The Level 0 Pixel Trigger System for the ALICE experiment

The ALICE Silicon Pixel Detector contains 1200 readout chips. Fast-OR signals indicate the presence of at least one hit in the 8192 pixel matrix of each chip. The 1200 bits are transmitted every 100 ns on 120 data readout optical links using the G-Link protocol. The Pixel Trigger System extracts and processes them to deliver an input signal to the Level 0 trigger processor targeting a latency of 800 ns. The system is modular and based on FPGA devices. The architecture allows the user to define and implement various trigger algorithms. The system uses advanced 12-channel parallel optical fiber modules operating at 1310 nm as optical receivers. Multi-channel G-Link receivers were realized in programmable hardware and tested. The design of the system and the progress of the ALICE Pixel Trigger project are described in this paper

The pixel Fast-OR signal for the ALICE trigger in p-p collisions

The silicon pixel detector of the ALICE experiment at LHC comprises the two innermost layers of the inner tracking system of the apparatus. It contains 1200 readout chips, each of them corresponding to a 8192 pixel matrix. The single chip outputs a digital Fast-OR signal which is active whenever at least one of the pixels in the matrix records a hit. The 1200 Fast-OR output signals can be used to implement a unique triggering capability: few details on the pixel trigger system and some of the possible applications for p-p collisions are presented

An investigative study into the sensitivity of different partial discharge φ-q-n pattern resolution sizes on statistical neural network pattern classification

This paper investigates the sensitivity of statistical fingerprints to different phase resolution (PR) and amplitude bins (AB) sizes of partial discharge (PD) φ-q-n (phase-amplitude-number) patterns. In particular, this paper compares the capability of the ensemble neural network (ENN) and the single neural network (SNN) in recognizing and distinguishing different resolution sizes of φ-q-n discharge patterns. The training fingerprints for both the SNN and ENN comprise statistical fingerprints from different φ-q-n measurements. The result shows that there exists statistical distinction for different PR and AB sizes on some of the statistical fingerprints. Additionally, the ENN and SNN outputs change depending on training and testing with different PR and AB sizes. Furthermore, the ENN appears to be more sensitive in recognizing and discriminating the resolution changes when compared with the SNN. Finally, the results are assessed for practical implementation in the power industry and benefits to practitioners in the field are highlighted

Death of physical body is not the end of life (medical-philosophic thoughts about human structure)

В статье приведены размышления о современном представлении сложности строения человека исходя из философских концепций об устройстве его внутреннего и внешнего мира, а также основываясь на религиозном объяснении феномена души, ее главенствующей роли над физическим телом и его смертью.In this article thoughts about complex human structure, taking to consideration the philosophic concepts of human inner and outer world’s structure, relying on religious explanation of soul’s existence, about dominating role of soul in comparison with physical body and about death are represented

Fractal-based autonomous partial discharge pattern recognition method for MV motors

On-line partial discharge (PD) monitoring is being increasingly adopted to improve the asset management and maintenance of medium-voltage (MV) motors. This study presents a novel method for autonomous analysis and classification of motor PD patterns in situations where a phase-reference voltage waveform is not available. The main contributions include a polar PD (PPD) pattern and a fractal theory-based autonomous PD recognition method. PPD pattern that is applied to convert the traditional phase-resolved PD pattern into a circular form addresses the lack of phase information in on-line PD monitoring system. The fractal theory is then presented in detail to address the task of discrimination of 6 kinds of single source and 15 kinds of multi-source PD patterns related to motors, as outlined in IEC 60034. The classification of known and unknown defects is calculated by a method known as centre score. Validation of the proposed method is demonstrated using data from laboratory experiments on three typical PD geometries. This study also discusses the application of the proposed techniques with 24 sets of on-site PD measurement data from 4 motors in 2 nuclear power stations. The results show that the proposed method performs effectively in recognising not only the single-source PD but also multi-source PDs

Себестоимость продукции и выявления резервов ее снижения

У даній статті розглядається поняття витрат підприємства, собівартості продукції підприємства та виявлення можливих резервів її зниження.The concept of charges of enterprise, unit of enterprise and exposure of possible backlogs of her decline cost is examined in this article.В данной статье рассматривается понятие расходов предприятия, себестоимости продукции предприятия и выявления возможных резервов ее снижения

The ALICE silicon pixel detector read-out electronics

The ALICE silicon pixel detector (SPD) constitutes the two innermost layers of the ALICE inner tracker system. The SPD contains 10 million pixels segmented in 120 detector modules (half staves), which are connected to the offdetector electronics with bidirectional optical links. Raw data from the on-detector electronics are sent to 20 FPGA-based processor cards (Routers) each carrying three 2-channel linkreceiver daughter-cards. The routers process the data and send them to the ALICE DAQ system via the ALICE detector data link (DDL). The SPD control, configuration and data monitoring is performed via the VME interface of the routers. This paper describes the detector readout and control via the off-detector electronics

Performance of ALICE pixel prototypes in high energy beams

The two innermost layers of the ALICE inner tracking system are instrumented with silicon pixel detectors. Single chip assembly prototypes of the ALICE pixels have been tested in high energy particle beams at the CERN SPS. Detection efficiency and spatial precision have been studied as a function of the threshold and the track incidence angle. The experimental method, data analysis and main results are presented.Comment: 10 pages, 9 figures, contribution to PIX2005 Workshop, Bonn (Germany), 5-8 September 200

Beam Test Performance and Simulation of Prototypes for the ALICE Silicon Pixel Detector

The silicon pixel detector (SPD) of the ALICE experiment in preparation at the Large Hadron Collider (LHC) at CERN is designed to provide the precise vertex reconstruction needed for measuring heavy flavor production in heavy ion collisions at very high energies and high multiplicity. The SPD forms the innermost part of the Inner Tracking System (ITS) which also includes silicon drift and silicon strip detectors. Single assembly prototypes of the ALICE SPD have been tested at the CERN SPS using high energy proton/pion beams in 2002 and 2003. We report on the experimental determination of the spatial precision. We also report on the first combined beam test with prototypes of the other ITS silicon detector technologies at the CERN SPS in November 2004. The issue of SPD simulation is briefly discussed.Comment: 4 pages, 5 figures, prepared for proceedings of 7th International Position Sensitive Detectors Conference, Liverpool, Sept. 200