Conductive 3D Printed PLA Composites: on the interplay of mechanical, electrical and thermal behaviours

I. Tirado-Garcia, D. Garcia-Gonzalez, S. Garzon-Hernandez, A. Rusinek, G. Robles, J.M. Martinez-Tarifa, A. Arias, Conductive 3D Printed PLA Composites: on the interplay of mechanical, electrical and thermal behaviours, Composite Structures, Volume 265, 2021, 113744, ISSN 0263-8223,

Abstract – Additive manufacturing (AM) techniques represent a real challenge to manufacture novel composites with coupled multifunctional properties. This work focuses on the mechanical, electrical and thermal behaviours of 3D printed polymeric composites of polylactic acid (PLA) filled with carbon black (CB) conductive particles. The incorporation of conductive particles within the polymer matrix allows for programmable conduction paths via the printing process, whose electric properties are intimately coupled to thermo-mechanical processes. In this study, samples were prepared using a fused deposition modelling (FDM) printer, controlling the filament orientation to manufacture three different types: longitudinal (0°); transverse (90°); oblique (±45°) printing orientations. Different types of multifunctional characterisation have been made: (i) electro-thermal tests, evaluating the influence of electrical conductivity on the sample temperature due to Joule’s heating; (ii) thermo-electrical tests, analysing the influence of temperature on the DC resistance of the samples (iii) mechano-electrical tests, analysing the effect of mechanical deformation on the specimens’ electric resistance. The results show a strong dependence of printing direction on the material properties of 3D printed conductive-PLA and identify strong thermo-electro-mechanical interplays. The results of this work will contribute to the AM progress in functional electro-mechanical components with potential applications in biosensing devices, composite sensors, 3D electrodes and soft robotic industry.

Keywords – Additive manufacturing (AM); Conductive Polymer Composites (CPC’s); Fused deposition modelling (FDM); carbon black (CB); polylactic acid (PLA); Multifunctional materials

Uncertainty Sources in the Estimation of the Partial Discharge Inception Voltage in Turn-to-Turn Insulation Systems

M. G. De La Calle, J. M. Martínez-Tarifa, Á. M. Gómez Solanilla and G. Robles, “Uncertainty Sources in the Estimation of the Partial Discharge Inception Voltage in Turn-to-Turn Insulation Systems,” in IEEE Access, vol. 8, pp. 157510-157519, 24 August 2020.
Electronic ISSN: 2169-3536

doi: 10.1109/ACCESS.2020.3018870

Abstract — Partial discharges (PD) are one of the main causes of premature failure in low-voltage motors driven by variable-speed drives. The use of these control systems are being quite extended due to new applications, such as the more electric aircraft (MEA) or hybrid and electric vehicles, and this has pushed research towards appropriate designs of electric motors to avoid, as much as possible, the presence of PD within their windings. This article presents a model to predict the partial discharge inception voltage (PDIV) in the insulation of low-voltage machines. A value for the secondary ionization coefficient based on a statistical study is also proposed. The deviations of the model are also studied by obtaining the uncertainty of the value of that coeficient and the predicted values of the PDIV for a set of wires. This uncertainty will be compared with other error sources such as generator harmonics and humidity. Finally, the tests are done for different temperatures extend the model applicability.

Keywords — Insulation design, inverter-fed machine, partial discharges, Paschen’s law, temperature, Townsend’s coefficients.

Insulation design of low voltage electrical motors fed by PWM inverters

L. Lusuardi, A. Cavallini, M. G. de la Calle, J. M. Martínez-Tarifa and G. Robles, “Insulation design of low voltage electrical motors fed by PWM inverters,” in IEEE Electrical Insulation Magazine, vol. 35, no. 3, pp. 7-15, May-June 2019.

doi: 10.1109/MEI.2019.8689431

Abstract— This paper proposes a model to determine the partial discharge inception voltage of magnet wires, including the effect of elevated temperatures, and shows its applicability to the complete range of wire geometries considered in IEC Standard 60317-13.

For long, the insulation of magnet wires used in low voltage motors was mostly stressed by temperature and vibrations. In addition, moisture sometimes hastened thermo-mechanical stress by hydrolyzing the insulation leading to crack formation. The ultimate breakdown mechanism was an excessive leakage current throughout cracks and pinholes in the insulation. Within this framework, the thickness of the insulation was dictated mostly by mechanical considerations, to prevent crack formation during manufacturing and operation. Electrical stress did not play a key role in the aging process.
Power electronics changed this picture…

Keywords— inverter-fed machine, partial discharges, insulation design.

Multiple Partial Discharge Source Localization in Power Cables Through Power Spectral Separation and Time-Domain Reflectometry

G. Robles, M. Shafiq and J. M. Martínez-Tarifa, “Multiple Partial Discharge Source Localization in Power Cables Through Power Spectral Separation and Time-Domain Reflectometry,” in IEEE Transactions on Instrumentation and Measurement, vol. 68, no. 12, pp. 4703-4711, Dec. 2019, doi: 10.1109/TIM.2019.2896553.

Open access post-print version (ie final draft post-refereeing) available (Copyright 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works).

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Abstract— Insulated power cables are becoming increasingly popular in today’s developing distribution and transportion networks. However, due to aging, deterioration, and various operational and environmental stresses, insulation defects may appear and so the cable needs to be monitored in a timely manner to avoid unexpected failures. Many of these defects are responsible for partial discharge (PD) activity. The localization of the sources of these discharges is a highly decisive facet in the condition-based monitoring of power cables. The techniques for the localization of single-PD defects in insulated power cables are well presented in the current bibliography. However, when several simultaneous PD sources are active, the localization of the sources becomes quite complex. This paper develops an efficient technique for the separation and localization of multiple PD sources in a medium voltage cable. The experimental results are obtained with single-end-based measurements using a high-frequency current transformer in a laboratory environment. The data processing based on the spectral characteristics of the signals is carried out by using the power ratios technique in order to determine the presence of different types of PD. Once the signals are separated, the PD sources can be localized with an individualized analysis of each source through time-domain reflectometry. The proposed methodology can be very valuable to improve the location diagnostic capability of the condition-based monitoring solutions, especially for underground cables.

Keywords— Condition monitoring; partial discharges (PDs); particle swarm optimization (PSO); power cables; signal characterization; signal propagation; spectral power ratios (PRs); time-domain reflectometry (TDR).

Online condition monitoring of MV cable feeders using Rogowski coil sensors for PD measurements

M. Shafiq, K. Kauhaniemi, G. Robles, M. Isa, L. Kumpulainen, “Online condition monitoring of MV cable feeders using Rogowski coil sensors for PD measurements”, Electric Power Systems Research, Volume 167, February 2019, Pages 150-162, ISSN 0378-7796,

Abstract— Condition monitoring is a highly effective prognostic tool for incipient insulation degradation to avoid sudden failures of electrical components and to keep the power network in operation. Improved operational performance of the sensors and effective measurement techniques could enable the development of a robust monitoring system. This paper addresses two main aspects of condition monitoring: an enhanced design of an induction sensor that has the capability of measuring partial discharge (PD) signals emerging simultaneously from medium voltage cables and transformers, and an integrated monitoring system that enables the monitoring of a wider part of the cable feeder. Having described the conventional practices along with the authors’ own experiences and research on non-intrusive solutions, this paper proposes an optimum design of a Rogowski coil that can measure the PD signals from medium voltage cables, its accessories, and the distribution transformers. The proposed PD monitoring scheme is implemented using the directional sensitivity capability of Rogowski coils and a suitable sensor installation scheme that leads to the development of an integrated monitoring model for the components of a MV cable feeder. Furthermore, the paper presents forethought regarding huge amount of PD data from various sensors using a simplified and practical approach. In the perspective of today’s changing grid, the presented idea of integrated monitoring practices provide a concept towards automated condition monitoring.

Keywords—Condition monitoring; Rogowski coil; Dielectric insulation; Partial discharge; Medium voltage cable; Transformer.

Partial Discharge Signal Propagation in Medium Voltage Branched Cable Feeder

M. Shafiq, K. Kauhaniemi, G. Robles, G. A. Hussain and L. Kumpulainen, “Partial discharge signal propagation in medium voltage branched cable feeder,” in IEEE Electrical Insulation Magazine, vol. 34, no. 6, pp. 18-29, November-December 2018.

doi: 10.1109/MEI.2018.8507714

Abstract— Rising global and regional electricity use is accelerating the need to upgrade networks. The adoption of sustainable ways of energy generation (renewables energy resources) is the top priority of today’s grid, and these resources are predominantly embedded within the distribution networks that are mostly connected by medium voltage (MV) cables. Driven by urbanization trends, negative land value impacts, public safety, environmental aesthetics, and network reliability, the resistance to overhead lines in distribution networks is gradually increasing in many countries. Either choosing the proactive path considering the operational superiority of underground cables compared with overhead lines or following the ongoing legislative policies, the use of cables has been increasing rapidly over the past 30 years. This trend is likely to accelerate.

Keywords— Power cables; Partial discharges; Power cable insulation; Cable shielding; Current measurement; Voltage measurement; Medium voltage; Condition monitoring; Cables; Branch; Joint; Diagnostic; Sensor},


Radio-Frequency Localization of Multiple Partial Discharges Sources with Two Receivers

Department of Electrical Engineering, Universidad Carlos III de Madrid, Avda, Universidad, 30, Leganés, 28911 Madrid, Spain
*Author to whom correspondence should be addressed.
Robles, G.; Fresno, J.M.; Martínez-Tarifa, J.M. Radio-Frequency Localization of Multiple Partial Discharges Sources with Two Receivers. Sensors 2018, 18, 1410.
  • 2018 Impact Factor: 3.031
  • 15/61 (Q1) in ‘Instruments & Instrumentation’
  • Journal Impact Factor Percentile: 76.23

This paper is Open Access and can be downloaded here.

Abstract—Spatial localization of emitting sources is especially interesting in different fields of application. The focus of an earthquake, the determination of cracks in solid structures, or the position of bones inside a body are some examples of the use of multilateration techniques applied to acoustic and vibratory signals. Radar, GPS and wireless sensors networks location are based on radiofrequency emissions and the techniques are the same as in the case of acoustic emissions. This paper is focused on the determination of the position of sources of partial discharges in electrical insulation for maintenance based on the condition of the electrical equipment. The use of this phenomenon is a mere example of the capabilities of the proposed method but it is very representative because the emission can be electromagnetic in the VHF and UHF ranges or acoustic. This paper presents a method to locate more than one source in space with only two receivers, one of them in a fixed position and the other describing a circumference around the first one. The signals arriving from the different sources to the antennas are first separated using a classification technique based on their spectral components. Then, the individualized time differences of arrival (TDOA) from the sources collected at different angles describe a function, angle versus TDOA, that has all the geometric information needed to locate the source. The paper will show how to derive these functions for any source analytically with the position of the source as unknown parameters. Then, it will be demonstrated that it is possible to fit the curve with experimental measurements of the TDOA to obtain the parameters of the position of each source. Finally, the technique is extended to the localization of the emitter in three dimensions.

Partial discharge spectral characterization in HF, VHF and UHF bands using particle swarm optimization

1Department of Electrical Engineering, Universidad Carlos III de Madrid, Leganés, 28911 Madrid, Spain
2Department of Electrical Engineering, Universidad Técnica Federico Santa María, 8940000 Santiago de Chile, Chile
3Department of Signal Processing and Communications, Universidad Carlos III de Madrid, Leganés, 28911 Madrid, Spain
*Author to whom correspondence should be addressed.

Robles, G.; Fresno, J.M.; Martínez-Tarifa, J.M.; Ardila-Rey, J.A.; Parrado-Hernández, E. Partial Discharge Spectral Characterization in HF, VHF and UHF Bands Using Particle Swarm Optimization. Sensors 2018, 18, 746.

  • 2018 Impact Factor: 3.031
  • 15/61 (Q1) in ‘Instruments & Instrumentation’
  • Journal Impact Factor Percentile: 76.23

This paper is Open Access and can be downloaded here.

Abstract— The measurement of partial discharge (PD) signals in the radio-frequency (RF) range has gained popularity among utilities and specialized monitoring companies in recent years. Unfortunately, in most of the occasions the data are hidden by noise and coupled interferences that hinder their interpretation and renders them useless especially in acquisition systems in the UHF band where the signals of interest are weak. This paper is focused on a method that uses a selective spectral signal characterization to feature each signal, type of partial discharge or interferences/noise, with the power contained in the most representative frequency bands. The technique can be considered as a dimensionality reduction problem where all the energy information contained in the frequency components is condensed in a reduced number of UHF or HF/VHF bands. In general, dimensionality reduction methods make the interpretation of results a difficult task because the inherent physical nature of the signal is lost in the process. The proposed selective spectral characterization is a preprocessing tool that facilitates further main processing. The starting point is a clustering of signals that could form the core of a partial discharge monitoring system. Therefore, the dimensionality reduction technique should find out the best frequency bands to enhance the affinity between signals in the same cluster and the differences between signals in different clusters. This is done maximizing the minimum Mahalanobis distance between clusters using particle swarm optimization (PSO). The tool is tested with three sets of experimental signals to demonstrate its capabilities in separating noise and partial discharges with low signal-to-noise ratio and separating different types of partial discharges measured in the UHF and HF/VHF bands.

Robust condition assessment of electrical equipment with One Class SVM based on the measurement of partial discharges

1Department of Signal Processing and Communications, Universidad Carlos III de Madrid, Avda. Universidad, 30, Leganés, Madrid 28911, Spain
2Department of Electrical Engineering, Universidad Carlos III de Madrid, Avda. Universidad, 30, Leganés, Madrid 28911, Spain; Emails:
3Department of Electrical Engineering, Federico Santa María Technical University, 8940000 Santiago de Chile, Chile


Parrado-Hernández, E.; Robles, G.; Ardila-Rey, J.A.; Martínez-Tarifa, J.M. Robust Condition Assessment of Electrical Equipment with One Class Support Vector Machines Based on the Measurement of Partial Discharges. Energies 2018, 11, 486.

  • 2018 Impact Factor: 2.707
  • 56/103 (Q3) in ‘Energy & Fuels’
  • Journal Impact Factor Percentile: 46.117

This paper is Open Access and can be downloaded here.

Abstract— This paper presents a system for the detection of partial discharges (PD) in industrial applications based on One Class Support Vector Machines (OCSVM). The study stresses the detection of Partial Discharges (PD) as they represent a major source of information related to degradation in the equipment. PD measurement is a widely extended technique for condition monitoring of electrical machines and power cables to avoid catastrophic failures and the consequent blackouts. One of the most important keystones in the interpretation of partial discharges is their separation from other signals considered as not-PD especially in low SNR measurements. In this sense, the OCSVM is an interesting alternative to binary SVMs since it does not need a training set with examples of all the output classes correctly labelled. On the contrary, the OCSVM learns a model of the signals acquired when the equipment is in PD-free mode, defined as a state where no degradation mechanism is active, so one only needs to make sure that the training signals were recorded under this setting. These default mode signals are easier to characterize and acquire in industrial environments than PD and lead to more robust detectors that practically do not need domain adaptation to perform in scenarios prone to different types of PD. In fact, the experimental results show that the performance of the OCSVM is comparable to that achieved by a binary SVM trained using both noise and PD pulses. Finally, the method is successfully applied to a more realistic scenario involving the detection of PD in a damaged distribution power cable.


Survey on the Performance of Source Localization Algorithms

1 Department of Electrical Engineering, Universidad Carlos III de Madrid, Avda. Universidad, 30, Leganés, 28911 Madrid, Spain
2 Department of Electronic and Electrical Engineering, University of Strathclyde, 204 George Street, Glasgow G1 1XW, UK

Fresno, J.M.; Robles, G.; Martínez-Tarifa, J.M.; Stewart, B.G. Survey on the Performance of Source Localization Algorithms. Sensors 2017, 17(11), 2666.

  • 2017 Impact Factor: 2.475
  • 16/62 (Q2) in ‘Instruments & Instrumentation’
  • Journal Impact Factor Percentile: 74.59

This paper is Open Access and can be downloaded here.

Abstract— The localization of emitters using an array of sensors or antennas is a prevalent issue approached in several applications. There exist different techniques for source localization, which can be classified into multilateration, received signal strength (RSS) and proximity methods. The performance of multilateration techniques relies on measured time variables: the time of flight (ToF) of the emission from the emitter to the sensor, the time differences of arrival (TDoA) of the emission between sensors and the pseudo-time of flight (pToF) of the emission to the sensors. The multilateration algorithms presented and compared in this paper can be classified as iterative and non-iterative methods. Both standard least squares (SLS) and hyperbolic least squares (HLS) are iterative and based on the Newton–Raphson technique to solve the non-linear equation system. The metaheuristic technique particle swarm optimization (PSO) used for source localisation is also studied. This optimization technique estimates the source position as the optimum of an objective function based on HLS and is also iterative in nature. Three non-iterative algorithms, namely the hyperbolic positioning algorithms (HPA), the maximum likelihood estimator (MLE) and Bancroft algorithm, are also presented. A non-iterative combined algorithm, MLE-HLS, based on MLE and HLS, is further proposed in this paper. The performance of all algorithms is analysed and compared in terms of accuracy in the localization of the position of the emitter and in terms of computational time. The analysis is also undertaken with three different sensor layouts since the positions of the sensors affect the localization; several source positions are also evaluated to make the comparison more robust. The analysis is carried out using theoretical time differences, as well as including errors due to the effect of digital sampling of the time variables. It is shown that the most balanced algorithm, yielding better results than the other algorithms in terms of accuracy and short computational time, is the combined MLE-HLS algorithm.