6results about How to "Overcoming adaptability" patented technology

The invention discloses a transmitter system based on multi-sensor fusion and edge AI and a self-diagnosis method, and belongs to the technical field of industrial process control instruments, and an industrial intelligent transmitter system comprises a multi-sensor unit, a signal acquisition unit, a microcontroller, an AI coprocessor and a dual-mode communication unit. The multiple sensing units are used for synchronously collecting original data; the signal acquisition unit is used for converting original data into digital signals; the microcontroller is used for processing the digital signal and carrying out environment adaptive compensation to obtain compensated sensor data; the AI coprocessor is used for performing feature extraction and fault probability reasoning on the compensated sensor data to realize real-time self-diagnosis; and the dual-mode communication unit is used for transmitting the compensated process control signal and diagnosis information in different channels. The system has the functions of environment adaptive compensation, real-time self-diagnosis and the like, and the problems of parameter drift and fault response delay in an industrial environment are remarkably improved.

The application discloses a kind of wind farm wake evaluation method, device, equipment and storage medium, method includes: constructing physical model and generating coarse grid and fine grid;First calculation result and first flow field are obtained by CFD solution to coarse grid, and first flow field is as the initial flow field of fine grid;Actuator disc parameter is determined according to first calculation result;According to boundary condition, initial flow field and actuator disc parameter, the CFD solution based on actuator disc is carried out to fine grid to obtain second calculation result;Second machine site wind direction is constantly corrected according to second calculation result in second machine site wind direction Actuator disc orientation, until the difference between actuator disc orientation and second machine site wind direction is less than preset threshold, stop correction and obtain the wake parameter in each machine site and preset downstream range.The application corrects actuator disc orientation according to machine site wind direction, can more truly consider the influence of complex terrain and upstream wind turbine wake to downstream wind turbine, improve the accuracy and effectiveness of wind farm wake evaluation.

This invention relates to an artificial intelligence-based data inspection quality control method, system, device, and medium. The method includes: cleaning and determining the distribution of raw inspection data to generate a qualified dataset; adaptively learning key model parameters such as the effective data range and optimal smoothing coefficient through iterative calculation and simulation optimization based on the dataset and its distribution type; training a long short-term memory neural network time-series prediction model using the qualified dataset, and setting quality control limits by combining the learned benchmark dispersion to construct a real-time quality monitoring model; inputting real-time inspection samples into the model, generating alarm signals by calculating an exponentially weighted moving average monitoring statistic and comparing it with the control limits; iteratively optimizing the model and parameters based on historical alarm signals and new data to achieve continuous self-updating of quality control, enabling automatic learning of quality control parameters and intelligent optimization of the model, and improving the real-time monitoring capability of minor system deviations during the inspection process.

The invention discloses a karst-related area interval underpass construction method, and relates to the technical field of tunnel engineering, and the karst-related area interval underpass construction method comprises the following steps: carrying out field classification and improvement treatment on soft rock muck discharged by shield tunneling to obtain aggregate muck which can be directly used for backfilling and fine-grain muck which can be used for preparing grouting slurry; muck improvement slurry is prepared from fine muck, karst cavities on the construction path are pre-filled, and advanced grouting reinforcement is conducted on the stratum of the underpass section; during the period that shield tunneling penetrates through a karst area or penetrates through an existing structure under the karst area, synchronous grouting is conducted through muck improvement grout, and grouting parameters and tunneling parameters are dynamically adjusted according to real-time monitoring data; and after segmental lining is completed, compensation grouting is conducted through muck improved grout, and a stacked grouting supporting system is formed in the surrounding rock. According to the method, the shield muck can be recycled, the grouting material cost is reduced, and the safety and reliability of shield underneath pass construction are ensured.

The invention provides a finished bridge linear smoothness judgment method and system based on a main beam splicing process, and relates to the technical field of linear smoothness judgment, and the method comprises the following steps: obtaining a design curve of a main beam finished bridge target elevation, an elevation curve of an actual main beam splicing section and a to-be-judged splicing section length; and if the actual elevation curve exceeds the preset threshold, determining the elevation curve of the first bridge section according to the design curve. And fitting the actual elevation curve with the elevation curve of the first bridge section by adopting a preset spline curve fitting method to generate an elevation curve of the second bridge section. And combining the elevation curves of the actual splicing section, the first bridge section and the second bridge section into a virtual bridge forming line shape, performing high-pass filtering on the line shape, extracting an irregularity maximum absolute amplitude, comparing the irregularity maximum absolute amplitude with a preset irregularity allowable limit value, and judging whether the smoothness of the splicing section meets the requirement or not. According to the method, the smoothness judgment precision of the finished bridge line shape can be effectively improved.