Fertilizer deposition as a function of angular velocity and inclination of the helical dosing mechanism

ABSTRACT The establishment of grain crops in Brazil is an important industrial process in the agricultural chain, requiring the correct deposition of granular fertilizer over the sowing furrow and more efficient, precise, and sustainable assessments in the operation, which can be achieved with the statistical process control. This study aimed to assess the effect of the angular velocity on different inclinations of the helical metering mechanism on the granular fertilizer deposition. An automated electronic bench was used to assess the deposition quality of granular fertilizers considering different angular velocities (1.11, 1.94, and 2.77 m s-1) and longitudinal and transverse inclinations (+15, +7.5, 0, −7.5, and −15°), with the helical doser by overflow. Flow data were collected and submitted to descriptive statistics and statistical process control. The metering mechanism showed expected variations, with acceptable performance under process control. The values of the flow rates of the granular fertilizer increased as velocity increased, standing out longitudinal inclinations of +7.5 and +15°, providing higher fertilizer depositions.

Clustering Application for Condition-Based Maintenance in Time-Varying Processes: A Review Using Latent Dirichlet Allocation

In the field of industrial process monitoring, scholars and practitioners are increasing interest in time-varying processes , where different phases are implemented within an unknown time frame. The measurement of process parameters could inform about the health state of the production assets, or products, but only if the measured parameters are coupled with the specific phase identification. A combination of values could be common for one phase and uncommon for another phase; thus, the same combination of values shows a high or low probability depending on the specific phase. The automatic identification of the production phase usually relies on clustering techniques. This is largely due to the difficulty of finding training fault data for supervised models. With these two considerations in mind, this contribution proposes the Latent Dirichlet Allocation as a natural language-processing technique for reviewing the topic of clustering applied in time-varying contexts, in the maintenance field. Thus, the paper presents this innovative methodology to analyze this specific research fields, presenting the step-by-step application and its results, with an overview of the theme.

Potential Risks of PM2.5-Bound Polycyclic Aromatic Hydrocarbons and Heavy Metals from Inland and Marine Directions for a Marine Background Site in North China

Ambient PM2.5-bound ions, OC, EC, heavy metals (HMs), 18 polycyclic aromatic hydrocarbons (PAHs), 7 hopanes, and 29 n-alkanes were detected at Tuoji Island (TI), the only marine background atmospheric monitoring station in North China. The annual PM2.5 average concentration was 47 ± 31 μg m−3, and the average concentrations of the compositions in PM2.5 were higher in cold seasons than in warm seasons. The cancer and non-cancer risks of HMs and PAHs in cold seasons were also higher than in warm seasons. BaP, Ni, and As dominated the ∑HQ (hazard quotient) in cold seasons, while the non-carcinogenic risk in warm seasons was mainly dominated by Ni, Mn, and As. The ILCR (incremental lifetime cancer risk) values associated with Cr and As were higher in the cold season, while ILCR-Ni values were higher in the warm season. The backward trajectory was calculated to identify the potential directions of air mass at TI. Through the diagnostic ratios of organic and inorganic tracers, the sources of particulate matter in different directions were judged. It was found that ship emissions and sea salt were the main sources from marine directions, while coal combustion, vehicles emissions, industrial process, and secondary aerosols were the main source categories for inland directions. In addition, potential HM and PAH risks from inland and marine directions were explored. The non-cancerous effects of TI were mainly affected by inland transport, especially from the southeast, northwest, and west-northwest. The cancerous effects of TI were mainly simultaneously affected by the inland direction and marine direction of transport.

Integrated near-infrared spectral sensing

Spectral sensing is increasingly used in applications ranging from industrial process monitoring to agriculture. Sensing is usually performed by measuring reflected or transmitted light with a spectrometer and processing the resulting spectra. However, realizing compact and mass-manufacturable spectrometers is a major challenge, particularly in the infrared spectral region where chemical information is most prominent. Here we propose a different approach to spectral sensing which dramatically simplifies the requirements on the hardware and allows the monolithic integration of the sensors. We use an array of resonant-cavity-enhanced photodetectors, each featuring a distinct spectral response in the 850-1700 nm wavelength range. We show that prediction models can be built directly using the responses of the photodetectors, despite the presence of multiple broad peaks, releasing the need for spectral reconstruction. The large etendue and responsivity allow us to demonstrate the application of an integrated near-infrared spectral sensor in relevant problems, namely milk and plastic sensing. Our results open the way to spectral sensors with minimal size, cost and complexity for industrial and consumer applications.

Development of Animal Fibres Composites for Construction Applications

Climate change has become one of the world’s leading threats. Currently, the construction industry has a high environmental footprint. For this reason, the scientific and technological sector is looking for new materials to reduce the environmental consequences of this division. It is well known that the valorisation of different by-products can contribute to the reduction of the energy global consumption and CO2 emissions. Magnesium Phosphate Cement (MPC) can be obtained by using Low Grade Magnesium Oxide (LG-MgO) as a by-product from the industrial process of magnesite calcination. In this research, a Sustainable MPC (Sust-MPC) for different construction purposes is developed by using LG-MgO along with monopotassium phosphate KH2PO4 (MKP) as raw materials. The increasing use of synthetic fibres in clothing, as well as China’s competitive prices on Animal Fibres (AF) market, have led to a commercial interest fibre decrease for wool-like AF in Spain. This study aims to formulate a Sust-MPC cement with Animal Fibre (AF) to reduce the cost of the new material (Sust-MPC-AF) and to increase the thermal insulation, allowing the use of Sust-MPC-AF in several potential applications. Besides, it should be emphasized that the final pH of Sust-MPC is neutral, which allows containing natural fibres. To develop Sust-MPC-AF, some properties such as thermal conductivity, density, Modulus of Elasticity (MoE), flexural strength, and economic cost were evaluated using the Design of Experiments (DoE). The DoE studies allowed obtaining a model for further optimization considering minimum thermal conductivity and cost dosages. The formulation 30L-25EW presents the minimum conductivity (λ=0.140 W·m-1·K-1). Therefore, two optimal dosages (36L-25EW and 24L-22EW) are obtained by considering mixing variables such as AF/Cement ratio (AF/C) and AF/Extra Water ratio (AF/EW).

In Situ LID and Regeneration of PERC Solar Cells from Different Positions of a B-Doped Cz-Si Ingot

In order to investigate the light-induced-degradation (LID) and regeneration of industrial PERC solar cells made from different positions of silicon wafers in a silicon ingot, five groups of silicon wafers were cut from a commercial solar-grade boron-doped Czochralski silicon (Cz-Si) ingot from top to bottom with a certain distance and made into PERC solar cells by using the standard industrial process after measuring lifetimes of minority carriers and concentrations of boron, oxygen, carbon, and transition metal impurities. Then, the changes of their I - V characteristic parameters (efficiency η , open-circuit voltage V oc , short-circuit current I sc , and fill factor FF ) with time were in situ measured by using a solar cell I - V tester during the 1st LID (45°C, 1 sun, 12 h), regeneration (100°C, 1 sun, 24 h), and 2nd LID (45°C, 1 sun, 12 h). The results show that the LID and regeneration of the PERC solar cells are caused by the transition of B-O defects playing a dominant role together with the dissociation of Fe-B pairs playing a secondary role. The decay of η during the 1st LID is caused by the degradation of V oc , I sc , and FF , while the increase of η during the regeneration is mainly contributed by V oc and FF , and the decay of η during the 2nd LID is mainly induced by the degradation of I sc . After regeneration, the decay rate of η reduces from 4.43%–5.56% (relative) during the 1st LID to 0.33%–1.75% (relative) during the 2nd LID.

Application of integrated PCA and FIS approach to the selection of current and vibration signal features in mechanical fault classification of induction motor

The detection as well as analysis of faults in Induction Motor (IM) is prominent in the industrial process in recent decades, since it has been a demanding issue in industries to confirm the safe and reliable operations of IM. Though the electrical faults, mechanical faults and environmental faults cause damages in IM, as per Electric Power Research Institute (EPRI) statistical studies, the faults due to (i) rotor mass unbalance and (ii) rotor shaft bending substantially contribute 8-9% of the total motor fault. This present research work focuses on the issue of detecting and analysing the faults by studying the current and vibration data obtained from the three-phase squirrel cage IM under healthy and faulty conditions using the experimental workbench. It also depicts the development of a fault detection model for IM which comprises the integrated approach of Principal Component Analysis (PCA) and Fuzzy Interference System (FIS) and two level decision fuzzy measures. Besides, fuzzy integral data fusion technique has been used in this work for the improvement of diagnosing accuracy. The data acquired from the workbench system are first investigated through the PCA to extricate the appropriate features that provide the major information of collected data without reducing its dimensions. The projected data space using the principal components is non-deterministic for further synthesis process of fault classification. Hence, to classify the faults in IM, the obtained feature vectors from PCA are fed into FIS as an input and the classification performance is compared finally. The work experiment has been carried out under the healthy and different faulty conditions of motor and the proposed integrated approach is executed by using MATLAB.