scholarly journals Increasing the Reliability of Data Collection of Laser Line Triangulation Sensor by Proper Placement of the Sensor

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2890
Author(s):  
Dominik Heczko ◽  
Petr Oščádal ◽  
Tomáš Kot ◽  
Daniel Huczala ◽  
Ján Semjon ◽  
...  

In this paper, we investigated the effect of the incidence angle of a laser ray on the reflected laser intensity. A dataset on this dependence is presented for materials usually used in the industry, such as transparent and non-transparent plastics and aluminum alloys with different surface roughness. The measurements have been performed with a laser line triangulation sensor and a UR10e robot. The presented results are proposing where to place the sensor relative to the scanned object, thus increasing the reliability of the sensor data collection.

2013 ◽  
Vol 404 ◽  
pp. 3-9 ◽  
Author(s):  
Nihat Tosun ◽  
Ihsan Dagtekin ◽  
Latif Ozler ◽  
Ahmet Deniz

Abrasive waterjet machining is one of the non-traditional methods of the recent years which found itself a wide area of application in the industry for machining of different materials. In this paper, the surface roughness of 6061-T6 and 7075-T6 aluminum alloys are being cut with abrasive waterjet is examined experimentally. The experiments were conducted with different waterjet pressures and traverse speeds. It has been found that the surface roughness obtained by cutting material with high mechanical properties is better than that of obtained by cutting material with inferior mechanical properties.


1994 ◽  
Vol 354 ◽  
Author(s):  
Shuji Kiyohara ◽  
Iwao Miyamoto

AbstractIn order to apply ion beam etching with hydrogen ions to the ultra-precision processing of diamond tools, hydrogen ion beam etching characteristics of single crystal diamond chips with (100) face were investigated. The etching rate of diamond for 500 eV and 1000 eV hydrogen ions increases with the increase of the ion incidence angle, and eventually reaches a maximum at the ion incidence angle of approximately 50°, then may decrease with the increase of the ion incidence angle. The dependence of the etching rate on the ion incidence angle of hydrogen ions is fairly similar to that obtained with argon ions. Furthermore, the surface roughness of diamond chips before and after hydrogen ion beam etching was evaluated using an atomic force microscope. Consequently, the surface roughness after hydrogen ion beam etching decreases with the increase of the ion incidence angle within range of the ion incidence angle of 60°.


2021 ◽  
Author(s):  
María Óskarsdóttir ◽  
Anna Sigridur Islind ◽  
Elias August ◽  
Erna Sif Arnardóttir ◽  
Francois Patou ◽  
...  

BACKGROUND The method considered the gold standard for recording sleep is a polysomnography, where the measurement is performed in a hospital environment for 1-3 nights. This requires subjects to sleep with a device and several sensors attached to their face, scalp, and body, which is both cumbersome and expensive. For longer studies with actigraphy, 3-14 days of data collection is typically used for both clinical and research studies. OBJECTIVE The primary goal of this paper is to investigate if the aforementioned timespan is sufficient for data collection, when performing sleep measurements at home using wearable and non-wearable sensors. Specifically, whether 3-14 days of data collection sufficient to capture an individual’s sleep habits and fluctuations in sleep patterns in a reliable way for research purposes. Our secondary goals are to investigate whether there is a relationship between sleep quality, physical activity, and heart rate, and whether individuals who exhibit similar activity and sleep patterns in general and in relation to seasonality can be clustered together. METHODS Data on sleep, physical activity, and heart rate was collected over a period of 6 months from 54 individuals in Denmark aged 52-86 years. The Withings Aura sleep tracker (non-wearable) and Withings Steel HR smartwatch (wearable) were used. At the individual level, we investigated the consistency of various physical activities and sleep metrics over different time spans to illustrate how sensor data from self-trackers can be used to illuminate trends. RESULTS Significant variability in standard metrics of sleep quality was found between different periods throughout the study. We show specifically that in order to get more robust individual assessment of sleep and physical activity patterns through wearable and non-wearable devices, a longer evaluation period than 3-14 days is necessary. Additionally, we found seasonal patterns in sleep data related to changing of the clock for Daylight Saving Time (DST). CONCLUSIONS We demonstrate that over two months worth of self-tracking data is needed to provide a representative summary of daily activity and sleep patterns. By doing so, we challenge the current standard of 3-14 days for sleep quality assessment and call for rethinking standards when collecting data for research purposes. Seasonal patterns and DST clock change are also important aspects that need to be taken into consideration, and designed for, when choosing a period for collecting data. Furthermore, we suggest using consumer-grade self-trackers (wearable and non-wearable ones) to support longer term evaluations of sleep and physical activity for research purposes and, possibly, clinical ones in the future.


2021 ◽  
Author(s):  
Ramesh Subramanian ◽  
David Rule ◽  
Onur Nazik

Abstract Laser Powder Bed Fusion (LPBF) of metallic components is unlocking new design options for high efficiency gas turbine component designs not possible by conventional manufacturing technologies. Surface roughness is a key characteristic of LPBF components that impacts heat transfer correlations and crack initiation from co-located surface defects — both are critical for gas turbine component durability and performance. However, even for a single material, there is an increasing diversity in laser machines (single vs multi-laser), layer thicknesses (∼20–80 microns) and orientations to the build plate (upskin, vertical and downskin) that result in significant variability in surface roughness. This study systematically compares the surface roughness across the above-mentioned variables to further develop a repeatable correlation of surface roughness to the angle between the substrate normal and laser incidence direction. This presented data will be discussed in detail, to show potential applicability of this process signature curve across materials, machines, and substrate orientations. Future steps to a rapid process qualification standard for surface roughness, across Siemens Energy’s global manufacturing footprint will also be discussed.


Author(s):  
Valeria Gelardi ◽  
Jeanne Godard ◽  
Dany Paleressompoulle ◽  
Nicolas Claidiere ◽  
Alain Barrat

Network analysis represents a valuable and flexible framework to understand the structure of individual interactions at the population level in animal societies. The versatility of network representations is moreover suited to different types of datasets describing these interactions. However, depending on the data collection method, different pictures of the social bonds between individuals could a priori emerge. Understanding how the data collection method influences the description of the social structure of a group is thus essential to assess the reliability of social studies based on different types of data. This is however rarely feasible, especially for animal groups, where data collection is often challenging. Here, we address this issue by comparing datasets of interactions between primates collected through two different methods: behavioural observations and wearable proximity sensors. We show that, although many directly observed interactions are not detected by the sensors, the global pictures obtained when aggregating the data to build interaction networks turn out to be remarkably similar. Moreover, sensor data yield a reliable social network over short time scales and can be used for long-term studies, showing their important potential for detailed studies of the evolution of animal social groups.


Sensors are gadgets, which can screen temperature, moistness, weight, commotion levels, setting mindfulness, lighting condition and identify speed, position, and size of an Object. Sensor information are getting accumulated in gigantic amount thus they are overseen utilizing NOSQL. The information will be gathered in an IOT cloud stage where it will be additionally prepared with machine learning methods for prescient examination. What's more, eventually with the required answer for the business structure will be created. This paper explain the proposed system for IoT data collection with AWS (Amazon Web Service) cloud platform. Various system components like Kinesis stream, M2M platform, Notification service and secured IoT service layout. The complete BMS system architecture is detailed in this paper.


2019 ◽  
Author(s):  
Anna L Beukenhorst ◽  
Kelly Howells ◽  
Louise Cook ◽  
John McBeth ◽  
Terence W O'Neill ◽  
...  

BACKGROUND Wearables provide opportunities for frequent health data collection and symptom monitoring. The feasibility of using consumer cellular smartwatches to provide information both on symptoms and contemporary sensor data has not yet been investigated. OBJECTIVE This study aimed to investigate the feasibility and acceptability of using cellular smartwatches to capture multiple patient-reported outcomes per day alongside continuous physical activity data over a 3-month period in people living with knee osteoarthritis (OA). METHODS For the KOALAP (Knee OsteoArthritis: Linking Activity and Pain) study, a novel cellular smartwatch app for health data collection was developed. Participants (age ≥50 years; self-diagnosed knee OA) received a smartwatch (Huawei Watch 2) with the KOALAP app. When worn, the watch collected sensor data and prompted participants to self-report outcomes multiple times per day. Participants were invited for a baseline and follow-up interview to discuss their motivations and experiences. Engagement with the watch was measured using daily watch wear time and the percentage completion of watch questions. Interview transcripts were analyzed using grounded thematic analysis. RESULTS A total of 26 people participated in the study. Good use and engagement were observed over 3 months: most participants wore the watch on 75% (68/90) of days or more, for a median of 11 hours. The number of active participants declined over the study duration, especially in the final week. Among participants who remained active, neither watch time nor question completion percentage declined over time. Participants were mainly motivated to learn about their symptoms and enjoyed the self-tracking aspects of the watch. Barriers to full engagement were battery life limitations, technical problems, and unfulfilled expectations of the watch. Participants reported that they would have liked to report symptoms more than 4 or 5 times per day. CONCLUSIONS This study shows that capture of patient-reported outcomes multiple times per day with linked sensor data from a smartwatch is feasible over at least a 3-month period. INTERNATIONAL REGISTERED REPORT RR2-10.2196/10238


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Honggang Wang ◽  
Ruixue Yu ◽  
Ruoyu Pan ◽  
Mengyuan Liu ◽  
Qiongdan Huang ◽  
...  

Purpose In manufacturing environments, mobile radio frequency identification (RFID) robots need to quickly identify and collect various types of passive tag and active tag sensor data. The purpose of this paper is to design a robot system compatible with ultra high frequency (UHF) band passive and active RFID applications and to propose a new anti-collision protocol to improve identification efficiency for active tag data collection. Design/methodology/approach A new UHF RFID robot system based on a cloud platform is designed and verified. For the active RFID system, a grouping reservation–based anti-collision algorithm is proposed in which an inventory round is divided into reservation period and polling period. The reservation period is divided into multiple sub-slots. Grouped tags complete sub-slot by randomly transmitting a short reservation frame. Then, in the polling period, the reader accesses each tag by polling. When tags’ reply collision occurs, the reader tries to re-query collided tags once, and the pre-reply tags avoid collisions through random back-off and channel activity detection. Findings The proposed algorithm achieves a maximum theoretical system throughput of about 0.94, and very few tag data frame transmissions overhead. The capture effect and channel activity detection in physical layer can effectively improve system throughput and reduce tag data transmission. Originality/value In this paper, the authors design and verify the UHF band passive and active hybrid RFID robot architecture based on cloud collaboration. And, the proposed anti-collision algorithm would improve active tag data collection speed and reduce tag transmission overhead in complex manufacturing environments.


2020 ◽  
pp. 55-57
Author(s):  
M.G. Galkin ◽  
A.S. Smagin ◽  
A.S. Pupyireva

An algorithm for the development of a mathematical model of cutting processing, as a multifactorial process, which determines the influence of significant parameters of the cutting mode on the roughness of the processed surface, is proposed. In the development of the algorithm, the method of extreme experimental design is used. Keywords cutting, mode, manufacturing process, surface roughness, mathematical model. [email protected]


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