32results about How to "No sampling required" patented technology

The invention relates to a synchronous on-line measurement device for steam-injection type oil well temperature, pressure and steam quality. The synchronous on-line measurement device comprises a temperature demodulator, a pressure demodulator, a reflectivity demodulator and an industrial personal computer located on the ground, as well as a temperature sensor, a pressure sensor, a reflectivity sensor and an underground probe located underground. The underground probe comprises a shell and an airtight barrel arranged in the shell, an annulus is formed between the shell and the airtight barrel, a flow guide hole is formed in the wall of the shell, and the annulus is communicated with the outside through the flow guide hole. Upper ends of the shell and the airtight barrel are all located at a wellhead. The temperature sensor and the reflectivity sensor are all placed in the airtight barrel, and the pressure sensor is located in the annulus and fixed at the wellhead. The technical problem that an existing underground temperature, pressure and saturated steam quality measurement method is not suitable for the underground high-temperature high-pressure environment and low in efficiency is solved, and the method is used for solving the problem about on-line measurement of three parameters of steam-injection type oil well temperature, pressure and steam quality and grasping steam injection situations of an oil well.

The invention provides a method for detecting nitrite on line through liquid core fiber resonance Raman spectrum.The method involves a light source, a reflector path system and a light path receiving processing system.A laser device with the continuously adjustable laser frequency is adopted as the light source.The reflector path system comprises a reflector, a light filter, a focusing lens and a liquid core fiber.The light path receiving processing system comprises a monochrometer, a charge coupled device, a S3C2440 chip and a touch screen.The liquid core fiber is adopted for monitoring a nitrite solution, sampling is not needed, a sample is not damaged, meanwhile, the Raman spectrum strength can be improved by 103 times through the liquid core fiber technology, the Raman spectrum strength can be improved by 106 times by adopting the resonance Raman spectrum technology, the Raman spectrum strength can be improved by 109 times by combining the liquid core fiber technology and the resonance Raman spectrum technology, the S3C2440 chip is used for processing data, a data change track is drawn on the touch screen in real time, manual operation is not needed in the whole process, and the concentration of nitrite in water can be continuously measured on line.

The invention relates to a novel coupled high-sensitivity single-mode optical fiber evanescent wave sensor, which belongs to the technical field of optical fibers and sensors. A coupled single-mode optical fiber evanescent wave sensor of the present invention is mainly composed of a light source, an optical fiber, an optical fiber evanescent wave sensing element, a detector, a signal processing unit, and a container containing a side medium; it is characterized in that the optical The micro is a single-mode optical fiber; the optical fiber evanescent wave sensing element is a fused-cone single-mode fiber coupler probe; the fused-cone single-mode fiber coupler probe is packaged in a matrix, and there is a sensing single-mode fiber cone in the matrix There is a single-mode optical fiber lead-in end of a single-mode optical fiber coupler for sensing at both ends, which fixes the optical fiber on the substrate by fixing glue; there is still a hole near the optical fiber taper area to allow the measured gas or liquid to pass through and surround the optical fiber. The hollow access groove in the cone area; the probe or sensing element of the fused cone single-mode fiber coupler is placed in a container containing the measured medium and is surrounded by the measured medium. The sensor of the present invention has the advantages of simple structure, high sensitivity, good selectivity, strong anti-interference ability, real-time detection, no need for sampling measurement, convenient networking, etc., and its minimum detection limit reaches ppb-ppm level.

The invention discloses a rock strength prediction system and method based on petrographic feature analysis. The technical scheme is as follows: a rotating mechanism is included, and a grinding mechanism, a cleaning mechanism, a drying mechanism, a structure identification mechanism and mineral An analysis mechanism; the structure identification mechanism and the mineral analysis mechanism are connected with the strength prediction system. The present invention realizes accurate prediction of various strengths of rocks through rapid acquisition and quantitative analysis of structural characteristics and material components of rocks, and fusion of machine learning algorithms.

The invention discloses a system and method for automatically collecting and analyzing information on rock slag excavated by a TBM. The system includes: a visual sensor for collecting images of rock slag; a TBM supporting belt for transporting rock slag, and the belt is provided with stripes; A controller used to process rock slag images to obtain the shape and size of each rock slag in the slag material; a TBM operating room monitor used to display rock slag information, and the controller is connected to the visual sensor. The method of arranging multiple measuring points on the TBM belt is used to obtain more comprehensive and accurate two-dimensional information of the rock slag. Through the processing of the controller, the three-dimensional characteristics of the rock slag such as the shape, particle size and gradation of the rock slag are estimated. Furthermore, it provides an important basis for judging the geological conditions of the surrounding rock and adjusting the TBM tunneling parameters according to the characteristics of rock slag. The invention solves the problems that operators cannot observe the surrounding rock conditions comprehensively in time and manually sieves rock slag, and can collect and analyze rock slag images in real time so as to provide face rock mass information in time.

The invention discloses a method for on-line analysis of methyl chlorosilane by using an online Raman spectrometer to establish a model. The Raman spectrogram of the sample is combined with the analysis data obtained by gas chromatography, and statistical methods are used to calculate and obtain each group of The distribution curve of each component was established, and the Raman spectrum model of each component was established. After the online Raman spectrometer scans the sample, the Raman spectroscopic model is used to predict the sample components, and the results and time series curves are output, realizing the real-time monitoring of the changes of various components in methylchlorosilane by the online Raman spectrometer. The method has the advantages of no sampling, no damage to samples, simple operation, rapid analysis, and no environmental pollution.

The invention relates to an online evaluation method of the concentration of acetobacter xylinus capable of generating cellulose. According to the online evaluation method, a model used for representing the relationship between bacteria concentration and capacitivity is established; an online capacitivity detection device is adopted for real time monitoring of the capacitivity value of a culturing solution; the model used for representing the relationship between bacteria concentration and capacitivity is established, so that real time observing on the change trend of bacteria concentration can be realized, and culturing endpoint is determined based on a bacteria concentration change trend chart. The online evaluation method is capable of avoiding influences of culture medium, cellulose filament, insoluble particles, and foam on bacteria concentration measuring results, and possesses excellent application effect in experimental production, pilot scale production, and industrial scale production.