Signals, Systems, Transforms, and Digital Signal Processing with MATLAB

Corinthios, M.J.

doi:10.1201/9781315218533

Cited by 37 publications

(23 citation statements)

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“…They create an individual signal spectrum which makes it possible to differentiate between various sources, even with the same sound pitch (fundamental frequency). The timbre of a given source can be changed depending on [20,26,27]:…”

Section: Abrasive Grains Identification Methodologymentioning

confidence: 99%

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The identification of abrasive grains in the decohesion process by acoustic emission signal patterns

Sutowski

Nadolny

2016

Int J Adv Manuf Technol

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The article presents the results of basic research focused on the decohesion phenomenon characteristics of selected abrasive grains using acoustic emission signal patterns. On the basis of the recorded signals, their detailed analysis in the time-frequency domain and their characteristic harmonic components were selected. The method developed for estimating the similarity of the harmonic sequences will be further used in a comparative analysis with the degree of similarity of acoustic emission signal patterns to determine the type of grain in the decohesion process inducted by an external force or stress field. The proposed technique of grain recognition can be used in grinding wheel wear diagnostic systems, especially in cases where it is significant for supervision or inspection of cracking and chipping abrasive grain vertices.

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Section: Abrasive Grains Identification Methodologymentioning

confidence: 99%

“…This frequency is usually marked with index 0 (f 0 ) [20]. All of the remaining signal components are the multiple of the fundamental frequency, whereby the fundamental component might be defined as the greatest common divisor (GCD) of the other greater harmonic components of the signal [26]:…”

Section: Abrasive Grains Identification Methodologymentioning

confidence: 99%

The identification of abrasive grains in the decohesion process by acoustic emission signal patterns

Sutowski

Nadolny

2016

Int J Adv Manuf Technol

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“…The main parameter, which has the greatest effect on the stability of G Total , is K, and it is chosen to be 9 in this study. The discrete time model of (17) can be obtained as follows [25]. Where, T represent sampling period.…”

Section: Stability Analysis Of a Controller With A Lcl Filtermentioning

confidence: 99%

Effects of an Angle Droop Controller on the Performance of Distributed Generation Units with Load Uncertainty and Nonlinearity

Niya¹,

Kargar²,

Derakhshandeh³

2017

Journal of Power Electronics

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The present study proposes an angle droop controller for converter interfaced (dispatchable) distributed generation (DG) resources in the islanded mode of operation. Due to the necessity of proper real and reactive power sharing between different types of resources in microgrids and the ability of systems to respond properly to abnormal conditions (sudden load changes, load uncertainty, load current disturbances, transient conditions, etc.), it is necessary to produce appropriate references for all of the mentioned above conditions. The proposed control strategy utilizes a current controller in addition to an angle droop controller in the discrete time domain to generate appropriate responses under transient conditions. Furthermore, to reduce the harmonics caused by switching at converters' output, a LCL filter is used. In addition, a comparison is done on the effects that LCL filters and L filters have on the performance of DG units. The performance of the proposed control strategy is demonstrated for multi islanded grids with various types of loads and conditions through simulation studies in the DigSilent Power Factory software environment.

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“…Um sistema muitas vezesé visto como uma coleção de componentes que recebem uma excitação forçada, chamada entrada, x(t), e produzem uma resposta y(t) chamada de saída [6]. O sistema não precisa necessariamente ser físico, também pode ser conceitual ou abstrato.…”

Section: Definiçãounclassified

Pré-processamento de dados na identificação de processos industriais.

Rodríguez¹,

Wilfredo²

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Signals, Systems, Transforms, and Digital Signal Processing with MATLAB

Cited by 37 publications

References 0 publications

The identification of abrasive grains in the decohesion process by acoustic emission signal patterns

The identification of abrasive grains in the decohesion process by acoustic emission signal patterns

Effects of an Angle Droop Controller on the Performance of Distributed Generation Units with Load Uncertainty and Nonlinearity

Pré-processamento de dados na identificação de processos industriais.

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