Integration of Wireless Sensors and Models for a Smart Machining System

2009 ◽  
Author(s):  
Robert B. Jerard ◽  
Barry K. Fussell ◽  
Chris A. Suprock ◽  
Yanjun Cui ◽  
Jeffrey Nichols ◽  
...  
Keyword(s):  
Low Cost ◽  
Spindle Motor ◽  
Vibration Sensor ◽  
Machining Process ◽  
Sensor Data ◽  
Research Progress ◽  
Force Model ◽  
Calibration Methods ◽  
Machining System ◽  
Smart Machining

This paper describes recent research progress at the University of New Hampshire in the area of “Smart Machining Systems (SMS)”. Our approach to SMS is to integrate models with wireless embedded sensor data to monitor and improve the machining process. This paper discusses recent progress in low-cost wireless sensor development, model calibration methods, model accuracy, and tool condition monitoring for SMS. We describe a system that can estimate tool wear using the coefficients of a tangential cutting force model. The model coefficients are estimated by online measurement of spindle motor power. We also show the use of a cutting tool embedded with a wireless vibration sensor to detect the onset of chatter in real-time.

scholarly journals Calibration and Characterization of a Low-Cost Wireless Sensor for Applications in CNC End Milling

2012 ◽  
Author(s):  
Andrew Harmon ◽  
Barry K. Fussell ◽  
Robert B. Jerard
Keyword(s):  
End Milling ◽  
Low Cost ◽  
Force Sensor ◽  
Industrial Applications ◽  
Milling Process ◽  
Research Progress ◽  
Machining System ◽  
Smart Machining ◽  
Band Limited ◽  
Cnc End Milling

This paper describes recent research progress at the University of New Hampshire in the area of smart machining systems. Central to creating a smart machining system is the challenge of collecting detailed information about the milling process at the tool tip. This paper discusses the design, static calibration, dynamic characterization, and implementation of a low-cost wireless force sensor for end-milling. The sensor is observed to accurately measure force when most of the cutting power is band-limited below the sensor’s natural frequency. Sensor geometry constrains the milling application to a single tooth cutter; while this constraint is impractical for industrial applications, our sensor is shown to provide useful information in a laboratory setting.

scholarly journals Development of smart machining system for optimizing feedrates to minimize machining time

2017 ◽  
Vol 5 (3) ◽  
pp. 299-304 ◽  
Author(s):  
Hong-seok Park ◽  
Bowen Qi ◽  
Duck-Viet Dang ◽  
Dae Yu Park
Keyword(s):  
Cutting Force ◽  
Machining Process ◽  
Cnc Machine ◽  
Machining Time ◽  
Virtual Machining ◽  
Milling Operations ◽  
Nc Program ◽  
Machining System ◽  
Optimal Feed ◽  
Smart Machining

Abstract Feedrate optimization is an important aspect of getting shorter machining time and increase the potential of efficient machining. This paper presents an autonomous machining system and optimization strategies to predict and improve the performance of milling operations. The machining process was simulated and analyzed in virtual machining framework to extract cutter-workpiece engagement conditions. Cutting force along the cutting segmentation is evaluated based on the laws of mechanics of milling. In simulation, constraint-based optimization scheme was used to maximize the cutting force by calculating acceptable feedrate levels as the optimizing strategy. The intelligent algorithm was integrated into autonomous machining system to modify NC program to accommodate these new feedrates values. The experiment using optimized NC file which generates by our smart machining system were conducted. The result showed autonomous machining system, was effectively reduced 26%. Highlights The smart machining system was implemented in the CNC machine. Optimal feed rates enhance machine tool efficiency. The smart machining system is reliable to reduce machine time.

Machining Force Modeling of Vibration-Assisted Nano-Machining Process

2015 ◽  
Author(s):  
Xiangcheng Kong ◽  
Li Zhang ◽  
Jingyan Dong ◽  
Paul H. Cohen
Keyword(s):  
Cutting Force ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Low Cost ◽  
Machining Process ◽  
Pmma Film ◽  
Force Model ◽  
Force Modeling ◽  
Machining Force

Nanofabrication technology is very important for many emerging engineering and scientific applications. Among different nanofabrication technologies, vibration-assisted nano-machining provides a low cost easy-to-setup approach to produce structures with nano-scale resolution. It is critical to understand the mechanism for the nano-machining process and predict the cutting force, so as to provide guidelines to achieve higher productivity and reduce tip wear. In this article, a machining force model for tip-based nano-machining process is developed and validated. We analyze the instantaneous engagement area between cutting tool (AFM tip) and workpiece (PMMA film) at the given tip position for the vibration-assisted nano-machining process. A discrete voxel method is adopted to calculate the material removal rate at each moment, and an empirical machining force model is developed by correlating the cutting force with material removal rate. The model was verified by experiments over a large range of machining conditions, and the coefficients and parameters in the force model was obtained using Mean Square Error (MSE) method by comparing the predicted machining force from the force model and measured machining force from experiments. The results show good fit between predicted machining force and measured machining force.

scholarly journals Development and Implementation of a Platform for Public Information on Air Quality, Sensor Measurements, and Citizen Science

Atmosphere ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 445 ◽  
Author(s):  
Wesseling ◽  
Ruiter ◽  
Blokhuis ◽  
Drukker ◽  
Weijers ◽  
...  
Keyword(s):  
Air Quality ◽  
Citizen Science ◽  
Low Cost ◽  
Public Information ◽  
Quality Monitoring ◽  
Sensor Data ◽  
Air Quality Monitoring ◽  
Case Examples ◽  
Air Quality Measurements ◽  
Calibration Methods

The use of low-cost sensors for air quality measurements is expanding rapidly, with an associated rise in the number of citizens measuring air quality themselves. This has major implications for traditional air quality monitoring as performed by Environmental Protection Agencies. Here we reflect on the experiences of the Dutch Institute for Public Health and the Environment (RIVM) with the use of low-cost sensors, particularly NO2 and PM10/PM2.5-sensors, and related citizen science, over the last few years. Specifically, we discuss the Dutch Innovation Program for Environmental Monitoring, which comprises the development of a knowledge portal and sensor data portal, new calibration approaches for sensors, and modelling and assimilation techniques for incorporating these uncertain sensor data into air pollution models. Finally, we highlight some of the challenges that come with the use of low-cost sensors for air quality monitoring, and give some specific use-case examples. Our results show that low-cost sensors can be a valuable addition to traditional air quality monitoring, but so far, their use in official monitoring has been limited. More research is needed to establish robust calibration methods while ongoing work is also aimed at a better understanding of the public’s needs for air quality information to optimize the use of low-cost sensors.

Optimum Design for the Frame of Open Type Abrasive Flow Polish Machine

2012 ◽  
Vol 497 ◽  
pp. 89-93
Author(s):  
Liang Liang Yuan ◽  
Ke Hua Zhang ◽  
Li Min
Keyword(s):  
Finite Element ◽  
Natural Frequency ◽  
Finite Element Methods ◽  
Optimization Design ◽  
Low Cost ◽  
Three Dimensional ◽  
Force Model ◽  
Optimization Analysis ◽  
Open Type ◽  
Set Up

In order to process heterotype hole of workpiece precisely, an open abrasive flow polish machine is designed, and the optimization design of machine frame is done for low cost. Firstly, basing on the parameters designed with traditional ways, three-dimensional force model is set up with the soft of SolidWorks. Secondly, the statics and modal analysis for machine body have been done in Finite element methods (FEM), and then the optimization analysis of machine frame has been done. At last, the model of rebuild machine frame has been built. Result shows that the deformation angle value of machine frame increased from 0.72′ to 1.001′, the natural frequency of the machine decreased from 75.549 Hz to 62.262 Hz, the weight of machine decreased by 74.178 Kg after optimization. It meets the strength, stiffness and angel stiffness requirement of machine, reduces the weight and cost of machine.

scholarly journals Implementation of a Six-Layer Smart Factory Architecture with Special Focus on Transdisciplinary Engineering Education

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2944
Author(s):  
Benjamin James Ralph ◽  
Marcel Sorger ◽  
Benjamin Schödinger ◽  
Hans-Jörg Schmölzer ◽  
Karin Hartl ◽  
...  
Keyword(s):  
Open Source ◽  
User Interfaces ◽  
Industrial Revolution ◽  
Low Cost ◽  
Material Behavior ◽  
Sensor Data ◽  
Management Tool ◽  
Special Focus ◽  
Programming Environments ◽  
Metal Processing

Smart factories are an integral element of the manufacturing infrastructure in the context of the fourth industrial revolution. Nevertheless, there is frequently a deficiency of adequate training facilities for future engineering experts in the academic environment. For this reason, this paper describes the development and implementation of two different layer architectures for the metal processing environment. The first architecture is based on low-cost but resilient devices, allowing interested parties to work with mostly open-source interfaces and standard back-end programming environments. Additionally, one proprietary and two open-source graphical user interfaces (GUIs) were developed. Those interfaces can be adapted front-end as well as back-end, ensuring a holistic comprehension of their capabilities and limits. As a result, a six-layer architecture, from digitization to an interactive project management tool, was designed and implemented in the practical workflow at the academic institution. To take the complexity of thermo-mechanical processing in the metal processing field into account, an alternative layer, connected with the thermo-mechanical treatment simulator Gleeble 3800, was designed. This framework is capable of transferring sensor data with high frequency, enabling data collection for the numerical simulation of complex material behavior under high temperature processing. Finally, the possibility of connecting both systems by using open-source software packages is demonstrated.

scholarly journals Recent Developments of Antimony-Based Anodes for Sodium- and Potassium-Ion Batteries

2021 ◽  
Author(s):  
Bochao Chen ◽  
Ming Liang ◽  
Qingzhao Wu ◽  
Shan Zhu ◽  
Naiqin Zhao ◽  
...  
Keyword(s):  
Structural Characteristics ◽  
Low Cost ◽  
Potassium Ion ◽  
Research Progress ◽  
Research Directions ◽  
Weak Charge ◽  
Recent Developments ◽  
High Theoretical Capacity ◽  
Further Development ◽  
Sodium And Potassium

AbstractThe development of sodium-ion (SIBs) and potassium-ion batteries (PIBs) has increased rapidly because of the abundant resources and cost-effectiveness of Na and K. Antimony (Sb) plays an important role in SIBs and PIBs because of its high theoretical capacity, proper working voltage, and low cost. However, Sb-based anodes have the drawbacks of large volume changes and weak charge transfer during the charge and discharge processes, thus leading to poor cycling and rapid capacity decay. To address such drawbacks, many strategies and a variety of Sb-based materials have been developed in recent years. This review systematically introduces the recent research progress of a variety of Sb-based anodes for SIBs and PIBs from the perspective of composition selection, preparation technologies, structural characteristics, and energy storage behaviors. Moreover, corresponding examples are presented to illustrate the advantages or disadvantages of these anodes. Finally, we summarize the challenges of the development of Sb-based materials for Na/K-ion batteries and propose potential research directions for their further development.

scholarly journals Development and Evaluation of a Low-Drift Inertial Sensor-Based System for Analysis of Alpine Skiing Performance

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2480
Author(s):  
Isidoro Ruiz-García ◽  
Ismael Navarro-Marchal ◽  
Javier Ocaña-Wilhelmi ◽  
Alberto J. Palma ◽  
Pablo J. Gómez-López ◽  
...  
Keyword(s):  
Data Fusion ◽  
Reference System ◽  
Inertial Sensor ◽  
Low Cost ◽  
Sampling Rate ◽  
Sensor Data ◽  
Fusion Algorithm ◽  
Improve Technique ◽  
Worst Case ◽  
Sensor Data Fusion

In skiing it is important to know how the skier accelerates and inclines the skis during the turn to avoid injuries and improve technique. The purpose of this pilot study with three participants was to develop and evaluate a compact, wireless, and low-cost system for detecting the inclination and acceleration of skis in the field based on inertial measurement units (IMU). To that end, a commercial IMU board was placed on each ski behind the skier boot. With the use of an attitude and heading reference system algorithm included in the sensor board, the orientation and attitude data of the skis were obtained (roll, pitch, and yaw) by IMU sensor data fusion. Results demonstrate that the proposed IMU-based system can provide reliable low-drifted data up to 11 min of continuous usage in the worst case. Inertial angle data from the IMU-based system were compared with the data collected by a video-based 3D-kinematic reference system to evaluate its operation in terms of data correlation and system performance. Correlation coefficients between 0.889 (roll) and 0.991 (yaw) were obtained. Mean biases from −1.13° (roll) to 0.44° (yaw) and 95% limits of agreements from 2.87° (yaw) to 6.27° (roll) were calculated for the 1-min trials. Although low mean biases were achieved, some limitations arose in the system precision for pitch and roll estimations that could be due to the low sampling rate allowed by the sensor data fusion algorithm and the initial zeroing of the gyroscope.

scholarly journals BIM and IoT Sensors Integration: A Framework for Consumption and Indoor Conditions Data Monitoring of Existing Buildings

2021 ◽  
Vol 13 (8) ◽  
pp. 4496
Author(s):  
Giuseppe Desogus ◽  
Emanuela Quaquero ◽  
Giulia Rubiu ◽  
Gianluca Gatto ◽  
Cristian Perra
Keyword(s):  
Energy Consumption ◽  
Low Cost ◽  
Application Programming Interface ◽  
Visual Programming ◽  
Information Modeling ◽  
Sensor Data ◽  
Time Data ◽  
Existing Building ◽  
Building Maintenance ◽  
Indoor Conditions

The low accessibility to the information regarding buildings current performances causes deep difficulties in planning appropriate interventions. Internet of Things (IoT) sensors make available a high quantity of data on energy consumptions and indoor conditions of an existing building that can drive the choice of energy retrofit interventions. Moreover, the current developments in the topic of the digital twin are leading the diffusion of Building Information Modeling (BIM) methods and tools that can provide valid support to manage all data and information for the retrofit process. This paper shows the aim and the findings of research focused on testing the integrated use of BIM methodology and IoT systems. A common data platform for the visualization of building indoor conditions (e.g., temperature, luminance etc.) and of energy consumption parameters was carried out. This platform, tested on a case study located in Italy, is developed with the integration of low-cost IoT sensors and the Revit model. To obtain a dynamic and automated exchange of data between the sensors and the BIM model, the Revit software was integrated with the Dynamo visual programming platform and with a specific Application Programming Interface (API). It is an easy and straightforward tool that can provide building managers with real-time data and information about the energy consumption and the indoor conditions of buildings, but also allows for viewing of the historical sensor data table and creating graphical historical sensor data. Furthermore, the BIM model allows the management of other useful information about the building, such as dimensional data, functions, characteristics of the components of the building, maintenance status etc., which are essential for a much more conscious, effective and accurate management of the building and for defining the most suitable retrofit scenarios.

scholarly journals 3D Affine: An Embedding of Local Image Features for Viewpoint Invariance Using RGB-D Sensor Data

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 291 ◽  
Author(s):  
Hamdi Sahloul ◽  
Shouhei Shirafuji ◽  
Jun Ota
Keyword(s):  
Low Cost ◽  
Image Features ◽  
Image Feature ◽  
Sensor Data ◽  
Invariant Representation ◽  
Depth Sensors ◽  
Viewpoint Invariance ◽  
Surface Discontinuities ◽  
Local Image ◽  
Local Image Features

Local image features are invariant to in-plane rotations and robust to minor viewpoint changes. However, the current detectors and descriptors for local image features fail to accommodate out-of-plane rotations larger than 25°–30°. Invariance to such viewpoint changes is essential for numerous applications, including wide baseline matching, 6D pose estimation, and object reconstruction. In this study, we present a general embedding that wraps a detector/descriptor pair in order to increase viewpoint invariance by exploiting input depth maps. The proposed embedding locates smooth surfaces within the input RGB-D images and projects them into a viewpoint invariant representation, enabling the detection and description of more viewpoint invariant features. Our embedding can be utilized with different combinations of descriptor/detector pairs, according to the desired application. Using synthetic and real-world objects, we evaluated the viewpoint invariance of various detectors and descriptors, for both standalone and embedded approaches. While standalone local image features fail to accommodate average viewpoint changes beyond 33.3°, our proposed embedding boosted the viewpoint invariance to different levels, depending on the scene geometry. Objects with distinct surface discontinuities were on average invariant up to 52.8°, and the overall average for all evaluated datasets was 45.4°. Similarly, out of a total of 140 combinations involving 20 local image features and various objects with distinct surface discontinuities, only a single standalone local image feature exceeded the goal of 60° viewpoint difference in just two combinations, as compared with 19 different local image features succeeding in 73 combinations when wrapped in the proposed embedding. Furthermore, the proposed approach operates robustly in the presence of input depth noise, even that of low-cost commodity depth sensors, and well beyond.

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