Imaging of solid flow in a gravity flow rig using infra-red tomography

Information on flow regimes is vital in the analysis and measurement of industrial process flow. Almost all currently available method of measuring the flow of two-component mixtures in industrial pipelines endeavors to average a property of the flow over the pipe cross-section. They do not give information on the nature of the flow regime and they are unsuitable for accurate measurement where the component distribution is spatially or time varying. The overall aim of this project is to investigate the use of an optical tomography method based on infra-red sensors for real-time monitoring of solid particles conveyed by a rotary valve in a pneumatic pipeline. The infra-red tomography system can be divided into two distinct portions of hardware and software development process. The hardware development process covers the infra-red sensor selection, fixtures and signals conditioning circuits, and control circuits. The software development involves data acquisition system, sensor modeling, image algorithms, and programming for a tomographic display to provide solids flow information in pipeline such as concentration and velocity profiles. Collimating the radiated beam from a light source and passing it via a flow regime ensures that the intensity of radiation detected on the opposite side is linked to the distribution and the absorption coefficients of the different phases in the path of the beam. The information is obtained from the combination of two orthogonal and two diagonal light projection system and 30 cycles of real-time measurements. Those information on the flow captured using upstream and downstream infra-red sensors are digitized by the DAS system before it was passed into a computer for analysis such as image reconstructions and cross-correlation process that provide velocity profiles represented by 16 × 16 pixels mapped onto the pipe cross-section. This project successfully developed and tested an infra-red tomography system to display two-dimensional images of concentration and velocity

Internet of Things (IoT) Application in Meliponiculture

This paper presents an investigation on the environmental factors affecting meliponiculture (the cultivation of stingless bees on a commercial scale for honey production or pollination) using an internet of thing (IOT) application. Manual collection of data for chosen factors can be sporadic and produce variations from incorrect measurement taking; this can cause complications in producing any important interpretation. The feasibility of online monitoring of bee hive based on IoT application has not been properly explored. For a particular bee hive, the amount of departing and arriving bee was estimated by using non-intrusive sensors of infrared transmitter and receiver. A basic temperature-humidity sensor to monitor the temperature and humidity was placed inside the bee hive.  All sensors were integrated with a microcontroller and a Wi-Fi module which sent the data wirelessly to IoT cloud platform where the data was continuously saved, monitored, and can be retrieved anytime. Colonies of Trigona Itama were active throughout the whole period at the experimental site but the daily activity period was intense in the warmer days (over 30 °C) whereas the relative humidity had no significant effect on the flight activities. Intensity of daily flight activity was greatest in December, 2016. Temperature was the most important variable affecting flight

Artificial Neural Network and Wavelet Features Extraction Applications in Nitrate and Sulphate Water Contamination Estimation

This work expounds the review of non-destructive evaluation using near-field sensors and its application in environmental monitoring. Star array configuration of planar electromagnetic sensor is explained in this work for nitrate and sulphate detection in water. The experimental results show that the star array planar electromagnetic sensor was able to detect nitrate and sulphate at different concentrations. Artificial Neural Networks (ANN) is used to classify different levels of nitrate and sulphate contaminations in water sources. The star array planar electromagnetic sensors were subjected to different water samples contaminated by nitrate and sulphate. Classification using Wavelet Transform (WT) was applied to extract the output signals features. These features were fed to ANN consequently, for the classification of different levels of nitrate and sulphate concentration in water. The model is capable of distinguishing the concentration level in the presence of other types of contamination with a root mean square error (RMSE) of 0.0132 or 98.68% accuracy

Planar electromagnetic sensor based estimation of nitrate contamination in water sources using independent component analysis

The main advantages of electromagnetic sensors can be listed as low-cost, convenient, suitable for in-situ measurement system, rapid response, and high durability. In this paper, the output parameters of the planar electromagnetic sensor have been observed with different kind of water samples at different concentrations. The output parameters have been derived and tested to be incorporated with independent component analysis (ICA) and used as inputs for an analysis model. The analysis model targeted to estimate the amount of nitrate contamination in water samples with the assistance of ICA based on FastICA fixed point algorithm under the contrast functions of pow3, tanh, gauss, and skew. Nitrates sample in the form of ammonium nitrates (NH 4NO 3), each of different concentration between 5 mg and 20 mg dissolved in 1 litre of deionized water (Milli-Q) was used as one of the main references. The analysis model was tested with eight sets of mixed NH 4NO 3 and (NH 4) 2HPO 4 water samples. It is seen from the results that the model can acceptably detect the presence of nitrate added in Milli-Q water and capable of distinguishing the concentration level in the presence of other type of contamination. The system and approach presented in this paper has the potential to be used as a useful low-cost tool for water sources monitoring

An ultrasonic system for profiling bubblers in water

Multi-phase flow occurs as two or more discrete phases flow in a closed pipe or a vessel. Examples of phases include gas, liquid or solid and also different immiscible liquids or solids[1]. Two phase flow of fluids (e.g. gas/liquid, liquid/liquid, etc.) is an important phenomenon in which two immiscible phases coexist in a thermodynamic equilibrium. As a two phase flow regime, bubbly flow column are intensively used as multiphase contactors and reactors in chemical, biochemical and petrochemical industries. Investigation of design parameters characterizing the operation and transport phenomena of bubble columns have led to better understanding of the hydrodynamic properties, heat and mass transfer mechanisms and flow regime characteristics ongoing during the operation[2, 3]. Due to the stringent regulations on precise flow control especially in the case of two phase fluid flow,, there has always been a necessity for developing an easier to use, yet more precise approaches or instrumentation. Accordingly, tomographic measurement is more significant and attractable especially in today's industrial process .

An Ultrasonic System for Determining Mango Physiological Properties

There is an increasing requirement for high qualityfruits such as mango. Hence it is vital to have a fast, accurate andreliable method for measuring and monitoring the quality of fruitfrom the field to the consumer. This paper presents aninvestigation on the use of an ultrasonic measurement system fordetermining the quality of mango

Determination of Pipe Deformity using an Ultrasonic System

Pipe deformation is of major concern as it can be an indication of pipe leakage. This paper presents an investigation using an ultrasonic system to measure the deformity on a pipe. The ultrasonic sensors are connected to aluminum probe cones which can collimate the ultrasonic signal towards the pipe surface. A deformation on the pipe will be represented by a specific voltage signal at the receiver circuit. Different weights were placed at the end of the pipe in order to make the pipe bend and thus causing deformation. Experimental result shows that the system can determine the modulus of elasticity which is identical to the predicted value. The modulus of elasticity represents the amount of deformation experienced by the pipe

Measurement of pipe strain using an ultrasonic system

Ultrasonic sensors can be used to measure strain occurring on an object. In this investigation, an ultrasonic signal utilized the reflected signal as a means of monitoring the condition of a pipe. This is an alternative to the strain gage which is commonly used but has a limited life span. The ultrasonic signal was transmitted to a specific location on the pipe, and then reflected by the pipe surface which experienced strain towards the ultrasonic receiver. Collimation of the transmitted and received signals is performed by aluminum probe cones attached to both ultrasonic transducers. Changes in the strain due to the pipe bending will result in changes in the electric signal due to the changes in the sound intensity. The received electric signal was processed by a signal conditioning circuit consisting of preamplifier, amplifier, band-pass filter and rectifier before being displayed. Two experiments were conducted to establish the relationship between strain on the pipe and the ultrasonic intensity. In order to verify the results, an experiment was conducted using a strain gage and the results were identical. The results show that the system is able to measure strain when the pipe bends

The application of WiFi-based wireless sensor network (WSN) in hill slope condition monitoring

In this paper, a wireless sensor network for landslide monitoring (WSNLM) system is described. WSNLM utilized a wireless protocol which is 802.11g. The hardware structure of the WSNLM is discussed where the important parts had been discussed in details. In order to assess the susceptibility of a hill slope to landslide, several parameters had been considered for the network. The important factors that affect landslide is the ground status, which is soil moisture, vibration in the land and also soil temperature. Other factors that can relate to landslide is the environment of the surrounding such as air temperature, humidity and atmospheric pressure. The outputs from the ADXL335 accelerometer were used for slope angle measurement. The output of a vibration transducer was also used to monitor the hill slope. To account for the susceptibility of the hill slope to the land slide, safety factor value is calculated in real time. The outcomes show that the average moisture content in the soil is around 3% on a sunny day and the safety factor for a sunny day is around 75. The moisture content in the soil on a rainy day increases tremendously to more than 20%. At the same time, the safety factor drops to around 70. The system in this paper has the potential to be used as a useful tool for the detection of lanslides

Image reconstruction methods for ultrasonic transmission mode tomography in bubbly flow regime

Image reconstruction from projections plays an important role in monitoring flow regimes by ultrasonic transmission mode tomography (UTMT) system. Fast and more accurate methods are necessary in case of on-line process e.g. bubbly flow regimes. In this work, analytical image reconstruction methods such as linear back projection (LBP), filter back projection (FBP) and convolution back projection (CBP) in bubbly flow regime is investigated and found that CBP is superior to other methods. Furthermore, different filters were applied to CBP to investigate the image quality improvement. Among different types of filters for CBP method, Ram-lack outperforms the others for UTMT. The peak signal to noise ratio (PSNR) of reconstructed images in this particular experiment was improved using Ram-lack in noiseless data