scholarly journals Testing the Capability of Low-Cost Tools and Artificial Intelligence Techniques to Automatically Detect Operations Done by a Small-Sized Manually Driven Bandsaw

Forests ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 739
Author(s):  
Marius Cheţa ◽  
Marina Viorela Marcu ◽  
Eugen Iordache ◽  
Stelian Alexandru Borz
Keyword(s):  
Artificial Intelligence ◽  
Low Cost ◽  
Electrical Power ◽  
Experimental System ◽  
Video Camera ◽  
Business Failure ◽  
Small Scale ◽  
Wood Processing ◽  
Artificial Neural Network Ann ◽  
Level Meter

Research Highlights: A low-cost experimental system was developed to enable the production monitoring of small-scale wood processing facilities by the means of sensor-collected data and the implementation of artificial intelligence (AI) techniques, which provided accurate results for the most important work operations. Background and Objectives: The manufacturing of wood-based products by small-scale family-held business is commonly affected by a lack of monitoring data that, on the one hand, may prevent the decision-making process and, on the other hand, may lead to less technical efficiency that could result in business failure. Long-term performance of such manufacturing facilities is limited because data collection and analysis require significant resources, thus preventing the approaches that could be pursued for competitivity improvement. Materials and Methods: An external sensor system composed of two dataloggers—a triaxial accelerometer and a sound pressure level meter—was used in combination with a video camera to provide the input signals and meta-documentation for the training and testing of an artificial neural network (ANN) to check the accuracy of automatic classification of the time spent in operations. The study was based on a sample of ca. 90 k observations collected at a frequency of 1 Hz. Results: The approach provided promising results in both the training (ca. 20 k) and testing (ca. 60 k) datasets, with global classification accuracies of ca. 85%. However, the events characterizing the effective sawing, which requires electrical power, were even better recognized, reaching a classification accuracy of 98%. Conclusions: The system requires low-cost devices and freely available software that could enable data feeding on local computers by their direct connection to the devices. As such, it could collect, analyze and plot production data that could be used for maintaining the competitiveness of traditional technologies.

scholarly journals EXPERIMENTAL INVESTIGATION OF TOOL WEAR AND INDUCED VIBRATION IN TURNING HIGH HARDNESS AISI52100 STEEL USING CUTTING PARAMETERS AND TOOL ACCELERATION

2020 ◽  
pp. 623
Author(s):  
Nitin Ambhore ◽  
Dinesh Kamble
Keyword(s):  
Tool Wear ◽  
Cutting Tool ◽  
Low Cost ◽  
High Hardness ◽  
Cutting Parameters ◽  
Small Scale ◽  
Wear Monitoring ◽  
Artificial Neural Network Ann ◽  
Experimental Values ◽  
Coated Carbide

In machining of high hardness steel, vibration of cutting tool increases tool wear which reduces its life. Tool wear is catastrophic in nature and hence investigation of its assessment is important. This study investigates experimentally induced vibration during turning of hardened AISI52100 steel of hardness 54±2 HRC using coated carbide insert. In this context, cutting tool acceleration is measured and used to develop a novel mathematical model based on acquired real time acceleration signals of cutting tool. The obtained model is validated as R2= 0.93 while its residuals values closely follow the straight line. The predictions are confirmed by conducting conformity test which revealed a close degree of agreement with respect to the experimental values. The Artificial Neural Network (ANN) examination is performed to determine the model regression value. The study shows that the examined reports forecasts of ANN are more exact than regression analysis. The future directon of this investigation is towards developing a low-cost microcontroller-based hardware unit for in-process tool wear monitoring which could be beneficial for small scale industries.

scholarly journals Integrating Offline Object Tracking, Signal Processing, and Artificial Intelligence to Classify Relevant Events in Sawmilling Operations

Forests ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1333
Author(s):  
Stelian Alexandru Borz ◽  
Marius Păun
Keyword(s):  
Artificial Intelligence ◽  
Signal Processing ◽  
Object Tracking ◽  
Low Cost ◽  
Small Scale ◽  
Differential Signal ◽  
The Time Domain ◽  
Basic Level ◽  
Tracking Signal

Sawmilling operations are typically one of the most important cells of the wood supply chain as they take the log assortments as inputs to which they add value by processing lumber and other semi-finite products. For this kind of operations, and especially for those developed at a small scale, long-term monitoring data is a prerequisite to make decisions, to increase the operational efficiency and to enable the precision of operations. In many cases, however, collection and handling of such data is limited to a set of options which may come at high costs. In this study, a low-cost solution integrating offline object tracking, signal processing and artificial intelligence was tested to evaluate its capability to correctly classify in the time domain the events specific to the monitoring of wood sawmilling operations. Discrete scalar signals produced from media files by tracking functionalities of the Kinovea® software (13,000 frames) were used to derive a differential signal, then a filtering-to-the-root procedure was applied to them. Both, the raw and filtered signals were used as inputs in the training of an artificial neural network at two levels of operational detail: fully and essentially documented data. While the addition of the derived signal made sense because it improved the outcomes of classification (recall of 92–97%) filtered signals were found to add less contribution to the classification accuracy. The use of essentially documented data has improved substantially the classification outcomes and it could be an excellent solution in monitoring applications requiring a basic level of detail. The tested system could represent a good and cheap solution to monitor sawmilling facilities aiming to develop our understanding on their technical efficiency.

Treatment of wastewater by constructed wetland in small settlements

2000 ◽  
Vol 41 (1) ◽  
pp. 69-72 ◽  
Author(s):  
S.Ç. Ayaz ◽  
I. Akca
Keyword(s):  
Environmental Pollution ◽  
Constructed Wetland ◽  
Pilot Plant ◽  
Low Cost ◽  
Experimental System ◽  
Suspended Solid ◽  
Loading Conditions ◽  
Treatment Performance ◽  
Per Capita ◽  
One Year

The constructed wetland is a low-cost technology to control environmental pollution. The system is especially suitable for small settlements. An innovative constructed wetland technology is described in this paper. A pilot plant was used to assess the performance of the system. The experimental system consists of two serial connected tanks that settled up with fillers and Cyperus as treatment media. Wastewater is recycled periodically upward and downward between the two tanks. The treatment performance was monitored in different loading conditions in a one-year period. The average COD removal efficiency of 90% was observed at 122 g COD/m2.day average loading conditions. Other average removal values in the same conditions are as follows: suspended solid 95%, TKN 77%, total nitrogen 61%, PO4-P 39%. The land requirement for this system will be 0.82 m2 per capita when applying as full-scale system.

Tools of Transformation: Appropriate Technology in U.S. Countercultural Literature

2012 ◽  
Vol 44 (2) ◽  
pp. 75-93
Author(s):  
Peter Mortensen
Keyword(s):  
Low Cost ◽  
Appropriate Technology ◽  
Small Scale ◽  
Environmental Transformation ◽  
Buckminster Fuller ◽  
1960S And 1970S ◽  
The 1960S ◽  
Environmentally Sound ◽  
User Friendly ◽  
Second Wave

This essay takes its cue from second-wave ecocriticism and from recent scholarly interest in the “appropriate technology” movement that evolved during the 1960s and 1970s in California and elsewhere. “Appropriate technology” (or AT) refers to a loosely-knit group of writers, engineers and designers active in the years around 1970, and more generally to the counterculture’s promotion, development and application of technologies that were small-scale, low-cost, user-friendly, human-empowering and environmentally sound. Focusing on two roughly contemporary but now largely forgotten American texts Sidney Goldfarb’s lyric poem “Solar-Heated-Rhombic-Dodecahedron” (1969) and Gurney Norman’s novel Divine Right’s Trip (1971)—I consider how “hip” literary writers contributed to eco-technological discourse and argue for the 1960s counterculture’s relevance to present-day ecological concerns. Goldfarb’s and Norman’s texts interest me because they conceptualize iconic 1960s technologies—especially the Buckminster Fuller-inspired geodesic dome and the Volkswagen van—not as inherently alienating machines but as tools of profound individual, social and environmental transformation. Synthesizing antimodernist back-to-nature desires with modernist enthusiasm for (certain kinds of) machinery, these texts adumbrate a humanity- and modernity-centered post-wilderness model of environmentalism that resonates with the dilemmas that we face in our increasingly resource-impoverished, rapidly warming and densely populated world.

scholarly journals Development of a simplified gas ultracleaning process: experiments in biomass residue-based fixed-bed gasification syngas

2021 ◽  
Author(s):  
Christian Frilund ◽  
Esa Kurkela ◽  
Ilkka Hiltunen
Keyword(s):  
Activated Carbons ◽  
Low Cost ◽  
Fixed Bed ◽  
Carbonyl Sulfide ◽  
Gas Analysis ◽  
Small Scale ◽  
Cleaning Process ◽  
Medium Temperature ◽  
Gas Cleaning ◽  
Adsorption Affinity

AbstractFor the realization of small-scale biomass-to-liquid (BTL) processes, low-cost syngas cleaning remains a major obstacle, and for this reason a simplified gas ultracleaning process is being developed. In this study, a low- to medium-temperature final gas cleaning process based on adsorption and organic solvent-free scrubbing methods was coupled to a pilot-scale staged fixed-bed gasification facility including hot filtration and catalytic reforming steps for extended duration gas cleaning tests for the generation of ultraclean syngas. The final gas cleaning process purified syngas from woody and agricultural biomass origin to a degree suitable for catalytic synthesis. The gas contained up to 3000 ppm of ammonia, 1300 ppm of benzene, 200 ppm of hydrogen sulfide, 10 ppm of carbonyl sulfide, and 5 ppm of hydrogen cyanide. Post-run characterization displayed that the accumulation of impurities on the Cu-based deoxygenation catalyst (TOS 105 h) did not occur, demonstrating that effective main impurity removal was achieved in the first two steps: acidic water scrubbing (AWC) and adsorption by activated carbons (AR). In the final test campaign, a comprehensive multipoint gas analysis confirmed that ammonia was fully removed by the scrubbing step, and benzene and H2S were fully removed by the subsequent activated carbon beds. The activated carbons achieved > 90% removal of up to 100 ppm of COS and 5 ppm of HCN in the syngas. These results provide insights into the adsorption affinity of activated carbons in a complex impurity matrix, which would be arduous to replicate in laboratory conditions.

scholarly journals A New Approach to Quantifying Bioaccumulation of Elements in Biological Processes

Biology ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 345
Author(s):  
Kinga Proc ◽  
Piotr Bulak ◽  
Monika Kaczor ◽  
Andrzej Bieganowski
Keyword(s):  
Element Concentration ◽  
Experimental System ◽  
Small Scale ◽  
New Approach ◽  
Realistic Situation ◽  
Initial Load ◽  
Test Elements ◽  
Organism Growth ◽  
Bioaccumulation Index ◽  
Phosphorous Concentration

Bioaccumulation, expressed as the bioaccumulation factor (BAF), is a phenomenon widely investigated in the natural environment and at laboratory scale. However, the BAF is more suitable for ecological studies, while in small-scale experiments it has limitations, which are discussed in this article. We propose a new indicator, the bioaccumulation index (BAI). The BAI takes into account the initial load of test elements, which are added to the experimental system together with the biomass of the organism. This offers the opportunity to explore the phenomena related to the bioaccumulation and, contrary to the BAF, can also reveal the dilution of element concentration in the organism. The BAF can overestimate bioaccumulation, and in an extremal situation, when the dilution of element concentration during organism growth occurs, the BAF may produce completely opposite results to the BAI. In one of the examples presented in this work (Tschirner and Simon, 2015), the concentration of phosphorous in fly larvae was lower after the experiment than in the younger larvae before the experiment. Because the phosphorous concentration in the feed was low, the BAF indicated a high bioaccumulation of this element (BAF = 14.85). In contrast, the BAI showed element dilution, which is a more realistic situation (BAI = −0.32). By taking more data into account, the BAI seems to be more valid in determining bioaccumulation, especially in the context of entomoremediation research.

scholarly journals A 40 Mb/s VLC System Reusing an Existing Large LED Panel in an Indoor Office Environment

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1697
Author(s):  
Xicong Li ◽  
Zabih Ghassemlooy ◽  
Stanislav Zvánovec ◽  
Paul Anthony Haigh
Keyword(s):  
Modulation Depth ◽  
Light Emitting Diode ◽  
Low Cost ◽  
Data Communication ◽  
Experimental System ◽  
Digital Signal ◽  
Visible Light Communication ◽  
Cost Driver ◽  
Limiting Factors ◽  
Light Sources

With advances in solid-state lighting, visible light communication (VLC) has emerged as a promising technology to enhance existing light-emitting diode (LED)-based lighting infrastructure by adding data communication capabilities to the illumination functionality. The last decade has witnessed the evolution of the VLC concept through global standardisation and product launches. Deploying VLC systems typically requires replacing existing light sources with new luminaires that are equipped with data communication functionality. To save the investment, it is clearly desirable to make the most of the existing illumination systems. This paper investigates the feasibility of adding data communication functionality to the existing lighting infrastructure. We do this by designing an experimental system in an indoor environment based on an off-the-shelf LED panel typically used in office environments, with the dimensions of 60 × 60 cm2. With minor modifications, the VLC function is implemented, and all of the modules of the LED panel are fully reused. A data rate of 40 Mb/s is supported at a distance of up to 2 m while using the multi-band carrierless amplitude and phase (CAP) modulation. Two main limiting factors for achieving higher data rates are observed. The first factor is the limited bandwidth of the LED string inside the panel. The second is the flicker due to the residual ripple of the bias current that is generated by the panel’s driver. Flicker is introduced by the low-cost driver, which provides bias currents that fluctuate in the low frequency range (less than several kilohertz). This significantly reduces the transmitter’s modulation depth. Concurrently, the driver can also introduce an effect that is similar to baseline wander at the receiver if the flicker is not completely filtered out. We also proposed a solution based on digital signal processing (DSP) to mitigate the flicker issue at the receiver side and its effectiveness has been confirmed.

scholarly journals Understanding Spatial Variability of NO2 in Urban Areas Using Spatial Modelling and Data Fusion Approaches

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 179
Author(s):  
Said Munir ◽  
Martin Mayfield ◽  
Daniel Coca
Keyword(s):  
Data Fusion ◽  
Spatial Variability ◽  
Urban Areas ◽  
Road Traffic ◽  
Dispersion Model ◽  
Low Cost ◽  
Spatial Modelling ◽  
City Centre ◽  
Small Scale ◽  
The City

Small-scale spatial variability in NO2 concentrations is analysed with the help of pollution maps. Maps of NO2 estimated by the Airviro dispersion model and land use regression (LUR) model are fused with measured NO2 concentrations from low-cost sensors (LCS), reference sensors and diffusion tubes. In this study, geostatistical universal kriging was employed for fusing (integrating) model estimations with measured NO2 concentrations. The results showed that the data fusion approach was capable of estimating realistic NO2 concentration maps that inherited spatial patterns of the pollutant from the model estimations and adjusted the modelled values using the measured concentrations. Maps produced by the fusion of NO2-LCS with NO2-LUR produced better results, with r-value 0.96 and RMSE 9.09. Data fusion adds value to both measured and estimated concentrations: the measured data are improved by predicting spatiotemporal gaps, whereas the modelled data are improved by constraining them with observed data. Hotspots of NO2 were shown in the city centre, eastern parts of the city towards the motorway (M1) and on some major roads. Air quality standards were exceeded at several locations in Sheffield, where annual mean NO2 levels were higher than 40 µg/m3. Road traffic was considered to be the dominant emission source of NO2 in Sheffield.

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