AI-INTEGRATED EDGE DEVICE WITH PREDICTIVE POWER CONSUMPTION AND HEALTH RECOMMENDATIONS FOR PRECISE MAINTENANCE OF STEEL FIXED GANTRY MACHINES USING NRF AND XBEE WIRELESS INTRANET

Abstract

An ai-integrated edge device with predictive power consumption and health recommendations for precise maintenance of steel fixed gantry machines using nrf and xbee wireless intranet comprises AIPPCT Node, which has a Cortex A710 Processor Board, an nRF Module, a present current measurement sensor, a vibration sensor, temperature and pressure sensors, a buzzer, and a power supply, it obtains the operating parameters of the equipment in accordance, and transmits them wirelessly to a private cloud this enhances industrial surveillance and monitoring predictive maintenance the case of the AIPPCR Node, the data can be instantly sent to the operator’s smartphone as it consists of features such as a Cortex A710 Processor Board, an XBee RF Module, an nRF Module, a Touch Display and a buzzer which goes a step further by allowing the user to watch data in real time and receive notifications whenever any of the data change or an alert is triggered which increases the chances for operators to intervene before problems surface in the equipment.

Specification

Description:FIELD OF THE INVENTION
This invention relates to ai-integrated edge device with predictive power consumption and health recommendations for precise maintenance of steel fixed gantry machines using nrf and xbee wireless intranet.
BACKGROUND OF THE INVENTION
This system makes it possible to integrate the monitoring, analysis and predictive maintenance of systems into industrial applications. It consists of nodes designed for intercommunication which allow measuring environmental parameters like current, vibration, temperature, and pressure. The system wirelessly transfers the data to be stored on the proprietary cloud server and twos up the information for analysis by AI-powered algorithms for development of recommendation on the AI-powered cloud server. Admins and authorized operators can interact with the system employing a simple interface that allows web dashboards and integrated displays to provide real time information and alerts for the right decision to be made. This expansion resolution automates the operations and performs predictive maintenance accompanied with intelligent operations.
This project focuses on artificial intelligence of a lower class level, which is applicable in industrial environments where monitoring and maintenance of processes is essential as a breakdown can mean losses in terms of time period, productivity, and safety. In most cases, traditional approaches to maintenance prove reactive and result in sub-optimal breakdowns, wastage of resources, and numerous chances of improvement are lost. The invention employs these approaches also advances them in the sense of real-time data collection, AI based analysis and predictive maintenance allowing addressing those issues of early diagnosis of prospective problems, less downtime and improved efficiency of work processes. The system performs a key role in industry management by arming industries with the necessary data required for maintaining flexibility, security as well as cost-efficiency of asset management.
CN212020915U: The invention discloses a precise gantry cutting machine which comprises a gantry upper bracket, a support table and a controller, wherein the support table and the controller are positioned under the gantry upper bracket; the gantry upper bracket is provided with a hydraulic assembly system, and two ends of the gantry upper bracket are provided with positioning guide pillars matched with the hydraulic assembly system; wherein each positioning guide pillar is provided with a stability maintaining and limiting mechanism; a cutting die is fixedly arranged at the bottom of the gantry upper bracket; the operating board is fixed on the supporting platform in a sliding manner; a plurality of sliding rail plates are sequentially arranged at the bottom of the operating plate; the bottom of each support platform is provided with a sliding assembly in sliding fit with the sliding rail plate; a front operating rod is arranged right in front of the gantry upper bracket; the front operating rod is provided with a plurality of material sucking components; wherein, two ends of the front operating rod extend to be connected and fixed with the operating motor; wherein the operation motor is fixedly connected with the first moving device. The invention can timely separate the cutting materials and fine adjust to ensure the stability of the operation of the hydraulic system.
RESEARCH GAP: AI-driven predictive maintenance and real-time monitoring of industrial parameters with integrated GSM, nRF, and XBee modules for seamless connectivity and scalability is the novelty of the system.
CN101966650A: The invention relates to a numerical control machine tool, in particular to a numerical control gantry vertical combined machine tool which mainly solves the problem that the machine tool structure can not meet the requirements for high-efficiency precision finishing because milling and boring heads, grinding heads and other devices arranged on a cross beam of the traditional machine tool in the prior art can not make vertical precise feed motions. The numerical control gantry vertical combined machine tool comprises a base (1), a workbench (2) and upright columns (3). The numerical control gantry vertical combined machine tool is characterized in that the upright columns (3) are movably connected with a composite cross beam (4) by an upright column guide or are fixedly connected with the composite cross beam (4) by fasteners, the composite cross beam (4) is movably connected with more than two saddles (503) by a cross beam guide or is fixedly connected with more than two saddles (503) by fasteners, and the saddles are movably connected with a spindle device (5) by a ram guide; and the base, the upright columns, the composite cross beam and the spindle device are respectively provided with a screw rod driving device, and all the screw rod driving devices are connected with an electrical numerical control device.
RESEARCH GAP: AI-driven predictive maintenance and real-time monitoring of industrial parameters with integrated GSM, nRF, and XBee modules for seamless connectivity and scalability 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 industrial environment uses nodes of the system placed on strategic locations to measure electrical current, vibration, temperature and pressure within the processes. Each node collects real-time data through sensors located in nearby machines or production processes. The gathered information is in turn processed on site, then sent wirelessly to a remote custom developed cloud server via communication modules. This offers a guarantee of steady and uninterrupted data transfer process from the industrial framework to the cloud for further investigations. The storage, once conclusive investigation on data using ML algorithms is who also carry out an investigation on the server. That is, these algorithms operate raw data from sensors and traces certain trends and deviations to determine the equipment that may not operate properly or is inactive. Potential malfunction AI based systems of monitoring contribute to advanced analysis, hence the failure can be forecasted. Such a strategy focuses on how and when to conduct the maintenance activities required which minimizes unplanned downtimes and costs that follow.
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 industrial environment uses nodes of the system placed on strategic locations to measure electrical current, vibration, temperature and pressure within the processes. Each node collects real-time data through sensors located in nearby machines or production processes. The gathered information is in turn processed on site, then sent wirelessly to a remote custom developed cloud server via communication modules. This offers a guarantee of steady and uninterrupted data transfer process from the industrial framework to the cloud for further investigations. The storage, once conclusive investigation on data using ML algorithms is who also carry out an investigation on the server. That is, these algorithms operate raw data from sensors and traces certain trends and deviations to determine the equipment that may not operate properly or is inactive. Potential malfunction AI based systems of monitoring contribute to advanced analysis, hence the failure can be forecasted. Such a strategy focuses on how and when to conduct the maintenance activities required which minimizes unplanned downtimes and costs that follow.
Such processed data and insights are made available to operator and authorized personnel using intuitive interfaces like web dashboards and touch displays. The informed interfaces allow users to monitor the present state of the system, its past developments, as well as forecasting its performance. Notifications and advice are also received in a matter of seconds, making it easier for users to make informed decisions quickly. This combined working practice makes certain that the cycle of collecting the data and emitting the useful recommendations is performed in the most efficient way allowing the system to be an important instrument in the process of improving industrial effectiveness, safety, and ecological sustainability.
BEST METHOD OF WORKING
Using the AIPPCT Node, which has a Cortex A710 Processor Board, an nRF Module, a present current measurement sensor, a vibration sensor, temperature and pressure sensors, a buzzer, and a power supply, it obtains the operating parameters of the equipment in accordance, and transmits them wirelessly to a private cloud - this enhances industrial surveillance and monitoring predictive maintenance.
In the case of the AIPPCR Node, the data can be instantly sent to the operator's smartphone as it consists of features such as a Cortex A710 Processor Board, an XBee RF Module, an nRF Module, a Touch Display and a buzzer which goes a step further by allowing the user to watch data in real time and receive notifications whenever any of the data change or an alert is triggered which increases the chances for operators to intervene before problems surface in the equipment.
With regards to the Node AIPPCRG that has a Cortex A710 Processor Board, an XBee RF Module, a GSM Modem, a Buzzer and a Power Supply, distant locations such as, sites with no wireless broadband can also help transfer data to the cloud for monitoring purposes using GSM communication.
The task of wireless data exchange between transceivers and local infrastructure will be enabled through nRF Module, which is fitted to both AIPPCT and AIPPCR Nodes allowing for positive management and monitoring of decision making in an industrial scenario on a continuous basis.
The XBee RF Module integrated within the AIPPCR and AIPPCRG Nodes, guarantees reliable operative network data transmission, resulting in node-to-node communication as well as communication to a customized cloud server.
The Touch Display in the AIPPCR Node affords an interface that is very much appealing and simple yet allows the operators in a position to appreciate the status of the system through real time data representations and quickly respond to alarms to enhance operational control.
The GSM Modem in the node AIPPCRG makes it possible to operate the system from remote location and transmit data to the customized clouds server via GSM networks which is feasible in remote locations or locations with low infrastructure systems.
ADVANTAGES OF THE INVENTION
1. One of the integrated sensors in the nodes, such as the current, vibration, temperature, and pressure sensors, allows for precise and uninterrupted data acquisition for parameters, which renders the operational conditions under view at any time.
2. nRF and XBee RF modules are equally effective in relaying data between nodes wirelessly, hence reducing the wiring needed and enhancing the system's scalability.
3. Every node contains a Cortex-A710 processor board which performs the data acquisition and pushes it to the cloud where the ML algorithms detect patterns and forecast possible breakdowns thereby reducing suspended activities for repairs and maintenance.
4. Similarly, the improvements in system performance and receipt of the alarms from any place could enhance the quality and speed of decision-making with respect to the operations by the operators and authorized personnel through data presentation and analysis in web dashboards and integrated touch displays.
5. The incorporation of GSM modem in the AIPPCRG node extends its connectivity to remote areas where there can be no presence of Wi-Fi and this makes the system a versatile application ideal for diverse industrial settings.
6. Local alarming can also be done by the integrated buzzers in all the nodes so that whenever critical conditions arise, the alarms can prevent any harm or accidents by allowing time for intervention.
, Claims:1. An ai-integrated edge device with predictive power consumption and health recommendations for precise maintenance of steel fixed gantry machines using nrf and xbee wireless intranet comprises AIPPCT Node, which has a Cortex A710 Processor Board, an nRF Module, a present current measurement sensor, a vibration sensor, temperature and pressure sensors, a buzzer, and a power supply, it obtains the operating parameters of the equipment in accordance, and transmits them wirelessly to a private cloud this enhances industrial surveillance and monitoring predictive maintenance.
2. The device as claimed in claim 1, wherein the case of the AIPPCR Node, the data can be instantly sent to the operator's smartphone as it consists of features such as a Cortex A710 Processor Board, an XBee RF Module, an nRF Module, a Touch Display and a buzzer which goes a step further by allowing the user to watch data in real time and receive notifications whenever any of the data change or an alert is triggered which increases the chances for operators to intervene before problems surface in the equipment.
3. The device as claimed in claim 1, wherein with regards to the Node AIPPCRG that has a Cortex A710 Processor Board, an XBee RF Module, a GSM Modem, a Buzzer and a Power Supply, distant locations such as, sites with no wireless broadband can also help transfer data to the cloud for monitoring purposes using GSM communication.
4. The device as claimed in claim 1, wherein the task of wireless data exchange between transceivers and local infrastructure will be enabled through nRF Module, which is fitted to both AIPPCT and AIPPCR Nodes allowing for positive management and monitoring of decision making in an industrial scenario on a continuous basis.
5. The device as claimed in claim 1, wherein the XBee RF Module integrated within the AIPPCR and AIPPCRG Nodes, guarantees reliable operative network data transmission, resulting in node-to-node communication as well as communication to a customized cloud server.
6. The device as claimed in claim 1, wherein the Touch Display in the AIPPCR Node affords an interface that is very much appealing and simple yet allows the operators in a position to appreciate the status of the system through real time data representations and quickly respond to alarms to enhance operational control.
7. The device as claimed in claim 1, wherein the GSM Modem in the node AIPPCRG makes it possible to operate the system from remote location and transmit data to the customized clouds server via GSM networks which is feasible in remote locations or locations with low infrastructure systems.

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