Position Soft-Sensing of Direct-Driven Hydraulic System Based on Back Propagation Neural Network

Automated operations are widely used in harsh environments, in which position information is essential. Although sensors can be equipped to obtain high-accuracy position information, they are quite expensive and unsuitable for harsh environment applications. Therefore, a position soft-sensing model based on a back propagation (BP) neural network is proposed for direct-driven hydraulics (DDH) to protect against harsh environmental conditions. The proposed model obtains a position by integrating velocity computed from the BP neural network, which trains the nonlinear relationship between multi-input (speed of the electric motor and pressures in two chambers of the cylinder) and single-output (the cylinder’s velocity). First, the model of a standalone crane with DDH was established and verified by experiment. Second, the data from batch simulation with the verified model was used for training and testing the BP neural network in the soft-sensing model. Finally, position estimation with a typical cycle was performed using the created position soft-sensing model. Compared with the experimental data, the maximum soft-sensing position error was about 7 mm, and the error rate was within ±2.5%. Furthermore, position estimations were carried out with the proposed soft-sensing model under differing working conditions and the errors were within 4 mm, but the periodically cumulative error was observed. Hence, a reference point is proposed to minimize the accumulative error, for example, a point at the middle of the cylinder. Therefore, the work can be applied to acquire position information to facilitate automated operation of machines equipped with DDH.

Research on parameter matching characteristics of pneumatic launch systems based on co-simulation

Pneumatic launch systems for Unmanned Aerial Vehicles (UAVs), including mechanical and pneumatic systems, are complex and non-linear. They are subjected to system parameters during launch, which leads to difficulty in engineering research analysis. For example, the mismatch between the UAV parameters and the parameter design indices of the launch system as well as the unclear design indices of the launching speed and overload of UAVs have a great impact on launch safety. Considering this situation, some studies are presented in this paper. Taking the pneumatic launch system as a research object, a pneumatic launcher dynamic simulation model is built based on co-simulation considering the coupling characteristics of the mechanical structure and transmission system. Its accuracy was verified by laboratory test results. Based on this model, the paper shows the effects of the key parameters, including the mass of the UAV, cylinder volume, pressure and moment of inertia of the pulley block, on the performance of the dynamic characteristics of the launch process. Then, a method for matching the parameter characteristics between the UAV and launch system based on batch simulation is proposed. The set of matching parameter values of the UAV and launch system that satisfy the launch take-off safety criteria are calculated. Finally, the influence of the system parameters of the launch process on the launch performance was analysed in detail, and the design optimised. Meaningful conclusions were obtained. The analysis method and its results can provide a reference for engineering and theoretical research and development of pneumatic launch systems.

Adaptive Threshold Based Scheduler for Batch of Independent Jobs for Cloud Computing System

Distributed systems are efficient means of realizing high-performance computing (HPC). They are used in meeting the demand of executing large-scale high-performance computational jobs. Scheduling the tasks on such computational resources is one of the prime concerns in the heterogeneous distributed systems. Scheduling jobs on distributed systems are NP-complete in nature. Scheduling requires either heuristic or metaheuristic approach for sub-optimal but acceptable solutions. An adaptive threshold-based scheduler is one such heuristic approach. This work proposes adaptive threshold-based scheduler for batch of independent jobs (ATSBIJ) with the objective of optimizing the makespan of the jobs submitted for execution on cloud computing systems. ATSBIJ exploits the features of interval estimation for calculating the threshold values for generation of efficient schedule of the batch. Simulation studies on CloudSim ensures that the ATSBIJ approach works effectively for real life scenario.

Separation of Gallium(III) and Indium(III) by Solvent Extraction with Ionic Liquids from Hydrochloric Acid Solution

The manufacture of semiconductor materials containing gallium and indium requires the separation of these metals owing to their coexistence in the resources of these materials. In this work, solvent extraction of In(III) and Ga(III) from a hydrochloric acid solution by ionic liquids (ILs) was investigated to separate them. The ILs were synthesized by reacting organophosphorus acids (Cyanex 272, PC88A and D2EHPA) and Aliquat 336 (ALi-CY, ALi-PC, and ALi-D2). In(III) was selectively extracted over Ga(III) by the ILs in the range of initial pH from 0.1 to 2.0. The equilibrium pH was always higher than the initial pH because of the coextraction of hydrogen ions. The highest separation factor between In(III) and Ga(III) was 87, which was obtained by ALi-PC at an initial pH of 1.0. Stripping of the loaded ALi-PC with hydrochloric and sulfuric acid led to selective stripping of In(III) over Ga(III). Scrubbing of the loaded ALi-PC with pure In(III) solution was not effective in removing the small amount of Ga(III) present in the loaded ALi-PC. Batch simulation experiments for the three counter-current extraction stages indicated that the complete separation of both metal ions was possible by extracting In(III) using ALi-PC, with remaining Ga(III) in the raffinate.

MODELO MATEMÁTICO APLICADO A MOLIENDA DISCONTINUA BATCH

El modelo matemático aplicado a molienda batch (a nivel laboratorio), es una herramienta muy importante para llegar a simular y luego predecir el producto granulométrico de cierto mineral tratado; esto es por cada cierto intervalo de tiempo transcurrido de molienda, obtener su respectivo análisis granulométrico reflejado a nivel laboratorio, que luego será corroborado con datos reales y además poder verificar su buena aproximación. El modelo involucra a las funciones selección y fractura quienes son constituidos por los tamaños granulométricos de cada malla en la referida distribución mineral. Consiguiendo de esta manera predecir en forma efectiva y confiable, evitando costo y sobre todo tiempo, sin la necesidad de realizar el proceso de molienda para cada predicción de molienda batch. Palabras clave.- molienda, batch, simular, análisis granulométrico, fractura, mineral. ABSTRACT Mathematical modelling applied to batch milling (at experimental level), is a very important tool to simulate and predict the granulometric yield of a given treated ore; this means, for a given duration of milling operation, to obtain an estimate of the corresponding granulometric analysis, which can then be tested with real data later on, to verify the estimates. The model involves the selection and fracture functions depending on each mesh size in the ore distribution. This will allow the prediction of effective and reliable results, saving costs and more importantly, time, without the need to perform the milling process for each prediction of batch milling. Keywords.- milling, batch, simulation, granulometric, analysis, fracture, ore.

SIMULASI PENGARUH UKURAN PARTIKEL DAN EQUIVALENCE RATIO DALAM PROSES GASIFIKASI TANDAN KOSONG KELAPA SAWIT

In this study, a simulation for gasification process of oil palm empty fruit bunches waste (OPEFB) using a fixed bed gasifier (throat downdraft) by varying the particle size of OPEFB and equivalence ratio (ER) was investigated. The rate of fuel consumption was 10 kg/h with air as the oxidizing medium and 1 hour process time for 1 batch. Simulation was performed with two-dimensional approach (2D) using Computational Fluid Dynamics (CFD) ANSYS FLUENT 14 software. Simulation results show that ideal amount of equivalence ratio (ER) for gasification process of OPEFB pellets with diameter (φ) of 6 mm and 8 mm is 0.1 ≤ ER ≤ 0.2. ER variation affects the higher heating value of syngas (HHV), the carbon efficiency (ηC), gasification efficiency and temperature distribution in the gasification reactor. Variations in particle size did not have a significant effect in the gasification process.Keywords: CFD, OPEFB gasification, particle size, equivalence ratio