A SX1278 RF AND CLOUD BASED ADDON MONITORING AND LOGGING DEVICE TO MONITOR THE ENERGY BY THE GAS TURBINE IN POWER PLANTS

Abstract

A sx1278 rf and cloud based addon monitoring and logging device to monitor the energy by the gas turbine in power plants comprises AMLDT_GTPMote (30), which is outfitted with an ATmega32 MCU Board (30F), an SX1278 RF Module (30A), a current sensor (30E), a voltage sensor (30D), a temperature sensor (30C), and a power supply (30B), is used to locally acquire and wirelessly transmit real-time data from gas turbine sensors the AMLDR_GTPMote, outfitted with an ATmega32 MCU Board, an SX1278 RF Module, an ESP8266 Wifi Board, an HMI Display, and a Power Supply, is utilized to establish a WiFi connection with the customized cloud server, this facilitates remote monitoring, presents real-time data on an HMI interface, and gives operators access to a secure web dashboard that offers insightful information on gas turbine performance.

Specification

Description:FIELD OF THE INVENTION
This invention relates to a sx1278 rf and cloud based addon monitoring and logging device to monitor the energy by the gas turbine in power plants.
BACKGROUND OF THE INVENTION
This cutting-edge monitoring and logging tool is essential to power plants because it makes it possible to follow and analyze gas turbine performance in real time. By use of well-positioned on-site sensors, the system reliably gathers vital information regarding voltage, current, and temperature fluctuations. A centralized cloud server receives the wirelessly transferred data for processing. In order to gain important insights into patterns of energy creation, machine learning algorithms are used here, such as Fast Fourier Transform analysis. Operators may quickly obtain processed data whether they are physically there or using a secure online dashboard from a distance. This helps in determining probable problems, comprehending general performance trends, and making well-informed decisions about the gas turbine's efficiency.
The way power plants are now operating presents difficulties for effectively managing and monitoring the performance of gas turbines, which is an essential component of producing energy. There aren't many comprehensive monitoring systems on the market today, which makes it difficult to get real-time insights into crucial variables like temperature fluctuations, voltage, and electrical current. This information is essential for assessing the gas turbine's condition, seeing possible problems, and maximizing its overall performance.
US7707818B2: An exhaust stack having a junction tube and a flue is provided. The flue has a silencer portion, a converging duct portion, a tubular portion, and a diverging diffuser portion. The silencer portion fluidly communicates with the junction tube. The silencer portion has a first hydraulic mean cross-sectional flow path, and the tubular portion has a second hydraulic mean cross-sectional flow path less than or equal to the first hydraulic mean cross-sectional flow path. The converging duct portion is coupled between the silencer portion and the tubular portion. The diverging diffuser portion is coupled to an end of the tubular portion opposite to the converging duct portion, such that exhaust gases flowing through the junction tube, the silencer portion, the converging duct portion, the tubular portion and the diverging diffuser portion have a reduced overall pressure drop, at least in part due to the diverging diffuser portion and the second hydraulic mean cross-sectional flow path being less than or equal to the first hydraulic mean cross-sectional flow path.
RESEARCH GAP: Monitoring and logging device for energy in Gas Turbine in Power Plants is the novelty of the system.
US8495858B2: A method of operating a gas turbine power plant including an auxiliary power output for reducing power plant emissions. A heat recovery steam generator receives an expanded working medium from a gas turbine and removes heat from the expanded working medium to form a reduced temperature exhaust gas and to generate steam from the heat removed from the expanded working medium. A steam turbine and generator assembly operates on the steam to produce an auxiliary plant output. A selective catalytic reduction (SCR) system is provided for receiving the reduced temperature exhaust gas; and an auxiliary fan is powered by the auxiliary plant output to supply dilution air for further reducing the temperature of the exhaust gas to prior to passing the exhaust gas through the SCR system.
RESEARCH GAP: Monitoring and logging device for energy in Gas Turbine in Power Plants is 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.
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.
The two-part AMLDT_GTPMote and AMLDR_GTPMote system is used by gas turbine monitoring and logging devices in power plants. On-site data collecting is handled by AMLDT_GTPMote, which is outfitted with an ATmega32 MCU Board, an SX1278 RF Module, and a number of sensors, including temperature, voltage, and current sensors. Critical performance factors of the gas turbine, like voltage levels, temperature fluctuations, and electrical current, are continuously monitored by these sensors. The SX1278 RF Module is used to transfer the collected data wirelessly once it has been locally processed on the ATmega32 MCU Board. However, AMLDR_GTPMote has extra parts for improved functionality and uses a comparable ATmega32 MCU Board and SX1278 RF Module. Internet access is made possible via an ESP8266 WiFi Board, which also connects the gadget to a cloud server that has been specially created for this breakthrough. This server acts as a central location for processing, storing, and retrieving data.
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.
The two-part AMLDT_GTPMote and AMLDR_GTPMote system is used by gas turbine monitoring and logging devices in power plants. On-site data collecting is handled by AMLDT_GTPMote, which is outfitted with an ATmega32 MCU Board, an SX1278 RF Module, and a number of sensors, including temperature, voltage, and current sensors. Critical performance factors of the gas turbine, like voltage levels, temperature fluctuations, and electrical current, are continuously monitored by these sensors. The SX1278 RF Module is used to transfer the collected data wirelessly once it has been locally processed on the ATmega32 MCU Board. However, AMLDR_GTPMote has extra parts for improved functionality and uses a comparable ATmega32 MCU Board and SX1278 RF Module. Internet access is made possible via an ESP8266 WiFi Board, which also connects the gadget to a cloud server that has been specially created for this breakthrough. This server acts as a central location for processing, storing, and retrieving data.
The cloud server analyzes incoming data using preset machine learning (ML) techniques, such as Fast Fourier Transform (FFT) analysis. This study provides important new information about the trends of energy generation by gas turbines throughout time. After processing, the data is available on a web dashboard with a personalized user experience. In parallel, the AMLDR_GTPMote provides a local view of the gas turbine's performance by projecting real-time data onto a Human-Machine Interface (HMI) Display. With this dual-display setup, operators may monitor remotely via the web dashboard and have instant access to vital information on-site. Operators can safely access the online dashboard by logging in with their credentials and learning about the energy generation and performance trends of the gas turbine.
BEST METHOD OF WORKING
To enable on-site monitoring and contribute to the thorough analysis of energy generation in power plants, the AMLDT_GTPMote, which is outfitted with an ATmega32 MCU Board, an SX1278 RF Module, a current sensor, a voltage sensor, a temperature sensor, and a power supply, is used to locally acquire and wirelessly transmit real-time data from gas turbine sensors.
The AMLDR_GTPMote, outfitted with an ATmega32 MCU Board, an SX1278 RF Module, an ESP8266 Wifi Board, an HMI Display, and a Power Supply, is utilized to establish a WiFi connection with the customized cloud server. This facilitates remote monitoring, presents real-time data on an HMI interface, and gives operators access to a secure web dashboard that offers insightful information on gas turbine performance.
The central processing unit in both the AMLDT_GTPMote and AMLDR_GTPMote is the ATmega32 MCU Board, which is integrated into both motes. It effectively manages control and data processing tasks, guaranteeing smooth operation and communication within the gas turbine monitoring and logging system.
The AMLDR_GTPMote-interfaced HMI Display serves as a local operator interface, offering real-time visualization of gas turbine performance and data, supporting on-site monitoring, and improving user interaction within the power plant's extensive monitoring and logging system.
The AMLDT_GTPMote and AMLDR_GTPMote can communicate wirelessly thanks to the SX1278 RF Module, which is also included in both motes. This allows vital data to be transmitted in real time from on-site gas turbine sensors to the cloud server, assisting in the thorough monitoring and analysis of energy generation in power plants.
The temperature, voltage, and current sensors are all connected to the AMLDT_GTPMote and are used to continuously monitor the electrical current, voltage levels, and temperature variations of the gas turbine. This real-time data is vital for thorough analysis and effective management of energy generation in power plants.
The AMLDR_GTPMote's integrated ESP8266 WiFi Board is used to enable internet connectivity. This connection allows the device to connect to the customized cloud server, enabling data transmission and remote monitoring. Additionally, the device offers operators real-time insights into gas turbine performance through a secure web dashboard.
ADVANTAGES OF THE INVENTION
1. One key component of this novel approach is the AMLDT_GTPMote, which wirelessly gathers and transmits real-time data from gas turbine sensors, including temperature, voltage, and current. This feature makes on-site monitoring easier and adds to the thorough examination of energy generation in power plants.
2. The AMLDR_GTPMote improves upon this innovation even more by connecting via WiFi to the dedicated cloud server. With the use of a secure web dashboard, operators can view real-time data on an HMI interface, monitor remotely, and gain vital insights into the functioning of gas turbines.
3. AMLDR_GTPMote's HMI Display provides operators with a localized interface that allows them to view data and performance information for gas turbines in real time. This facilitates user involvement within the power plant's complete monitoring and logging system and adds to on-site monitoring.
4. By enabling wireless connection between AMLDT_GTPMote and AMLDR_GTPMote, the SX1278 RF Module makes it possible to transmit vital data from on-site gas turbine sensors to the cloud server in real time. The thorough monitoring and analysis of energy generation in power plants is greatly aided by this technique.
5. The AMLDT_GTPMote's integration of the Current, Voltage, and Temperature sensors is essential for the continuous monitoring of the gas turbine's important characteristics. These sensors provide vital real-time data for thorough analyses and effective management of energy generation in power plants by tracking electrical current, voltage levels, and temperature fluctuations.
6. The ESP8266 Wifi Board's integration with AMLDR_GTPMote makes it possible for the device to connect to the internet and connect to the customized cloud server. Through a secure web dashboard, this functionality makes it easier to monitor and transfer data remotely while giving operators real-time insights into the performance of gas turbines.
, Claims:1. A sx1278 rf and cloud based addon monitoring and logging device to monitor the energy by the gas turbine in power plants comprises AMLDT_GTPMote (30), which is outfitted with an ATmega32 MCU Board (30F), an SX1278 RF Module (30A), a current sensor (30E), a voltage sensor (30D), a temperature sensor (30C), and a power supply (30B), is used to locally acquire and wirelessly transmit real-time data from gas turbine sensors.
2. The device as claimed in claim 1, wherein the AMLDR_GTPMote, outfitted with an ATmega32 MCU Board, an SX1278 RF Module, an ESP8266 Wifi Board, an HMI Display, and a Power Supply, is utilized to establish a WiFi connection with the customized cloud server, this facilitates remote monitoring, presents real-time data on an HMI interface, and gives operators access to a secure web dashboard that offers insightful information on gas turbine performance.
3. The device as claimed in claim 1, wherein the central processing unit in both the AMLDT_GTPMote and AMLDR_GTPMote is the ATmega32 MCU Board, which is integrated into both motes, it effectively manages control and data processing tasks, guaranteeing smooth operation and communication within the gas turbine monitoring and logging system.
4. The device as claimed in claim 1, wherein the AMLDR_GTPMote-interfaced HMI Display serves as a local operator interface, offering real-time visualization of gas turbine performance and data, supporting on-site monitoring, and improving user interaction within the power plant's extensive monitoring and logging system.
5. The device as claimed in claim 1, wherein the AMLDT_GTPMote and AMLDR_GTPMote communicate wirelessly thanks to the SX1278 RF Module, which is also included in both motes, this allows vital data to be transmitted in real time from on-site gas turbine sensors to the cloud server, assisting in the thorough monitoring and analysis of energy generation in power plants.
6. The device as claimed in claim 1, wherein the temperature, voltage, and current sensors are all connected to the AMLDT_GTPMote and are used to continuously monitor the electrical current, voltage levels, and temperature variations of the gas turbine, this real-time data is vital for thorough analysis and effective management of energy generation in power plants.
7. The device as claimed in claim 1, wherein the AMLDR_GTPMote's integrated ESP8266 WiFi Board is used to enable internet connectivity, this connection allows the device to connect to the customized cloud server, enabling data transmission and remote monitoring, additionally, the device offers operators real-time insights into gas turbine performance through a secure web dashboard.

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