Papers by Keyword: Multi-Fractal Spectrum

Abstract: Based on Bandelet transform and Multi-fractal, the metal fracture surface image denoising is described in the paper. Using multi-fractal analysis, eight multi-fractal spectrum values which are used as shape characteristic parameter of metal fracture surface are extracted. Experimental results showed that different metal fracture surfaces have different shape characteristics and the same kind of metal fracture surfaces have similar shape characteristics. So the shape characteristic parameter of metal fracture surface can be used to study the fracture surface recognition and as the sample of failure analysis.

Abstract: As for different shape features for different wheat diseases, it can make use of multi-fractal analysis to extract 7 Multi-fractal spectrum value of wheat diseases image as the parameters of the wheat disease characteristics. Eight feature parameters can be applied to index the image database as a learning vector quantization neural network input. According, Sample training, classification and recognition is to be carried out. Experimental results show that the wheat disease recognition rate of the algorithm can reach more than 90%.

Abstract: Wheat diseases image noise was effectively removed using lifting scheme multi-wavelet transform and multi-fractal analysis, and then it used multi-fractal theory to segment diseases image and extract eight multi-fractal spectrum values as wheat shape feature of diseases. Experiments showed that the shape characteristic value of different wheat diseases had great difference, and the shape characteristic value of similar diseases had certain regularity. Therefore, it could extract shape characteristic value to recognize wheat diseases.

Abstract: Spark plasma sintering (SPS) technology was used in-situ to fabricate the Ti₂AlC/TiAl (Nb, B) composites. And the composites were treated by rapid heat treatment. which had many advantages, such as heating-up quickly, short holding time and relatively slow cooling. The hidden relationship between images could be reflected by Multi-fractal spectrum, which also could show irregularity apparently. In this paper, the SEM images which fabricated after rapid heat treatment were researched by multifractals. And the parameter was calculated by MATLAB through anglicizing the multi-fractal spectrum theory. There was only small fluctuate between lnχq (r) and lnr when r=0.00625, and lnχ_{q (r)} and lnr had well linear relationship in spite of the value of q. After the rapid heat treatment at T=1403 K, the correlation coefficient between τ (q) and q reached 99.99% . The trend of D (q) and q turned to be gently, and the fracture appeared uniformity, and these SEM images were single fractures. τ (q) and q show nonlinear relationship in q∈[-3,-1], and there was one observe steep.The clock shape relationship between the α and f (α) revealed good symmetry of spectrum, wider spectral width, uneven distribution of the fracture, multi-fractal feature clearly, and obvious characteristic of multi-fractal. Key words: multi-fractal spectrum, rapid heating heat treatment, fractal dimension

Abstract: The SEM images of Ti₂AlC/TiAl materials with different samples showed different fractal dimension.In Multi-fractal spectrum, the parameter is calculated by the multi-fractal spectrum theory. Without r=0.00625, giving rise to the small fluctuate, lnχq(r) and lnr shows the well linear relationship in spite of the value of q. τ (q) and q show nonlinear relationship and the protuberance existed in q∈[-3,-1], D(q) and q turn to be more steep, at last the clock shape relationship between the α and f(α) reveals the good symmetry of spectrum, uneven distribution of the fracture, multi-fractal feature clearly.

Abstract: The method of monitoring the tank vibration is becoming an effective method to detect the winding deformation of power transformer for the reliable and secure operation of power system. In order to further identify the relationship between the winding deformation fault of power transformer and the measured tank vibration signals, the short-circuit test is done in a 220kV transformer with the developed vibration measurement system and the vibration frequency response curves for some pre-setting winding deformation faults are obtained. Multi-fractal spectrum is applied to analyze the of the obtained vibration signals when winding conditions of power transformer are changed. It is shown that multi-fractal spectrum can effectively indicate the geometric structure features of vibration signals. The parameter variations of multi-fractal spectrum are agreed well with the preset winding faults, which provides another method for the feature extraction of vibration signal to detect the winding deformation of power transformer.