AI-ENABLED EDGE VISION DEVICE FOR CONDITION MONITORING AND BEHAVIOR ANALYSIS OF INDUSTRIAL SWIVEL HEAD MILLING MACHINES USING LPWAN AND XBEE MULTI-WIRELESS NETWORKS

Abstract

An ai-enabled edge vision device for condition monitoring and behavior analysis of industrial swivel head milling machines using lpwan and xbee multi-wireless networks comprises EdgeV Mote, which comprises a Jetson Nano Enhanced Board, XBee Module, ADS1117, a Current Sensor, an Accelerometer, a Temperature Sensor, and a Liquid Pressure Sensor along with a Power supply, facilitates the real-time measurement and transmission of important machine parameters which in turn maximizes predictive and operational maintenance in the case of the industrial swivel head milling machines the Central Mote, which includes a Jetson Nano, an XBee Module, a LoRa RF Module, a display, and Power Supply Unit, serves an added value purpose to the whole system by integrating data from EdgeV Mote and displaying it in real time, the onsite operators are thus able to access critical indicators of machine health quickly which reside in the monitoring device.

Specification

Description:FIELD OF THE INVENTION
This invention relates to ai-enabled edge vision device for condition monitoring and behavior analysis of industrial swivel head milling machines using lpwan and xbee multi-wireless networks.
BACKGROUND OF THE INVENTION
AI Edge vision monitoring system with the ability to observe the condition and the performance of industrial swivel head milling machines. It employs a Multi-node system where every node is in charge of data acquisition, data forwarding and data processing of relatively important operational information including the machine parameters like active power, vibrations, temperature and pressure. It uses both short-range and long-range wireless transmission to provide reliable data communication across the industrial network. In due time, when the data is collected, the data is sent to a cloud system and analyzed with the use of artificial intelligence and machine learning and appropriate recommendations regarding machine and anticipatory measures are provided. Users with suitable permissions can view current events and history through a cloud vane and take necessary actions within a short period of time to improve the operating machine.
This invention is devoted to the pressing problem of ensuring quick and accurate monitoring and routine maintenance of the swivel head milling machines which get worn out and yawnic performance degradation. Conventional practices of performance appraisal have been limited to certain temporally spaced intervals, which fail to take into consideration the symptoms indicating the onset of any form of mechanical failure, eventually leading to unanticipated breaks in operation of machines, expensive repair costs and low production levels. This system solves the problems of real time condition monitoring and behavior diagnostics and therefore enables problem anticipation and AI recommendations for improvement of machine. Such racon packages conserve time and avoid the need for unplanned maintenance, increase average lifetime of equipment as well as effective usage of the equipment making certain that the industrial operations are never disrupted by obnoxious expenses.
CN105171074B: The present invention relates to a kind of gantry vertical numerical control double end double-pole storehouse milling machine machining center, including main slide unit unit, gantry beam unit, work piece platform and magnechuck/hydraulically operated fixture is provided with the main slide unit body of X-axis;Gantry beam unit is made up of two-way cross nc sliding table, on the two-way slide unit in crossbeam both sides, provided with two special vertical main shaft milling heads, to realize the milling to workpiece;In the outside of crossbeam two, disc type tool magazine is installed respectively;Under the programmed instruction control of digital control system, realize bilateral to the curved surface symmetrical expression of workpiece while process.It is attached to help unit to also have automatic chip-removal system, cooling, centralized lubrication and protective cover.The main axle unit band tool-broaching mechanism, under the cooperation of cutter-exchange mechanism and tool magazine, can be achieved fast automatic tool changing.For main shaft using alternating current servo spindle motor tooth-adding profile band deceleration transmission, stable drive, slewing range is wide, and it is big to transmit moment of torsion.After workpiece clamped one time, boring, milling, brill, the Continuous maching for twisting multiple operation can be automatically performed.
RESEARCH GAP: AI-enabled condition monitoring and behavior analysis for swivel head milling machines using a hybrid LPWAN and XBee multi-wireless network is the uniqueness of this innovation.
CN206047589U: A kind of straight driving force knife rest of inverted complex milling machine tool and straight driving force head device, it is characterised in that the lathe bed under gantry frame is arranged vertically inverted main shaft, lathe bed horizontal plane and is correspondingly arranged a straight driving force knife rest, multiple straight driving force heads:Straight driving force knife rest is installed by tool support on the right side of lathe bed, power head bracket is set on the left of lathe bed, milling cutter, drill bit, screw tap are installed on straight driving force head and are integrated, multiple straight driving force heads and its cutter are mounted side by side above straight driving force head bracket, the vertical lathe bed arrangement of inverted main shaft, make linear axis motion, workpiece, chuck are fixed on main shaft.Advantage is to complete the processing such as the inverted turning to workpiece and the milling to workpiece axial end, drilling, tapping, concentrate can work pieces process operation, the position error for avoiding workpiece from causing because of multiple clamping, the power of unit head can be improved simultaneously, be conducive to the utilization rate of the working (machining) efficiency and equipment of raising part.
RESEARCH GAP: AI-enabled condition monitoring and behavior analysis for swivel head milling machines using a hybrid LPWAN and XBee multi-wireless network is the uniqueness of this innovation.
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 development is an all-in-one advanced system that combines the capabilities of AI to the edge of the visual system and focuses on monitoring and analyzing the condition of industrial swivel head milling machines. The system consists of three nodes: EdgeV Mote, Central Mote, and End Mote, whose functions are related to the processes of data collection, communication, and cloud connection. They are interlinked through a strong multi-node architecture that employs short range and long range wireless networks in transmitting data from the machine to the cloud for processing and analytical purposes. This configuration facilitates the permanent retrieval of monitoring information for key parameters of the machine with AI and machine learning algorithms also present in the cloud to assist with interpreting the current state and the history of the machine in operation.
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 development is an all-in-one advanced system that combines the capabilities of AI to the edge of the visual system and focuses on monitoring and analyzing the condition of industrial swivel head milling machines. The system consists of three nodes: EdgeV Mote, Central Mote, and End Mote, whose functions are related to the processes of data collection, communication, and cloud connection. They are interlinked through a strong multi-node architecture that employs short range and long range wireless networks in transmitting data from the machine to the cloud for processing and analytical purposes. This configuration facilitates the permanent retrieval of monitoring information for key parameters of the machine with AI and machine learning algorithms also present in the cloud to assist with interpreting the current state and the history of the machine in operation.
The primary element of data acquisition in this procedure is the EdgeV Mote, which was installed next to the NC swivel head milling machine in order to measure the parameters such as power, elevation, temperature, and pressure. These parameters can be used to better assess machine health and its mechanical state. This data is first sent to the Central Mote which connects to the local area network while aggregating and forwarding the information within the network. The Central Mote uses more than one communication protocol facilitating communication under the impact of a strong noise or physical barriers. At last, the End Mote is in charge of long distance communication and cloud connection, sending all the data to a remote cloud computing server for further research.
Autonomous AI and machine learning algorithms in the cloud service analyze the captured data in order to learn trends, recognize deviations from the norm, and forecast possible breakdowns of the equipment. Drawing from these studies, the model creates tailored proposals which ensure maximum efficiency of the equipment. Such proposals can be found on the secured web dashboard which the authorized users have access to for operators to use when observing the current state of the machines and their historical state. The machine local display also does provide this information with some time lags and is helpful in giving the machine operators present at the floor immediate status related feedback. Such attributes make it possible for the system to undertake a more maintenance oriented approach as unexpected failures are less likely to happen and scheduled maintenance can be adjusted. The user interface is equally intuitive and can be deployed with little or no technical skills making it an ideal tool for site operators and maintenance personnel.
BEST METHOD OF WORKING
The EdgeV Mote, which comprises a Jetson Nano Enhanced Board, XBee Module, ADS1117, a Current Sensor, an Accelerometer, a Temperature Sensor, and a Liquid Pressure Sensor along with a Power supply, facilitates the real-time measurement and transmission of important machine parameters which in turn maximizes predictive and operational maintenance in the case of the industrial swivel head milling machines.
The Central Mote, which includes a Jetson Nano, an XBee Module, a LoRa RF Module, a display, and Power Supply Unit, serves an added value purpose to the whole system by integrating data from EdgeV Mote and displaying it in real time. The onsite operators are thus able to access critical indicators of machine health quickly which reside in the monitoring device.
The End Mote, which consists of a Jetson Nano Board, LoRa RF Module, a GSM Modem, Indicator LED lights along with Power supply allows users for remote cloud monitoring and provides an option for authorized personnel to view the machine data in real time through a custom-designed cloud dashboard which improves the usability and dynamics of the operating environment in the industry
The short range communication within the facility is further enhanced with XBee module which provides reliable communication for real time supervision and maintenance in Industrial networks. This XBee Module, deployed in both the EdgeV Mote and Central Mote, ensures reliable short-range wireless transmission of data within the area of the machine.
The LoRa RF module operates effectively in such environments including the Central Mote and End Mote where long-range data relay to cloud infrastructure is required to maintain constant data flow in data sensitive industries that are seeking remote support even at harsh environments.
With their inclusion of the End Mote, the GSM Modems provide internet-based access to machine data to people or authorized personnel allowing them to monitor operational conditions and predictive data from anywhere which in turn enhances operational flexibility and efficiency of response.
As a simple display unit, the display comprises a user-friendly element providing on-site machine operators with real time information about the condition and behavior of the machines enabling quicker awareness and action. This Display included in the Central Mote is an effective means for on-site operators to receive feedback from the machine's operation.
ADVANTAGES OF THE INVENTION
1. EdgeV Mote current and accelerometer as well as temperature sensors constantly monitor the main parameters of the machine and provide up to date information related to its working state and any issues that may arise regarding performance in future.
2. EdgeV Mote's XBee Module and the Central Mote's LoRa RF Module together allow for effective data transmission over short and long distances to ensure data transfer and connection even in high noise situation.
3. Each node's Jetson Nano Board captures and forwards important information to the cloud data center where machine learning algorithms study the operational activity of the machines and recommend maintenance actions to avoid machine breakdowns as well as recommend the best time to perform maintenance.
4. Data collected from the End Mote's GSM Modem is sent to the cloud which enables authorized users to log into a secure web dashboard and view real time and past data about machines from any location.
5. The display in the central mote presents another opportunity for data visualization by offering the operators a quick access to the current status of the machines, which allows faster interventions and better awareness on the shop floor.
, Claims:1. An ai-enabled edge vision device for condition monitoring and behavior analysis of industrial swivel head milling machines using lpwan and xbee multi-wireless networks comprises EdgeV Mote, which comprises a Jetson Nano Enhanced Board, XBee Module, ADS1117, a Current Sensor, an Accelerometer, a Temperature Sensor, and a Liquid Pressure Sensor along with a Power supply, facilitates the real-time measurement and transmission of important machine parameters which in turn maximizes predictive and operational maintenance in the case of the industrial swivel head milling machines.
2. The device as claimed in claim 1, wherein the Central Mote, which includes a Jetson Nano, an XBee Module, a LoRa RF Module, a display, and Power Supply Unit, serves an added value purpose to the whole system by integrating data from EdgeV Mote and displaying it in real time, the onsite operators are thus able to access critical indicators of machine health quickly which reside in the monitoring device.
3. The device as claimed in claim 1, wherein the End Mote, which consists of a Jetson Nano Board, LoRa RF Module, a GSM Modem, Indicator LED lights along with Power supply allows users for remote cloud monitoring and provides an option for authorized personnel to view the machine data in real time through a custom-designed cloud dashboard which improves the usability and dynamics of the operating environment in the industry
4. The device as claimed in claim 1, wherein the short range communication within the facility is further enhanced with XBee module which provides reliable communication for real time supervision and maintenance in Industrial networks, this XBee Module, deployed in both the EdgeV Mote and Central Mote, ensures reliable short-range wireless transmission of data within the area of the machine.
5. The device as claimed in claim 1, wherein the LoRa RF module operates effectively in such environments including the Central Mote and End Mote where long-range data relay to cloud infrastructure is required to maintain constant data flow in data sensitive industries that are seeking remote support even at harsh environments.
6. The device as claimed in claim 1, wherein with their inclusion of the End Mote, the GSM Modems provide internet-based access to machine data to people or authorized personnel allowing them to monitor operational conditions and predictive data from anywhere which in turn enhances operational flexibility and efficiency of response.
7. The device as claimed in claim 1, wherein as a simple display unit, the display comprises a user-friendly element providing on-site machine operators with real time information about the condition and behavior of the machines enabling quicker awareness and action, this Display included in the Central Mote is an effective means for on-site operators to receive feedback from the machine's operation.

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