Abstract-As the use of electric motors increases in the aerospace and transportation industries where operating conditions continuously change with time, fault detection in electric motors has been gaining importance. Motor diagnostics in a nonstationary environment is difficult and often needs sophisticated signal processing techniques. In recent times, a plethora of new time-frequency distributions has appeared, which are inherently suited to the analysis of nonstationary signals while offering superior frequency resolution characteristics. The Zhao-Atlas-Marks distribution is one such distribution. This paper proposes the use of these new time-frequency distributions to enhance nonstationary fault diagnostics in electric motors. One common myth has been that the quadratic time-frequency distributions are not suitable for commercial implementation. This paper also addresses this issue in detail. Optimal discrete-time implementations of some of these quadratic time-frequency distributions are explained. These time-frequency representations have been implemented on a digital signal processing platform to demonstrate that the proposed methods can be implemented commercially.
The erythrokeratodermas are a distinct but clinically variable group of rare geno-dermatoses, characterized by circumscribed erythematous and hyperkeratotic lesions. All attempts to establish a valid classification have been based on purely clinical and morphologic criteria. Erythrokeratoderma en cocardes, also known as genodermatose en cocardes or Degos' syndrome, was first described by Degos in 1947. The condition is characterized by large round plaques with concentric erythema and scaling having a target configuration, which remit and recur, in addition to scaly plaques as seen in erythrokeratoderma variabilis. A case of this rare genodermatosis is described.
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