Accepted Manuscripts

Dengji Zhou, Tingting Wei, Huisheng Zhang, Shixi Ma and Fang Wei
ASME J. Risk Uncertainty Part B   doi: 10.1115/1.4037328
An abnormal operating effect can be caused by different faults, and a fault can cause different abnormal effects. An information fusion model, with hybrid-type fusion frame, is built in this paper, so as to solve this problem. This model consists of data layer, feature layer and decision layer, based on an improved D-S evidence algorithm. After the data preprocessing based on event reasoning in data layer and feature layer, the information will be fused based on the new algorithm in decision layer. Application of this information fusion model in fault diagnosis is beneficial in two aspects, diagnostic applicability and diagnostic accuracy. Additionally, this model can overcome the uncertainty of information and equipment to increase diagnostic accuracy. Two case studies are implemented by this information fusion model to evaluate it. In the first case, fault probabilities calculated by different methods are adopted as inputs to diagnose a fault, which is quite different to be detected based on the information from a single analytical system. The second case is about sensor fault diagnosis. Fault signals are planted into the measured parameters for the diagnostic system, to test the ability to consider the uncertainty of measured parameters. The case study result shows that the model can identify the fault more effectively and accurately. Meanwhile, it has good expansibility, which may be used in more fields.
TOPICS: Sensors, Algorithms, Fault diagnosis, Probability, Signals, Uncertainty, Risk
Hossein Salimi, Saeed Kiad and Mohammad Pourgol-Mohammad
ASME J. Risk Uncertainty Part B   doi: 10.1115/1.4037219
In this study, stochastic analysis is aimed for space structures (satellite in LEO, made of aluminum 2024-T3), with the focus on fatigue failure. Primarily, the deterministic fatigue simulation is conducted using Walker and Forman models with constant amplitude loading. Deterministic crack growth was numerically simulated by the authors developed algorithm and is compared with commercial software for accuracy verification as well as validation with the experimental data. For the stochastic fatigue analysis of this study, uncertainty is estimated by using the Monte Carlo simulation. It is observed that by increasing the crack length, the standard deviation (the measure of uncertainty) increases. Also, it is noted that the reduction in stress ratio has the similar effect. Then stochastic crack growth model, proposed by Yang and Manning, is employed for the reliability analysis. This model converts the existing deterministic fatigue models to stochastic one by adding a random coefficient. Applicability of this stochastic model completely depends on accuracy of base deterministic function. In this study, existing deterministic functions (power and second polynomial) are reviewed and three new function I) fractional, II) global and III) exponential are proposed. It is shown that the proposed functions are potentially used in the Yang and Manning model for better results.
TOPICS: Fatigue, Aluminum, Reliability, Simulation, Stress, Event history analysis, Space frame structures, Fracture (Materials), Algorithms, Computer software, Fatigue analysis, Fatigue cracks, Polynomials, Satellites, Fatigue failure, Uncertainty, Risk
Javad Sovizi, Rahul Rai and Venkat Krovi
ASME J. Risk Uncertainty Part B   doi: 10.1115/1.4037122
Loosely-interconnected cooperative systems such as cable robots are particularly susceptible to uncertainty. Such uncertainty is exacerbated by addition of the base mobility to realize reconfigurability within the system. However, it also sets the ground for predictive base reconfiguration in order to reduce the uncertainty level in system response. To this end, in this paper we systematically quantify the output wrench uncertainty based on which a base reconfiguration scheme is proposed to reduce the uncertainty level for a given task (uncertainty manipulation). Variations in tension and orientation of the cables are considered as the primary sources of the uncertainty responsible for non-deterministic wrench output on the platform. For non-optimal designs/configurations, this may require complex control structures or lead to system instability. The force vector corresponding to each agent (e.g., pulley and cable) is modeled as random vector whose magnitude and orientation are modeled as random variables with Gaussian and von Mises distributions, respectively. In a probabilistic framework, we develop the closed-form expressions of the mean and variances of the output force and moment given the current state (tension and orientation of the cables) of the system. This is intended to enable the designer to efficiently characterize an optimal configuration (location) of the bases in order to reduce the overall wrench fluctuations for a specific task. Numerical simulations as well as real experiments with multiple iRobots are performed to demonstrate the effectiveness of the proposed approach.
TOPICS: Computer simulation, Robots, Cables, Fluctuations (Physics), Pulleys, Tension, Uncertainty, Mechanical admittance, Risk, Uncertainty quantification
Kasmet T. Niyongabo and Scott B. Nokleby
ASME J. Risk Uncertainty Part B   doi: 10.1115/1.4032634
A proof-of-concept detector prototype capable of collecting and storing radiometric data in the Jet Boring System (JBS) during pilot hole drilling at the Cigar Lake uranium mine is presented. Cigar Lake is the world’s second highest known grade uranium mine and is located in northern Saskatchewan, Canada. Variant design is used to design, develop, test and implement the detector’s firmware, software and hardware. The battery powered detector is attached inside a JBS drill rod to collect radiometric data through the drilling cycle. A readout box is used to initiate the detector, recharge the battery and download radiometric data afterthe pilot hole drilling cycle is complete.Functional testing results are presented and comparative test results between the JBS gamma probe and the AlphaNUCLEAR Hi-Flux probe are evaluated. Field data collected from a pilot hole is plotted against the pilot hole’s driving layout and jetting recipe to show the accuracy of the readings collected.

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