Low-cost, high-resolution, fault-robust position and speed estimation for PMSM drives operating in safety-critical systems

In this paper it is shown how to obtain a low-cost, high-resolution and fault-robust position sensing system for permanent magnet synchronous motor drives operating in safety-critical systems, by combining high-frequency signal injection with binary Hall-effect sensors. It is shown that the position error signal obtained via high-frequency signal injection can be merged easily into the quantization-harmonic-decoupling vector tracking observer used to process the Hall-effect sensor signals. The resulting algorithm provides accurate, high-resolution estimates of speed and position throughout the entire speed range; compared to state-of-the-art drives using Hall-effect sensors alone, the low speed performance is greatly improved in healthy conditions and also following position sensor faults. It is envisaged that such a sensing system can be successfully used in applications requiring IEC 61508 SIL 3 or ISO 26262 ASIL D compliance, due to its extremely high mean time to failure and to the very fast recovery of the drive following Hall-effect sensor faults at low speeds. Extensive simulation and experimental results are provided on a 3.7 kW permanent magnet drive

Exploring the Role of Interdisciplinarity in Physics: Success, Talent and Luck

Although interdisciplinarity is often touted as a necessity for modern research, the evidence on the relative impact of sectorial versus to interdisciplinary science is qualitative at best. In this paper we leverage the bibliographic data set of the American Physical Society to quantify the role of interdisciplinarity in physics, and that of talent and luck in achieving success in scientific careers. We analyze a period of 30 years (1980-2009) tagging papers and their authors by means of the Physics and Astronomy Classification Scheme (PACS), to show that some degree of interdisciplinarity is quite helpful to reach success, measured as a proxy of either the number of articles or the citations score. We also propose an agent-based model of the publication-reputation-citation dynamics reproduces the trends observed in the APS data set. On the one hand, the results highlight the crucial role of randomness and serendipity in real scientific research; on the other, they shed light on a counter-intuitive effect indicating that the most talented authors are not necessarily the most successful ones.Comment: 21 pages, 19 figure

Effect of the ingestion in the WRF model of different Sentinel-derived and GNSS-derived products: analysis of the forecasts of a high impact weather event

This paper presents the first experimental results of a study on the ingestion in the Weather Research and Forecasting (WRF) model, of Sentinel satellites and Global Navigation Satellite Systems (GNSS) derived products. The experiments concern a flash-floodevent occurred in Tuscany (Central Italy) in September 2017. The rationale is that numerical weather prediction (NWP) models are presently able to produce forecasts with a km scale spatial resolution, but the poor knowledge of the initial state of the atmosphere may imply an inaccurate simulation of the weather phenomena. Hence, to fully exploit the advances in numerical weather modelling, it is necessary to feed them with high spatiotemporal resolution information over the surface boundary and the atmospheric column. In this context, the Copernicus Sentinel satellites represent an important source of data, because they can provide a set of high-resolution observations of physical variables (e.g. soil moisture, land/sea surface temperature, wind speed) used in NWP models runs. The possible availability of a spatially dense network of GNSS stations is also exploited to assimilate water vapour content. Results show that the assimilation of Sentinel-1 derived wind field and GNSS-derivedwater vapour data produce the most positive effects on the performance of the forecast

Combined Effects of Dewatering, Composting and Pelleting to Valorize and Delocalize Livestock Manure, Improving Agricultural Sustainability

An agronomic strategy to mitigate climate change impact can be the build-up of soil organic carbon. Among agronomic management approaches, the administration of organic fertilizers like livestock manure represents an eective strategy to increase soil organic carbon. However, livestock manure usually contains a high amount of water, reducing its sustainable delocalization and impacting on greenhouse gas emissions and nutrient leaching. Furthermore, the possible presence of weed seeds and harmful microorganisms could reduce the agronomic value of the manure. To overcome these issues, the combined eects of dewatering, composting and pelleting were investigated on livestock manure to produce sustainable organic fertilizers. Our results showed that composting and pelleting can represent a feasible and sustainable solution to reduce the potential risks related to the presence of weed seeds and harmful bacteria, concentrating nutrients and allowing a sustainable valorization and delocalization of the livestock manure. In addition, the processed manures were assessed as fertilizers in the growing medium (GM), displaying an increase in water retention and nutrient availability and a decrease of GM temperature and weed seed emergences. However, further study is needed to validate, both in open field and greenhouse productions, the eects of the proposed fertilizers in real cropping systems

!CHAOS: A cloud of controls

The paper is aimed to present the !CHAOS open source project aimed to develop a prototype of a national private Cloud Computing infrastructure, devoted to accelerator control systems and large experiments of High Energy Physics (HEP). The !CHAOS project has been financed by MIUR (Italian Ministry of Research and Education) and aims to develop a new concept of control system and data acquisition framework by providing, with a high level of abstraction, all the services needed for controlling and managing a large scientific, or non-scientific, infrastructure. A beta version of the !CHAOS infrastructure will be released at the end of December 2015 and will run on private Cloud infrastructures based on OpenStack

2016 IEEE IAS Industrial Drives Committee Third Prize Paper Award

This paper investigates Hall-effect sensor faults in brushless dc drives and proposes a very effective methodology for their detection, identification and compensation. It is shown that these faults cause erroneous commutation, generally leading to unstable operation. By using a fault detection and identification technique proposed by the authors in a previous paper related to low cost field-oriented drives, together with appropriate fault-compensated position and speed estimation algorithms, it is shown for the first time that proper operation is guaranteed for both single and double faults. Comparative experimental results are provided for operation with three state of the art, Hall-effect sensor based, estimation algorithms: the zeroth order algorithm, the hybrid observer, and the vector-tracking observer. It is verified that stable operation is achieved with three, two or only a single Hall-effect sensor functioning correctly

Hall-effect sensor fault detection, identification and compensation in brushless DC drives

This paper investigates Hall-effect sensor faults in brushless dc drives and proposes a very effective methodology for their detection, identification and compensation. It is shown that these faults cause erroneous commutation, generally leading to unstable operation. By using a fault detection and identification technique proposed by the authors in a previous paper related to low cost field-oriented drives, [22], together with appropriate fault-compensated position and speed estimation algorithms, it is shown for the first time that proper operation is guaranteed for both single and double faults. Comparative experimental results are provided for operation with three state of the art, Hall-effect sensor based, estimation algorithms: the zeroth order algorithm, [19], the hybrid observer, [20], and the vector-tracking observer, [21]. It is verified that stable operation is achieved with three, two or only a single Hall-effect sensor functioning correctly

Hall-Effect Sensor Fault Detection, Identification, and Compensation in Brushless DC Drives

In this paper, binary Hall-effect sensor faults are investigated in rectangular-current-fed brushless DC drives and a very effective methodology for their detection, identification and compensation is explored. It is shown that these faults cause erroneous commutation, generally leading to unstable operation. By using a fault detection and identification technique proposed by the authors in a recent paper on low cost field-oriented drives, it is possible to pinpoint the faulty sensors. In this paper it is demonstrated that the destabilizing effect of these faults on motion state estimation can be compensated for in any position and speed estimation algorithm, as long as it is properly readapted. To this end, it is shown how to incorporate such faultcompensation in three state-of-the-art estimation algorithms: the zeroth order algorithm, the hybrid observer, and the vectortracking observer. Comparative experimental tests are performed and it is verified that stable operation is achieved with three, two or only a single Hall-effect sensor functioning correctly. These results show that the classical BLDC drive with three Hall-effect sensors has an inherent double redundancy to position-sensor faults. With the proposed method, this property can be exploited in systems that require very high reliability, such as in aerospace and automotive applications. Redundancy can be increased, by using more than three Hall-effect sensors; reduced by using two sensors; or eliminated by using a single sensor, in ultra low-cost applications where redundancy is not a requirement

Signal-injection-aided position and speed estimation for PMSM drives with low-resolution position sensors

The aim of this paper is to reduce the low-speed limitation of PMSM drives that use low-resolution position sensors. It is recognized, for the first time, that this may be overcome by merging signal-injection-based self-sensing and low-resolution sensor technologies, if the machine possesses a detectable amount of electromagnetic saliency. The supplementary information coming from the injection of an additional high frequency magnetic field may be used to aid the low-resolution-based position and speed estimation algorithm, significantly improving the low-speed performance of the drive. In this research contribution, the quantization-harmonic decoupling vector-tracking observer is used for speed and position estimation. It is shown how this algorithm can be easily integrated with any high frequency signal injection method. Extensive experimental results are provided demonstrating the significant performance improvements at low speeds for a PMSM drive using 1, 2 and 3 bit-per-pole-pair sensing systems, when signal injection is used to aid position and speed estimation

NUP-98 Rearrangements Led to the Identification of Candidate Biomarkers for Primary Induction Failure in Pediatric Acute Myeloid Leukemia

Conventional chemotherapy for acute myeloid leukemia regimens generally encompass an intensive induction phase, in order to achieve a morphological remission in terms of bone marrow blasts (<5%). The majority of cases are classified as Primary Induction Response (PIR); unfortunately, 15% of children do not achieve remission and are defined Primary Induction Failure (PIF). This study aims to characterize the gene expression profile of PIF in children with Acute Myeloid Leukemia (AML), in order to detect molecular pathways dysfunctions and identify potential biomarkers. Given that NUP98-rearrangements are enriched in PIF-AML patients, we investigated the association of NUP98-driven genes in primary chemoresistance. Therefore, 85 expression arrays, deposited on GEO database, and 358 RNAseq AML samples, from TARGET program, were analyzed for “Differentially Expressed Genes” (DEGs) between NUP98+ and NUP98-, identifying 110 highly confident NUP98/PIF-associated DEGs. We confirmed, by qRT-PCR, the overexpression of nine DEGs, selected on the bases of the diagnostic accuracy, in a local cohort of PIF patients: SPINK2, TMA7, SPCS2, CDCP1, CAPZA1, FGFR1OP2, MAN1A2, NT5C3A and SRP54. In conclusion, the integrated analysis of NUP98 mutational analysis and transcriptome profiles allowed the identification of novel putative biomarkers for the prediction of PIF in AML