14 results about "Site analysis" patented technology

This invention belongs to the field of oil and gas development and exploitation engineering technology, specifically relating to a method for determining the initiation zone and sequence of fractures during multi-layer fracturing and filling operations in loose sandstone reservoirs. Based on the basic physical properties and pumping parameters of each sub-layer, this invention establishes the time-varying process of fluid absorption and wellbore pressure at each sub-layer during multi-layer fracturing and filling operations, enabling rapid identification of sub-layers that have initiated fractures and those that have not. Furthermore, based on the fractured sub-layers, this invention iteratively corrects the fluid absorption capacity of each sub-layer and calculates the changes in fluid pressure at the wellbore of the un-fractured sub-layers, thus determining the sub-layers that will subsequently initiate fractures at each stage. This provides the order and timing of fracture initiation for construction design and on-site analysis, offering a basis for construction design and field analysis.

The invention relates to the technical field of construction methods, in particular to an unmanned aerial vehicle surveying and mapping method for a construction site. The method comprises the following steps: planning a flight path of an unmanned aerial vehicle according to region division and measurement requirements of a construction site, the flight path covering all regions of the construction site; setting data acquisition parameters of the unmanned aerial vehicle based on the flight path, controlling the unmanned aerial vehicle to execute data acquisition operation according to the flight path and the data acquisition parameters, and obtaining surveying and mapping data of the construction site; performing preprocessing and three-dimensional modeling on the surveying and mapping data to generate a three-dimensional terrain model of the construction site; and performing construction site analysis and result output based on the three-dimensional terrain model, wherein the result output comprises a terrain analysis file meeting a preset standard. The method is based on three-dimensional terrain model analysis and outputs a terrain analysis file meeting the standard, and can provide an accurate basis for construction analysis. The method is mainly applied to field surveying and mapping.

The invention discloses a device for edge algorithm deployment and violation problem output in the field of ecological environment, and the device comprises a data collection unit, an edge calculation unit and a violation output unit, the data collection unit is used for collecting the historical operation data of an enterprise site, comprising key operation parameters obtained from a distributed control system (DCS) of thermal equipment such as a waste incineration boiler and a coal-fired boiler and recorded environment parameter data such as flue gas components, temperature, pressure, oxygen content and particulate matter concentration, an edge calculation unit operates a deployed analysis algorithm model locally, the collected data are analyzed and processed, and the data are stored in a database. And judging whether a violation event or an environment abnormity exists in the operation process or not. By means of the equipment, on-site analysis can be conducted on historical operation data of an enterprise, abnormal operation states or potential illegal behavior clues can be found rapidly, and therefore the timeliness and accuracy of environment law enforcement are improved.

The invention discloses a spectrum detection system for rock substance component analysis and content statistics, which comprises a display screen, a spectrum detection system, a light source system and a data processing and analysis module, and is characterized in that the display screen and the data processing and analysis module carry out information interaction and are used for displaying an analysis result; a spectrum sensor is arranged in the spectrum detection system and is used for collecting spectrum data of the reflected light or the transmitted light and sending the spectrum data to the data processing and analyzing module; the light source system is used for irradiating the rock sample surface and exciting the spectral characteristics of the rock sample; the data processing and analyzing module receives the spectral data and is used for processing and analyzing the spectral data, identifying rock substance components and performing content statistics and sending an analysis result to the display screen. The invention further discloses a spectrum detection method for rock substance component analysis and content statistics. The device can be conveniently carried to the field for field analysis by a user, and rapid analysis of rock substance components and contents thereof is realized.

The application discloses a kind of non-normal power consumption field analysis method and system, comprising: obtaining power consumption data;The power consumption data is integrated, and data of different sources is loaded into a new data source;Electricity data filling is carried out in new data source, and abnormal power consumption data is eliminated;The data source is different in the value range of the characteristics of the data that too much difference is normalized;The characteristics of the data after normalization are selected;Selected data is trained using ELM algorithm to obtain a prediction model;Real-time power consumption data is predicted using the obtained prediction model to determine whether there is non-normal power consumption.The non-normal power consumption field analysis method and system based on extreme learning provided by the application not only can reduce the model network parameter adjustment time and enhance the model generalization performance, but also can ensure the accuracy of power consumption non-normal inspection work.

The present invention discloses a flood classification method based on a graph attention neural network, comprising: constructing a flood event dataset; constructing a flood atlas; extracting graph-level features of the flood map corresponding to each flood event based on the graph attention neural network (GAT); and classifying floods using a K-means clustering method based on the graph-level features of the flood atlas. The present invention introduces graph neural networks into the field of flood classification, achieving deep learning modeling of the spatial correlation characteristics of river basin floods. The graph attention network is used to integrate synchronously monitored flow data from multiple sites within the basin, extracting the spatiotemporal evolution characteristics of floods in the river network of the basin, and breaking through the limitations of traditional single-site analysis methods. The method proposed in the present invention relatively considers the spatial heterogeneity of floods, and the classification results contain richer information.

The invention relates to the technical field of social media site analysis, and discloses a regional site characterization method and system, and the method comprises the steps: extracting a user group from a social media user group; performing entity feature word and camp feature word analysis on texts published by users in the sampled user group to obtain a first vertical distribution prediction result; carrying out double labeling of the standing and personality characteristics on the users whose activeness is higher than a set condition, training a personality-standing association model by using labeled data, analyzing the personality characteristics of the users whose activeness is low, deducing the standing, and carrying out statistics to obtain a second standing distribution prediction result; and carrying out weighted fusion on the first vertical field distribution prediction result and the second vertical field distribution prediction result to generate a final regional vertical field representation. According to the method, the quantitative mapping relationship among the user behaviors, the personality characteristics and the potential site is established, and accurate sampling is performed according to the population distribution in the real world, so that accurate and full-quantitative insight of the regional site is realized.

The utility model relates to the technical field of liquid filling, and discloses on-site analysis equipment for filling backup liquid. The on-site analysis equipment for backup liquid filling comprises a connecting pipe, rubber pads are fixedly installed at the two ends of the connecting pipe, an electromagnetic valve is fixedly installed at the front end of the connecting pipe, a bolt is installed on the front side of the connecting pipe in a penetrating mode, a nut is installed at the tail end of the bolt in a penetrating mode, and a limiting pipe is fixedly installed above the connecting pipe; the bottom end of the probe is located in the center of the connecting pipe, flange structures are arranged at the front end and the rear end of the connecting pipe, and flange structures are also arranged at the two ends of the electromagnetic valve. In the filling process, the filled liquid substance is in contact with the probe, and in this way, the step of erecting a sampling tube can be omitted while the probe is in contact with the liquid substance, so that equipment is convenient to install.

A method for constructing a pre-fabricated component of a building, including: configuring a pre-fabricated component of a building based on energy informed modelling; wherein the pre-fabricated component is able to be assembled with at least one other pre-fabricated component into the building at a final site for the building. A method for constructing a building, including: performing site analysis to determine at least one environmental condition; and optimizing at least one pre-fabricated component of the building based on energy informed modelling based on one or more of historical data of a location of the building, weather patterns of the location, climate data of the location, temperature data of the location, solar data of the location, orientation data of the location, occupancy rate of the building, building insulation data, ventilation and infiltration data, exterior fenestration, shades implementation, or pre-fabricated component configuration.

The invention provides a system for real-time and on-site analysis of water quality issues utilizing advanced algorithms, machine learning, and AI-based assessment, the system employing a state-of-the-art rover equipped with advanced sensors to detect issues and anomalies in an aquatic biome and supply collected data to computing units, also deployed locally on the rover, which then operate to assess the collected data by employing advanced algorithms to generate search engine queries, identify and extract pertinent terms from search results, assess likely causes of detected issues and anomalies, and provide real-time, on-site reports and analysis of findings.

The invention provides a geological survey method for recovering metamorphic rock protolith types by utilizing boron isotope fractionation characteristics. The method comprises the following steps: establishing a benchmark database containing a plurality of non-metamorphic protorock boron isotopes and key inactive element contents; a double-control correction model of boron isotope fractionation is established, quantitative function relationships between a distribution coefficient and pressure and between a fractionation coefficient and temperature are respectively established through high-temperature and high-pressure experimental data, and a fluid activity factor is introduced to form an inversion calculation equation. The model is used for inversion to obtain original boron isotope composition, then the original boron isotope composition and key element indexes are subjected to collaborative analysis, a two-dimensional discrimination diagram is constructed, and the protolith type is finally determined by comparing discrimination regions in a reference database. According to the method, the metamorphic fractionation effect is effectively corrected, and the accuracy and reliability of high-grade metamorphic rock protolith recovery are remarkably improved in combination with double geochemical index constraints. The method can be matched with portable on-site analysis equipment, and field rapid discrimination is realized.

Mobile forensic system for on-site analysis and comparison of paint and damage traces on vehicles, comprehensive: a) a 3D scanner module for capturing the three-dimensional surface geometry, local height deviations and the exact position of the damage area relative to the vehicle coordinate system and the ground reference, b) a camera module for macroscopic imaging with automatic focus and optimized lighting, c) at least one spectroscopic analytical module, selected from the group XRF, LIBS and Raman, for chemical characterization of the trace regions, d) optionally a module for optical profilometry for high-resolution analysis, e) a control unit for the automatic co-registration of all measurement data, in particular geometric 3D data, high-resolution image data, spectroscopic analysis data as well as optional profilometry measurement data and other sensor signals, in a common, three-dimensional coordinate system, f) a logging unit that generates a legally valid measurement log with chain-of-custody, ID, timestamp, user identification, calibration data and digital signature, wherein the radiation-carrying analytical modules are arranged in one or more protective hoods and are designed to ensure safe operation and prevent the escape of X-rays and laser light.

A system and method for analyzing industrial environments through integrated multi-modal sensing, artificial intelligence, and automated deployment optimization. The system includes a dome base with multiple integrated sensors generating data streams from different sensing directions and sensor types. Machine learning workflows utilize multi-modal sensor fusion, computer vision algorithms, and predictive modeling techniques to transform reactive maintenance approaches into proactive, autonomous maintenance systems optimized for both technical performance and economic outcomes. The system includes mobile device integration capabilities for automated site analysis, equipment recognition, and sensor placement optimization using three-dimensional environmental mapping. Synthetic data generation enables customer demonstrations and system validation through simulated equipment behavior across operational and failure states. AI-driven sales automation generates technical proposals, cost-benefit analyses, and maintenance recommendations based on real-time sensor data and predictive modeling. Distributed intelligence architecture enables autonomous transaction processing, vendor management, and maintenance coordination throughout industrial maintenance ecosystems.