Mobile Machines Research Articles

Design of Intelligent Ultrasonic Guided Vehicle

Due to the requirement of the development of the times, all walks of life require more and more intelligence, so more and more intelligent mobile machines and equipment are popularized. Compared with traditional equipment, smart cars have better mobility, safety and practicality. However, nowadays, domestic follow-up equipment generally exists in various highly specialized venue environments, which have certain environmental requirements, or track following camera cars in other specific sites, which have certain environmental requirements. There is no follow-up equipment or personal products for public places with complex situations, such as supermarkets, airports, railway stations, etc. This paper designs an intelligent vehicle based on Arduino programming, which is simple and practical, highly modular and highly portable. The smart car with low design cost, simple and mature technology and high portability can be used in work and ordinary life without manual operation. The smart car can use Arduino Nano, acoustic distance measurement module, motor, etc. in this design to achieve the positioning of specific targets and calculate the distance, including forward and backward, turning, At the same time, according to the feedback information, we can adjust the speed and turn behavior to track the target. Using mature ultrasonic ranging technology, chip, accurate positioning control algorithm, this simple, cheap and practical intelligent tracking car is designed

Analisis Uji Kesesuaian Pesawat Sinar X Radiografi Mobile Merk ALLENGERS Type MARS-6 SBM

The advances in technology experience significant developments anually, especially in the medical devices in the form of mobile x ray. The use of mobile x-ray radiation in the field of radiodiagnostics for various medical purposes needs to pay attention to two aspects, namely the risks and benefits. Therefore, the radiation protection is needed to reduce the damaging effects of radiation caused by radiation exposure. To ensure the accuracy and safety in the use of X-ray radiation, calibration procedures or conformity tests are carried out periodically. This study performs a conformity test on a mobile general radiography machine ALLENGERS, type MARS-6 SBM, with serial number 2162 used to examine the patients. The results of the conformity test using the Collimator Test and coin markers, mobile X-ray were declared to have passed the test as seen in the results from measurements using a Lux Meter, namely 101 Lux, with the score of a coin marker collimator of 3%.

Achieving excellent electromagnetic wave absorption property by constructing VO2 coated biomass carbon heterostructures

Lightweight, high-efficiency and low-cost electromagnetic wave absorption (EMA) material is playing an increasingly critical role in the areas of mobile communications, electronic machines and military science and technology. Heterostructures of biomass-derived porous carbon (BPC) from chestnut needle coated by VO 2 were constructed. Microstructure, morphology as well as EMA performance of as-prepared VO 2 /BPC composites were explored. The special porous structure of BPC-based composites boosted multi-reflections and scattering of EM wave. The higher surface area provided more channels for charge transfer, benefiting the dissipation of EM wave energy. The formed VO 2 was uniformly dispersed in BPC matrix resulting in more polarization loss. Additionally, the reduzate of VO 2 improved the impedance matching further optimizing the EMA performance immensely. With the joint action of excellent impedance matching and attenuation capacity, the VO 2 /BPC composites exhibited favorable EMA performance that the minimum reflection loss of −54.0 dB was achieved with wide effective absorption bandwidth of 2.5 GHz. The obtained results suggest the VO 2 /BPC composites would be a hopeful candidate for high-efficient, lightweight and green EMA material. • Preparation of EMA materials derived from natural biomass carbon. • Improved EMA performance was achieved that RL min was −54 dB. • The impedance matching and polarization loss was enhanced drastically by introduction of VO 2 . • The EMA mechanism was investigated.

Application of Fuzzy PID in Walking along the Wall Strategy of Mobile Robot

Aiming at the walk-along-the-wall strategy of the mobile machine, a guidance method based on two analogue laser ranging sensors and a fuzzy PID control algorithm is proposed in this paper, which solves the shortcoming that traditional PID control algorithm does not apply to the nonlinear movement of mobile machine. The fuzzy controller and fuzzy rules were first designed, and the control effect was simulated in MATLAB to verify the superiority of fuzzy PID control in the walking along the wall strategy, making the movement smoother and more stable.

침대 연동 이동식 재활 운동기 개발을 위한 침대-운동기 도킹 메커니즘

본 논문에서는 침대와 연동되는 재활 운동기 시스템에 적용하기 위한 침대-운동기 도킹 메커니즘을 제안 할 것이다. 연구의 최종 목표는 요양원 및 요양병원에서 침대 위주의 생활을 하는 고령자 및 환자를 위한 이동식 운동기 시스템을 개발 하는 것이다. 이를 위한 이동식 운동기 시스템은 운동 시 발생하는 하중 및 환자의 체중 등의 부하에 대해 안정적인 자세를 유지할 수 있어야 한다. 운동기를 침대에 안정적으로 고정시킬 수 있으면 운동기를 소형, 경량의 이동식으로 제작 할 수 있다. 이를 위해 본 논문에서는 운동기와 침대를 기계적으로 결합하는 도킹 메커니즘을 제안한다. 제안하는 도킹 메커니즘은 간단한 페달의 조작으로 운동기를 침대에 큰 힘으로 정확한 위치에 고정할 수 있다. 제안하는 도킹 메커니즘의 특징 및 장점을 설명하기 위해 기구학적 해석 및 간단히 제작된 실험 모델을 활용한 실험 결과를 제시할 것이다.

Quality Assessment of Biofuel Briquettes Obtained from Greenhouse Waste Using a Mobile Prototype Briquetting Machine with PTO Drive

Turkey has a large agricultural area and produces 55–60 million tons of biomass waste/year. This study aimed to obtain bio-briquettes from three types of dried greenhouse wastes and to determine their strength parameters. A prototype of a mobile briquetting machine driven by power take-off (PTO), with hydraulic pistons, and comprising a shredder and grinding or crushing unit with a briquetting pressure in the range of 0–190 MPa, was used. The physical parameters of the obtained briquettes were determined, including density, tumbler and shatter resistance, compression resistance, water intake capacity, and resistance to moisture-humidity. The results of physical and mechanical tests showed that the briquettes are of an extremely high quality. The maximum density, shatter and tumbler resistance were 1143.52 kg·m−3, 99.24% in pepper plant waste, and 98.52% in eggplant plant waste, respectively. Based on the analysis of compression tests obtained under 190 MPa (maximum compaction force of 450 kN), the maximum compression force, compression stress, and specific compression force were found in briquettes made from tomato plant wastes (3315 N, 69.43 N·mm−2, 40.09 N·mm−1, respectively). Overall, the results and variables affecting the strength parameters showed that greenhouse waste biomass is an excellent feedstock for the production of high quality bio-briquettes. The valorization of briquetted greenhouse waste with the proposed prototype contributes to the sustainability of the environment and to a reduction in energy costs for farmers.

Evaluating the knowledge and training of forensic pathologists and registrars performing forensic radiography at a forensic pathology mortuary in the Free State province, South Africa.

Forensic radiography is an important component in forensic sciences. There seems to be a lack of recent studies in the literature on the knowledge and training of forensic pathologists and registrars performing forensic radiography at forensic pathology mortuaries in South Africa. To evaluate the knowledge and training of forensic pathologists (consultants) and registrars performing forensic radiography at a forensic pathology mortuary in the Free State province, South Africa. A prospective study was conducted at a conveniently selected forensic pathology mortuary located in the Free State province of South Africa. Personnel performing forensic radiography at the selected mortuary were invited to participate in the study. An exploratory quantitative study design was used. The research tool was a self-administered questionnaire comprising open- and closed-ended questions. Four registrars and four consultants (n = 8) completed the questionnaire. Training was only received on computed tomography (n = 1; 12.5%), the C-arm machine (n = 1; 12.5%) and the digital X-ray mobile machine (n = 1; 12.5%) Lodox on corpse positioning (n = 7; 87.5%) and setting of exposure factors (n = 2; 25%). Lack of training of the personnel performing forensic radiography, at the selected mortuary was identified. Training is required in image acquisition protocols, quality control tests of the X-ray machines, setting technical factors and operation of various X-ray machines. Training of registered radiation workers who perform forensic radiography in mortuaries is essential to produce high-quality ionising radiation images and ensure their own and other staff members' safety.

Influence of High Pressure Drop Rates on Fatigue Crack Growth

AbstractHydraulic components in mobile machines are subjected to varying conditions and loads, which limit their lifetime. In particular, high pressure drop rates are suspected to increase fatigue crack growth rates. Existing studies on the fluid‐structure interaction inside fatigue cracks during fast pressure drops do not explain increased crack growth in hydraulic systems. A laminar flow model was developed to simulate the fluid flow inside a crack under periodic pressure loads. The viscosity restrained the oil inside the crack, and the mechanical resistance of the closing crack led to a high pressure increase. Knowledge of the pressure profiles inside fatigue cracks helps to estimate the effective fatigue damage during transient loads.

Introduction of an Assistance System to Support Domain Experts in Programming Low-Code to Leverage Industry 5.0

The rapid technological leaps of Industry 4.0 increase the pressure and demands on humans working in automation, which is one of the main motivators of Industry 5.0. In particular, automation software development for mechatronic systems becomes increasingly challenging, as both domain knowledge and programming skills are required for high-quality, maintainable software. Especially for small companies from automation and robotics without dedicated software engineering departments, domain-specific low-code platforms become indispensable that enable domain experts to develop code intuitively using visual programming languages, e.g., for tasks such as retrofitting mobile machines. However, for extensive functionalities, visual programs may become overwhelming due to the scaling-up problem. In addition, the ever-shortening time-to-market increases the time pressure on programmers. Thus, an assistance system concept is introduced that can be implemented by low-code platform suppliers based on combining data mining and static code analysis. Domain experts are supported in developing low-code by targeted recommendations, metric-based complexity measurement, and reducing complexity by encapsulating functionalities. The concept is implemented for the industrial low-code platform HAWE eDesign to program hydraulic components in mobile machines, and its benefits are confirmed in a user study and an industrial expert workshop.

A Torque Conversion Solution to the Powertrain of Mobile Machine and Its Control Strategy

The demand for reducing fuel consumption and emission of mobile machines is increasing since they consume large amount of energy and generate huge exhaust each year. The wheel loader is a representative mobile machine and large wheel loader typically employs a hydrodynamic torque converter and an automatic transmission in the powertrain. The torque converter provides large torque amplification at low vehicle speed, however generates large amount of heat inside. This brings a challenge during frequent vehicle start and stop. In this study, an alternative torque conversion solution to the powertrain of mobile machine with a power split hydraulic transmission is proposed, where the hydraulic transmission is a substitute for the torque converter. It eliminates overheating problem by dissipating the heat inside through its outlet. The mathematical models of the proposed powertrain including the wheel drive and working function are developed. An engine-speed-based system optimization is conducted and a rule-based control strategy based on optimization results is developed. The engine operations and engine fuel consumptions with optimization-based and rule-based control strategies are compared using three different loading cycles (57 s, 30 s, 90 s). The results show the effectiveness of proposed powertrain solution and its control strategy.

Predicting asthma attacks using connected mobile devices and machine learning: the AAMOS-00 observational study protocol

IntroductionSupported self-management empowering people with asthma to detect early deterioration and take timely action reduces the risk of asthma attacks. Smartphones and smart monitoring devices coupled with machine learning could...

Control Design of a Hydraulic Cooling Fan Drive for Off-Road Vehicle Diesel Engine With a Power Split Hydraulic Transmission

The engine cooling fan drive is crucial for an engine as it ensures safe and efficient engine operation. In heavy-duty mobile machine, the engine cooling fan consumes a considerable amount of engine power. To meet high cooling demand a hydraulic fan drive is usually employed. A simple and cost-effective way is to use two fixed displacement hydrostatic units and a pressure relief valve where it has severe valve throttling losses. A more efficient way is to use a variable displacement pump to drive a fixed displacement motor. It eliminates valve throttling however the drive efficiency is still relatively low due to variable pump displacement control. Therefore, an engine cooling fan drive system with a power split hydraulic transmission was proposed in the previous study. The hydraulic transmission is a compact unit with both pumping and motoring functions. The fan speed is controlled by adjusting the transmission outlet pressure. Although previous results showed the system has relatively higher drive efficiency than conventional hydraulic fan drive at different fan speeds, the control design, and system dynamic performance have not yet been studied. Therefore, in this article, the control design of the cooling fan drive system with power split hydraulic transmission is studied. A feedforward controller based on transmission characteristics is designed to achieve better system performance. A hydraulic fan drive test bench is developed to evaluate system control design. The system dynamic performance with feedforward and feedback controls are compared through both simulation and experimental studies.

Energy Management Based on Neural Networks for a Hydraulic Hybrid Wheel Loader

This paper presents a method to derive optimised energy management strategies for a hydraulic hybrid wheel loader. Energy efficiency is a key aspect for the sustainability of off-road mobile machines. Energy management strategies for on-road hybrid vehicles cannot be directly applied to off-road hybrid machines. One significant reason is that there are added degrees of freedom with respect to how power can be recovered, exchanged and reused in the different functions, such as drivetrain or work functions. This results in more complex energy management strategies being derived. This paper presents an analysis and preliminary conclusions for a proposed method to derive optimised online energy management strategies for a hydraulic hybrid wheel loader. Dynamic programming is used to obtain optimal offline energy management strategies for a series of drive cycles. The results are used as examples to train a neural network. The trained neural network then implements the energy management strategy and is used to make optimised control decisions. Through simulation, the neural network’s ability to learn the dynamic programming decision-making process is shown, resulting in the machine operating with fuel consumption similar to that of the offline optimal energy management strategy. Aspects of simplicity to model these machines for dynamic programming optimisation, the data necessary to train the network, the training process, variables used to learn the dynamic programming decision-making process and the robustness of the network when facing unseen operational conditions are discussed. The paper demonstrates the simplicity of the method for taking into account variables that affect the control decisions, therefore achieving optimised solutions.

Tennis Video Target Tracking Based on Mobile Network Communication and Machine Learning Algorithm

The application of information technology has realized the transformation of people’s production and lifestyle and also promoted the development of the sports industry. At present, the application of informatization in the field of sports is becoming more and more powerful. By using the advanced methods and technologies of its information display, this paper aimed to realize the research on the tracking of tennis sports video objects in the mobile network environment. It is helpful to analyze and solve the objectivity problems such as most of the loopholes in the single research and traditional methods of tennis video target tracking research. By drawing on the principles and rules of machine learning algorithms, the tennis video target tracking research is carried out, and the informatization and dataization of tennis are realized. In the experiment of the target tracking algorithm, 12 tracking videos have higher tracking accuracy than other parameters. The overall tracking accuracy of the video sequence under grayscale feature was 0.694; the tracking accuracy was the highest, but the tracking speed was the lowest compared to other parameters in the experiment. Therefore, it is very important to study the target tracking of tennis sports in the tennis field.

Everything Connects

Electronics play the central role in implementing new features in mobile machines, raising their performance, flexibility and reliability. A current trend is the connection of on-board electronics to the outer world. The advantages range from preventive maintenance and optimising the operation modes to implementing machine learning and autonomous operation

Optimal Control of the Energy-Saving Hybrid Hydraulic-Electric Architecture (HHEA) for Off-Highway Mobile Machines

Most off-highway constructions and agriculture equipment use hydraulics, which has unmatched power density, for power transmission and throttling as a means for control. A novel hybrid hydraulic–electric architecture (HHEA) has recently been proposed to improve efficiency for high-power machines that would have been cost-prohibitive to electrify directly. HHEA uses a set of common pressure rails (CPRs) to transmit the majority of power hydraulically and small electric motor drives to modulate that power and to achieve precise control. This article proposes a computationally efficient Lagrange multiplier method (LMM) for computing the optimal sequence of pressure rail selections to minimize energy use. This is needed to evaluate HHEA’s energy-saving potential and for iterative architecture design and sizing. An interesting complication is that the cost function is not fully defined until the candidate control sequence is fully specified. This issue is dealt with by decomposing the original problem into a set of sub-problems with additional constraints that can be solved efficiently. Computational effort can be further reduced if actuators are optimized individually instead of together. However, additional steps are required to prevent the constraint functions from becoming discontinuous with respect to the Lagrange multipliers, which is necessary for meeting the constraints. A case study of a construction machine demonstrates the efficacy of the method and shows that the HHEA reduces energy consumption by 68%–73% compared to the baseline load-sensing architecture.

A Method for Large Underground Structures Geometry Evaluation Based on Multivariate Parameterization and Multidimensional Analysis of Point Cloud Data

In underground mining, new workings (tunnels) are constructed by blasting or mechanical excavation. The blasting technique used in underground mines is supported by economic aspects, especially for deposits characterized by hard rocks. Unfortunately, the quality of the result may be different than expected in terms of the general geometry of work or the roughness of excavation surfaces. The blasting technique is also a source of vibrations that may affect other existing structures, affecting their stability. Therefore, it is of great importance to monitor both the quality of the new tunnels and changes in existing tunnels that may cause rockfall from the sidewalls and ceilings of both new and existing tunnels. The length of mining tunnels and support structures in underground mines is massive. Even if one would like to limit monitoring of tunnel geometry to those used every day for major technological processes such as transport, it is a vast amount of work. What is more, any stationary monitoring system is hard to utilize both due to everyday blasting procedures and mobile machine operation. The method proposed here is based on quick LiDAR/Terrestrial Laser Scanner measurements to obtain a cloud of points, which allows generating the spatial model of a mine’s geometry. Data processing procedures are proposed to extract several parameters describing the geometry of the tunnels. Firstly, the model is re-sampled to obtain its uniform structure. Next, a segmentation technique is applied to separate the cross sections with a specific resolution. Statistical parameters are selected to describe each cross section for final 1D feature analysis along the tunnel length. Such a set of parameters may serve as a basis for blasting evaluation, as well as long-term deformation monitoring. The methodology was tested and validated for the data obtained in a former gold and arsenic mine Zloty Stok, Poland.

Penuras Terbitan Gaussian Berorientasi untuk Peruasan Imej Paru-Paru Radiograf Mesin Pegun dan Mudah Alih

Unsupervised lung segmentation method is one of the mandatory processes in order to develop a Content Based Medical Image Retrieval System (CBMIRS) of CXR. There is limited study found on segmentation of mobile chest radiographs, that is relatively important especially for very sick patients whenever their radiographs will be taken using portable X-Ray machine.The purpose of the study is to present a solution for lung segmentation of standard and mobile chest radiographs using fully automated unsupervised method, based on oriented Gaussian derivatives filter with seven orientations, combined with Fuzzy C-Means clustering and thresholding to refine the lung region. A new algorithm to automatically generate a threshold value for each Gaussian response is also proposed. The algorithms are applied to both PA and AP chest radiographs from both public JSRT and private datasets from collaborative hospital. Two pre-processing blocks are introduced to standardize the images from different machines. Comparisons with the previous works found in the literature on JSRT dataset shows that our method gives a reasonably good result. Performance measures (accuracy, F-score, precision, sensitivity and specificity) for the segmentation of lung in public JSRT dataset are above 0.90 except for the overlap measure is 0.87. The median of overlap score for the private image database is 0.83 (standard machine) and 0.75 (mobile machines). The algorithm is also fast, with the average execution time of 12.5s. Our proposed method is fully automated, unsupervised, with no training or learning stage is necessary to segment the lungs taken using both a standard and mobile machines, and useful for the application of the CBMIRS.

CREATION OF A MOBILE INSTALLATION FOR SORTING GRAIN IMPURITIES

The problem of the imperfection of the process of cleaning grain masses in time for refinement to basic quality indicators is considered. It is shown that grain waste contains a significant amount of grain and oilseed admixture. The state of waste generation at the enterprises of the elevator, grain processing and oil and fat industries is described. An analysis was made of the prospects for their processing as raw materials for the production of food products – cereals, vegetable oils and others. It is emphasized that in the conditions of the declared state of war in Ukraine, the allocation of "valuable fractions" from grain waste is financially relevant. A mobile plant for sorting grain waste has been developed and its production tests have been carried out. The rational productivity of such a machine is noted - no more than 48 tons per day (for grain waste). This will ensure the processing of sunflower waste up to 1000 tons of sunflower seeds per day, and the processing of grain crop waste – up to 800 tons of grain per day. It is shown that the developed sorting machine is advisable to use in small farms, where the volume of grain waste is 140-150 kg per hour, and sunflower waste and husks – 100-120 kg per hour. In the conditions of the Limited Liability Company Scientific and Production Enterprise "Sorting Machines" in the city of Dnipro, a study was made of the process of sorting grain waste on a developed mobile unit. The test results confirmed the productivity of the sorting machine. The design of the main unit of a mobile unit for sorting grain masses – a channel for sorting – is described. Improvements in the design of the sorting machine have been proposed and a package of computer programs has been developed for sorting sunflower, wheat, soybean, amaranth, hemp, and rapeseed waste. In the course of research, the necessity of using an anti-adhesive coating and a special form of a vibrating feeder of the developed machine was proved. This allows you to reduce the cleaning time of the feeder, eliminate the compaction of raw materials and eliminate areas of accumulation of grain material. In the program of the sorting unit, a separation channel cleaning module has been developed, which has two modes - the frequency and duration of the channel purge. The description and technical characteristics of the developed mobile machine for sorting grain waste are given.

The Role of Digital Technology in Curbing COVID-19.

Introduction: Using digital technology to provide support, medical consultations, healthcare services, and to track the spread of the coronavirus has been identified as an important solution to curb the transmission of the virus. This research paper aims to (1) summarize the digital technologies used during the COVID-19 pandemic to mitigate the transmission of the COVID-19; (2) establish the extent to which digital technology applications have facilitated mitigation of the spread of COVID-19; and (3) explore the facilitators and barriers that impact the usability of digital technologies throughout the pandemic. Methods: A rapid electronic search following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted of available records up to June 2022 on the medical databases PubMed, Ovid, Embase, CINHAIL, the Cochrane Library, Web of Science, and Google Scholar. Results: An increasing number and variety of digital health applications have been available throughout the pandemic, such as telehealth, smartphone mobile health apps, machine learning, and artificial intelligence. Each technology has played a particular role in curbing COVID-19 transmission. Different users have gained benefits from using digital technology during the COVID-19 pandemic and different determinants have contributed to accelerating the wheel of digital technology implementation during the pandemic. Conclusion: Digital health during the COVID-19 pandemic has evolved very rapidly, with different applications and roles aimed at curbing the pandemic.