WPAN-BASED VIBRATION MONITORING AND FFT ANALYSIS OF PORTAL MILLING MACHINES IN THE AEROSPACE INDUSTRY

Abstract

A system of WPAN-based vibration monitoring and fft analysis of portal milling machines in the aerospace industry comprises WPVTC_PMMNode (200), a data acquisition hub for capturing vibrations and accelerations from Portal Milling Machines, is outfitted with a Raspberry Pi Processor Board (205), an XBee Module with Base (204), a vibration sensor (203), a MEMS accelerometer (202), an HMI display (503), and a power supply (201), this allows for real-time monitoring and analysis for proactive maintenance in the aerospace industry the WPVRC_PMMNode, which has an ESP32 Wifi Board, an HMI Display, a Power Supply, an XBee Module with Base, a Raspberry Pi Processor Board, and other components, is used to wirelessly transmit data from Portal Milling Machines to the cloud server, this helps with the real-time vibration analysis and monitoring in the aerospace industry.

Specification

Description:FIELD OF THE INVENTION
This invention relates to wpan-based vibration monitoring and fft analysis of portal milling machines in the aerospace industry.
BACKGROUND OF THE INVENTION
This ground-breaking development serves as an invaluable resource for the aerospace sector by offering a comprehensive method for the real-time observation and examination of vibrations in portal milling machines. The system uses cloud computing and wireless connectivity to gather critical data from the machines' sensors. It then applies a pre-programmed machine learning algorithm for in-depth analysis, which includes Fast Fourier Transform (FFT) at certain intervals. The results of this research enable the timely detection of important issues, which are then shown as alerts on an intuitive interface that may be accessed through a web dashboard.
One of the biggest challenges facing the aerospace industry is effectively tracking and analyzing vibrations in Portal Milling Machines (PMMs). The inability of conventional monitoring techniques to provide real-time insights into machine performance usually leads to possible inefficiencies and unforeseen issues. Initiatives for proactive maintenance and optimization are hampered by the absence of a comprehensive and integrated solution.
KR20170088777A: The present invention relates to a design of a machine tool, in particular a multi-spindle and/or double-spindle milling machine. The machine tool comprises: a machine frame; a workpiece clamping device for clamping a workpiece; an axis slide assembly which is arranged on the machine frame and is configured to linearly move the workpiece clamped on the workpiece clamping device by way of two controllable linear axes in a Y-direction and a Z-direction; and a spindle carrier assembly which is arranged on the machine frame and has at least two tool-carrying work spindles that can be moved independently of each other in the S1- and S2-directions which are each inclined with respect to the Y-direction and Z-direction and to one another.
RESEARCH GAP: An innovation through WPAN-Based Vibration Monitoring and FFT Analysis of Portal Milling Machines is the novelty of the system.
CN106256468A: The invention discloses a kind of duplex head milling machine.It includes base, pedestal, workbench, crossbeam, column, two milling heads and two drive mechanisms, described pedestal is placed in the center of base and is slidably connected with base, described workbench is arranged on pedestal, described crossbeam is placed in the top of pedestal and is arranged on pedestal by column, described drive mechanism is placed on base and is slidably connected with base, two of which drive mechanism is respectively placed in the right and left of pedestal and symmetrical, and described milling head is arranged on drive mechanism.The invention has the beneficial effects as follows: can rotational workpieces automatically, realized the purpose of two-sided processing by the design of two milling heads simultaneously, simple in construction, easy to operate, effectively reduce the labor intensity of operator, improve the work efficiency of planer-type milling machine, being conducive to the maintenance in later stage, service life is long, and security performance is high, the precision simultaneously processing workpiece is high, it is possible to realize the function that automatic chip-removal reclaims with scrap.
RESEARCH GAP: An innovation through WPAN-Based Vibration Monitoring and FFT Analysis of Portal Milling 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.
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.
This innovation operates by using a network that consists of two nodes: the WPVRC_PMMNode and the WPVTC_PMMNode. The Raspberry Pi Processor Board, XBee Module with Base, Vibration Sensor, MEMS Accelerometer, HMI Display, and Power Supply are all included in the WPVTC_PMMNode's configuration. On the other hand, the WPVRC_PMMNode is composed of an ESP32 WiFi Board, an XBee Module with Base, a Raspberry Pi Processor Board, an HMI Display, and a Power Supply. The Vibration Sensor and MEMS Accelerometer on the WPVTC_PMMNode begin the data acquisition process by gathering relevant data from the Portal Milling Machine. The XBee Module is then used to wirelessly transfer this data to a cloud server that has been specially created for this breakthrough. In a similar manner, the WPVRC_PMMNode with its ESP32 Wifi Board helps to this data transmission.

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 innovation operates by using a network that consists of two nodes: the WPVRC_PMMNode and the WPVTC_PMMNode. The Raspberry Pi Processor Board, XBee Module with Base, Vibration Sensor, MEMS Accelerometer, HMI Display, and Power Supply are all included in the WPVTC_PMMNode's configuration. On the other hand, the WPVRC_PMMNode is composed of an ESP32 WiFi Board, an XBee Module with Base, a Raspberry Pi Processor Board, an HMI Display, and a Power Supply. The Vibration Sensor and MEMS Accelerometer on the WPVTC_PMMNode begin the data acquisition process by gathering relevant data from the Portal Milling Machine. The XBee Module is then used to wirelessly transfer this data to a cloud server that has been specially created for this breakthrough. In a similar manner, the WPVRC_PMMNode with its ESP32 Wifi Board helps to this data transmission.
Once in the cloud server, a preset machine learning algorithm is used for thorough analysis, which includes Fast Fourier Transform (FFT) analysis in a predetermined amount of time. The results of this examination provide the basis for determining important problems with the functioning of the milling machine. Afterwards, both nodes' HMI Displays produce and display vital alerts, making sure that operators on the scene are informed of any irregularities as soon as possible. Furthermore, the system has an intuitive user interface that can be accessed via an online dashboard. Operators have the ability to evaluate the data analysis in real time, monitor machine conditions, and examine critical alerts by logging into their accounts. The integration of email alerts improves communication by ensuring that accountable staff members receive notices promptly, enabling prompt action and response.
BEST METHOD OF WORKING
The WPVTC_PMMNode, a data acquisition hub for capturing vibrations and accelerations from Portal Milling Machines, is outfitted with a Raspberry Pi Processor Board, an XBee Module with Base, a vibration sensor, a MEMS accelerometer, an HMI display, and a power supply. This allows for real-time monitoring and analysis for proactive maintenance in the aerospace industry.
The WPVRC_PMMNode, which has an ESP32 Wifi Board, an HMI Display, a Power Supply, an XBee Module with Base, a Raspberry Pi Processor Board, and other components, is used to wirelessly transmit data from Portal Milling Machines to the cloud server. This helps with the real-time vibration analysis and monitoring in the aerospace industry.
For real-time monitoring and FFT analysis of Portal Milling Machines in the Aerospace Industry, data processing and analysis from vibration sensors and accelerometers on both WPVTC_PMMNode and WPVRC_PMMNode are made easier by the Raspberry Pi Processor Board, which is integrated into both of the motes.
The XBee Module with Base, which is also a part of both motes, serves as the innovation's wireless communication backbone. It permits smooth data transfer between WPVTC_PMMNode and WPVRC_PMMNode, making it easier to build a WPAN-based network for the aerospace industry's real-time vibration analysis and monitoring of portal milling machines.
Precise data from Portal Milling Machines is captured by the Vibration Sensor and MEMS Accelerometer, both of which are included into the WPVTC_PMMNode. This allows for real-time monitoring and FFT analysis for preventive maintenance and optimization in the aerospace industry.
The WPVRC_PMMNode's embedded ESP32 WiFi Board is utilized to enable wireless data transmission to the cloud server, aiding in the aerospace industry's real-time vibration analysis and monitoring of portal milling machines.
The HMI Display, which is interfaced on both of the motes, improves the operator's capacity to monitor and react to vibrations in Portal Milling Machines used in the aerospace industry by instantly visualizing critical alerts and real-time data from the WPVTC_PMMNode and WPVRC_PMMNode.
ADVANTAGES OF THE INVENTION
1. At the heart of this novel system is the WPVTC_PMMNode, which acts as a hub for data collecting and is fitted with sensors to record accelerations and vibrations from Portal Milling Machines. In the aerospace industry, this capacity promotes preventive maintenance by enabling real-time monitoring and analysis.
2. The WPVRC_PMMNode, which uses an ESP32 Wifi Board to wirelessly transfer data from Portal Milling Machines to the cloud server, is essential to the invention. The aerospace industry's real-time vibration monitoring and analysis is greatly improved by this contribution.
3. This innovation's wireless communication backbone, the XBee Module with Base, enables smooth data transmission between the WPVTC_PMMNode and WPVRC_PMMNode. This permits the establishment of a WPAN-based network devoted to vibration analysis and real-time monitoring in aerospace industry portal milling machines.
4. The MEMS Accelerometer and Vibration Sensor are essential parts that operate in tandem with the Raspberry Pi Processor Board on the WPVTC_PMMNode. In order to enable real-time monitoring and FFT analysis, as well as preventive maintenance and optimization within the aerospace industry, their job is to precisely record data from Portal Milling Machines.
5. The WPVRC_PMMNode's ESP32 Wifi Board is essential because it makes wireless data transmission to the cloud server possible. The aerospace industry's real-time vibration monitoring and analysis of portal milling machine vibrations is improved by this proactive contribution.
, Claims:1. A system of WPAN-based vibration monitoring and fft analysis of portal milling machines in the aerospace industry comprises WPVTC_PMMNode (200), a data acquisition hub for capturing vibrations and accelerations from Portal Milling Machines, is outfitted with a Raspberry Pi Processor Board (205), an XBee Module with Base (204), a vibration sensor (203), a MEMS accelerometer (202), an HMI display (503), and a power supply (201), this allows for real-time monitoring and analysis for proactive maintenance in the aerospace industry.
2. The system as claimed in claim 1, wherein the WPVRC_PMMNode, which has an ESP32 Wifi Board, an HMI Display, a Power Supply, an XBee Module with Base, a Raspberry Pi Processor Board, and other components, is used to wirelessly transmit data from Portal Milling Machines to the cloud server, this helps with the real-time vibration analysis and monitoring in the aerospace industry.
3. The system as claimed in claim 1, wherein for real-time monitoring and FFT analysis of Portal Milling Machines in the Aerospace Industry, data processing and analysis from vibration sensors and accelerometers on both WPVTC_PMMNode and WPVRC_PMMNode are made easier by the Raspberry Pi Processor Board, which is integrated into both of the motes.
4. The system as claimed in claim 1, wherein the XBee Module with Base, which is also a part of both motes, serves as the innovation's wireless communication backbone, it permits smooth data transfer between WPVTC_PMMNode and WPVRC_PMMNode, making it easier to build a WPAN-based network for the aerospace industry's real-time vibration analysis and monitoring of portal milling machines.
5. The system as claimed in claim 1, wherein precise data from Portal Milling Machines is captured by the Vibration Sensor and MEMS Accelerometer, both of which are included into the WPVTC_PMMNode, this allows for real-time monitoring and FFT analysis for preventive maintenance and optimization in the aerospace industry.
6. The system as claimed in claim 1, wherein the WPVRC_PMMNode's embedded ESP32 WiFi Board is utilized to enable wireless data transmission to the cloud server, aiding in the aerospace industry's real-time vibration analysis and monitoring of portal milling machines.
7. The system as claimed in claim 1, wherein the HMI Display, which is interfaced on both of the motes, improves the operator's capacity to monitor and react to vibrations in Portal Milling Machines used in the aerospace industry by instantly visualizing critical alerts and real-time data from the WPVTC_PMMNode and WPVRC_PMMNode.

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