7results about How to "Comprehensive judgment" patented technology

The invention discloses a geotechnical engineering geological investigation system and method, relates to the technical field of geological investigation, and solves the problems of difficulty in multi-source data fusion, low geological anomaly intelligent identification precision and weak regional comprehensive evaluation and visual expression ability in the existing investigation method. According to the method, the unified comprehensive parameter vector is constructed, scattered drilling data, in-situ test parameters and real-time sensor monitoring data are subjected to standardized integration and collaborative analysis, the limitation that various types of data are independently stored in traditional exploration, and a data island is formed is broken through, efficient fusion of multi-source heterogeneous information is achieved, and the method has the advantages of being simple in structure and convenient to use. The problem of data fragmentation is solved, and deep cognition and judgment of complex geological conditions can be more comprehensively carried out.

The invention relates to an elevator guide rail flatness anomaly detection method and a corresponding installation and maintenance judgment method and device in the technical field of elevator safety detection. According to the elevator guide rail flatness anomaly detection method, P, D1 and D2 of any position of a to-be-detected guide rail are obtained and subtracted from a target position parameter P0 and two target distances D10 and D20 respectively, then absolute values are obtained, corresponding deviation values are obtained, the deviation values are compared with a preset threshold value, and the flatness anomaly of the to-be-detected guide rail is detected. And whether the actual state of the position is the flatness abnormity of the guide rail to be detected caused by self factors can be directly judged. According to the method, the specific state of the flatness of the elevator guide rail can be directly reflected through collection and calculation of multiple sets of data, the state of the guide rail can be accurately distinguished into serious deformation, normal or local abnormal protrusion, and therefore complex operation of manual data rechecking is avoided.

This invention provides a target-controlled assisted drug delivery system for painless surgery anesthesia, belonging to the field of medical technology. It includes: an initial protocol generation module for determining the initial drug delivery protocol based on the type of painless surgery anesthesia and the patient's basic physiological information; a trial drug delivery control module for administering trial drugs to the patient based on the initial drug delivery protocol and recording the changes in the patient's electroencephalogram (EEG) signals and physiological signs during the trial drug delivery process; a resistance analysis module for analyzing the patient's resistance to the anesthetic drug in real time based on the EEG signal changes and physiological sign changes; and a drug delivery adjustment module for adjusting the initial drug delivery protocol in real time based on the resistance level and continuing drug delivery to the patient based on the adjusted protocol and medical intervention instructions until the drug delivery is completed. This improves the target control accuracy of anesthetic drug dosage and delivery rate during painless surgery.

The invention discloses a monitoring and protecting method and system for a speed reducer, which can extract micro-features strongly related to stator winding faults, such as fundamental frequency and side frequency components, specific sub-harmonic components and the like, by synchronously collecting three-phase current of a driving motor and performing spectral analysis. The characteristics are very sensitive to winding turn-to-turn short circuit, insulation aging and other early faults, effective coverage of traditional vibration monitoring blind areas is achieved, and fault discovery time is greatly advanced. By calculating the health degree index of the stator winding, the electrical characteristics are quantified into a visual and continuous evaluation index. Furthermore, the electrical health index is intelligently combined with the analysis result of the vibration signal. The fusion breaks the barrier between electrical and mechanical monitoring, so that the system can comprehensively consider electrical hidden dangers and mechanical conditions like experienced engineers, and make more comprehensive and more accurate judgment on the overall health state and risk level of the speed reducer system.

The invention relates to the technical field of chemical engineering system optimization, and discloses a planning design verification method for an electrolytic manganese hydrogen production-chlor-alkali chemical engineering coupling system. The method comprises the following steps: acquiring first real-time operation parameters such as current density and cell pressure of an electrolytic manganese hydrogen production unit, and second real-time operation parameters such as alkali liquor concentration and hydrogen purity of a chlor-alkali chemical unit; screening a matching operation section matched with the current hydrogen production fluctuation characteristic from the historical coupling operation data; analyzing the bath pressure change on the time sequence of the matched operation section to determine a coupling response action point, and calculating the coupling delay amount from the starting point to the action point; then comparing the current density before and after the coupling response action point with the change trend of the hydrogen purity data sequence, and determining a parameter matching degree; determining a coupling weight coefficient by combining the coupling delay amount, the parameter matching degree and the fluctuation characteristic difference; and inputting the generated dynamic efficiency coefficient and the first real-time operation parameter into a system verification controller, and outputting a system adjustment instruction, so that accurate planning verification of the coupling system can be realized.

The invention discloses an interface function detection method and device and a readable storage medium, and the method comprises the steps: applying a test signal to a control interface of a tested device; wherein the test signal is configured to simulate cooperative work between at least one external device and the device under test; collecting feedback information output by the tested equipment in response to the test signal through at least two different functional channels; and judging whether the function of the control interface is normal or not by analyzing the relationship between the feedback information and / or the logic association between the feedback information and the test signal. According to the invention, the system can achieve the integrated and automatic detection of the functions of a complex control interface through simulating a real cooperative working condition and carrying out the cross verification through a multifunctional channel.

The application discloses a multi-modal battery life estimation model training method, application method and device, and relates to the technical field of battery health management. The method comprises: in the training stage, constructing an attribute pool through battery-specific attributes and synthesizing multivariate battery time series data, and generating diversified battery life question and answer pairs based on the synthesized data using a large language model combined with an evolutionary algorithm; the large language model is pre-trained using the synthesized data, and instruction fine-tuning is performed using the battery life question and answer pairs to obtain a battery life estimation model. In the application stage, the real battery time series data is encoded for numerical preservation and then fused with natural language queries to input the model, multi-modal understanding and reasoning are performed, and a structured natural language diagnosis report is output. Through semantic alignment of attribute-driven battery time series data and a large language model, the application solves the problem that a large language model cannot directly understand battery time series data, and realizes high-precision, few-sample and interpretable battery life estimation.