A SYSTEM OF IOT-ENABLED 3-AXIS VIBRATION MONITORING AND FFT ANALYSIS FOR BORING MILL-STYLE VERTICAL LATHE MACHINES IN STEEL INDUSTRIES

Abstract

A system of IoT-Enabled 3-Axis Vibration Monitoring and FFT Analysis for Boring Mill-Style Vertical Lathe Machines in Steel Industries comprises a TAVMT_BMSVLNode (100), which integrates advanced sensors, cloud-based machine learning, and an intuitive user interface for proactive maintenance and increased operational efficiency, is utilized to facilitate real-time 3-Axis vibration monitoring and FFT analysis for Boring Mill-Style Vertical Lathe Machines in the steel industry; and it is outfitted with a Raspberry Pi Processor Board (100F), GSM Modem (100A), GPS Modem (100D), Precise Triple Axis Accelerometer (100C), HMI Display (100E), and Power supply (100B). The Raspberry Pi Processor Board processes data from the Precise Triple Axis Accelerometer and coordinates the information's real-time transmission to a dedicated cloud server, allowing for sophisticated analysis and smooth connectivity for thorough 3-Axis vibration monitoring and FFT analysis in Boring Mill-Style Vertical Lathe Machines used in the steel industry. The GSM modem, which is also a part of the TAVMT_BMSVLNode, is utilized to facilitate smooth communication; and it permits the real-time transfer of processed 3-Axis vibration data from Vertical Lathe Machines in the Boring Mill style to a dedicated cloud server, guaranteeing prompt monitoring and analysis in the steel sector.

Specification

Description:FIELD OF THE INVENTION
This invention relates to A system of IoT-Enabled 3-Axis Vibration Monitoring and FFT Analysis for Boring Mill-Style Vertical Lathe Machines in Steel Industries.
BACKGROUND OF THE INVENTION
One of the biggest challenges facing the steel industry is effectively monitoring and maintaining the operational health of Boring Mill-Style Vertical Lathe Machines. Existing methods sometimes do not have real-time capabilities and comprehensive analysis tools, which results in delayed detection of possible issues and increased downtime. Conventional monitoring systems do not have an interface that is easy to use for operators who are located remotely or on-site. Moreover, the lack of sophisticated analytics and machine learning hinders the ability to anticipate and address important problems in advance, leading to less than ideal performance and increased maintenance costs.
US7062999B2 provides an inverted vertical lathe comprising a device for replacing collets automatically, and having a detector for detecting that the collet has been gripped correctly. A chuck mounted on a headstock grips a collet in a replaceable manner via a tapered bore provided to the end thereof. A collet end face eccentricity detector comprises a detecting member (sensor) fixed to the end of an arm. The detecting member detects the eccentricity of the end face of the collet in a contactless manner. A variation pattern of the eccentricity occurring when each collet is gripped correctly by the chuck on the main spindle is detected in advance, and this pattern is compared with the variation pattern of the eccentricity detected by the present detection, and thus, whether or not the collet has been gripped correctly is detected.
Research Gap: A n innovation with IoT and Cloud technology for 3-Axis Vibration Monitoring and FFT Analysis for Boring Mill-Style Vertical Lathe Machines is the novelty of the system.
JPH06114602A discloses a plurality of spindle tables are installed on a bed 1 in such a sway that spindle axes are situated parallel, and a tool rest supporting table is installed on the bed 1 positioned ahead of the spindle tables, and on this supporting table, mounting is made in such a way as mating with the respective spindles. A plurality of tool rests is furnished which are arranged movable independently in the first direction perpendicular to the corresponding spindle axis. Therein the spindle tables or tool rests are relatively movable independently in the spindle axis direction, and processing spaces are provided between the spindle and the tool rest mating with the applicable spindle.
Research Gap: An innovation with IoT and Cloud technology for 3-Axis Vibration Monitoring and FFT Analysis for Boring Mill-Style Vertical Lathe Machines 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.
The innovative system plays a pivotal role in the steel sector by enabling precise and instantaneous tracking of 3-Axis vibrations in Vertical Lathe Machines designed for Boring Mills. By combining cutting-edge sensors with cloud-based machine learning, the system continuously collects and evaluates vibration data, making it easier to spot potential problems or anomalies in machine performance early on. With an intuitive interface that is available from both on-site and distant locations, the system provides a thorough picture of the state of the machinery and delivers critical notifications.
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.
In the steel sector, the TAVMT_BMSVLNode provides a complete solution for 3-Axis Vibration Monitoring and FFT Analysis in Boring Mill-Style Vertical Lathe Machines. The Raspberry Pi Processor Board, GPS, GSM, and HMI displays, along with a precise triple axis accelerometer and power supply, are the main parts of this invention. Together, these components create an advanced system for tracking and evaluating the performance of machinery. This invention revolves around the Precise Triple Axis Accelerometer, which records precise vibration data from vertical lathe machines. As the main processing unit, the Raspberry Pi Processor Board processes this data. The GSM Modem is then used to send the processed data in real-time to a dedicated cloud server, guaranteeing uninterrupted connectivity even in remote areas. A GPS modem is included to enable precise location tracking and to provide context for the recorded data. The vibration data is analyzed by cloud-based machine learning algorithms as soon as it gets to the cloud server. These algorithms look at the data over time, using a timer and FFT analysis to find frequency patterns linked to vibrations in the equipment. By incorporating machine learning, the system gains intelligence and gains the ability to identify regular patterns of operation as well as anomalies or serious problems. Critical alerts and other analytical results are disseminated via a variety of ways. For on-site operators, the HMI Display provides a real-time visualization of the machine's state. In addition, a personalized web dashboard that may be accessed via user accounts enables distant observation and analysis. Not only are critical alerts shown on these interfaces, but operators are notified via email as soon as possible. This comprehensive strategy guarantees that pertinent staff members are instantly notified of any possible problems, facilitating quick action and preventive maintenance.
ADVANTAGES OF THE INEVENTION
1. The TAVMT_BMSVLNode, which enables real-time 3-Axis vibration monitoring and FFT analysis for Boring Mill-Style Vertical Lathe Machines in the steel sector, is a key component of this achievement. To enable preventative maintenance and boost operational effectiveness, it integrates cutting-edge sensors, cloud-based machine learning, and an intuitive user interface.
2. A key component of this invention is the GSM modem, which provides smooth communication for the real-time transfer of processed 3-Axis vibration data from vertical lathe machines in the Boring Mill style to a dedicated cloud server. In the steel sector, this guarantees timely monitoring and analysis.
3. By offering precise location tracking and contextual information for recorded 3-Axis vibration data from Boring Mill-Style Vertical Lathe Machines, the GPS Modem improves this innovation. This advances a thorough knowledge of the operation of machines in the steel sector.
4. A key component of this innovation is the Precise Triple Axis Accelerometer, which records detailed vibration data from vertical lathe machines in the style of a boring mill. The Raspberry Pi Processor Board then processes this data for FFT analysis and real-time 3-Axis vibration monitoring in the steel sector.
5. The HMI Display is essential because it provides on-site operators with a real-time visual representation of machine conditions and important alerts. This improves situational awareness for Boring Mill-Style Vertical Lathe Machines in the steel sector during 3-Axis vibration monitoring and FFT analysis.
, Claims:1. A system of IoT-Enabled 3-Axis Vibration Monitoring and FFT Analysis for Boring Mill-Style Vertical Lathe Machines in Steel Industries comprises a TAVMT_BMSVLNode (100), which integrates advanced sensors, cloud-based machine learning, and an intuitive user interface for proactive maintenance and increased operational efficiency, is utilized to facilitate real-time 3-Axis vibration monitoring and FFT analysis for Boring Mill-Style Vertical Lathe Machines in the steel industry; and it is outfitted with a Raspberry Pi Processor Board (100F), GSM Modem (100A), GPS Modem (100D), Precise Triple Axis Accelerometer (100C), HMI Display (100E), and Power supply (100B).
2. The system as claimed in claim 1, wherein Raspberry Pi Processor Board processes data from the Precise Triple Axis Accelerometer and coordinates the information's real-time transmission to a dedicated cloud server, allowing for sophisticated analysis and smooth connectivity for thorough 3-Axis vibration monitoring and FFT analysis in Boring Mill-Style Vertical Lathe Machines used in the steel industry.
3. The system as claimed in claim 1, wherein the GSM modem, which is also a part of the TAVMT_BMSVLNode, is utilized to facilitate smooth communication; and it permits the real-time transfer of processed 3-Axis vibration data from Vertical Lathe Machines in the Boring Mill style to a dedicated cloud server, guaranteeing prompt monitoring and analysis in the steel sector.
4. The system as claimed in claim 1, wherein Accurate location tracking and contextual information for the recorded 3-Axis vibration data from Boring Mill-Style Vertical Lathe Machines are provided by the GPS modem integrated into TAVMT_BMSVLNode, which helps to provide a thorough understanding of machinery performance in the steel industry.
5. The system as claimed in claim 1, wherein to process detailed vibration data from Boring Mill-Style Vertical Lathe Machines for real-time 3-Axis vibration monitoring and FFT analysis in the steel industry, the Raspberry Pi Processor Board processes the data obtained from the Precise Triple Axis Accelerometer that is integrated into the TAVMT_BMSVLNode.
6. The system as claimed in claim 1, wherein the HMI Display, which is interfaced on the TAVMT_BMSVLNode, is utilized to improve situational awareness during 3-Axis vibration monitoring and FFT analysis for Boring Mill-Style Vertical Lathe Machines in the steel industry by giving on-site operators a real-time visualization of critical alerts and machine conditions.
7. The system as claimed in claim 1, wherein the TAVMT_BMSVLNode's externally plugged power supply is employed to offer effective electrical energy, ensuring a steady and dependable operation.

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