Abstract: A system includes a robotic arm of a robotic device, an imaging device coupled to the robotic arm, and a processor configured to control movement of the robotic arm to move the imaging device along a preprogrammed measurement path of a transparency while prompting the imaging device to record images of localized portions of the transparency. The processor is configured to determine one or more localized transparency characteristics based on an analysis of the images of the localized portions.

Abstract: Method and apparatus of denoising recurrent signals comprising: providing first and second noisy signals each comprising a deterministic signal and (different realizations of) white noise; selecting one of the noisy signals as an input signal and the other noisy signal as a desired signal; providing an estimate of the deterministic signal in the input signal; determining the error between the estimated deterministic signal and the desired signal; adjusting the estimate of the deterministic signal using the error and producing an adjusted estimate of the deterministic signal.

Abstract: A method and apparatus comprising acquiring spectral measurements from an optical fiber sensor. The optical fiber sensor is an SBS-based sensor such as a BOTDA. The acquired measurements are of Brillouin interactions at a point along the optical fiber being excited by the lasers of the SBS-based sensor. The acquired measurements can comprise discreet measurements of the Brillouin gain spectrum (“BGS”) at the point along the fiber. The discreet measurements can be plotted as data points. A BGS can be defined by three parameters: the Brillouin frequency shift (“BFS”), the bandwidth and the peak gain. A Lorentzian curve can be used to model a BGS. A BFS can be determined by estimating the central frequency of the Lorentzian curve which is used to model the BGS.

Abstract: Method and apparatus of denoising recurrent signals comprising: providing first and second noisy signals each comprising a deterministic signal and (different realizations of) white noise; selecting one of the noisy signals as an input signal and the other noisy signal as a desired signal; providing an estimate of the deterministic signal in the input signal; determining the error between the estimated deterministic signal and the desired signal; adjusting the estimate of the deterministic signal using the error and producing an adjusted estimate of the deterministic signal.

Abstract: A distributed fiber optic sensor simultaneously interrogates the sensing fiber with two counter propagating light beams. One beam is set to a constant frequency. The second beam is modified to contain a “comb” of frequencies, with each frequency component in the comb offset by a predetermined amount. Each of the frequency components in the comb, herein referred to as teeth, is able to interact with the counter-propagating beam through the Brillouin scattering process. With proper selection of the comb characteristics such as the number of teeth, the frequency spacing of teeth, the spectral width of teeth, and the relative amplitude of the teeth, a representation of the Brillouin spectrum at each point in the fiber can be obtained simultaneously with a single pass through the fiber.