A depth-based hybrid approach for safe flight corridor generation in memoryless planning

This paper presents a depth-based hybrid method to generate safe flight corridors for a memoryless local navigation planner. It is first proposed to use raw depth images as inputs in the learning-based object-detection engine with no requirement for map fusion. We then employ an object-detection network to directly predict the base of polyhedral safe corridors in a new raw depth image. Furthermore, we apply a verification procedure to eliminate any false predictions so that the resulting collision-free corridors are guaranteed. More importantly, the proposed mechanism helps produce separate safe corridors with minimal overlap that are suitable to be used as space boundaries for path planning. The average intersection of union (IoU) of corridors obtained by the proposed algorithm is less than 2%. To evaluate the effectiveness of our method, we incorporated it into a memoryless planner with a straight-line path-planning algorithm. We then tested the entire system in both synthetic and real-world obstacle-dense environments. The obtained results with very high success rates demonstrate that the proposed approach is highly capable of producing safe corridors for memoryless local planning. © 2023 by the authors

Investigation of Field Performance and Film Properties of Natural Rubber Latex Preserved with a Novel Chemical

The traditional long-term preservative system of latex has an impact on environmental air pollution by ammonia and leads to the production of carcinogenic nitrosamine substances by tetramethyl thiuram disulfide (TMTD). In this research, ammonia and a novel preservative with a polysulfidic link were compounded and tested as a novel traditional long-term latex preservative system, to overcome the drawbacks of traditional preservative systems. Control samples were prepared with ammonia as the standard preservative. In addition, ammonia and the novel chemical mixed samples were also prepared for investigating the combined effect. After the preservation treatment, the stable nature of field NR latex was evaluated via the Volatile Fatty Acid (VFA) test based on ASTM D 1076 standard. The Dry Rubber Content (DRC) test and Total Solid Content (TSC) test were carried out for VFA calculation purposes based on ISO126:2005 and ASTM D 1076 standards, respectively. The alkalinity test was carried out to maintain the required ammonia content in latex. In the first trial, traditional dispersion preparation of novel chemical dispersion failed due to the large particle size of the novel chemical. Therefore, two different novel chemical dispersions were prepared in the second trial, where dispersions 1 and 2 were prepared with wetting agents and without using a wetting agent, respectively. It was found that 0.020%v/v and 0.025% v/v concentrations of the novel chemical from dispersion 1 allowed the preservation of field NR latex for 8 days. A low concentration (0.015% v/v) of the novel chemical was able to keep latex with good stability for 5 days. The novel chemical dispersion without a wetting agent exhibited a marvelous preservative system to NR latex than with a wetting agent, because the wetting agent creates a barrier between particles of novel chemical and latex particles. The novel preservative acts as a good preservative while reducing the fumes of ammonia being emitted and eliminating the carcinogenic nitrosamine emission from TMTD

Assessing transformer oil quality using deep convolutional networks

Electrical power grids comprise a significantly large number of transformers that interconnect power generation, transmission and distribution. These transformers having different MVA ratings are critical assets that require proper maintenance to provide long and uninterrupted electrical service. The mineral oil, an essential component of any transformer, not only provides cooling but also acts as an insulating medium within the transformer. The quality and the key dissolved properties of insulating mineral oil for the transformer are critical with its proper and reliable operation. However, traditional chemical diagnostic methods are expensive and time-consuming. A transformer oil image analysis approach, based on the entropy value of oil, which is inexpensive, effective and quick. However, the inability of entropy to estimate the vital transformer oil properties such as equivalent age, Neutralization Number (NN), dissipation factor (tanδ) and power factor (PF); and many intuitively derived constants usage limit its estimation accuracy. To address this issue, in this paper, we introduce an innovative transformer oil analysis using two deep convolutional learning techniques such as Convolutional Neural Network (ConvNet) and Residual Neural Network (ResNet). These two deep neural networks are chosen for this project as they have superior performance in computer vision. After estimating the equivalent aging year of transformer oil from its image by our proposed method, NN, tanδ and PF are computed using that estimated age. Our deep learning based techniques can accurately predict the transformer oil equivalent age, leading to calculate NN, tanδ and PF more accurately. The root means square error of estimated equivalent age produced by entropy, ConvNet and ResNet based methods are 0.718, 0.122 and 0.065, respectively. ConvNet and ResNet based methods have reduced the error of the oil age estimation by 83% and 91%, respectively compared to that of the entropy method. Our proposed oil image analysis can calculate the equivalent age that is very close to the actual age for all images used in the experiment. © 2019 IEEE.E

Using Fiber Optic Sensors for Bridge Monitoring

This paper presents the data obtained from monitoring a steel Struss bridge using Fiber Bragg Grating (FBG) sensors before and after a proposed repair for a crack propagation in the end plates. This paper details the operating mechanism behind the FBG sensors and advantages of using FBG sensors over resistive foil strain gauges for bridge structural health monitoring and also details how cracks on the outer web’s end plate originated and then provides a step-by-step guide to the completed repair. This technology can be use in other practical applications where structural health monitoring is needed.   &nbsp

On the apex seal analysis of limaçon positive displacement machines

Rotary machines, and limaçon machines in particular, offer a better power to weight ratio compared to reciprocating machines; however, leakage due to improper apex and side sealing have prevented rotary machines from thriving. In this paper, a modelling approach is presented to analyse the vibration of apex seal during the machine operation and the power loss caused by the seal friction. The seal and spring are modelled as a spring-mass system in which the seal deformation is negligible. The seal-groove relative positions have then been categorised into nine different possible cases based on the number of contact points between the seal and the seal groove. A case study has been presented to demonstrate the reliability of the model

Time-minimum motion handling of open liquid-filled objects using sparse sequential quadratic programming

The paper presents an efficient approach to minimize motion time of an industrial robot so that it can successfully manipulate an open and liquid-filled object in pick-and-place operations. It is first proposed a motion planning optimization problem, where the total motion duration is considered as a cost function. Moreover, the robot physical limits such as its joint positions, velocities and accelerations are used as the optimization constrains. On the other hand, to ensure an open and liquidfilled object always upright, orientation constraints of the robot end-effector are taken into account. More specifically, roll and pitch of the end-effector are proposed to be fixed during the transportation, which ensures there is no tipping over in the object. The formulated motion planning optimization problem is then efficiently solved by using the sparse sequential quadratic programming method. Our approach excels in optimizing the motion trajectory by leveraging its flexibility, accommodating various trajectory shapes that satisfy the kinematic conditions. The optimization leads to more efficient and effective motion execution, resulting in a substantial reduction in the overall motion profile duration. Extensive evaluation of the proposed approach on a KUKA robot model demonstrates its effectiveness. © 2023 IEEE

Cybersecurity risks in meat processing plant and impacts on total productive maintenance

Technological changes have been happening in production facilities including food manufacturing industries in an ever-increasing rate. This includes advancement in data capture devices, signal processing, communication capabilities and automated process control systems such as Internet of Things. It is more challenging where production systems are highly reliant on automation and robotics. Remote performance monitoring and controls are becoming progressively vulnerable due to risks associated with cyber security and corporate espionage. May 2021 cyber-Attack forced JBS meats USA to pay 11m in ransom money to stop any further disruptions in services. This heavily impacted JBS global operations including JBS Australian food manufacturing facilities. Food production facilities in Australia have critical control points supported by smart technologies as part of their food safety management systems. Cyber-Attacks on production facilities could result in financial, operational, health and safety consequences. As survey by the Australian Cyber Security Centre in 2020 revealed that Australian small businesses are impacted by cybercime each year with a loss of 300m. To present the potential cyber security threats and their associated risk level, a case study is presented based on the processing and manufacture of meat products in Australia. From this case study, to protect the meat industries from attacks, we identify cyber security attacks and their possible mitigation strategies. This research shows cyber security attacks can severely affect Overall Equipment Effectiveness which motivate us to embed cyber security as an additional pillar in existing 8 pillars Total Productive Maintenance. If cyber security is added as additional pillar, it will improve the quality of end products and overall productivity of manufacturing industries. © 2021 IEEE

Agoraphilic navigation algorithm under dynamic environment

This article presents a summary of the work done on the development of a new algorithm for mobile robot navigation in unknown dynamic environment. The developed humanlike algorithm uses a free-space attraction (Agoraphilic) concept for robot navigation. The algorithm presented in this article is an advanced development of the Agoraphilic navigation algorithm. The Agoraphilic algorithm does not look for obstacles (problems) to avoid but rather for free spaces toward the goal (solutions) to follow. The original Agoraphilic while it was able to overcome the limitations of the traditional algorithms had its own limitations in navigating robots in environments cluttered with moving obstacles. The new Agoraphilic Navigation Algorithm under Dynamic Environment (ANADE) was developed to overcome those limitations. ANADE consists of seven main modules reported in this article. The objects tracking and objects prediction methodologies developed for the algorithm estimate future growing free-space passages toward the goal. The algorithm generates a time-varying single attractive force to pull the robot through the free space toward the predicted (future) growing free-space passages leading to the goal. The new algorithm was tested, not only through simulation, but also through experimental work. Summary of the experimental results is presented and discussed in this article. © 1996-2012 IEEE

Signal monitoring system for monitoring strain applied to a composite component

A system for estimating a strain of a component and method of estimating strain is provided. The system includes a signal generator configured to transmit a signal toward the component. A sensor is coupled to the component and configured to receive the signal and to generate a reflected signal, The system includes a Fibre Bragg grating filter coupled to the sensor and configured to filter the reflected signal and to generate filtered signal. A detector is coupled to the filter and configured to convert filtered signal to a time domain signal. The system includes an artificial neural network coupled to the detector and configured to process the time domain signal to facilitate estimating the strain of the component

Optimum grasp force and resistance to slippage

This paper presents an analysis and experimental results as part of the research into the optimal rate of grasp force application in precision grasping. It also offers the concept of resistance to object rotation in the robot gripper, which in turn contributes to the resistance to object slippage during robotic object manipulation. It is envisaged that this knowledge will be useful to researchers and designers of robotic grippers, especially those for industrial applications