A system and method using remote sensing instrument with hyper spectrum quantitatively measure metal dust elements in lubricating oil, which includes (no limited): Al, Cd, Cr, Cu, Fe, Pb, Mg, Mn, Mo, Ni, Ag, Sn, Ti, V, Zn, B (Boron, for Coolant), Ca (Calcium for water contaminant), and particle size, cone penetration, dropping point, steel mesh oil separation, moisture, PQ concentration, in few seconds. The instrument integrates near-field communication (NFC) Internet of Thing (IoT) Cloud computing, spectral matching and other data processing, and application software forming a system to easily operated and build a model enable self-learning to improve precision through collection accumulation. With the system, the instrument as FIG. 1 can provide comprehensive on-site analysis enable preventive maintenance of mission critical engine and rotating equipment. The characteristics of the system are easy to operate, get result quickly, and self-learning to improve precision.

An image processing method of converting spectral image data of a plurality of spectral wavelengths imaged by a spectral camera into a color image by using a processor, wherein the processor acquires a plurality of pieces of the spectral image data from a storage unit, calculates a correction value by multiplying a optical spectrum of each pixel of a corresponding one of the plurality of spectral image data by a correction constant set for each wavelength, calculates a color conversion value by summing the correction values of the same pixel positions, and generates a color composite image based on the color conversion value. Then, the correction constant is set such that a sum spectrum obtained by summing characteristic spectra obtained by multiplying a sensitivity characteristic with respect to each spectral wavelength of the spectral camera by the correction constant corresponding to each wavelength matches a target spectrum of any color filter.

An object recognition apparatus includes a first spectrometer configured to obtain a first type of spectrum data from light scattered, emitted, or reflected from an object; a second spectrometer configured to obtain a second type of spectrum data from the light scattered, emitted, or reflected from the object, the second type of spectrum data being different from the first type of spectrum data; an image sensor configured to obtain image data of the object; and a processor configured to identify the object using data obtained from at least two from among the first spectrometer, the second spectrometer, and the image sensor and using at least two pattern recognition algorithms.

A flip top spectrometer sample cell including first and second members each includes a window aligned with each other when the first and second members are coupled together defining a predefined spacing between the windows when the first and second members are coupled together, the first and second members decoupled for manually placing a fluid sample on a the window. The flip top spectrometer sample cell is configured to be withdrawn out of a housing for cleaning of the windows.

Systems and methods here may be used for automated capturing and analyzing spectrometer data of multiple sample gemstones on a stage, including mapping digital camera image data of samples, applying a Raman Probe to a first sample gemstone under evaluation on the stage, receiving spectrometer data of the sample gemstone from the probe, automatically moving the stage to a second sample, using the image data, and analyzing the other samples.

A method of generating object surface texture in thermal infrared images is disclosed which includes receiving heat radiation from a scene by a spectropolarimetric imaging system, generating a plurality of spectral frames associated with the scene, each frame having a plurality of pixels, for each pixel from the generated plurality of spectral frames, extracting spectral information associated with the scene, including pixel-specific temperature representing an objects temperature, and thermal texture factor representing the objects texture, for each of a plurality of materials having a specific emissivity in a library, generating reference spectral information as a function of temperature and thermal texture, matching the extracted spectral information for each pixel from the generated plurality of spectral frames to the generated reference spectral information using a statistical method to minimize the associated variation, and extracting spectral metadata from the matched reference spectral information for the associated material based on the match.

Disclosed are a method and a device for reconstructing a spectrum, a spectrometer, a computer-readable storage medium, and an electronic device, and solves a problem of poor anti-noise ability of the method for reconstructing a spectrum. According to a feature that a spectrum must be positive, the present application converts the negative spectral value in the spectral data to be processed into positive spectral value by the objective function, so that the anti-noise ability of an iterative solution process of the objective function may be improved, and thus accuracy of the reconstructed spectral data may be improved.

A non-contact system for the sensing of pH includes a hyperspectral imaging device configured to capture a hyperspectral image of a fluid, a flow cell configured to enable the capturing of a hyperspectral image of a fluid, a process, and a memory. The memory includes instructions stored thereon, which, when executed by the processor, cause the system to generate a hyperspectral image of the fluid in the flow cell, generate several spectral signals based on the hyperspectral image, provide the spectral signal as an input to a machine learning network, and predict by the machine learning network a pH of a fluid.

A high-resolution spectral image fast acquisition apparatus comprises an illumination source, an objective lens, a beam splitter, a single shot spectral image acquisition assembly and a reference image acquisition assembly, wherein the objective lens is used to align a sample to be measured; the illumination source is used to project an illumination light onto the sample to be measured so that the sample to be measured is amplified by the objective lens; wherein one part of amplified light enters the single shot spectral image acquisition assembly so as to acquire a low-resolution spectral cube of the sample to be measured, and another part of the amplified light enters the reference image acquisition assembly to acquire a high-resolution spectral cube. The apparatus enables rapid access to high-resolution spectral images, thereby speeding up the process of using spectral images for medical diagnosis.

A method, apparatus, and computer-readable storage medium for analyzing component separation/mass spectrometer data for a sample having known characteristic includes analyzing reference ion data for a relationship between ion mass, retention time, and intensity. The analyzed data is added to a repository, wherein each ion therein has an intensity maxima within a characteristic retention time range for a characteristic ion mass. If the reference ion is in the repository, the range is modified according to the characteristic retention time of the reference ion intensity maxima. Based on the known characteristic, an ion expected in the sample is selected from the repository, and sample data is compared to data for the ion selected from the repository to determine whether the ion is present in the sample. The range in the repository is then modified according to the characteristic retention time of the intensity maxima for the ion present in the sample.