HYDRAULIC OIL CONDITION MONITORING FOR CONTROLLING HIGH-CAPACITY TRUCK-MOUNTED CHIPPER IN FORESTRY OPERATIONS VIA XBEE-BASED WPAN NETWORK

Abstract

Hydraulic oil condition monitoring for controlling high-capacity truck-mounted chipper in forestry operations via xbee-based wpan network comprises the HOCT_TMCMote (10) is equipped with a Raspberry Pi PICO Board (10E), an XBee RF Module with Explorer (10F), a NAS Sensor (10B), a Vibrational Viscometer Sensor (10A), a Capacitive Viscometer Sensor (10C), and a Power supply (10D) to improve control and decision-making in the management of hydraulic oil condition for high-capacity truck-mounted chippers in forestry operations, the HOCR_TMCMote, which consists of the Raspberry Pi PICO Board, XBee RF Module with Explorer, ESP32 Wifi Board, HMI Display, and Power Supply, is used as an interface for operators to receive and visualize real-time data, critical alerts, and insights generated by machine learning algorithms.

Specification

Description:FIELD OF THE INVENTION
This invention relates to hydraulic oil condition monitoring for controlling high-capacity truck-mounted chipper in forestry operations via xbee-based wpan network.
BACKGROUND OF THE INVENTION
This ground-breaking solution integrates sophisticated Hydraulic Oil Condition Monitoring to revolutionize the maintenance and performance monitoring of high-capacity truck-mounted chippers in forestry operations. The system continuously collects real-time data about various aspects of the hydraulic oil state of the chipper through the use of wireless communication and a network of sensors. Machine learning algorithms carefully examine this data over time when it is effectively transferred to a cloud-based platform. Operators are then notified of the resulting insights and critical alerts through an easy-to-use online dashboard and user interface.
One of the biggest challenges facing the forestry industry is effectively managing and maintaining the hydraulic systems in large truck-mounted chippers. Proactive maintenance procedures are hindered by the lack of an advanced and all-inclusive Hydraulic Oil Condition Monitoring solution, which leads to increased downtime and inefficiencies in operations. The inability of conventional monitoring techniques to provide accurate real-time information on hydraulic oil condition makes it more difficult to identify and address such problems in a timely manner.
CN107263655A: This technology discloses a kind of cutterhead fixing device of wood chipper, including cutterhead, the outer circumferential walls of the cutterhead offer equally distributed insert groove, and the quantity of insert groove is eight to ten, blade is formed between described two insert grooves to lean on, the side two ends that the blade is leaned on are offered is threaded with the first blade fastening bolt and the second blade fastening bolt respectively in two screwed holes parallel to the circumference of cutterhead, and two screwed holes.The first motor rotated with movable knife disc is fixed on contiguous block, contiguous block can be moved up and down by the second motor with screw mandrel, move up and down cutterhead, and timber is processed with the need for tackling different thicknesses size, improve the efficiency of wood chipping equipment, the each blade of cutterhead is installed with two fastening bolts, and thrust is strong, blade is brought into close contact with cutterhead, rigidity reinforced, reduce the blade caused by vibrations to be lost, cost is lower, and processing effect is more preferable.
RESAERCH GAP: An innovation involves XBee RF and Cloud technologies for High-Capacity Truck-Mounted Chipper in Forestry is the novelty of the system.
CN212193553U: The utility model discloses a drum chipper, the top of the frame is fixedly connected with a chipper shell, the front plate and the back plate are respectively fixedly connected with the front side and the back side of the frame, one side of the top plate is rotatably connected with one side of the front plate and the back plate, the other side of the front plate and the back plate is provided with a feeding part, a driving gear is sleeved on the feeding motor, a driven gear is sleeved on the material conveying roller shaft, a transmission chain is sleeved between the driving gear and the driven gear, a chipper cavity at one side of the material conveying roller shaft is arranged between the front plate and the back plate, one side of the top plate is provided with a chipper motor, the output shaft of the chipper motor is connected to a chipper shaft through a transmission belt, two ends of the chipper shaft respectively pass through the front plate and the back plate, a chipper roller is sleeved on the surface of the chipper shaft, a plurality of blades are evenly arranged on the surface of the chipper, and a discharge hole is reserved at the bottom of the frame. The utility model discloses effectively make timber cutting even.
RESEARCH GAP:An innovation involves XBee RF and Cloud technologies for High-Capacity Truck-Mounted Chipper in Forestry 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 works by utilizing a number of interrelated parts and procedures that are intended to make it easier to monitor and regulate hydraulic oil condition for high-capacity truck-mounted chippers in forestry operations. The two primary components of the system are HOCT_TMCMote and HOCR_TMCMote. The HOCT_TMCMote is equipped with a Raspberry Pi PICO Board and various sensors, including the NAS Sensor, Vibrational Viscometer Sensor, and Capacitive Viscometer Sensor. These sensors gather data that is remotely transferred over a Wireless Personal Area Network (WPAN) using the XBee RF Module with Explorer. This data includes metrics relating to hydraulic oil condition. In contrast, the HOCR_TMCMote uses an ESP32 Wifi Board, a Raspberry Pi PICO Board, and an HMI Display for user interface.
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 works by utilizing a number of interrelated parts and procedures that are intended to make it easier to monitor and regulate hydraulic oil condition for high-capacity truck-mounted chippers in forestry operations. The two primary components of the system are HOCT_TMCMote and HOCR_TMCMote. The HOCT_TMCMote is equipped with a Raspberry Pi PICO Board and various sensors, including the NAS Sensor, Vibrational Viscometer Sensor, and Capacitive Viscometer Sensor. These sensors gather data that is remotely transferred over a Wireless Personal Area Network (WPAN) using the XBee RF Module with Explorer. This data includes metrics relating to hydraulic oil condition. In contrast, the HOCR_TMCMote uses an ESP32 Wifi Board, a Raspberry Pi PICO Board, and an HMI Display for user interface.
This gadget is in charge of gathering and presenting data in real time, allowing operators to keep an eye on the chipper's hydraulic oil condition and other important details. The information gathered by both gadgets is sent to a customized cloud server created especially for this invention. The data is analyzed over time by the cloud server using pre-programmed machine learning algorithms. By seeing patterns, trends, and abnormalities in the hydraulic oil condition, these machine learning algorithms are essential for enabling predictive maintenance and prompt treatments. The operator is then shown the results of the data analysis through the HMI Display and a personalized online dashboard that can be accessed through user accounts. These results include important alerts and insights. Operators may easily understand and evaluate the condition of the chipper's hydraulic system with the help of the online dashboard's intuitive design. Apart from the display interfaces, operators receive important alerts via email immediately, guaranteeing rapid awareness of possible problems.
BEST METHOD OF WORKING
To integrate sensors with a Raspberry Pi PICO Board and use the XBee RF Module to wirelessly transmit real-time data on hydraulic oil condition, allowing for continuous monitoring and analysis in forestry operations, the HOCT_TMCMote is equipped with a Raspberry Pi PICO Board, an XBee RF Module with Explorer, a NAS Sensor, a Vibrational Viscometer Sensor, a Capacitive Viscometer Sensor, and a Power supply.
To improve control and decision-making in the management of hydraulic oil condition for high-capacity truck-mounted chippers in forestry operations, the HOCR_TMCMote, which consists of the Raspberry Pi PICO Board, XBee RF Module with Explorer, ESP32 Wifi Board, HMI Display, and Power Supply, is used as an interface for operators to receive and visualize real-time data, critical alerts, and insights generated by machine learning algorithms.
The innovation's core processing unit is the Raspberry Pi PICO Board, which is built within both motes. In order to provide real-time hydraulic oil condition monitoring and analysis in high-capacity truck-mounted chippers during forestry operations, it facilitates the easier integration and coordination of sensor data, wireless communication modules, and machine learning algorithms.
Real-time monitoring and analysis of hydraulic oil condition in high-capacity truck-mounted chippers is made possible by the XBee RF Module with Explorer, which is also included in both motes. This module allows for seamless wireless communication between sensor-equipped devices (HOCT_TMCMote) and the data display interface (HOCR_TMCMote) over a Wireless Personal Area Network (WPAN).
During forestry operations, the NAS Sensor, Vibrational Viscometer Sensor, and Capacitive Viscometer Sensor-all integrated into HOCT_TMCMote-combine to provide extensive data on the hydraulic oil condition, enabling accurate monitoring and analysis for preventive maintenance and operational optimization in high-capacity truck-mounted chippers.
Using the customized web dashboard in forestry operations, operators can access real-time data, critical alerts, and insights on hydraulic oil condition thanks to the ESP32 Wifi Board integrated into HOCR_TMCM. This board also serves to facilitate the wireless connection between the HOCR_TMCMote and the cloud-based platform.
During forestry operations, operators can monitor and control the hydraulic oil condition in high-capacity truck-mounted chippers more effectively by using the HMI Display that is interfaced on HOCR_TMCM. This display gives operators a real-time visual representation of data, critical alerts, and machine learning insights.
ADVANTAGES OF THE INVENTION
1. A key component of this innovation is the HOCT_TMCMote, which combines a number of sensors with a Raspberry Pi PICO Board and uses the XBee RF Module to transmit real-time data on hydraulic oil condition wirelessly. This makes it possible for forestry operations to continuously monitor and analyze data.
2. The interface via which operators receive and view real-time data, important alerts, and insights produced by machine learning algorithms is the HOCR_TMCMote. This improves control and judgment when it comes to high-capacity truck-mounted chippers' hydraulic oil condition management in forestry operations.
3. A crucial element that enables smooth wireless connection between the data display interface (HOCR_TMCMote) and the sensor-equipped devices (HOCT_TMCMote) is the XBee RF Module with Explorer. This makes it possible to use a Wireless Personal Area Network (WPAN) to monitor and analyze the hydraulic oil condition in high-capacity truck-mounted chippers in real time.
4. The Vibrational Viscometer Sensor, Capacitive Viscometer Sensor, and NAS Sensor are essential parts that together offer thorough information on the state of the hydraulic oil. This makes it possible for high-capacity truck-mounted chippers used in forestry operations to have exact monitoring and analysis for preventive maintenance and operational optimization.
5. The ESP32 Wifi Board is an essential communication component that makes it possible for the HOCR_TMCMote and the cloud-based platform to connect wirelessly. This enables the customized online dashboard in forestry operations to provide operators with real-time data, vital alerts, and insights on hydraulic oil status.
6. The HMI Display is an essential interface that gives operators a visual depiction of data in real time, as well as important alarms and machine learning insights. This improves their capacity to keep an eye on and manage the hydraulic oil condition in truck-mounted, high-capacity chippers while conducting forestry operations.
, Claims:1. A system of Hydraulic oil condition monitoring for controlling high-capacity truck-mounted chipper in forestry operations via XBEE-based wpan network comprises the HOCT_TMCMote (10) is equipped with a Raspberry Pi PICO Board (10E), an XBee RF Module with Explorer (10F), a NAS Sensor (10B), a Vibrational Viscometer Sensor (10A), a Capacitive Viscometer Sensor (10C), and a Power supply (10D).
2. The system as claimed in claim 1, wherein to improve control and decision-making in the management of hydraulic oil condition for high-capacity truck-mounted chippers in forestry operations, the HOCR_TMCMote, which consists of the Raspberry Pi PICO Board, XBee RF Module with Explorer, ESP32 Wifi Board, HMI Display, and Power Supply, is used as an interface for operators to receive and visualize real-time data, critical alerts, and insights generated by machine learning algorithms.
3. The system as claimed in claim 1, wherein the innovation's core processing unit is the Raspberry Pi PICO Board, which is built within both motes; and in order to provide real-time hydraulic oil condition monitoring and analysis in high-capacity truck-mounted chippers during forestry operations, it facilitates the easier integration and coordination of sensor data, wireless communication modules, and machine learning algorithms.
4. The system as claimed in claim 1, wherein Real-time monitoring and analysis of hydraulic oil condition in high-capacity truck-mounted chippers is made possible by the XBee RF Module with Explorer, which is also included in both motes; and this module allows for seamless wireless communication between sensor-equipped devices (HOCT_TMCMote) and the data display interface (HOCR_TMCMote) over a Wireless Personal Area Network (WPAN).
5. The system as claimed in claim 1, wherein During forestry operations, the NAS Sensor, Vibrational Viscometer Sensor, and Capacitive Viscometer Sensor-all integrated into HOCT_TMCMote-combine to provide extensive data on the hydraulic oil condition, enabling accurate monitoring and analysis for preventive maintenance and operational optimization in high-capacity truck-mounted chippers.
6. The system as claimed in claim 1, wherein Using the customized web dashboard in forestry operations, operators can access real-time data, critical alerts, and insights on hydraulic oil condition thanks to the ESP32 Wifi Board integrated into HOCR_TMCM; and this board also serves to facilitate the wireless connection between the HOCR_TMCMote and the cloud-based platform.
7. The system as claimed in claim 1, wherein During forestry operations, operators can monitor and control the hydraulic oil condition in high-capacity truck-mounted chippers more effectively by using the HMI Display that is interfaced on HOCR_TMCM; and display gives operators a real-time visual representation of data, critical alerts, and machine learning insights.

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