151 research outputs found

    Deep Learning for Pipeline Damage Detection: an Overview of the Concepts and a Survey of the State-of-the-Art

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    Pipelines have been extensively implemented to transfer oil as well as gas products at wide distances as they are safe, and suitable. However, numerous sorts of damages may happen to the pipeline, for instance erosion, cracks, and dent. Hence, if these faults are not properly refit will result in the pipeline demolitions having leak or segregation which leads to tremendously environment risks. Deep learning methods aid operators to recognize the earliest phases of threats to the pipeline, supplying them time and information in order to handle the problem efficiently. This paper illustrates fundamental implications of deep learning comprising convolutional neural networks. Furthermore the usages of deep learning approaches for hampering pipeline detriment through the earliest diagnosis of threats are introduced

    Virtual Delay Unit Based Digital nk ± m-order Harmonic Repetitive Controller for PWM Converter

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    Repetitive control (RC) scheme presents an attractive solution to achieve excellent steady-state tracking error and low total harmonic distortion (THD) for periodic signals. RC can produce extremely large gains at fundamental and each harmonic frequency of reference signal to achieve all harmonics suppression. However, a DC-AC inverter always has uneven THD distribution, e.g. THD concentrates at 4fc ± 1 orders for signal-phase inverter, and 6k ± 1 orders for three-phase inverter. Furthermore, a digital RC requires a integral ratio of the sampling frequency and the reference frequency, whereas the digital control system cannot always meet this requirement. For example, (e.g. 60 Hz reference signal with a 5 kHz sampling frequency, or grid-connected converter under grid frequency fluctuation, etc.). In this paper, virtual delay unit (VDU) based digital nk ± m-order harmonic RC is presented to solve the problems above. The VDU produces a different virtual RC sampling frequency from the system sampling frequency. The virtual sampling frequency for digital RC can be flexibly adjusted based on the integral ratio requirement. The advantage of VDU is that it does not vary the system sampling frequency and it is easy to be realized. Furthermore, nk ± m-order harmonic repetitive controller is selected to provide a selective harmonic compensation (SHC). Experimental results of VDU based nk±m-order harmonic RC for 60 Hz single-phase DC/AC inverter with 5 kHz system sampling frequency are provided to show the effectiveness of the proposed VDU-based SHC

    Destructive Attacks Detection and Response System for Physical Devices in Cyber-Physical Systems

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    Nowadays, physical health of equipment controlled by Cyber-Physical Systems (CPS) is a significant concern. This paper reports a work, in which, a hardware is placed between Programmable Logic Controller (PLC) and the actuator as a solution. The proposed hardware operates in two conditions, i.e. passive and active. Operation of the proposed solution is based on the repetitive operational profile of the actuators. The normal operational profile of the actuator is fed to the protective hardware and is considered as the normal operating condition. In the normal operating condition, the middleware operates in its passive mode and simply monitors electronic signals passing between PLC and Actuator. In case of any malicious operation, the proposed hardware operates in its active mode and both slowly stops the actuator and sends an alert to SCADA server initiating execution of the actuator’s emergency profile. Thus, the proposed hardware gains control over the actuator and prevents any physical damage on the operating devices. Two sample experiments are reported in which, results of implementing the proposed solution are reported and assessed. Results show that once the PLC sends incorrect data to actuator, the proposed hardware detects it as an anomaly. Therefore, it does not allow the PLC to send incorrect and unauthorized data pattern to its actuator. Significance of the paper is in introducing a solution to prevent destruction of physical devices apart from source or purpose of the encountered anomaly and apart from CPS functionality or PLC model and operation

    SoC estimation for lithium-ion batteries : review and future challenges

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    ABSTRACT: Energy storage emerged as a top concern for the modern cities, and the choice of the lithium-ion chemistry battery technology as an effective solution for storage applications proved to be a highly efficient option. State of charge (SoC) represents the available battery capacity and is one of the most important states that need to be monitored to optimize the performance and extend the lifetime of batteries. This review summarizes the methods for SoC estimation for lithium-ion batteries (LiBs). The SoC estimation methods are presented focusing on the description of the techniques and the elaboration of their weaknesses for the use in on-line battery management systems (BMS) applications. SoC estimation is a challenging task hindered by considerable changes in battery characteristics over its lifetime due to aging and to the distinct nonlinear behavior. This has led scholars to propose different methods that clearly raised the challenge of establishing a relationship between the accuracy and robustness of the methods, and their low complexity to be implemented. This paper publishes an exhaustive review of the works presented during the last five years, where the tendency of the estimation techniques has been oriented toward a mixture of probabilistic techniques and some artificial intelligence

    Virtual Inertia: Current Trends and Future Directions

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    The modern power system is progressing from a synchronous machine-based system towards an inverter-dominated system, with large-scale penetration of renewable energy sources (RESs) like wind and photovoltaics. RES units today represent a major share of the generation, and the traditional approach of integrating them as grid following units can lead to frequency instability. Many researchers have pointed towards using inverters with virtual inertia control algorithms so that they appear as synchronous generators to the grid, maintaining and enhancing system stability. This paper presents a literature review of the current state-of-the-art of virtual inertia implementation techniques, and explores potential research directions and challenges. The major virtual inertia topologies are compared and classified. Through literature review and simulations of some selected topologies it has been shown that similar inertial response can be achieved by relating the parameters of these topologies through time constants and inertia constants, although the exact frequency dynamics may vary slightly. The suitability of a topology depends on system control architecture and desired level of detail in replication of the dynamics of synchronous generators. A discussion on the challenges and research directions points out several research needs, especially for systems level integration of virtual inertia systems

    Neighboring-Pixel-Based Maximum Power Point Tracking Algorithm for Partially Shaded Photovoltaic (PV) Systems

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    In this paper, a neighboring-pixel-based virtual imaging (NPBVI) technique is developed to comprehensively detect the shading conditions on PV arrays. The proposed VI technique is then merged with a probabilistic mechanism of shaded module currents. Finally, a mathematical model is presented, which predicts the current voltage (I-V) region corresponding to the global maximum (GM) of the shaded PV array. The effectiveness of the proposed NPBVI MPPT is validated through numerous experiments that were carried out using a hardware prototype with a 150 W power rating. For the experiments, a PV array consisting of 3 Ă— 2 (NpĂ— Ns ) 20 W PV modules was utilized. The experiments showcase agreement that the proposed method successfully identified the GM region of a partially shaded PV array

    An Estimator for the Kinematic Behaviour of a Mobile Robot Subject to Large Lateral Slip

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    In this paper, the effects of wheel slip compensation in trajectory planning for mobile tractor-trailer robot applications are investigated. Firstly, a kinematic model of the proposed robot architecture is marked out, then an experimental campaign is done to identify if it is possible to kinematically compensate trajectories that otherwise would be subject to large lateral slip. Due to the close connection to the experimental data, the results shown are valid only for Epi.q, the prototype that is the main object of this manuscript. Nonetheless, the base concept can be usefully applied to any mobile robot subject to large lateral slip

    Influence of Battery Parametric Uncertainties on the State-of-Charge Estimation of Lithium Titanate Oxide-Based Batteries

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    State of charge (SOC) is one of the most important parameters in battery management systems, as it indicates the available battery capacity at every moment. There are numerous battery model-based methods used for SOC estimation, the accuracy of which depends on the accuracy of the model considered to describe the battery dynamics. The SOC estimation method proposed in this paper is based on an Extended Kalman Filter (EKF) and nonlinear battery model which was parameterized using extended laboratory tests performed on several 13 Ah lithium titanate oxide (LTO)-based lithium-ion batteries. The developed SOC estimation algorithm was successfully verified for a step discharge profile at five different temperatures and considering various initial SOC initialization values, showing a maximum SOC estimation error of 1.16% and a maximum voltage estimation error of 44 mV. Furthermore, by carrying out a sensitivity analysis it was showed that the SOC and voltage estimation error are only slightly dependent on the variation of the battery model parameters with the SOC

    Semi-Analytical Approach Towards Design and Optimization of Induction Machines for Electric Vehicles

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    Electric machine design is a comprehensive task depending on the several factors, such as material resource limitations and economic factors. Therefore, an induction machine is a promising candidate because of the absence of magnetic material in the rotor. However, the conventional design approach can neither reflect the advances of the induction machine(IM) design nor exploit the trade-offs between design factors and the multi-physics nature of the electrical machine. Therefore, proposing fast and accurate novel methods to design, develop and analyze IMs using electromagnetic field oriented approaches is competitive to the old-fashion numerical methods. To achieve improved IM design from a baseline design to an optimal design, this dissertation: (1) Investigates the challenges of the high speed IM design specified for the electric vehicle application at the rated operating condition considering electromagnetic boundaries for the reasonable saturation level within a compact volume; (2) Proposes a new design approach of IM using modified equivalent circuit parameters to reduce spatial harmonics because of slotting effect and skewing effect; and also presents the importance of the 3-D analysis over 2-D analysis while developing the IM; (3) Proposes a novel electromagnetic field oriented mathematical model considering the slotting effect and axial flux variation because of skewing rotor bars to evaluate the IM performance with a lower and precise computational effort; (4) developed baseline IM is optimized with genetic algorithm incorporated in proposed subdomain model to improve the torque-speed profile. In order to further simplify the optimization procedure, a parametric and sensitivity based design approach is implemented to reduce the design variables. To evaluate the proposed optimal IM with extended constant power region and high torque density within a compact volume using novel 3-D subdomain model, the machine has been prototyped and tested from low to high speed under no-load and loaded condition. Electrical circuit parameter variation is demonstrated and compared to the one simulated in the FEA environment. This innovation can be applied to a family of electric machines with various topologies
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