A Novel Fault Detection and Identification Framework for Rotating Machinery Using Residual Current Spectrum

A novel framework of model-based fault detection and identification (MFDI) for induction motor (IM)-driven rotating machinery (RM) is proposed in this study. A data-driven subspace identification (SID) algorithm is employed to obtain the IM state-space model from the voltage and current signals in a quasi-steady-state condition. This study aims to improve the frequency–domain fault detection and identification (FDI) by replacing the current signal with a residual signal where a thresholding method is applied to the residual signal. Through the residual spectrum and threshold comparison, a binary decision is made to find fault signatures in the spectrum. The statistical Q-function is used to generate the fault frequency band to distinguish between the fault signature and the noise signature. The experiment in this study is performed on a wastewater pump in an existing industrial facility to verify the proposed FDI. Two faulty conditions with mathematically known and mathematically unknown faulty signatures are experimented with and diagnosed. The study results present that the residual spectrum demonstrated to be more sensitive to fault signatures compare to the current spectrum. The proposed FDI has successfully shown to identify the fault signatures even for the mathematically unknown faulty signatures.

The Herschel SPIRE Fourier Transform Spectrometer Spectral Feature Finder I. The Spectral Feature Finder and Catalogue

ABSTRACT We provide a detailed description of the Herschel/SPIRE Fourier Transform Spectrometer (FTS) Spectral Feature Finder (FF). The FF is an automated process designed to extract significant spectral features from SPIRE FTS data products. Optimizing the number of features found in SPIRE-FTS spectra is challenging. The wide SPIRE-FTS frequency range (447–1568 GHz) leads to many molecular species and atomic fine structure lines falling within the observed bands. As the best spectral resolution of the SPIRE-FTS is ∼1.2 GHz, there can be significant line blending, depending on the source type. In order to find, both efficiently and reliably, features in spectra associated with a wide range of sources, the FF iteratively searches for peaks over a number of signal-to-noise ratio (SNR) thresholds. For each threshold, newly identified features are rigorously checked before being added to the fitting model. At the end of each iteration, the FF simultaneously fits the continuum and features found, with the resulting residual spectrum used in the next iteration. The final FF products report the frequency of the features found and the associated SNRs. Line flux determination is not included as part of the FF products, as extracting reliable line flux from SPIRE-FTS data is a complex process that requires careful evaluation and analysis of the spectra on a case-by-case basis. The FF results are 100 per cent complete for features with SNR greater than 10 and 50–70 per cent complete at SNR of 5. The FF code and all FF products are publicly available via the Herschel Science Archive.

The quasars’ redshift estimation method based on piecewise Gaussian fitting

To solve the problem that high-redshift and broad emission lines weaken the quasar discovery and observation severely, a new redshift calculation method based on piecewise Gaussian fitting is proposed. The denoised and normalized spectrum is divided into two regions, peak and non-peak, by mean square error threshold segmentation first. Then, the non-peak region spectrum is applied to fit the continuous spectrum, removal of which gains access to the residual spectrum. And, the peak of each segment in the residual spectrum is precisely fitted by single-peak Gaussian fitting to replace the original multi-peak Gaussian fitting. Finally, through matching the accurate peak value with the stationary template, the redshift value is acquired. Compared with traditional methods, the method proposed improves the precision of continuous spectrum fitting and redshift calculation. The effectiveness and accuracy of this method have been verified by experiments based on the Sloan Digital Sky Survey data.

OMI total bromine monoxide (OMBRO) data product: algorithm, retrieval and measurement comparisons

This paper presents the retrieval algorithm for the operational Ozone Monitoring Instrument (OMI) total bromine monoxide (BrO) data product (OMBRO) developed at the Smithsonian Astrophysical Observatory (SAO) and shows comparisons with correlative measurements and retrieval results. The algorithm is based on direct nonlinear least squares fitting of radiances from the spectral range 319.0–347.5 nm. Radiances are modeled from the solar irradiance, attenuated by contributions from BrO and interfering gases, and including rotational Raman scattering, additive and multiplicative closure polynomials, correction for Nyquist undersampling and the average fitting residual spectrum. The retrieval uses albedo- and wavelength-dependent air mass factors (AMFs), which have been pre-computed using a single mostly stratospheric BrO profile. The BrO cross sections are multiplied by the wavelength-dependent AMFs before fitting so that the vertical column densities (VCDs) are retrieved directly. The fitting uncertainties of BrO VCDs typically vary between 4 and 7×1012 molecules cm−2 (∼10 %–20 % of the measured BrO VCDs). Additional fitting uncertainties can be caused by the interferences from O2-O2 and H2CO and their correlation with BrO. AMF uncertainties are estimated to be around 10 % when the single stratospheric-only BrO profile is used. However, under conditions of high tropospheric concentrations, AMF errors due to this assumption of profile can be as high as 50 %. The retrievals agree well with GOME-2 observations at simultaneous nadir overpasses and with ground-based zenith-sky measurements at Harestua, Norway, with mean biases less than -0.22±1.13×1013 and 0.12±0.76×1013 molecules cm−2, respectively. Global distribution and seasonal variation of OMI BrO are generally consistent with previous satellite observations. Finally, we confirm the capacity of OMBRO retrievals to observe enhancements of BrO over the US Great Salt Lake despite the current retrieval setup considering a stratospheric profile in the AMF calculations. OMBRO retrievals also show significant BrO enhancements from the eruption of the Eyjafjallajökull volcano, although the BrO retrievals are affected under high SO2 loading conditions by the sub-optimum choice of SO2 cross sections.

The point spectrum and residual spectrum of upper triangular operator matrices

The point and residual spectra of an operator are, respectively, split into 1,2-point spectrum and 1,2-residual spectrum, based on the denseness and closedness of its range. Let H,K be infinite dimensional complex separable Hilbert spaces and write MX = (AX0B) ? B(H?K). For given operators A ? B(H) and B ? B(K), the sets ? X?B(K,H) ?+,i(MX)(+ = p,r;i = 1,2), are characterized. Moreover, we obtain some necessary and sufficient condition such that ?*,i(MX) = ?*,i(A) ?*,i(B) (* = p,r;i = 1,2) for every X ? B(K,H).