Ultrasonic-based Sensor Fusion Approach to Measure Flow Rate in Partially Filled Pipes

Flow rate measurement in pipes is essential for many applications. Thus, there have been a variety of flow meters developed that incorporate different technologies. However, a typical limitation in flow meters is that the pipe must be full in order to get an accurate flow reading. In many cases, this is not possible for practical reasons. When the pipe is full, ultrasonic flow meters can calculate the flow rate using known properties of the pipe and fluid, namely the cross-section, propagation path and fluid sound velocity. However, when the pipe is only partially filled, the propagation path is unknown which leads to an inability to calculate the correct flow rate. This paper presents a cost-effective sensor fusion approach to extend the capabilities of transit time ultrasonic flow meters to handle such scenarios. The approach determines the propagation path using capacitance-based level sensing, combined with fluid velocities ascertained via an ultrasonic sensor, leading to a significantly more accurate estimation of flow rates. Experiments in low flow rate situations validated the efficacy of the proposed model, with a 92% reduction of mean error in the lowest water height when compared to a conventional ultrasonic flow meter

Vision-Based Incoming Traffic Estimator Using Deep Neural Network on General Purpose Embedded Hardware

Traffic management is a serious problem in many cities around the world. Even the suburban areas are now experiencing regular traffic congestion. Inappropriate traffic control wastes fuel, time, and the productivity of nations. Though traffic signals are used to improve traffic flow, they often cause problems due to inappropriate or obsolete timing that does not tally with the actual traffic intensity at the intersection. Traffic intensity determination based on statistical methods only gives the average intensity expected at any given time. However, to control traffic accurately, it is required to know the real-time traffic intensity. In this research, image processing and machine learning have been used to estimate actual traffic intensity in real time. General-purpose electronic hardware has been used for in-situ image processing based on the edge-detection method. A deep neural network (DNN) was trained to infer traffic intensity in each image in real time. The trained DNN estimated traffic intensity accurately in 90% of the real-time images during road tests. The electronic system was implemented on a Raspberry Pi single-board computer; hence, it is cost-effective for large-scale deployment.Comment: 6 pages, 11 figures, journa

Direct-write fabrication of wear profiling IoT sensor for 3D printed industrial equipment

© 2019 International Association for Automation and Robotics in Construction I.A.A.R.C. All rights reserved. Additive Manufacturing (AM), also known as 3D printing, is an emerging technology, not only as a prototyping technology, but also to manufacture complete products. Gravity Separation Spirals (GSS) are used in the mining industry to separate slurry into different density components. Currently, spirals are manufactured using moulded polyurethane on fibreglass substructure, or injection moulding. These methods incur significant tooling cost and lead times making them difficult to customise, and they are labour-intensive and can expose workers to hazardous materials. Thus, a 3D printer is under development that can print spirals directly, enabling mass customisation. Furthermore, sensors can be embedded into spirals to measure the operational conditions for predictive maintenance, and to collect data that can improve future manufacturing processes. The localisation of abrasive wear in the GSS is an essential factor in optimising parameters such as suitable material, print thickness, and infill density and thus extend the lifetime and performance of future manufactured spirals. This paper presents the details of a wear sensor, which can be 3D printed directly into the spiral using conductive material. Experimental results show that the sensor can both measure the amount of wear and identify the location of the wear in both the horizontal and vertical axes. Additionally, it is shown that the accuracy can be adjusted according to the requirements by changing the number and spacing of wear lines

A virtual odometer for a Quadrotor Micro Aerial Vehicle

This paper describes the synthesis and evaluation of a "virtual odometer" for a Quadrotor Micro Aerial Vehicle. Availability of a velocity estimate has the potential to enhance the accuracy of mapping, estimation and control algorithms used with quadrotors, increasing the effectiveness of their applications. As a result of the unique dynamic characteristics of the quadrotor, a dual axis accelerometer mounted parallel to the propeller plane provides measurements that are directly proportional to vehicle velocities in that plane. Exploiting this insight, we encapsulate quadrotor dynamic equations which relate acceleration, attitude and the aerodynamic propeller drag in an extended Kalman filter framework for the purpose of state estimation. The result is a drift free estimation of lateral and longitudinal components of translational velocity and roll and pitch components of attitude of the quadrotor. Real world data sets gathered from two different quadrotor platforms, together with ground truth data from a Vicon system, are used to evaluate the effectiveness of the proposed algorithm and demonstrate that drift free estimates for the velocity and attitude can be obtained

Seed dormancy and germination in three annual canarygrass (Phalaris canariensis L.) cultivars relative to spring wheat (Triticum aestivum L.)

Non-Peer ReviewedSeed dormancy in annual canarygrass may lead to unsatisfactory germination in seed tests. The objectives of this study were (i) to quantify the levels of seed dormancy in three morphologically diverse annual canarygrass cultivars (‘Keet’, ‘CDC Maria’, & ‘CY 184’) relative to spring wheat & (ii) to determine the effectiveness of three treatments (GA3, KNO3, & chilling) & two temperature regimes (15/25°C & 15°C) in promoting germination of dormant annual canarygrass seeds. The hard red spring wheat cultivar ‘Katepwa’ control was included as a representative of a cereal crop that has been extensively characterized with regards to seed dormancy. In 1998 & 1999, the four cultivars were grown at Saskatoon, Canada. At maturity, panicles & spikes were hand harvested & stored at –20°C. Four replications of 50 seeds per cultivar were used in each experiment. Three experiments were conducted: (i) seeds were germinated at 10, 15, 20, & 25°C for one week, (ii) seeds were stored at 24°C for zero to eight weeks prior to germination at 22°C for one week, & (iii) seeds were treated with GA3, KNO3, & chilling prior to germination at 15/25°C (16/8h) or 15°C for two weeks. For experiment one & three, a split-plot analysis was used to analyze arc sin transformed percentage germination data. Average percentage germination data in experiment two were tested to be significantly different from 98% germination (P=0.05) based on one-tailed t-tests. Annual canarygrass developed deeper dormancy than the wheat cultivar in both years, particularly when germinated at 20 & 25°C. The highest percentage germination was observed at 15°C. Two (1998) & four weeks (1999) of storage at 24°C were required to overcome dormancy in annual canarygrass. Pre-chilling or KNO3 treatment prior to germination at 15/25°C (16/8h in darkness) resulted in average germination levels of 94% (1998) & 66% (1999). Potassium nitrate treatment prior to incubation at 15°C in darkness was the most effective method of promoting germination in dormant seeds, resulting in 99% (1998) & 97% (1999) germination. Thus, we recommend the use of the latter method, instead of the former or currently recommended method (pre-chilling or KNO3 treatment prior to germination at 15/25°C [16/8h] in darkness), for testing germination levels of dormant seed of annual canarygrass

3-D Printed Strain Sensor for Structural Health Monitoring

Additive manufacturing, or 3D printing, is evolving from a technology that can only aid rapid prototyping, to one that can be used to directly manufacture large-scale, real-world equipment. Gravity Separation Spirals (GSS) are vital to the mining industry for separating mineral-rich slurry into its different density components. In order to overcome inherent drawbacks of the traditional mould base manufacturing methods, including significant tooling costs, limited customisation and worker exposure to hazardous materials, a 3D printer is under development to directly print spirals. By embedding small Internet of Things (IoT) sensors inside the GSS, it is possible to remotely determine the operation conditions, predict faults, and use collected data to optimise production output. This work presents a 3D printed strain sensor, which can be directly printed into the GSS. This approach uses a carbon-based conductive filament to print a strain gauge on top of a Polylactic Acid (PLA) base material. Printed sensors have been tested using an Instron E10000 testing machine with an optical extensometer to improve accuracy. Testing was conducted by both loading and unloading conditions to understand the effect of hysteresis. Test results show a near-linear relationship between strain and measured resistance, and show a 6.05% increase in resistance after the test, which indicates minor hysteresis. Moreover, the impact of viscoelastic behaviour is identified, where the resistance response lags the strain. Results from both conductive and non-conductive material show the impact of the conductive carbon upon the tensile strength, which will help to inform future decisions about sensor placement

Integrated 3-D Printable Temperature Sensor for Advanced Manufacturing

As technology continues to develop at a rapid pace, the world progresses towards the fourth industrial revolution, Industry 4.0, with advancements in automation and machine intelligence, as well as manufacturing breakthroughs leading to more efficient and advanced methods. Additive manufacturing (AM), also known as 3D printing, is a type of manufacturing method that has experienced great development and has revolutionised end-product manufacturing. The authors are involved in a project to develop a large-scale industrial 3D printer to print equipment called a Gravity Separation Spiral (GSS), and in an effort to make the equipment "smart", sensors need to be embedded inside to monitor the operating conditions remotely. This paper presents a temperature sensor able to be printed by a multi-material 3D printer, into 3D printed equipment. In this method, a conductive carbon-based filament has been used to print temperature-sensitive traces inside a Polylactic Acid (PLA) base. The printed sensor was temperature tested in a controlled environment using a programmable heat pad, and the change in resistance has been measured as a voltage change using a data acquisition device. Tests were conducted within in the expected operating range, between 25 °C and 36 °C , and the absolute temperature error was found to be less than ±2°C

Evaluation of salt content and effectiveness of excessive salt reduction methods in selected commercially available dried fish types in Sri Lanka

High salt intake elevates the risk of non-communicable diseases such as high blood pressure, cardiovascular diseases and stroke worldwide. Sri Lanka has recorded in 2010 as the country with highest average fish & fish products consumption in South Asia. In the current study, salt in ten types of commonly available dried fish namely; sprats, prawns, smoothbelly sardinella, queen fish, cat fish, sail fish, shark, skipjack tuna, Bombay duck and trenched sardinella was analyzed and determined salt reduction methods with minimal protein loss. Four salt reduction methods were tested; Method 1: washed with water at Room Temperature (RT) for five times; Method 2: washed with water for five times at RT and kept in hot water for 5min; Method 3: washed with water for five times at RT and boiled for 5min; Method 4: washed with water for five times at RT and kept in coconut water for 5min. Using Volhard method, sodium chloride was analyzed while protein was determined using Kjeldahl method. All four methods showed significant reduction of salt level in tested dried fish (p < 0.05). Among the tested salt reduction methods, Method 3 showed the highest salt reduction for all types of dried fish except smoothbelly sardinella and cat fish.The highest salt mean value of 28.8% was recorded in queen fish and the lowest mean value of 12.8% was recorded in smoothbelly sardinella. The highest protein loss was recorded in Method 3. To reduce considerable amount of salt, the easiest and fairly effective method is method 1 except for prawns and Shark. Although higher salt reduction showed in method 2 and 3, they are not recommended due to high protein loss, high energy expenditure and reduction of freshness of dried fish. Method 4 can be applied for all dried fish types because it is economical and reduces considerable amount of salt, removes less amount of protein comparatively. The results revealed that all tested dried fish except smoothbelly sardinella contain significantly high amount of salt (p < 0.05) than the standard value specified (12%) by the Sri Lanka Standards Institution (SLSI).Keywords: Dried fish, protein loss, salt-intake, salt reduction, non-communicable disease

Use of a rapid diagnostic test to detect cutaneous leishmaniasis in Sri Lanka

Objectives: This study was initiated to determine the sensitivity and specificity of a commercially available rapid diagnostic test (RDT) to detect leishmania antigen in cutaneous leishmaniasis(CL) skin lesions among Sri Lankan patients compared to PCR and Slit skin smear(SSS).Methods: Patients clinically suggestive of CL lesions were subjected to parasitological investigations. The clinical history was collected by the researcher. Samples were collected by a qualified trained medical officer from the suspected CL lesions at the dermatology clinic in the Hambantota hospital and from the patients coming to the Department of Parasitology, Faculty of Medical Sciences, University of Sri Jayewardenepura. RDT was done at the Hambantota hospital and samples were brought to the Department of Parasitology, to perform SSS, PCR and cultures.Results: Fifty samples have been collected thus far and PCR was performed only in 48 samples. Out of the 50 samples only 9 were positive by RDT and 32 by SSS and PCR. The 9 samples that were positive for RDT were positive by SSS and 7 positive by PCR. Of the 41 samples that were negative by RDT, 16 were negative by PCR as well as SSS.Conclusions: From the data collected it can concluded that RDT is not the best method to diagnose CL skin lesions in patients in Sri Lanka. Also it confirms that the best method to diagnose leishmaniasis is PCR

Comparing Floristic Diversity between a Silviculturally Managed Arboretum and a Forest Reserve in Dambulla, Sri Lanka

Repeated slash and burn cultivation creates wasteland with thorny shrubs, which then takes a long time to become secondary forests through serial stages of succession. Assisted natural regeneration through silvicultural management is a useful restoration method to accelerate succession. This survey evaluates the effectiveness of a simple silvicultural method for the rehabilitation of degraded lands to productive forest, thereby increasing floristic wealth. Field-based comparative analyses of floristic composition were carried out at a silviculturally managed forest (Popham Arboretum) and a primary forest (Kaludiyapokuna Forest Reserve) which is located in Dambulla in Sri Lanka. Floristic analysis was used to examine the effectiveness of silvicultural techniques for successful restoration of degraded forest in the dry zone. Nine 20 m × 20 m plots in each forest were enumerated and the vegetation ≥ 10 cm girth at breast height was quantitatively analyzed. Cluster analysis resulted in five distinguishable clusters (two from Popham Arboretum and three from Kaludiyapokuna Forest Reserve). Similarity indices were generated to compare the plots within and between sites. Floristic similarity was higher in forest reserve plots compared to arboretum plots. A total of 72 plant species belonging to 60 genera and 26 families were recorded from the study sites. Of the recorded species, Grewia damine and Syzygium cumini (Importance Value Index, IVI = 24 and 23 respectively) were the ecologically co-dominant taxa at the Popham Arboretum. In contrast, Mischodon zeylanicus (IVI = 31), Schleichera oleosa (IVI = 25) and Diospyros ebenum (IVI = 21) were the abundant taxa in the forest reserve