8 results about "Performing Laboratory" patented technology

The invention provides a method for optimizing a detection sensing material for trace characteristic gas in transformer oil, and belongs to the technical field of detection of gas in transformer oil, and the method comprises the following steps: firstly, obtaining basic data of candidate materials, including material composition, atomic structure, electron energy band structure and theoretical gas sensing performance parameters; and establishing a sensing performance prediction model considering the material composition and structure, and training a material-performance correlation model by using a machine learning algorithm. A large number of theoretical material data sets are generated through computer traversal, and multi-dimensional clustering analysis is performed on candidate materials to obtain a clustering center. And carrying out laboratory performance testing by taking a clustering center corresponding material as a to-be-tested set, and collecting actual performance data. And carrying out multi-generation iterative optimization on the material with the optimal performance by adopting a genetic algorithm to finally obtain the transformer oil trace characteristic gas detection sensing material. The problem that an existing gas sensing material is difficult to meet harsh requirements of an electric power system on online detection of a transformer in the aspects of sensitivity, selectivity and stability is solved.

The application provides a life prediction method and system for airtight multi-cell steel structure, and relates to the technical field of structure finite element analysis, which comprises the following steps: taking the airtight multi-cell steel structure as a prototype, determining a scale reduction ratio, and establishing a scaled structure of the airtight multi-cell steel structure; performing laboratory accelerated environmental testing and mechanical testing on the scaled structure under the equivalent service environment of the airtight multi-cell steel structure, obtaining mechanical response test data of the scaled structure, and determining test targets of the scaled structure at different times; taking scaled plate material data as input to establish a simulation model of the scaled structure and obtain a transfer coefficient; taking original plate material data as input to establish a full-size structure simulation model of the airtight multi-cell steel structure; and using the full-size structure simulation model to output crack propagation size and residual life of a target welded structure at different times under the full-size structure. The application effectively improves the accuracy of life prediction of the airtight multi-cell steel structure.

This invention relates to the field of pollutant detection technology, and more particularly to a pollutant detection method and system based on an environmental consulting knowledge base. The method includes: receiving basic information about the project to be tested, inputting it into a pre-built environmental consulting knowledge base for matching, and outputting a preliminary detection plan; generating a final detection plan after verification using historical cases; performing on-site sampling and in-situ testing, linking the knowledge base to complete real-time quality control early warning and on-site calibration, and obtaining a calibrated in-situ detection dataset; performing laboratory testing on environmental samples and performing three-level calibration to obtain a valid pollutant detection dataset; performing compliance analysis on the valid detection data, and outputting the detection results. This invention effectively solves the core problems of fragmented processes and lack of unified knowledge support in existing detection technologies, overcomes the shortcomings of manual reliance, insufficient quality control and calibration, low data accuracy, and poor analysis efficiency, and achieves intelligent standardization of the entire detection process, significantly improving detection efficiency and data accuracy.

This invention relates to the field of detector operating temperature determination technology, and more particularly to a method for determining the optimal operating temperature of a spectrometer detector. The method includes the following steps: performing theoretical analysis to determine the signal-to-noise ratio (SNR) formula, analyzing the relationship between detector signal and temperature, and the relationship between detector noise and temperature, and theoretically calculating the SNR-temperature relationship; simultaneously performing laboratory measurements, including experimental setup and data acquisition and calculation; and finally, combining the theoretical calculations and the actual measured SNR results to determine the optimal operating temperature of the InGaAs detector. This invention can obtain the operating temperature at which the InGaAs detector achieves the highest SNR. When using the InGaAs detector for measurements, a temperature control module is used to stabilize the InGaAs detector at this temperature, resulting in better performance of the short-wave infrared spectrometer based on the InGaAs detector and improved instrument measurement accuracy.

The present invention provides a reliability assessment platform and method for underwater shield tunnel waterproofing systems, relating to the technical field of shield tunnel evaluation. The method divides the outer surface of an underwater shield tunnel into N equal-sized regions, collects water samples with unknown centers at each location, and performs laboratory testing to obtain inorganic and organic data. A biocorrosion coefficient is generated based on the inorganic and organic data. Property data for the waterproofing material of the underwater shield tunnel waterproofing layer is obtained, and a waterproofing coefficient is generated based on the property data. A waterproofing system reliability assessment coefficient is generated based on the minimum value of the waterproofing coefficient and the biocorrosion coefficient of all regions. The reliability assessment of the tunnel waterproofing system is then completed based on the waterproofing system reliability assessment coefficient. This method considers the impact of microorganisms on the waterproofing system, making the waterproofing system reliability assessment more accurate.

The invention discloses an AI-based intelligent health management system, which comprises an acquisition layer, a data layer, an algorithm layer, an application layer and a security layer, and is characterized in that the acquisition layer comprises Internet of Things data acquisition, test data acquisition and user input acquisition; the test data acquisition is performed by summarizing samples to be tested of a user by using a test data acquisition auxiliary device and then performing test operation, and the test data acquisition auxiliary device comprises a sample transfer mechanism, a sample storage and installation mechanism and a regional transportation mechanism. According to the AI-based intelligent health management system, an AI algorithm and a sensor technology are utilized, multi-dimensional data are integrated to form a complete health portrait, health changes are captured in time, the data processing efficiency and accuracy are improved, automatic and efficient collection and transportation of samples from a family end to a laboratory are achieved, and the problems that in traditional collection and transportation, the labor efficiency is low, and the cost is low are solved. Therefore, key support is provided for full-chain automation of a health management system.

Methods, compositions, and systems for preparing and using pooled biological samples for laboratory testing are disclosed. In certain embodiments, the methods and systems may be used to pooling basophilic granulocyte donors for laboratory testing against chronic spontaneous urticaria.