WPAN-BASED HEALTH MONITORING OF SYNCHRONOUS GENERATOR IN POWER PLANTS WITH CLOUD INTEGRATION

Abstract

A WPAN-Based Health Monitoring of Synchronous Generator in Power Plants with Cloud Integration A cutting-edge WPAN-based health monitoring system for synchronous generators integrates a WPHMT_SGNode with a TI MSP430 MCU, XBee RF Module, MEMS Vibration Sensor, Metallic Temperature Sensor, and Pressure Sensor for real-time data collection. The system also features a WPHMR_SGNode equipped with a TI MSP430 MCU, XBee RF Module, ESP32 WiFi Module, and HMI Display for seamless wireless communication and remote monitoring. The collected data is transmitted to a cloud server, where advanced machine learning algorithms analyze it to provide actionable insights, critical alerts, and trend-based analytics. This innovation ensures proactive maintenance, reduced downtime, and enhanced operational efficiency in power plants.

Specification

Description:FIELD OF THE INVENTION
This invention relates to WPAN-Based Health Monitoring of Synchronous Generator in Power Plants with Cloud Integration
BACKGROUND OF THE INVENTION
This innovation is an inventive attempt to tackle the problem of efficiently and effectively monitoring synchronous generators in power plants. Because traditional monitoring techniques frequently don't have real-time capabilities, it might be difficult to identify possible problems before they become expensive failures or disruptions to operations.
CN109167545B - The invention relates to the technical field of flux linkage online identification, in particular to a permanent magnet synchronous generator flux linkage online identification method and system, wherein the permanent magnet synchronous generator flux linkage online identification method comprises the following steps of acquiring a current Q-axis instruction voltage value, a real current value and a rotating speed value of a permanent magnet synchronous generator of a machine side converter unit in a current running state; calculating a back electromotive force value according to a stator voltage equation, and averaging or obtaining a stable equivalent back electromotive force by adopting a low-pass filter; and calculating the flux linkage of the permanent magnet according to the equivalent back electromotive force under different rotating speeds and a differential elimination method. According to the method, the flux linkage and back electromotive force relation of the stator voltage equation of the permanent magnet synchronous generator is utilized, the real stator command voltage at the permanent magnet synchronous generator end is obtained through the voltage reconstruction theory and distortion compensation, the rotor resistance value is corrected by adopting the rotor temperature-resistance relation curve, the permanent magnet flux linkage is obtained through calculation, and the accuracy of permanent magnet synchronous generator flux linkage identification is improved.
Research Gap:A WPAN based wireless Solution for the health monitoring of Synchronous Generator in Power Plantsis the novelty of the system.
JPH10229686A - Synchronous generators are started individually, by outputting the AC voltage of a variable frequency to the terminal circuit of the synchronous generator by thyristor starters, provided separately for each of plural synchronous generator. Then, when any of the thyristors becomes faulty, a connection switch switches a connection and supplies to the terminal circuit of the synchronous generator which the faulty thyristor starter should have started, an AV voltage of variable frequency from other sound thyristor starter. Hereby, the reliability for the start of the synchronous generator is improved.
Research Gap: A WPAN based wireless Solution for the health monitoring of Synchronous Generator in Power Plantsis the novelty of the system.
SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention.
This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
With its novel use of wireless sensor nodes and seamless cloud integration, this development completely changes the way synchronous generator health monitoring is done at power plants. It makes it possible to continuously monitor vital indicators like pressure, temperature, and vibration, which helps to identify possible problems early. The sensor nodes gather data, which is effectively transferred to a specialized cloud server where sophisticated machine learning algorithms process it and produce insightful analysis. To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein:
FIGURE 1: SYSTEM ARCHITECTURE
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms "a"," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In addition, the descriptions of "first", "second", "third", and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
This cutting-edge system combines machine learning techniques, cloud computing, and wireless sensor nodes to enable proactive synchronous generator health monitoring in power plants. WPHMT_SGNode and WPHMR_SGNode are the two nodes that make up the system. The data acquisition unit, or WPHMT_SGNode, is furnished with a number of sensors, such as a metallic temperature sensor, a pressure sensor, and a MEMS vibration sensor. These sensors are arranged in a deliberate manner to gather vital indicators of the generator's health. The node is powered by a TI MSP430 MCU board and uses an XBee RF module for wireless communication. The WPHMT_SGNode gathers real-time data on the operational characteristics of the generator through continuous monitoring. The WPHMR_SGNode serves as both the hub for data communication and visualization at the same time. For wireless communication, it combines an ESP32 Wi-Fi module, an XBee RF module, and a TI MSP430 MCU board. It also has an EEPROM for local data storage and an HMI display.
Data sent by the WPHMT_SGNode is received by the WPHMR_SGNode, which prepares it for visualization. The node can communicate with the customized cloud server by connecting to the internet thanks to the ESP32 Wi-Fi module. The synchronized generator nodes' data is intended to be received, stored, and analyzed by the cloud server. The cloud server uses pre-programmed machine learning algorithms to examine the data it receives and derive valuable insights. Trending data charts, real-time data visualization, and generator condition monitoring are some of these insights. Based on the study, critical notifications are produced that point out possible problems or irregularities in the generator's performance. Operators are then shown the data analysis results via a variety of interfaces. The WPHMR_SGNode's HMI display offers on-site visualization for real-time monitoring. Additionally, operators can view extensive reports and insights remotely through a local web dashboard that is available over the internet. Operators can obtain real-time data, trending charts, and crucial warnings by entering into their accounts. This empowers them to make well-informed decisions on maintenance and operation strategies.
BEST METHOD OF WORKING
1. Data acquisition is accomplished by the WPHMT_SGNode, which is outfitted with a TI MSP430 MCU Board, an XBee RF Module with Patch, a MEMS vibration sensor, a metallic temperature sensor, a pressure sensor, an RTC module, and a power supply. This allows for proactive maintenance and the early identification of potential problems by collecting real-time data from sensors monitoring critical parameters of the synchronous generator in power plants.
2. The WPHMR_SGNode is a data communication and visualization receiver that is outfitted with a TI MSP430 MCU Board, an XBee RF Module with Patch, an ESP32 WiFi Module, an HMI display, an EEPROM, and a power supply. It enables the wireless transmission of data gathered by the WPHMT_SGNode to a customized cloud server and gives operators access to local displays and web dashboards for real-time insights and alerts.
3. The invention for synchronous generator health monitoring in power plants uses the TI MSP430 MCU Board, which is integrated inside both of the motes, as its core processing unit. This allows for data gathering, processing, and communication features within the nodes.
4. The innovation's XBee RF Module with Patch, which is also integrated into both of the motes, is used to enable dependable wireless communication between the nodes, enabling the smooth transfer of sensor data for real-time synchronous generator health monitoring and analysis in power plants.
5. The Metallic Temperature Sensor, Pressure Sensor, and MEMS Vibration Sensor are all connected to the WPHMT_SGNode and work together to monitor the synchronous generator's critical parameters. They provide real-time data on temperature fluctuations, pressure fluctuations, and vibration levels for proactive health monitoring and the early identification of possible problems with power plant operations.
6. The WPHMR_SGNode's integrated ESP32 WiFi Module is used to enable wireless internet connectivity, enabling communication between the innovation's nodes and the custom cloud server for smooth data transmission, analysis, and remote synchronous generator health monitoring in power plants.
7. Operators can visualize real-time data, critical alerts, and trending charts on-site with the help of the HMI Display interfaced on WPHMR_SGNode. This improves situational awareness and makes it possible to make well-informed decisions about the performance and health of synchronous generators in power plants.
ADVANTAGES OF THE INVENTION
1. The primary data acquisition unit, or WPHMT_SGNode, gathers data in real time from a range of sensors that keep an eye on important synchronous generator parameters in power plants. Proactive maintenance and the early identification of possible problems are made possible by this capacity.
2. The WPHMR_SGNode serves as the primary hub for communication and visualization, enabling the wireless transfer of data collected by the WPHMT_SGNode to a dedicated cloud server. Additionally, this node offers operators real-time insights and alarms through web-based dashboards and local displays.
3. The system's nodes are guaranteed to communicate wirelessly and seamlessly thanks to the XBee RF Module with Patch. This technology makes it possible for sensor data to be reliably sent, which makes it easier to monitor and analyze the condition of synchronous generators in power plants in real time.
4. The system thoroughly monitors vital synchronous generator characteristics thanks to its MEMS vibration sensor, metallic temperature sensor, and pressure sensor. This sensor array provides real-time data on temperature swings, pressure variations, and vibration levels, enabling proactive health monitoring and early problem detection in power plant operations.
5. The ESP32 WiFi Module offers necessary internet wireless access. With the help of this functionality, system nodes and the assigned cloud server may communicate with ease, allowing for effective data transmission, analysis, and remote monitoring of the health of synchronous generators in power plants.
The system provides operators with a clear on-site representation of real-time data, important alarms, and trending charts through its user-friendly HMI Display. By enabling operators to make knowledgeable judgments on the condition and functionality of synchronous generators in power plants, this feature improves situational awareness.
, Claims:1. A WPAN-Based Health Monitoring of Synchronous Generator in Power Plants with Cloud Integration system, comprises a WPHMT_SGNode (101) equipped with a TI MSP430 MCU Board (102), XBee RF Module with Patch (103), MEMS Vibration Sensor (104), Metallic Temperature Sensor (105), Pressure Sensor (106), RTC Module (107), and Power Supply (108), and a WPHMR_SGNode (201) equipped with a TI MSP430 MCU Board (202), XBee RF Module with Patch (203), ESP32 WiFi Module (204), HMI Display (205), EEPROM (206), and Power Supply (207). Together, these nodes enable real-time data collection, monitoring, and wireless communication with a customized cloud server for proactive maintenance and operational efficiency in power plants.
2. The system, as claimed in Claim 1, wherein the XBee RF Module with Patch (103, 203) facilitates seamless wireless communication between WPHMT_SGNode and WPHMR_SGNode, ensuring reliable data transmission for real-time synchronous generator health monitoring and analysis.
3. The system, as claimed in Claim 1, wherein the MEMS Vibration Sensor (104), Metallic Temperature Sensor (105), and Pressure Sensor (106) integrated into WPHMT_SGNode provide comprehensive monitoring of critical synchronous generator parameters, enabling early detection of temperature, vibration, and pressure anomalies.
4. The system, as claimed in Claim 1, wherein the ESP32 WiFi Module (204) in WPHMR_SGNode ensures seamless internet connectivity, facilitating remote monitoring and data synchronization with a cloud server for advanced analysis and insights.
5. The system, as claimed in Claim 1, wherein the RTC Module (107) ensures precise timekeeping, enabling the chronological recording of sensor data for trend-based analysis and operational decision-making.
6. The system, as claimed in Claim 1, wherein the HMI Display (205) interfaced with WPHMR_SGNode provides operators with real-time visualization of data, critical alerts, and trending charts, enhancing situational awareness and decision-making.
7. The system, as claimed in Claim 1, wherein the cloud server processes data transmitted from the nodes using advanced machine learning algorithms, generating actionable insights, real-time notifications, and detailed reports to improve operational reliability and efficiency.

Documents