CLOUD-INTEGRATED IOT DEVICE FOR ONLINE VIBRATION FFT ANALYSIS AND TRENDING DATA ANALYSIS IN BED-TYPE TURRET MILLING MACHINE AT A METAL PLANT

Abstract

A cloud-integrated iot device for online vibration fft analysis and trending data analysis in bed-type turret milling machine at a metal plant comprises CIID_TMMTMote (51a), which is outfitted with an STM32 board (56f), CC3000 RF module (52b), vibration sensor (54d), RTC module (55e), and power supply (53c), it actively gathers real-time vibration data from the Bed-Type Turret Milling Machine and uses FFT analysis in conjunction with a Real-Time Clock module to offer vital insights into the mechanical condition of the machine, enabling proactive maintenance and maximizing operational performance the critical components of the Bed-Type Turret Milling Machine are the CIID_TMMRMote, which is outfitted with a used STM32 board, CC3000 RF module, ESP32 Wifi board, SD Card Module, and Power Supply, an ESP32 Wifi board allows for internet connectivity, a customized web dashboard allows for remote monitoring, and an SD Card Module stores analyzed data with timestamps to improve accessibility and historical performance tracking.

Specification

Description:FIELD OF THE INVENTION
This invention relates to cloud-integrated iot device for online vibration fft analysis and trending data analysis in bed-type turret milling machine at a metal plant.
BACKGROUND OF THE INVENTION
The maintenance plan and operational effectiveness of Bed-Type Turret Milling Machines in metal industries are greatly enhanced by this novel approach. By utilizing state-of-the-art monitoring technologies, the system obtains vibration data in real time from the milling machine and analyzes it using Fourier transform (FFT) techniques, thereby enabling timely identification of any mechanical anomalies. Operators may easily access the results of this research and trending data through an intuitive web dashboard, which facilitates remote monitoring and prompt decision-making. Moreover, this data is precisely captured and timestamped by the system onto an SD card, which simplifies historical analysis for preventive maintenance. This all-encompassing strategy gives plant managers the ability to proactively address possible problems, save downtime, and maximize the milling machines' lifespan and overall performance. As such, it makes a substantial contribution to increased efficiency and economy in the processes involved in the production of metals.
It is challenging for the metal manufacturing industry to effectively monit or and maintain the performance of Bed-Type Turret Milling Machines. Traditional maintenance techniques often lead to unplanned downtime, increased repair costs, and inefficiencies in operations.
CN103962602B: Patent of the present invention discloses a kind of numerical control multi-shaft gantry drilling and milling machine tool, including a gantry, is arranged below at described gantry and workpiece can be made at the X-direction of horizontal plane and a lathe bed of Y-direction motion;Described lathe bed is provided with the clamping device for clamping workpiece, the most hard-wired gantry frame in described lathe bed top is provided with gang drill, described gang drill includes multiple drilling-milling apparatus, described drilling-milling apparatus is driven its in the vertical direction to move up and down by two-stage power set, the two-stage realizing vertical range between drilling-milling apparatus and workpiece adjusts, and drilling-milling apparatus is driven it to rotate by same set of driving means.The present invention substantially increases high-volume and bores the operating efficiency of Milling Machining, reduces the gap with advanced country.
RESEARCH GAP: Cloud And IoT integrated Solution with FFT analysis for Bed-Type Turret Milling Machine with in industry is the novelty of the system.
US10239131B2: The present invention relates to embodiments of a machine tool, in particular a multi-spindle milling machine, comprise a machine frame, a workpiece clamping device for clamping a workpiece, an axis slide assembly arranged on the machine frame, and a spindle carrier assembly which is arranged on the machine frame and has at least two tool-carrying work spindles. The axis slide assembly is configured to linearly move the workpiece clamped at the workpiece clamping device by way of three controllable linear axes X, Y and Z. The work spindles are arranged at a turret which can be rotated or swiveled about a turret axis at respectively equal distance from the turret axis, and the spindle axes of the work spindles are aligned or can be aligned in parallel to one another and in parallel to the turret axis.
RESEARCH GAP: Cloud And IoT integrated Solution with FFT analysis for Bed-Type Turret Milling Machine with in industry 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 key elements of the innovation are CIID_TMMTMote and CIID_TMMRMote, which are intended to be used in metal facilities for the purpose of monitoring Bed-Type Turret Milling Machines. The STM32 board, CC3000 RF module, vibration sensor, RTC module, and power supply are all integrated into the CIID_TMMTMote. A STM32 board, CC3000 RF module, ESP32 WiFi board, SD Card Module, and Power Supply are used by its equivalent, CIID_TMMRMote. Together, these gadgets allow for real-time milling machine condition monitoring and analysis. Real-time vibration data is captured by the Vibration Sensor in the CIID_TMMTMote from the milling machine. The STM32 board uses FFT Analysis, a mathematical algorithm that breaks complex signals down into frequency components, to process the vibration data. This examination provides information about the mechanical state of the machine by pointing out anomalies or irregularities. To track changes over time, the RTC Module makes sure that time stamps are correct.
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 key elements of the innovation are CIID_TMMTMote and CIID_TMMRMote, which are intended to be used in metal facilities for the purpose of monitoring Bed-Type Turret Milling Machines. The STM32 board, CC3000 RF module, vibration sensor, RTC module, and power supply are all integrated into the CIID_TMMTMote. A STM32 board, CC3000 RF module, ESP32 WiFi board, SD Card Module, and Power Supply are used by its equivalent, CIID_TMMRMote. Together, these gadgets allow for real-time milling machine condition monitoring and analysis. Real-time vibration data is captured by the Vibration Sensor in the CIID_TMMTMote from the milling machine. The STM32 board uses FFT Analysis, a mathematical algorithm that breaks complex signals down into frequency components, to process the vibration data. This examination provides information about the mechanical state of the machine by pointing out anomalies or irregularities. To track changes over time, the RTC Module makes sure that time stamps are correct.
Transmission and storage of data are the main foci of CIID_TMMRMote. By enabling internet access, the ESP32 WiFi board makes it possible to remotely monitor machines via a personalized online interface. While the SD Card Module retains the analyzed data together with timestamps, the CC3000 RF module guarantees dependable connection between the devices. This two-pronged strategy of data storage and real-time monitoring offers both historical performance data and instant insights into the milling machine's operation. The findings of the Trending Data Analysis and FFT Analysis can be seen visually through the online dashboard's user-friendly design. By enabling remote monitoring of CIID_TMMRMote, operators may improve overall operating efficiency from any place. The SD card's stored data enables comprehensive analysis, trend detection, and predictive maintenance scheduling based on past performance trends.
BEST METHOD OF WORKING
A key element of this innovation is the CIID_TMMTMote, which is outfitted with an STM32 board, CC3000 RF module, vibration sensor, RTC module, and power supply. It actively gathers real-time vibration data from the Bed-Type Turret Milling Machine and uses FFT analysis in conjunction with a Real-Time Clock module to offer vital insights into the mechanical condition of the machine, enabling proactive maintenance and maximizing operational performance.
The critical components of the Bed-Type Turret Milling Machine are the CIID_TMMRMote, which is outfitted with a used STM32 board, CC3000 RF module, ESP32 Wifi board, SD Card Module, and Power Supply. An ESP32 Wifi board allows for internet connectivity, a customized web dashboard allows for remote monitoring, and an SD Card Module stores analyzed data with timestamps to improve accessibility and historical performance tracking.
The STM32 board is integrated with CIID_TMMTMote, which acts as the central processing unit. It effectively manages and processes data from the vibration sensor and makes FFT analysis easier in the mote. This helps with the Bed-Type Turret Milling Machine's condition monitoring and analysis in real-time.
The CIID_TMMTMote and CIID_TMMRMote can exchange data easily thanks to the CC3000 RF module, which is integrated with both motes and serves as a dependable communication link between them. This enhances the overall efficacy of the Bed-Type Turret Milling Machine real-time condition monitoring and analysis system.
The Vibration Sensor, which is integrated with CIID_TMMTMote, is crucial to the acquisition of real-time vibration data from the Bed-Type Turret Milling Machine. It offers vital information for FFT analysis and facilitates accurate mechanical condition monitoring of the machine.
The Bed-Type Turret Milling Machine's FFT analysis and real-time condition monitoring depend on the precise timestamping of data in the Mote, which is made possible by the integration of the RTC Module with CIID_TMMTMote. This improves the accuracy of maintenance planning and performance analysis.
The Bed-Type Turret Milling Machine may be remotely monitored via a customized web dashboard thanks to the ESP32 Wifi board's integration of CIID_TMMRMote, which also improves accessibility and offers real-time performance insights.
To store analyzed data with timestamps and enable historical tracking and reference of the Bed-Type Turret Milling Machine's performance, the SD Card Module is coupled with CIID_TMMRMote. This helps with extensive data analysis and predictive maintenance planning.
The Power Supply plug in CIID_TMMTMote and CIID_TMMRMote guarantees the consistent and dependable functioning of the Bed-Type Turret Milling Machine monitoring system by supplying the electrical energy required to maintain the integrated components' functionality.
ADVANTAGES OF THE INVENTION
1. By actively gathering real-time vibration data from the Bed-Type Turret Milling Machine, the CIID_TMMTMote plays a crucial part in this breakthrough. In order to provide crucial information on the mechanical state of the machine, it makes use of FFT analysis in conjunction with a Real-Time Clock module. This allows for preventative maintenance and enhances operating performance.
2. This invention would not be possible without the CIID_TMMRMote, which uses an ESP32 Wifi board to provide internet connectivity. It includes an SD Card Module for storing analyzed data with timestamps and allows for remote monitoring through a customized web dashboard, improving accessibility and allowing for historical tracking of the operation of the Bed-Type Turret Milling Machine.
3. The CIID_TMMTMote's STM32 board serves as the central processing unit, effectively handling and processing data from the vibration sensor. By making FFT analysis easier, it helps with the Bed-Type Turret Milling Machine's real-time condition monitoring and analysis.
4. To provide smooth data interchange between CIID_TMMTMote and CIID_TMMRMote, the CC3000 RF module acts as a dependable communication link between devices. The bed-type turret milling machine real-time condition monitoring and analysis system performs better overall thanks to this feature.
5. A key component in gathering vibration data in real time from the Bed-Type Turret Milling Machine is the Vibration Sensor. It offers crucial input for the CIID_TMMTMote's FFT analysis, allowing for accurate mechanical condition monitoring of the machine.
6. Accurate timestamping of data is ensured by the RTC Module in the CIID_TMMTMote, which is an essential component for monitoring changes over time during real-time condition monitoring and FFT analysis of the Bed-Type Turret Milling Machine. This improves the accuracy of maintenance scheduling and performance analysis.
7. Internet communication is made possible by the ESP32 Wifi board in the CIID_TMMRMote, which enables remote monitoring of the Bed-Type Turret Milling Machine via a personalized web interface. This improves accessibility and offers instantaneous machine performance data.
8. Analyzed data with timestamps is stored in the SD Card Module of the CIID_TMMRMote. This feature helps with complete data analysis and predictive maintenance planning by enabling historical tracking and reference of the Bed-Type Turret Milling Machine's performance.

, Claims:1. A cloud-integrated iot device for online vibration fft analysis and trending data analysis in bed-type turret milling machine at a metal plant comprises CIID_TMMTMote (51a), which is outfitted with an STM32 board (56f), CC3000 RF module (52b), vibration sensor (54d), RTC module (55e), and power supply (53c), it actively gathers real-time vibration data from the Bed-Type Turret Milling Machine and uses FFT analysis in conjunction with a Real-Time Clock module to offer vital insights into the mechanical condition of the machine, enabling proactive maintenance and maximizing operational performance.
2. The device as claimed in claim 1, wherein the critical components of the Bed-Type Turret Milling Machine are the CIID_TMMRMote, which is outfitted with a used STM32 board, CC3000 RF module, ESP32 Wifi board, SD Card Module, and Power Supply, an ESP32 Wifi board allows for internet connectivity, a customized web dashboard allows for remote monitoring, and an SD Card Module stores analyzed data with timestamps to improve accessibility and historical performance tracking.
3. The device as claimed in claim 1, wherein the STM32 board is integrated with CIID_TMMTMote, which acts as the central processing unit, it effectively manages and processes data from the vibration sensor and makes FFT analysis easier in the mote, this helps with the Bed-Type Turret Milling Machine's condition monitoring and analysis in real-time.
4. The device as claimed in claim 1, wherein the CIID_TMMTMote and CIID_TMMRMote can exchange data easily thanks to the CC3000 RF module, which is integrated with both motes and serves as a dependable communication link between them, this enhances the overall efficacy of the Bed-Type Turret Milling Machine real-time condition monitoring and analysis system.
5. The device as claimed in claim 1, wherein the Vibration Sensor, which is integrated with CIID_TMMTMote, is crucial to the acquisition of real-time vibration data from the Bed-Type Turret Milling Machine, it offers vital information for FFT analysis and facilitates accurate mechanical condition monitoring of the machine.
6. The device as claimed in claim 1, wherein the Bed-Type Turret Milling Machine's FFT analysis and real-time condition monitoring depend on the precise timestamping of data in the Mote, which is made possible by the integration of the RTC Module with CIID_TMMTMote. This improves the accuracy of maintenance planning and performance analysis.
7. The device as claimed in claim 1, wherein the Bed-Type Turret Milling Machine may be remotely monitored via a customized web dashboard thanks to the ESP32 Wifi board's integration of CIID_TMMRMote, which also improves accessibility and offers real-time performance insights.
8. The device as claimed in claim 1, wherein to store analyzed data with timestamps and enable historical tracking and reference of the Bed-Type Turret Milling Machine's performance, the SD Card Module is coupled with CIID_TMMRMote, this helps with extensive data analysis and predictive maintenance planning.
9. The device as claimed in claim 1, wherein the Power Supply plug in CIID_TMMTMote and CIID_TMMRMote guarantees the consistent and dependable functioning of the Bed-Type Turret Milling Machine monitoring system by supplying the electrical energy required to maintain the integrated components' functionality.

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