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The use of pneumatic conveying of solid bulk over long distance has become a popular technique due to low operational cost, low maintenance requirement, layout flexibility and ease of automation. The purpose of this paper is to identifity the flow regime in a pneumatic conveyor system by electrodynamic sensor placed around the pipe using fuzzy logic tools.

Electrical charge tomography is used to detect the existence of inherent charge on the moving particles through the pipe. Linear back projection algorithm and filtered back projection algorithm are employed to produce tomography image. Baffles of different shapes are inserted to create various flow regimes, such as full flow, three quarter flow, half flow and quarter flow. Fuzzy logic tools are used to identify different flow regimes and produce filtered back concentration profiles for each flow regime.

The results show significant improvement in the pipe flow image resolution and measurement.

This paper presents a flow identifier method using electrical charge tomography and fuzzy logic to monitor solid particles flow in pipeline.

Solid particles flowing in a pipeline is a common mode of transport in industries. This is because pipeline transportation can avoid waste through spillage and minimizes the risk of handling of hazardous materials. Pharmaceutical industries, food stuff manufacturing industries, cement, and chemical industries are a few industries to exploit this transportation technique. For such industries, monitoring and controlling material flow through the pipe is an essential element to ensure efficiency and safety of the system. The purpose of this paper is to present electrical charge tomography, which is one of the most efficient, robust, cost‐effective, and non‐invasive tomographic methods of monitoring solid particles flow in a pipeline.

Process flow data are captured by fitting an array of 16 discrete electrodynamic sensors about the circumference of the flow pipe. The captured data are processed using two tomographic algorithms to obtain tomographic images of the flow. Then a neural network tool is used to improve image resolution and accuracy of measurements.

The results from the above technique show significant improvements in the pipe flow image resolution and measurements.

The paper presents electrical charge tomography, which is one of the most efficient, robust, cost‐effective, and non‐invasive tomographic methods of monitoring solid particles flow in a pipeline.

Since the importance role of ultrasonic tomography (UT) in industry, especially in oil industry, to produce noninvasive and nondestructive plane images, research on UT system with a metal pipe conveyor is investigated. The produced cross-sectional images are used for detecting the concentration of solid and liquid mixture inside the pipe, noninvasively. In practice, due to application of metal pipes as the conveyor of oil mixture so the capability of manufacturing an UT system with a metal pipe is investigated in this paper. The paper aims to discuss these issues.

Finite element software (COMSOL Multiphysics 3.5) for visualizing the structure of pipe with mounted sensors on the periphery of the pipe is used. The manner of ultrasonic wave propagation on different layers on various frequencies and finding the time of flight for transmission mode signal and lamb mode signal are achieved by the means of done simulations. Finding the proper ultrasonic sensor base on its efficiency is the main step of designing an UT system. This is done by estimating the resonance frequency of sensor due to the manner of ultrasonic wave propagation in different frequencies shown in simulation results.

Due to simulation results, lamb wave is a permanent propagation mode of ultrasonic wave which makes interference in measuring process of straight path signal and it is impossible to remove. Relief of the mentioned problem finding an optimum frequency to decrease the affection of lamb wave in detecting point. Optimum frequency of ultrasonic wave to satisfy the objective is 45 kHz which is measured by considering of mathematic of ultrasonic wave propagation in different layers. The reaching time of straight path signal and lamb wave signal in opposite sensor as the receiver are 5.5 and 4.6 μs, respectively.

This investigation is the first step to perform the UT in a noninvasive method to produce the cross-sectional images of metal pipe. Due to the wide application of metal pipes as the conveyor of the liquids/gases, metal pipe for the UT application is studied in this research.

Micro-focus X-ray computed tomography (CT) can be used to quantitatively evaluate the packing density, pore connectivity and provide the basis for specimen derived simulations of gas permeability of sand mould. This non-destructive experiment or following simulations can be done on any section of any size sand mould just before casting to validate the required properties. This paper aims to describe the challenges of this method and use it to simulate the gas permeability of 3D printed sand moulds for a range of controlling parameters. The permeability simulations are compared against experimental results using traditional measurement techniques. It suggests that a minimum volume of only 700 × 700 × 700 µm³ is required to obtain, a reliable and most representative than the value obtained by the traditional measurement technique, the simulated permeability of a specimen.

X-ray tomography images were used to reconstruct 3D models to simulate them for gas permeability of the 3D printed sand mould specimens, and the results were compared with the experimental result of the same.

The influence of printing parameters, especially the re-coater speed, on the pore connectivity of the 3D printed sand mould and related permeability has been identified. Characterisation of these sand moulds using X-ray CT and its suitability, compared to the traditional means, are also studied. While density and 3PB strength are a measure of the quality of the moulds, the pore connectivity from the tomographic images precisely relates to the permeability. The main conclusions of the present study are provided below. A minimum required sample size of 700 × 700 × 700 µm³ is required to provide representative permeability results. This was obtained from sand specimens with an average sand grain size of 140 µm, using the tomographic volume images to define a 3D mesh to run permeability calculations. Z-direction permeability is always lower than that in the X-/Y-directions due to the lower values of X-(120/140 µm) and Y-(101.6 µm) resolutions of the furan droplets. The anisotropic permeability of the 3D printed sand mould is mainly due to, the only adjustable, X-directional resolution of the furan droplets; the Y-directional resolution is a fixed distance, 102.6 µm, between the printhead nozzles and the Z-directional one is usually, 280 µm, twice the size of an average sand grain.A non-destructive and most representative permeability value can be obtained, using the computer simulation, on the reconstructed 3D X-ray tomography images obtained on a specific location of a 3D printed sand mould. This saves time and effort on printing a separate specimen for the traditional test which may not be the most representative to the printed mould.

The experimental result is compared with the computer simulated results.

Three-dimensional (3D) printing is increasingly used to produce orthopaedic components for hip arthroplasty, such as acetabular cups, which show complex lattice porous structures and shapes. However, limitations on the quality of the final implants are present; thus, investigations are needed to ensure adequate quality and patients safety. X-ray microcomputed tomography (micro-CT) has been recognised to be the most suitable method to evaluate the complexity of 3D-printed parts. The purpose of this study was to assess the reliability of a micro-CT analysis method comparing it with reference systems, such as coordinate measuring machine and electron microscopy.

3D-printed acetabular components for hip arthroplasty (n = 2) were investigated. Dimensions related to the dense and porous regions of the samples were measured. The micro-CT scanning parameters (voltage – kV, current – µA) were optimised selecting six combinations of beam voltage and current.

Micro-CT showed good correlation and agreement with both coordinate measuring machine and scanning electron microscopy when optimal scanning parameters were selected (130 kV – 100 µA to 180 kV – 80 µA). Mean discrepancies of 50 µm (± 300) and 20 µm (± 60) were found between the techniques for dense and porous dimensions. Investigation method such as micro-CT imaging may help to better understand the impact of 3D printing manufacturing technology on the properties of orthopaedic implants.

The optimisation of the scanning parameters and the validation of this method with reference techniques may guide further analysis of similar orthopaedic components.

This paper aims to focus on the evaluation of a polymer concrete as a three-dimensional (3D) printing material. An associated company has developed plastic concrete made from reused unrecyclable plastic waste. Its intended use is as a construction material.

The concrete mix, called PolyBet, composed of polypropylene and glass sand, is printed by the fused deposition modelling process. The process of material and parameter selection is described. The mechanical properties of the filled material were compared to its cast state. Samples were made from castings and two different orientations of 3D-printed parts. Three-point flex tests were carried out, and the area of the break was examined. Computed tomography of the samples was carried out.

The influence of the 3D printing process on the material was evaluated. The mechanical performance of the longitudinal samples was close to the cast state. There was a difference in the failure mode between the states, with cast parts exhibiting a tougher behaviour, with fractures propagating in a stair-like manner. The 3D-printed samples exhibited high degrees of porosity.

The results suggest that the novel material is a good fit for 3D printing, with little to no degradation caused by the process. Layer adhesion was shown to be excellent, with negligible effect on the finished part for the longitudinal orientation. That means, if large-scale testing of buildability is successful, the material is a good fit for additive manufacturing of building components and other large-scale structures.

The purpose of this paper is to view the flow concentration of the flowing material in a pipeline conveyor.

Optical tomography provides a method to view the cross sectional image of flowing materials in a pipeline conveyor. Important flow information such as flow concentration profile, flow velocity and mass flow rate can be obtained without the need to invade the process vessel. The utilization of powerful computer together with expensive data acquisition system (DAQ) as the processing device in optical tomography systems has always been a norm. However, the advancements in silicon fabrication technology nowadays allow the fabrication of powerful digital signal processors (DSP) at reasonable cost. This allows the technology to be applied in optical tomography system to reduce or even eliminate the need of personal computer and the DAQ. The DSP system was customized to control the data acquisition of 16 × 16 optical sensors (arranged in orthogonal projection) and 23 × 23 optical sensors (arranged in rectilinear projections). The data collected were used to reconstruct the cross sectional image of flowing materials inside the pipeline. In the developed system, the accuracy of the image reconstruction was increased by 12.5 per cent by using new hybrid image reconstruction algorithm.

The results proved that the data acquisition and image reconstruction algorithm is capable of acquiring accurate data to reconstruct cross sectional images with only little error compared to the expected measurements.

The DSP system was customized to control the data acquisition of 16 × 16 optical sensors (arranged in orthogonal projection) and 23 × 23 optical sensors (arranged in rectilinear projections).

The purpose of this study is to develop a reconstruction and measurement system for data analysis using ultrasonic transmission tomography. The problem of reconstruction from the projection is encountered in practical implementation, which consists in reconstructing an image that is an estimation of an unknown object from a finite set of projection data. Reconstructive algorithms used in transmission tomography are based on linear mathematical models, which makes it necessary to process non-linear data into estimates for a finite number of projections. The application of transformation methods requires building a mathematical model in which the projection data forming the known and unknown quantities are functions with arguments from a continuous set of real numbers, determining the function describing the unknown quantities sought in the form of inverse relation and adapting it to operate on discrete and noisy data. This was done by designing a tomographic device and proprietary algorithms capable of reconstructing two-dimensional images regardless of the size, shape, location or number of inclusions hidden in the examined object.

The application consists of a device and measuring sensors, as well as proprietary algorithms for image reconstruction. Ultrasonic transmission tomography makes it possible to analyse processes occurring in an object without interfering with the examined object. The proposed solution uses algorithms based on ray integration, the Fermat principle and deterministic methods. Two applications were developed, one based on C and implemented on the embedded device, while the other application was made in Matlab.

Research shows that ultrasonic transmission tomography provides an effective analysis of tested objects in closed tanks.

In the presented technique, the use of ultrasonic absorption wave has been limited. Nevertheless, the effectiveness of such a solution has been confirmed.

The presented solution can be used for research and monitoring of technological processes.

Author’s tomographic system consisting of a measuring system and image reconstruction algorithms.

Accurately, positioning is a fundamental requirement for vision measurement systems. The calculation of the harvesting width can not only help farmers adjust the direction of the intelligent harvesting robot in time but also provide data support for future unmanned vehicles.

To make the length of each pixel equal, the image is restored to the aerial view in the world coordinate system. To solve the problem of too much calculation caused by too many particles, a certain number of particles are scattered near the crop boundary and the distribution regularities of particles’ weight are analyzed. Based on the analysis, a novel boundary positioning method is presented. In the meantime, to improve the robustness of the algorithm, the back-projection algorithm is also used for boundary positioning.

Experiments demonstrate that the proposed method could well meet the precision and real-time requirements with the measurement error within 55 mm.

In visual target tracking, using particle filtering, a rectangular is used to track the target and cannot obtain the boundary information. This paper studied the distribution of the particle set near the crop boundary and proposed an improved particle filtering algorithm. In the algorithm, a small amount of particles is used to determine the crop boundary and accurate positioning of the crop boundary is realized.

In large-scale environments and unstructured scenarios, the accuracy and robustness of traditional light detection and ranging (LiDAR) simultaneous localization and mapping (SLAM) algorithms are reduced, and the algorithms might even be completely ineffective. To overcome these problems, this study aims to propose a 3D LiDAR SLAM method for ground-based mobile robots, which uses a 3D LiDAR fusion inertial measurement unit (IMU) to establish an environment map and realize real-time localization.

First, we use a normal distributions transform (NDT) algorithm based on a local map with a corresponding motion prediction model for point cloud registration in the front-end. Next, point cloud features are tightly coupled with IMU angle constraints, ground constraints and gravity constraints for graph-based optimization in the back-end. Subsequently, the cumulative error is reduced by adding loop closure detection.

The algorithm is tested using a public data set containing indoor and outdoor scenarios. The results confirm that the proposed algorithm has high accuracy and robustness.

To improve the accuracy and robustness of SLAM, this method proposed in the paper introduced the NDT algorithm in the front-end and designed ground constraints and gravity constraints in the back-end. The proposed method has a satisfactory performance when applied to ground-based mobile robots in complex environments experiments.