This article shows a new Te-transform and its periodogram for applications that mainly exhibit stochastic behavior with a signal-to-noise ratio lower than −30 dB. The Te-transform is a dyadic transform that combines the properties of the dyadic Wavelet transform and the Fourier transform. This paper also provides another contribution, a corollary on the energy relationship between the untransformed signal and the transformed one using the Te-transform. This transform is compared with other methods used for the analysis in the frequency domain, reported in literature. To perform the validation, the authors created two synthetic scenarios: a noise-free signal scenario and another signal scenario with a signal-to-noise ratio equal to −69 dB. The results show that the Te-transform improves the sensitivity in the frequency spectrum with respect to previously reported methods.
This article solves the problem of detecting water leaks with a minimum size of down to 1 mm in diameter. Two new mathematical tools are used to solve this problem: the first one is the Te cross-spectral density and the second is Te coherence. These mathematical tools provide the possibility of discriminating spurious frequency components, making use of the property of multi-sensitivity. This advantage makes it possible to maximize the sensitivity of the frequency spectrum. The wavelet function used was Daubechies 45, because it provides an attenuation of 150 dB in the rejection band. The tools were validated with two scenarios. For the first scenario, a synthetic signal was analyzed. In the second scenario, two types of background leakage were analyzed: the first one has a diameter of 1 mm with a signal-to-noise ratio of 2.82 dB and flow rate of 33.7 mL/s, and the second one has a diameter of 4 mm with a signal-to-noise ratio of 9.73 dB with a flow rate of 125.0 mL/s. The results reported in this paper show that both the Te cross-spectral density and Te coherence are higher than those reported in scientific literature.
In this work, we propose a fuzzy inference as a decision support system built in the MATLAB Fuzzy Logic Designer for evaluating manual material handling risk conditions. The input variables for the fuzzy decision were: (1) the total time duration of the manual material handling in one shift of 450 min, with 3 h considered the maximal exposition time; (2) 25 kg as a maximal mass reference which should never be exceeded; (3) the repetitiveness of the manual material handling task through the shift considering as the maximal frequency of four lifts per min. Results of 135 earlier direct ergonomic evaluations made using the method proposed by the ISO 11228-1 were used as validator results, and called “expected results”. The experimentation intended to simulate an ergonomic evaluation in different boundary conditions of work and verify if the fuzzy interface could correctly replicate the results of the ergonomic evaluations. As validation, the list with the 135 expected results was compared against the evaluation made by the fuzzy logic interface, called “Work_Conditions”. From the comparison, only three evaluations (0.02%) differed with respect to the expected results. Consequently, it is concluded that the fuzzy interface can be used as a tool for automating the determination of manual material handling ergonomic risk levels, with great precision.
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