warning information or alarm information when the corresponding threshold is reached; Execute corresponding warning operation or alarm operation according to the warning information or alarm information.

10. The method for IoT monitoring of the basic status of a steam turbine generator according to claim 9, characterized in that: The acquisition of static and dynamic characteristic status data of key parts of the steam turbine generator foundation includes: Detecting vibration velocity data of a bedplate and / or a bedplate bearing seat and / or a spring of the steam turbine generator foundation; Detecting static displacement data of a bedplate and / or a bedplate bearing seat of the steam turbine generator foundation; Detecting the settlement displacement data of the key position of the steam turbine generator foundation in the vertical direction when the steam turbine generator set is in operation; Detecting deformation data of the spring on the steam turbine generator foundation; Detecting ambient temperature data of the environment in which the steam turbine generator foundation is located.

11. The method for IoT monitoring of the basic status of a steam turbine generator according to claim 9, characterized in that: The threshold analysis of the static and dynamic characteristic status data of each key part and the generation of corresponding early warning information or alarm information when the corresponding threshold is reached include: Obtain the current state value and state change trend of the static and dynamic characteristic state data of each key part; When the state change trend of the corresponding static and dynamic characteristic state data reaches the corresponding preset trend, the corresponding warning information is generated; When the current state value of the corresponding static and dynamic characteristic state data reaches the preset state value, the corresponding alarm information is generated.

12. The method for IoT monitoring of the basic status of a steam turbine generator according to claim 9, characterized in that: Also includes: The 3D model information, real-time status and real-time early warning alarm information of the steam turbine generator foundation are displayed through the status data display interface; Displaying building information related to the steam turbine generator foundation and sensor information for collecting static and dynamic characteristic status data through an equipment information display interface; The current value and historical record of each static and dynamic characteristic status data are displayed through the status monitoring unit interface, and the measurement point location and the measurement results at the measurement point location can be presented in the form of a 3D model mounted measurement point according to user screening; The functions of querying, displaying, confirming and downloading information of warning signals and alarm signals are displayed through the warning alarm management interface; The system management interface displays the relevant thresholds of each static and dynamic characteristic status data, manages basic equipment information and provides file upload functions.

13. The method for IoT monitoring of the basic status of a steam turbine generator according to claim 9, characterized in that: Also includes: Regularly analyze the historical static and dynamic characteristic status data of each key part, confirm the historical maintenance nodes of each key part and obtain the historical maintenance cycle between the historical maintenance nodes; Through intelligent algorithms, the future maintenance node of the next maintenance is predicted based on the time patterns of historical maintenance cycles.

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