Browse Topic: Industrial vehicles and equipment

Items (415)
To precisely simulate the nonlinear dynamic characteristics of a robotic arm grasping cylindrical objects from storage units, this study establishes a dynamic model of the robotic grasping process incorporating Coulomb and viscous friction models to characterize frictional properties. Furthermore, to effectively identify unknown parameters in the dynamic model, a parameter identification method based on the Superb Fairy-wren Optimization Algorithm (SFOA) is proposed. The root-mean-square error (RMSE) between the displacement responses from the dynamic model and the experimentally acquired displacement data serves as the optimization objective. Multiple sets of experimental data are utilized to identify the unknown parameters of the dynamic model. The results demonstrate that when the identified parameters are applied to the dynamic model, the goodness-of-fit between the model’s response displacement data and the experimental displacement data exceeds 0.999. This validates the effectiveness and accuracy of the proposed method for identifying unknown parameters in dynamic models.
Shen, ShaofengYang, LiuWang, ZihanHan, Qunyi
With the development of the power industry, 10kV switchgear (circuit breaker switches) are increasingly widely applied in power grids. When performing power-off maintenance or testing on 10kV switchgear (circuit breaker switches) at substations, maintenance personnel require transport carts to move the equipment to suitable locations for operation. Traditional transfer carts suffer from structural design flaws and significant shortcomings. These include difficulty operating in the confined spaces of switchgear cabinets, high risks associated with manual handling, low efficiency in secondary transfers, and poor adaptability across multiple workstations. These issues collectively pose safety hazards during power-off maintenance or testing. When operating in a 3m×5m high-voltage room, traditional maintenance carts achieve less than 0.5 units transported per hour, with equipment damage rates reaching 3% annually due to drops, resulting in low work efficiency. To address these challenges, a 10kV switch cart maintenance platform has been developed. This standardized equipment facilitates 10kV switch cart maintenance, supporting the intelligent upgrade of power grid operation and maintenance.
Yang, SenZhou, HanSu, HainanYu, XinHu, YutaoWang, Xisheng
In order to achieve precise control of refueling volume, improve oil change efficiency, reduce oil pollution and waste, a new oil change device for the reducer of the range hood equipment is studied. We design a new oil change device that integrates oil discharge and refueling functions based on the operating characteristics of the reducer in the range hood equipment. Using the rotational speed of the power pump and the flow rate of the oil pipeline as variables, we determine the refueling flow rate using a one-dimensional quadratic formula. Based on direct control theory, we optimize the relative position parameters of each component of the device, establish a control matrix, and achieve precise control. The experimental results show that the new oil change device exhibits good performance during both one-time oil discharge and refueling processes, meeting the precise control standards for refueling volume. The design and application of a new oil change device can effectively improve the efficiency and accuracy of oil change in the reducer of the range hood equipment, and have practical application value.
He, PengtaoWei, BoLiang, ZhiyuanDeng, WeirenLiang, WenbinXing, Yuquan
A rotatable pressure vessel transfer device has been designed to meet the positioning requirements of pressure vessels in old factory buildings with limited lifting space or insufficient crane lifting capacity, as well as small factory buildings with limited overall space. The device consists of a main driving rail car, a cable reel, a control box, and a towed transport car. In order to test the load-bearing capacity, passability, and stability of the transfer device for hill parking, experiments were conducted at the factory. The experimental results show that under full load conditions, the transfer device can park stably on the sloping track without any sliding phenomenon. The curved track passes smoothly without any jamming or derailment, meeting the design requirements.
Chen, JinshanSun, YeZhu, JialeiLiang, XiaodongWang, Hongfei
This SAE Recommended Practice covers the safety alert symbol intended for use on construction and industrial equipment as defined in SAE J1116 and on agricultural tractors and machinery as defined in ASABE S390.
HFTC2, Machine Displays and Symbols
OEMs, integrators and suppliers must continuously process, assess and identify platform vulnerabilities to prioritize and implement updates that protect systems from cyberattacks and data breaches. Security researchers have demonstrated that the control systems in vehicles and machines are open to attack. In 2010, researchers from the University of Washington and the University of California, San Diego demonstrated that by gaining physical access to a vehicle, they could manipulate critical systems like brakes and engines. Just a few years later, security researchers Charlie Miller and Chris Valasek remotely compromised a vehicle over the internet, controlling steering, braking and acceleration, leading to a 1.4 million vehicle recall. In 2024, researchers at Colorado State University successfully demonstrated a wireless drive-by hack by exploiting vulnerabilities in common electronic logging devices (ELDs). In their proof-of-concept test, they achieved remote control over a truck by reflashing the ELD with malicious firmware, which allowed them to slow down a moving truck and show a design for a truck-to-truck worm virus that could theoretically spread through a fleet.
McGuirk, Finn
The legislation of CEV Stage V emission norms has necessitated advanced Diesel Particulate Filter calibration strategies to ensure optimal performance across diverse construction equipment applications in the Indian market. Considering the various duty cycles of cranes, backhoe loaders, forklifts, compactors, graders, and other equipment, different load conditions and operational environments require a comprehensive strategy to enhance DPF efficiency, minimize regeneration frequency, and maintain compliance with emission standards. The DPF, as an after-treatment system in the exhaust layout, is essential for meeting emission standards, as it effectively traps particulate matter. Regeneration occurs periodically to burn the soot particles trapped inside the DPF through ECU management. Therefore, understanding soot loading and in-brick DPF temperature behavior across various applications is key. This paper explores the challenges in DPF calibration for CEV Stage V and provides a comprehensive approach to address these challenges, including optimizing soot loading and thermal management for different duty cycles across various applications within a unified calibration framework. The frugal Off-Highway Vehicle market expects a leaner Exhaust Gas Treatment approach, which increases the challenges of thermal management and soot loading. Additionally, the market is moving towards extracting maximum BMEP from their engines, which impacts passive regeneration and DPF thermal stability, among other parameters.
Mohanty, SubhamChaudhari, KuldeepakPatil, LalitMahajan, AtishMadhukar, Prahlad
In this article we will discuss the development and implementation of a computer vision system to be used in decision-making and control of an electro-hydraulic mechanism in order to guarantee correct functioning and efficiency during the logistics project. To achieve this, we have brought together a team of engineering students with knowledge in the area of Artificial Intelligence, Front End and mechanical, electrical and hydraulic devices. The project consists of installing a system on a forklift that moves packaged household appliances that can identify and differentiate the different types of products moved in factories and distribution centers. Therefore, the objective will be to process this identification and control an electro-hydraulic pressure control valve (normally controlled in PWM) so that it releases only the hydraulic pressure configured for each type of packaging/product, and thus correctly squeezing (compressing) the specific volume, without damaging it due to excessive force, and without little force to the point of allowing the load to fall.
Furquim, Bruno BuenoPivetta, Italo MeneguelloIbusuki, Ugo
The de-rated capacity of forklifts plays a crucial role in determining their safety, efficiency, and overall performance, particularly when modifications are introduced to meet stringent industrial standards. The term "de-rated capacity" refers to the reduction in a forklift's rated load-carrying capacity caused by various factors, including load center shifts, lifting height, attachment usage, tire types, and counterweight adjustments. This reduction occurs as a safety measure to account for potential instabilities or mechanical limitations when operating under less-than-ideal conditions. Accurate understanding and calculation of de-rated capacity are vital to ensure safe and efficient forklift operation. This research provides a detailed examination of forklift variants, specifically evaluated under the IS 4357:2004 standards [1], to understand the intricate relationship between tire types and counterweight adjustments on the derated capacity. With advanced Multibody Simulations, as demonstrated in prior studies on dynamic stability assessment, the study assesses how different tire configurations—such as solid tires and pneumatic tires affect critical factors like load stability, traction, under varying operational conditions. Additionally, the study explores the role of counterweight modifications in ensuring optimal load balancing, maintaining a stable center of gravity, and enhancing overall lifting efficiency in challenging environments. The results of this investigation demonstrate that careful selection of tire types and precise counterweight optimization are indispensable for maximizing forklift performance without compromising safety. The findings further emphasize that improper configurations can lead to significant de-rating, potentially increasing operational risks, and reducing productivity. Multibody Dynamics (MBD) analysis serves as a powerful tool for optimizing forklift design, offering industry professionals a structured approach to making informed choices during the early development phase. By leveraging MBD simulations, engineers can fine-tune load balance and traction properties before constructing physical prototypes. Integrating these simulations into the design workflow enables manufacturers to minimize time and costs associated with extensive testing, ultimately improving efficiency, ensuring safety, and meeting industrial standards.
Shende, KalyaniShingavi, ShreyasHingade, Nikhil
This paper studies an important industrial controls engineering problem statement on mitigating vibrations in a mechanical boom structure for an off-highway agricultural vehicle. The work discusses the implementation of an active force control concept to efficiently dampen out vibrations in a boom. Through rigorous simulation comparison with respect to an existing PID mechanism, the efficacy of the AFC is demonstrated. A notable reduction of 60 % to 70 % in the boom vibrations was observed.
Patil, BhagyeshBawankar, Shubham
Marine ports are an important source of emissions in many urban areas, and many ports are implementing plans to reduce emissions and greenhouse gases using zero-emission cargo handling equipment. This paper evaluates the performance and activity profiles for various zero-emission (ZE) cargo transport equipment being demonstrated at different ports in California. This included 23 battery-electric (BE) 8,000 lb. (8K) and 36,000 lb. (36K) forklifts, a BE railcar mover, and an electrified rubber-tired gantry crane (eRTG). The study focused on evaluating the performance of the ZE equipment in terms of activity patterns and the potential emissions reductions. Data loggers were used to collect activity data, including hours of use, energy consumption, and charging information over periods from 6 to 21 months. The results showed that the BE forklifts, BE railcar mover, and the eRTG averaged 2-3 hours, 5 hours, and 14 hours of use per day of operation, respectively. The average energy use for the 8k and 36k, railcar mover, and eRTG were 7.5 kWh, 17.2 kWh, 130.7 kWh and 605 kWh, respectively. Energy consumption per day of operation in terms of battery state of charge (SOC) use, for the 8K and 36K forklifts were on average, 40% and 26%, respectively. The study provides valuable insights into the operational characteristics of ZE port equipment. The annual emissions of the conventional port equipment are estimated and compared with estimated emissions generated by electricity generation that would be required to operate the electric equipment. This comparison showed nitrogen oxide (NOx) emissions could be reduced 76% to 99% for the BE equipment, carbon dioxide (CO2) emissions could be reduced from 76% to 95% compared to the conventional equipment for the BE forklifts and the eRTG and 26% for the railcar mover, and particulate matter (PM) emissions for the electric equipment would negligible.
Frederickson, ChasVu, AlexanderMakki, MaedehJohnson, KentDurbin, ThomasBurnette, AndrewHuang, EddyAlvarado, EricaRao, Leela
The performance differences of multiple sensors lead to inconsistencies, incompleteness, and distortion in the perception data of multi-source vehicle information in highway scenarios. Optimizing data fusion methods is important for intelligent toll collection systems on highways. First, this paper constructs a dataset for matching and fusing multi-source vehicle information in highway gantry scenarios. Second, it develops convolutional neural network models, Match-Pyramid-MVIMF-EGS and CDSSM-MVIMF-EGS, for this purpose. Finally, comparative experiments are conducted based on the constructed dataset to assess the performance of the Match-Pyramid-MVIMF-EGS and CDSSM-MVIMF-EGS models. The experimental results indicate that the Match-Pyramid-MVIMF-EGS model performs better than the CDSSM-MVIMF-EGS model, achieving matching and fusion accuracy of 93.07%, precision of 95.71%, recall of 89.17%, F1 scores of 92.32%, and 186 of training throughput respectively.
Wang, JunjunZhao, Chihang
This SAE Recommended Practice applies to technical publications which present instructions for the proper unloading, set-up, installations, pre-delivery inspection, operation, and servicing of off-road self-propelled work machines as categorized in SAE J1116. Advertising/marketing and other pre-purchase publications are not included.
Machine Technical Steering Committee
This article presents an optimization scheme for LoRaWAN-based electric vehicle batteries monitoring system located in warehouses by utilizing techniques to optimize packet delivery and power settings. Utilizing simulations, we identify that system optimization largely depends on network traffic, influenced by active users and the adoption of the pure ALOHA protocol. We define a reward metric based on the packet delivery rate and power efficiency, aiming for settings that yield the maximum reward. Our approach includes duty cycle management to minimize network traffic and maximize throughput, especially critical when handling urgent data from batteries. Traffic management based on the number of critical batteries in the warehouse also plays a crucial role. Predictive modeling of future traffic further refines power settings for optimal performance. The proposed system, tested through simulations, shows an average of 31% higher reward compared to traditional methods without duty cycle management.
Tabatowski-Bush, BenjaminXiang, Weidong
The scope of this SAE Recommended Practice is limited to cranes mounted on a fixed platform lifting loads from a vessel alongside. The size of the vessel is assumed not to exceed that of a work boat as defined in 3.14.
Cranes and Lifting Devices Committee
The scope of this SAE Information Report is limited to a lift crane mounted on a fixed or floating platform, lifting loads from a vessel alongside. The size of the vessel is assumed not to exceed that of a workboat as defined in 3.15.
Cranes and Lifting Devices Committee
Autonomous Driving is used in various settings, including indoor areas such as industrial halls and warehouses. For perception in these environments, LIDAR is currently very popular due to its high accuracy compared to RADAR and its robustness to varying lighting conditions compared to cameras. However, there is a notable lack of freely available labeled LIDAR data in these settings, and most public datasets, such as KITTI and Waymo, focus on public road scenarios. As a result, specialized publicly available annotation frameworks are rare as well. This work tackles these shortcomings by developing an automated AI-based labeling tool to generate a LIDAR dataset with 3D ground truth annotations for industrial warehouse scenarios. The base pipeline for the annotation framework first upsamples the incoming 16-channel data into dense 64-channel data. The upsampled data is then manually annotated for the defined classes and this annotated 64-channel dataset is used to fine-tune the Part-A2-Net that has been pretrained on the KITTI dataset. This fine-tuned network shows promising results for the defined classes. To overcome some shortcomings with this pipeline, which mainly involves artefacts from upsampling and manual labeling, we extend the pipeline to make use of SLAM to generate the dense point cloud and use the generated poses to speed up the labeling process. The progression, therefore shows the three generations of the framework which started with manual upsampling and labeling. This then was extended to a semi-automated approach with automatic generation of dense map using SLAM and automatic annotation propagation to all the scans for all static classes and then the complete automatic pipeline that generates ground truth using the Part-A2-Net which was trained using the dataset generated from the manual and semi-automated pipelines. The dataset generated for this warehouse environment will continuously be extended and is publicly available at https://github.com/anavsgmbh/lidar-warehouse-dataset.
Abdelhalim, GinaSimon, KevinBensch, RobertParimi, SaiQureshi, Bilal Ahmed
To provide specifications for lighting and marking of industrial wheeled equipment whenever such equipment is operated or traveling on a highway.
OPTC3, Lighting and Sound Committee
Electrification isn't just a matter of switching out the diesel engine for an electric motor. It requires a thorough review of connected systems - particularly the hydraulic system. Using the same components in electric machines as those used in conventional machines often requires more battery power or a larger electric motor. For this reason, OEMs have discovered the need to rethink efficiency and productivity when electrifying machines. MPG Makine Prodüksiyon Grubu learned this firsthand when designing a truck-mounted electric crane for one of its Netherlands-based customers. The Konya, Turkey-based OEM produces truck-mounted hydraulic cranes with folding and telescopic booms as well as aerial work platforms and tree trans-planter machines.
Avci, Gökhan
iMotions employs neuroscience and AI-powered analysis tools to enhance the tracking, assessment and design of human-machine interfaces inside vehicles. The advancement of vehicles with enhanced safety and infotainment features has made evaluating human-machine interfaces (HMI) in modern commercial and industrial vehicles crucial. Drivers face a steep learning curve due to the complexities of these new technologies. Additionally, the interaction with advanced driver-assistance systems (ADAS) increases concerns about cognitive impact and driver distraction in both passenger and commercial vehicles. As vehicles incorporate more automation, many clients are turning to biosensor technology to monitor drivers' attention and the effects of various systems and interfaces. Utilizing neuroscientific principles and AI, data from eye-tracking, facial expressions and heart rate are informing more effective system and interface design strategies. This approach ensures that automation advancements improve rather than hinder the driving experience.
Nguyen, Nam
Accurate estimation of battery state of health (SOH) has become indispensable in ensuring the predictive maintenance and safety of electric vehicles (EVs). While supervised machine learning excels in laboratory settings with adequate SOH labels, field-based SOH data collection for supervised learning is hindered by EVs' complex conditions and prohibitive data collection costs. To overcome this challenge, a battery SOH estimation method based on semi-supervised regression is proposed and validated using field data in this paper. Initially, the Ampere integral formula is employed to calculate SOH labels from charging data, and the error of labeled SOH is reduced by the open-circuit voltage correction strategy. The calculation error of the SOH label is confirmed to be less than 1.2%, as validated by the full-charge test of the battery packs. Subsequently, statistical features are extracted from charging data, and health indicator sets are selected by two correlation analysis methods (Pearson correlation and grayscale correlation). Moreover, two regressors are trained by learning the mapping between labeled SOH and various health indicator sets. To enhance the training dataset, semi-supervised with co-training is utilized to estimate pseudo-labels for unlabeled charging data. The final SOH estimation is achieved through the fusion of these two regressors. Finally, the proposed method is validated using field data from 20 electric forklifts collected over approximately one year. Remarkably, even with only 10 labeled data points, the proposed method achieves a mean absolute error in SOH estimation of a mere 3.96%. This represents a significant reduction of 20% compared to the traditional supervised learning method. Compared with the two benchmarks without co-training, the estimation error drops by 7.69% and 8.76%, respectively.
Li, JinwenChen, WenqiangKhalatbarisoltani, ArashLiu, HongaoLin, XiankeHu, Xiaosong
Heavy vehicles such as construction machinery generally require a large traction force. For this reason, axle components are equipped with a final reduction gear to provide a structure that can generate a large traction force. Basic analysis of vertical load, horizontal load (traction force), centrifugal force, and torsional torque applied to the wheels of heavy vehicles such as construction machinery and industrial vehicles, as well as actual working load analysis during actual operations, were conducted and compiled into a load analysis diagram. The loosening tendency of wheel bolts and nuts that fasten the wheel under actual working load was measured, and the loosening analysis method was presented. The causes of wheel fall-off accidents in heavy trucks, which have recently become a problem, were examined. Wheel bolts are generally tightened by the calibrated wrench method using a torque wrench. The method is susceptible to variations in friction coefficient and tightening torque, and human error affects the tightening torque. Even if the tightening torque (initial clamping force) is insufficient, effective loosening prevention is considered necessary to prevent serious accidents such as wheels falling off. In forklifts, the number of hub bolts is limited due to space limitations, so hub nuts have a spherical or conical alignment structure that allows each nut and bolt to absorb the drive torque and slippage of the bearing surface. In wheel loaders, for example, there is space to install hub bolts, and the clamping force of the bolt sustained slippage of the bearing surface to prevent loosening and fatigue”
Hareyama, SoichiManabe, Ken-ichiKobayashi, Satoshi
Engineers at the University of California San Diego have developed electronic “stickers” that measure the force exerted by one object upon another. The force stickers are wireless, run without batteries and fit in tight spaces. That makes them versatile for a wide range of applications, from arming robots with a sense of touch to elevating the immersive experience of VR and AR, making biomedical devices smarter, monitoring the safety of industrial equipment, and improving the accuracy and efficiency of inventory management in warehouses.
NMC and LFP lithium-ion batteries find favor in different regions as OEMs move to electrify larger excavators and loaders. The success of electric vehicles in the construction industry will largely be determined by battery prices being low enough that the total cost of ownership is cheaper than diesel alternatives. IDTechEx's new report, “Electric Vehicles in Construction 2023-2043,” shows that there is a battery price tipping point, under which it will be cheaper over the vehicle lifetime to operate an EV. Selecting the right chemistry will be imperative for getting a low enough vehicle price. So why is a clear dichotomy seen between the batteries being deployed in China compared to Europe? Electric vehicles in construction are an emerging market. IDTechEx has built a database of more than 100 example makes and models across seven different construction-vehicle categories: mini excavators, excavators (>6 tonne), compact loaders, backhoe loaders, wheel loaders, telehandlers and mobile cranes. However, with lots of vehicles yet to be released, only 49 database entries have confirmed chemistry information.
Jeffs, James
Like the shift from horse drawn carriages to cars, the emergence of delivery robots marks a shift from driverless vehicles to automated logistics vehicles where form follows function. On paper, the business cases are compelling and the use cases seemingly unbounded. Vehicles may be conventional in the form of trucks and industrial equipment of all types, or as purpose-built vehicles on with widely varying cargo capacities. Proof of concepts and pilots are moving forward on roadways, sidewalks, and doorsteps, as well as in low altitude airways, ports, and even inside of buildings. Automated Vehicles and Infrastructure Enablers: Logistics and Delivery addresses the current state of the industry, benefits of ADVs, challenges, and expanding use. It also touches on opportunities to design, modify, and expand infrastructure—both digital and physical—to supports safe and equitable usage. The report draws on experience and research on these topics in North America, the United Kingdom, the European Union, Australia, and the United Arab Emirates, among others. Click here to access The Mobility Frontier: Accelerating Infrastructure Readiness for Autonomy Click here to access the full SAE EDGETM Research Report portfolio.
Coyner, KelleyBittner, Jason
In order to guarantee the dependability and effectiveness of industrial machinery, real-time gearbox malfunction detection is extremely important. Traditional approaches to condition monitoring systems sometimes rely on time-consuming human inspections or routine maintenance, which can result in unanticipated failures and expensive downtime. The rise of the industrial Internet of things (IIoT) in recent years has paved the way for more sophisticated and automated monitoring methods. An IIoT-based condition monitoring system is suggested in this study for real-time gearbox failure detection. The gearbox health state is continually monitored by the system using sensor data from the gearbox, such as temperature, vibration, and oil analysis. Real-time transmission of the gathered data is made to a central monitoring hub, where sophisticated analytics algorithms are used to look for any flaws. This study’s potential to improve the dependability and operational effectiveness of industrial gear is what makes it so significant. Real-time defect identification makes it possible to undertake maintenance tasks preemptively, avoiding catastrophic failures and cutting down on downtime. This reduces not just the expenses of unanticipated maintenance but also boosts general productivity and client happiness. The uniqueness of this study comes from the way sophisticated analytics and IIoT technologies were used to find gearbox defects. Despite the literature’s exploration of IIoT-based condition monitoring systems, this work focuses especially on gearbox defect detection, which presents special difficulties because of complicated mechanical dynamics and the existence of several failure scenarios. The suggested methodology provides a thorough and automated method that can precisely identify and diagnose gearbox faults, leading to timely maintenance actions and increased operational reliability. Overall, employing IIoT-based condition monitoring, this work offers a unique and useful method for real-time gearbox failure diagnosis. The results of this study can help improve industrial maintenance procedures, which will enhance machinery performance and decrease downtime across a variety of industries, including manufacturing, energy, and transportation.
Sivaraman, P.Ilakiya, P.Prabhu, M.K.Ajayan, Adarsh
This SAE Standard provides general design performance requirements and related test procedures for composite lighting unit assemblies, other than signaling and marking devices, used on earthmoving and road building and maintenance off-road work machines as defined in SAE J1116.
OPTC3, Lighting and Sound Committee
This SAE Standard establishes the maximum gradient rating during hopper discharge of self-propelled, driver-operated sweepers and scrubbers as defined by SAE J2130-1 and SAE J2130-2.
MTC2, Sweeper, Cleaner, and Machinery
Industrial vehicles such as forklifts, cranes and tractors have come a long way in terms of applying technology, enhancing performance with improved operation and safety. With the advancements in computer vision, robotics and artificial intelligence (AI), these vehicles now are equipped with functionality that utilizes information to support and optimize performance. One of the key enablers of these advances is the integration of machine learning (ML) derived platforms and powerful computers, neural processing units and cameras integrated into the digital system. System designers and OEMs can get started with AI and computer vision using just a standard Ethernet camera and a Cortex A35 dual- or quad-core next-generation display. Using the detection and recognition of objects, designers can implement and train neural networks to realize new solutions for process guidance, automation, augmented reality and operator awareness. For example, the dual-core CCpilot V700 from CrossControl can provide adequate detections for automating processes.
Persson, Johan
This analysis applies to crane types as covered by ASME B30.5.
Cranes and Lifting Devices Committee
In this article, a 300-ton truck crane was used as the research object, and the data and experience of telescopic boom design were integrated to optimize the design research under three dangerous working conditions of the telescopic boom. Three-dimensional (3D) modeling software and finite element software were used to model and statistically analyze the truck crane telescopic boom. Then the correctness of the finite element model was verified by static experiments, and the design was optimized. Under the condition of satisfying the strength and stiffness, the telescopic crane boom was optimized by using the response surface optimization module in Ansys workbench software to be lightweight, and more satisfactory results were obtained. Finally, through the modal and flexural analysis of the optimized model, ideas and suggestions were provided for the further optimization of the telescopic boom.
Wang, ChaosongXing, Bangsheng
At Bauma 2022 in Munich, Germany, Danfoss revealed that its electrified powertrain system was driving a new electric crawler crane, the Sany SCE800TB-EV. This will be Sany's first fully electric volume-model crawler crane and is available for batch order in the European market, where Danfoss states that there is increasing demand for zero-emission construction machines. The Sany SCE800TB-EV is an 80-ton telescopic crane with a maximum lifting moment of 300 ton-meters and a maximum boom length of 47 meters (155 ft). The electric system features a permanent-magnetic synchronous motor and an inverter supplied by Danfoss's Editron division as well as a Danfoss D1P hydraulic pump.
Wolfe, Matt
Ethernet is widely used among consumer and commercial systems throughout the world, and it is well understood by all levels of end-users. Due to economies of scale, coupled with availability of industrial-grade devices, Ethernet has also become suitable, and often dominant, for many types of more rigorous applications. Unfortunately, industrial-grade Ethernet devices are often associated with high costs and complex network management and configuration requirements.
This analysis applies to crane types as covered by ASME B30.5.
Cranes and Lifting Devices Committee
Cranes for lifting and lowering heavy objects are an important and sometimes essential tool in modern industries such as construction, transportation, and manufacturing. NASA uses overhead and mobile cranes for assembly of load lines employed in full-scale testing of its Space Launch System (SLS), a super-heavy-lift launch vehicle for deep space human space exploration. Structural testing of the SLS requires precision placement of heavy objects with soft contact during mating connections, which proved to be problematic with the relatively coarse control available with motor-driven overhead cranes and the existing rigging devices.
What Is It? What Does it Do? How Does It Work? The Distributed Extreme Environment Drive System (DEEDS) is an advanced space-rated avionic and actuation control system that addresses a wide thermal range of operations for harsh environments. This new technology development, undertaken by Motiv Space Systems (Motiv), addresses some of the most stringent environmental requirements of lunar and deep space exploration. It will enable sustained operations for critical systems like lunar rovers, robotics, cranes, offload equipment, ISRU processing equipment, and cargo manipulation systems. DEEDS was funded under NASA's SBIR ‘Moon to Mars’ Sequential Program and builds on previously established cryogenic operating avionic SBIR-funded technologies that have been successfully commercialized for orbital and lunar lander systems.
The Distributed Extreme Environment Drive System (DEEDS) is an advanced space-rated avionic and actuation control system that addresses a wide thermal range of operations for harsh environments. This new technology development, undertaken by Motiv Space Systems (Motiv), addresses some of the most stringent environmental requirements of lunar and deep space exploration. It will enable sustained operations for critical systems like lunar rovers, robotics, cranes, offload equipment, ISRU processing equipment, and cargo manipulation systems. DEEDS was funded under NASA’s SBIR ‘Moon to Mars’ Sequential Program and builds on previously established cryogenic operating avionic SBIR-funded technologies that have been successfully commercialized for orbital and lunar lander systems.
This document establishes safety limits and performance requirements for gaseous hydrogen fuel dispensers used to fuel Hydrogen Powered Industrial Trucks (HPITs). It also describes several example fueling methods for gaseous hydrogen dispensers serving HPIT vehicles. SAE J2601-3 offers performance based fueling methods and provides guidance to fueling system builders as well as suppliers of hydrogen powered industrial trucks and operators of the hydrogen powered vehicle fleet(s). This fueling protocol for HPITs can support a wide range of hydrogen fuel cell hybrid electric vehicles including fork lifts, tractors, pallet jacks, on and off road utility, and specialty vehicles of all types. The mechanical connector geometry for H25 and H35 connectors are defined in SAE J2600 Compressed Hydrogen Surface Vehicle Refueling Connection Devices. Multiple fueling methods are described in this document and include: 1 Fill to Service Pressure with fixed area flow-limiting device 2 Fill to Target Pressure with fixed area flow-limiting device 3 Fill to Target Pressure with variable area flow-limiting device These three dispensing methods are detailed in Section 6 and include a schematic of control components for vehicle fueling. These methods allow for market differentiation with varied target fill pressures relative to 100% SOC. These methods are examples of how dispensers may function but are not intended to limit options for new dispenser technologies or fueling methods, provided they meet the performance based requirements. This document is suitable for all vehicle tank fueling systems above 18 L water volume and may be used for fueling of all types of Hydrogen Powered Industrial Trucks (HPIT’s), and Battery Replacement modules (BRM’s). The fueling limits shown in Section 5 are harmonized with the fueling assumptions used for on-board fuel systems that comply with CSA HPIT-1.
Fuel Cell Standards Committee
This SAE Recommended Practice applies to stationary usage of mobile construction-type cranes, crawler or rubber-tire mounted, on outriggers or on tires, when used for lifting, clamshell, dragline, magnet, pile driver, or similar service.
Cranes and Lifting Devices Committee
This SAE Recommended Practice applies to cranes in lifting crane service which are equipped with two-block warning, limiting, and/or damage prevention systems.
Cranes and Lifting Devices Committee
This article aims at the calibration of an onboard sensor and actuator parameters as well as the identification of the open-loop transfer function of the steering and traction control systems of tripod electric vehicles (EVs). Tripod EVs are commonly used as forklifts and automatic guided vehicles in a factory or wheelchairs in a hospital. A test procedure called the circular, linear, and cornering motions (CLCM) test is introduced in this article for making the corrections which are caused by many factors including the potentiometer of the steering angle error, hall sensor error of the traction speed, the backlash of the steering system, and the tire slip angle that can lead the tripod EV to deviate from the path. The CLCM test is subdivided into circular, linear, and cornering motion subtasks for each individual identification and calibration purposes. The effect of the CLCM test has been verified by both simulation and experiment via an 8-shape navigation path consisting of all linear, circular, and cornering motions. After the CLCM test, the motor control unit (MCU) was coded with the calibrated transfer function of the tripod EV. As a result, the shift of the rotation center with a radius of 1200 mm during circular motion has been reduced to 50 mm. The deviation of the linear motion test has been confined to 20 mm/10 m at a constant speed. The tripod EV is able to perform a 90° cornering motion with a maximum error θ within 10°. The experimental results show that the CLCM test is applicable to identify the error sources of the tripod EV and estimate the wheel slip angle as well as the backlash.
Ismail, HasanChiang, Chien-HsunChieng, Wei-Hua
Although industrial factories and processing plants have long been automated, it remains vital for human decision-making to be involved in operations, sometimes to a great extent. Automation in and of itself is very effective, but it can deliver the best performance, efficiency, and quality when it is coordinated to inform operators so they can make decisions, and even impact the logical control.
This SAE Information Report is intended to provide design guidance in the selection of steel tubing and related tube fittings for general hydraulic system applications. The information presented herein is based on tubing products which conform to SAE and ISO standards listed in the reference section. All pressure rating data found in the charts included in this document are calculated per the formula found in ISO 10763 and the main body of this document.
Metallic Tubing Committee
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