87,068 research outputs found
Discussion of "A new criterion for the quantification of broken rotor bars in induction motors"
No full textThe paper proposes an improvement on the motor current signature analysis diagnostic procedure for induction machines broken rotor bars detection. The procedure, referred to as the “Filippetti criterion” in the paper, is based on the sum of the sidebands amplitude [1]
Guest editorial, ADVANCES IN ELECTRIC MACHINE MONITORING AND DIAGNOSIS - Part II
No full textADVANCES IN ELECTRIC MACHINE MONITORING AND DIAGNOSI
Neural networks aided on-line diagnostics of induction motor rotor faults
No full textAn improvement of induction machine rotor fault diagnosis based on a neural network approach is presented. A neural network can substitute in a more effective way the faulted machine models used to formalize the knowledge base of the diagnostic system when inputs and outputs are suitably chosen. Training the neural network by data achieved through experimental tests on healthy machines and through simulation in case of faulted machines, the diagnostic system can discern between 'healthy' and 'faulty' machines. This procedure substitutes the statement of a trigger threshold, required by the diagnostic procedure based on the machine models
Guest Editorial: "SPECIAL SECTION ON ADVANCES IN ELECTRICAL MACHINE MONITORING AND DIAGNOSIS"
No full textELECTRICAL machines are critical components of many industrial processes. Safety, reliability, efficiency, and per- formance are some of the major concerns. With issues such as aging, high reliability requirements, and cost competitiveness, the issues of electrical machines’ fault detection and diagnosis are of increasing importance
Diagnosis of Induction Machines Rotor Faults in Time-Varying Conditions
No full textMotor current signature analysis is the reference method for the diagnosis of induction machines’ rotor faults; however, in time-varying conditions, it fails as slip and speed vary, and, thus, sideband components are spread in a bandwidth that is proportional to the variation. Variable speed drive applications are common in the aerospace, appliance, railway, and automotive industries and also in electric generators for wind turbines. In this paper, a simple and effective method is presented that allows the diagnosis of rotor faults for induction machine drives in time- varying conditions. It is tailored to direct rotor flux field- oriented controlled drives, where the control system provides suitable signals that are exploited for the demodulation to a con- stant frequency of time-varying signatures related to the rotor faults. Simulations and experiments are reported to validate the proposed method on a critical speed transient
Diagnosis of induction machines in time-varying conditions
No full textA method is here presented that allows the diagnosis of broken rotor bars in time varying operations with simple post processing of input currents. Extensive simulations are presented to validate the proposed approach for open loop and closed loop induction machines. A diagnostic index is presented also, that is quite robust versus load and inertia variations
LabVIEW based virtual instrument for on-line induction motor parameters identification
No full textAn automatic procedure to identify on-line the induction machine parameters of the steady-state equivalent circuit is presented. The procedure starts with the acquisition of input current and voltage instantaneous values and their process to obtain the following dataset of variables: current and voltage first harmonic values, their displacement and the slip value. The slip value is obtained through the current spectrum lines due to the rotor slotting. This first step is automatically iterated if the operating condition changes, to obtain more sets of variables. Different methods identify the parameters of the equivalent circuit, starting from the available sets of variables. All the process, configured as a virtual instrument, is implemented in LabVIEW environment and can be included in a diagnostic system to detect machine healthy conditions, in order to expand system capabilities
AI techniques in induction machines diagnosis including the speed ripple effect
No full textVarious applications of AI techniques (expert systems, neural networks and fuzzy logic) presented in the literature prove that such technologies are well suited to cope with on-line diagnostics tasks for induction machines. The features of these techniques and the improvements that they introduce in the diagnostic process are recalled, showing that, in order to obtain indication on the fault extent, faulty machine models are still essential. The models must trade off between simulation result effectiveness and simplicity. With reference to rotor electrical faults of induction machines, a new and simple model which includes the speed ripple effect is developed. This model leads to a new diagnostic index, independent of the machine operating condition and inertia value, that allows the implementation of the diagnostic system with a minimum configuration intelligence
Broken bar detection in induction machines: comparison between current spectrum approach and parameter estimation approach
No full textThe diagnosis of induction machine rotor electrical faults is studied by comparing the (a) current spectrum analysis and the (b) apparent rotor resistance estimation. The first approach is used to develop several procedures based on fault models of the machine. The experience gained in the development of such procedures is used to approach the estimation method from a theoretical point of view. Using a simplified model of faulted machine, a relationship that correlates the apparent resistance variation with the number of broken bars is obtained. By this relationship it is possible to have indication on the sensitivity of the parameter estimation approach. The superiority of the current spectrum approach over the parameter estimation approach is shown
Riflessioni sulle pratiche di costruzione del database Atlante delle Case d’Autore
No full textQuesto contributo vuole essere una riflessione sulla costruzione del
database Atlante delle Case d’Autore e su come competenze tecniche e conoscenza
del dominio d’indagine abbiano interagito. Molto spesso, come si
vedrà, queste interazioni hanno preso la forma di operazioni minime, ma
che comunque hanno costretto a compiere valutazioni, scelte e correzioni
di natura più sostanziale. I paragrafi del testo avranno lo stesso titolo
delle fasi di lavoro sul database: pianificazione, raccolta dati, elaborazione
e pulizia dei dati, analisi dei dati, raccolta dati sulle case (arricchimento),
pubblicazione
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