7 results about "Site engineer" patented technology

The present disclosure provides a method (500) and a system (102) for visualizing survey data of a building collected by a field engineer. A mobile application (152) associated with the field engineer is configured to collect survey data, and backend servers (154) are configured to receive the survey data from the mobile application (152). To view the collected survey data, the field engineer, uses a search option in the mobile application to search the building by typing the name / identifier of the building and a plurality of building names / identifiers is displayed matching with a partial name / identifier of the building. The user interface presents multiple selectable options for viewing the survey data according to different wireless technologies and frequency bands. The survey data is retrieved and displayed based on the selection. The user interface facilitates the field engineer to perform analysis of the survey based on the displayed survey data.

This disclosure relates to the technical field of power engineering related tools. One embodiment of this disclosure provides a measuring toolbox for power engineering design, comprising: a portable case, a drawer provided on the side wall of the portable case, a portable lifting component disposed within the portable case, and a plug-in locking component including a plug-in cavity. The above technical solution solves the problem that existing traditional measuring toolboxes for power engineering design, when facing complex and ever-changing work scenarios, have gradually revealed many limitations. Common toolboxes often adopt simple box structures, only achieving rough storage of tools, with relatively limited functions. On construction sites, engineers often need to frequently switch between multiple tools, and existing toolboxes lack reasonable partitioning and fixing measures. Tools are placed randomly inside the box, which is not only inconvenient to retrieve but also prone to collision and wear during transport, shortening the tool's lifespan.

The invention discloses a real-time intelligent judgment method, system and device for the operation state of a downhole instrument and a medium, and the method comprises the steps: carrying out the data expansion through employing a CGAN, building a plurality of downhole instrument operation algorithm parameter libraries according to the classification of different well types, avoiding the limitation of a model for discriminating the operation state of the downhole instrument through a single parameter, and improving the recognition precision; and the hyper-parameters of the DNN-GRU network are optimized, so that the hyper-parameters of the machine learning model are accurately obtained, time and labor cost are saved, and the overall performance of the model is improved. According to the method, the operation state of the underground instrument can be timely and accurately judged, and the abnormal working condition can be judged, so that an important basis and a monitoring means are provided for safe and efficient conveying of the underground instrument, the burden of field engineers is relieved, the operation safety degree is improved, and automation and intelligentization of well logging service are promoted.

The utility model relates to the technical field of pressure calibrators, and discloses a pressure instrument calibration device on an assembly pipeline, which comprises a square box, a fixing mechanism is fixedly connected in the square box, and a positioning sealing mechanism is fixedly connected at the top end of the square box. The fixing mechanism comprises an air cylinder, the outer portion of the air cylinder is fixedly connected to the interior of the square box, a circular block is fixedly connected to the driving end of the air cylinder, transmission plates are fixedly connected to the left side and the right side of the circular block correspondingly, and inclined sliding holes are formed in the far sides of the interiors of the two transmission plates correspondingly. And the inner wall of the inclined sliding hole is connected with a sliding rod in a sliding manner. According to the utility model, the pressure sensor is ensured not to generate errors due to factors such as shaking of the device when detecting the pressure in the pipeline, the detection precision is improved, the device is simple and convenient to operate, an on-site engineer can quickly check key parameters, the influence of human factors is reduced, the detection standard is unified, and the reinspection requirement is reduced.

The application discloses a kind of fault online diagnosis method and device, wherein the method includes: obtaining the fault state data of multiple faults defined to vehicle parts;Fault state data characterizes whether the corresponding fault occurs currently;Mapping is carried out based on multiple fault state data, and obtain fault list signal;Fault list signal includes multiple data segments, and a data segment at least corresponds to the fault state of a fault, and fault state indicates whether the corresponding fault occurs;Based on fault list signal, output target fault list signal in multiple fault list signals.The application can completely show any defined fault of vehicle parts currently occurred through fault list signal, and finally output according to needs, so as to provide on-site engineer real-time positioning fault, with good timeliness, improve fault troubleshooting efficiency.

The invention belongs to the crossing field of road engineering technology and artificial intelligence, and particularly relates to a road structure modulus back calculation method based on a large model and reinforcement learning. Analyzing and extracting structured parameters by a large language model, and generating initial modulus estimation driven by engineering knowledge; constructing a forward mechanical model based on a two-dimensional axisymmetric finite element, and calculating a theoretical deflection basin; designing a composite reward function, and driving a reinforcement learning agent to iteratively adjust the modulus of each structural layer; and in the optimization process, a large language model is periodically called to provide optimization direction guidance, and local optimum is prevented. Compared with a traditional back calculation method, the method has the advantages that the convergence rate is 100% on a synthetic data set, and the average deflection error is 1.69 + / -0.69%; the method supports adaptive processing of various road surface types such as flexible road surfaces, semi-rigid base layers and atypical structures, and has high robustness and engineering practicability.

The invention particularly relates to a method for realizing real-time optimization and reverse control of cable wrapping. The method for realizing real-time optimization and reverse control of cable wrapping comprises the following steps: acquiring wrapping process data in real time, and establishing a process quality associated data set; a pre-trained large model is loaded for fine tuning, whether the current wrapping state has deviation or not is analyzed in real time, and a process optimization suggestion is generated and pushed to an operation terminal, and whether the process optimization suggestion is adopted or not is confirmed by an on-site engineer; a control signal is sent according to the confirmation instruction, the wrapping machine is controlled to dynamically adjust wrapping parameters, and closed-loop adjustment of technological parameters is achieved; new process data and quality inspection results are fed back, and online fine adjustment and continuous optimization of a large model are achieved. The method for realizing real-time optimization and reverse control of cable wrapping is suitable for dynamic optimization and automatic adjustment of key parameters such as pitch, tension, speed and the like in a copper strip wrapping process, supports rapid adaptation of new-specification cables, can remarkably reduce the wrapping reject ratio, and improves the product quality consistency and the production line intelligent level.