A Low Cost Flexible Power Line Communication System

Pantoli, Leonardo; Muttillo, Mirco; Stornelli, Vincenzo; Ferri, Giuseppe; Gabriele, Tullio

doi:10.1007/978-3-319-55077-0_52

Cited by 11 publications

(6 citation statements)

References 33 publications

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“…The purpose of monitoring is to know the behavior of a building in a timely manner and from different points of view. For this reason, energy monitoring systems [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ] are often used combined with environmental monitoring systems and sensors [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 ]. This combination allows the building to remain in optimal conditions in terms of consumption and durability over time and for its increasing connection to the Internet of Thing (IoT) world.…”

Section: Introductionmentioning

confidence: 99%

Structural Health Monitoring: An IoT Sensor System for Structural Damage Indicator Evaluation

Muttillo

Stornelli

Alaggio

et al. 2020

Sensors

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In the last decades, the applications of structural monitoring are moving toward the field of civil engineering and infrastructures. Nevertheless, if the structures have damages, it does not mean that they have a complete loss of functionality, but rather that the system is no longer in an optimal condition so that, if the damage increases, the structure can collapse. Structural Health Monitoring (SHM), a process for the identification of damage, periodically collects data from suitable sensors that allow to characterize the damage and establishes the health status of the structure. Therefore, this monitoring will provide information on the structure condition, mostly about its integrity, in a short time, and, for infrastructures and civil structures, it is necessary to assess performance and health status. The aim of this work is to design an Internet of Things (IoT) system for Structural Health Monitoring to find possible damages and to see how the structure behaves over time. For this purpose, a customized datalogger and nodes have been designed. The datalogger is able to acquire the data coming from the nodes through RS485 communication and synchronize acquisitions. Furthermore, it has an internal memory to allow for the post-processing of the collected data. The nodes are composed of a digital triaxial accelerometer, a general-purpose microcontroller, and an external memory for storage measures. The microcontroller communicates with an accelerometer, acquires values, and then saves them in the memory. The system has been characterized and the damage indicator has been evaluated on a testing structure. Experimental results show that the estimated damage indicator increases when the structure is perturbed. In the present work, the damage indicator increased by a maximum value of 24.65 when the structure is perturbed by a 2.5 mm engraving.

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Section: Introductionmentioning

confidence: 99%

Structural Health Monitoring: An IoT Sensor System for Structural Damage Indicator Evaluation

Muttillo

Stornelli

Alaggio

et al. 2020

Sensors

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“…In recent years, the great use of low-power autonomous systems and sensors [1][2][3][4][5][6] increased the need for self-sustainable devices, which are capable of harvesting and using energy from the environment, particularly for those that need a continuous power supply (such as human health monitoring systems) [7][8][9][10][11][12][13]. These devices, such as low-voltage front-ends for photomultiplier [4] or monitoring systems for buildings with a low power consumption [6], can use energy scavenged from the environment, which is typically poor but enough to ensure the system functionality.…”

Section: Introductionmentioning

confidence: 99%

Rectifiers’ Design and Optimization for a Dual-Channel RF Energy Harvester

Colaiuda

Ulisse

Ferri

2020

JLPEA

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This paper presents the design and implementation of two front-ends for RF (Radio Frequency) energy harvesting, comparing them with the commercial one—P2110 by Powercast Co. (Pittsburgh, PA, USA) Both devices are implemented on a discrete element board with microstrip lines combined with lumped elements and are optimized for two different input power levels (−10 dBm and 10 dBm, respectively), at the GSM900 frequencies. The load has been fixed at 5kΩ, after a load-pull analysis on systems. The rectifiers stages implement two different Schottky diodes in two different topologies: a single diode and a 2-stage Dickson’s charge pump. The second one is compared with the P2110 by generating RF fields at 915 MHz with the Powercast Powerspot. The main aim of this work is to design simple and efficient low-cost devices, which can be used as a power supply for low-power autonomous sensors, with better performances than the current solutions of state-of-the-art equipment, providing an acceptable voltage level on the load. Measurements have been conducted for input power range −20 dBm up to 10 dBm; the best power conversion efficiency (PCE) is obtained with the second design, which reaches a value of 70% at 915 MHz. In particular, the proposed device exhibited better performance compared to the P2110 commercial device, allowing a maximum distance of operation of up to 22 meters from the dedicated RF power source, making it suitable even for IoT (Internet of Things) applications.

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“…These models allow to compare the standard I-V characteristics with the operative one. Despite the ease of approach, such comparison is quite complex: PV modelling requires the knowledge of specific circuit variables and environmental parameters normally supplied by acquisition systems [7][8][9][10][11][12][13]. Therefore, attention must be paid to the estimation of the elements involved in the model itself, in terms of components and variables, usually referred to as "model parameters", like photocurrent, saturation current, diode ideality factor, and shunt and series resistances.…”

Section: Introductionmentioning

confidence: 99%

On Field Infrared Thermography Sensing for PV System Efficiency Assessment: Results and Comparison with Electrical Models

Muttillo

Nardi

Stornelli

et al. 2020

Sensors

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The evaluation of photovoltaic (PV) system’s efficiency loss, due to the onset of faults that reduce the output power, is crucial. The challenge is to speed up the evaluation of electric efficiency by coupling the electric characterization of panels with information gathered from module diagnosis, amongst which the most commonly employed technique is thermographic inspection. The aim of this work is to correlate panels’ thermal images with their efficiency: a “thermal signature” of panels can be of help in identifying the fault typology and, moreover, for assessing efficiency loss. This allows to identify electrical power output losses without interrupting the PV system operation thanks to an advanced PV thermography characterization. In this paper, 12 faulted working panels were investigated. Their electrical models were implemented in MATLAB environment and developed to retrieve the ideal I-V characteristic (from ratings), the actual (operative) I-V characteristics and electric efficiency. Given the curves shape and relative difference, based on three reference points (namely, open circuit, short circuit, and maximum power points), faults’ typology has been evidenced. Information gathered from infrared thermography imaging, simultaneously carried out on panels during operation, were matched with those from electrical characterization. Panels’ “thermal signature” has been coupled with the “electrical signature”, to obtain an overall depiction of panels’ health status.

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A Low Cost Flexible Power Line Communication System

Cited by 11 publications

References 33 publications

Structural Health Monitoring: An IoT Sensor System for Structural Damage Indicator Evaluation

Structural Health Monitoring: An IoT Sensor System for Structural Damage Indicator Evaluation

Rectifiers’ Design and Optimization for a Dual-Channel RF Energy Harvester

On Field Infrared Thermography Sensing for PV System Efficiency Assessment: Results and Comparison with Electrical Models

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