129 results about "Data stability" patented technology

The invention discloses a metabonomics data batch correction method based on multi-kernel learning, and belongs to the cross technical field of bioinformatics and analytical chemistry. According to the method, the multi-kernel learning technology is utilized, the advantages of different kernel functions are fused in a self-adaptive mode, a model conforming to data reality is constructed, complex drift characteristics of metabolite signals are accurately captured, and efficient and accurate normalization processing of metabonomics data is achieved. Compared with traditional data standardization methods such as SVR and LOESS, the method has the advantages that the performance is excellent in the aspect of reducing the metabolite peak intensity variability, and the data stability is remarkably improved. In the subsequent multivariate statistical analysis, the classification accuracy is greatly improved, the comparability among different batches of data is also remarkably enhanced, reliable data support can be provided for discovery of disease biomarkers, and the method plays a key role in large-scale metabonomics research.

The invention discloses a high arch dam global deformation analysis method and system fusing InSAR and measuring point data, particularly relates to the technical field of radar interference deformation monitoring, and is used for solving the problem of inaccurate shielding failure compensation. According to the method, data stability is guaranteed by obtaining InSAR image data and extracting sight line direction displacement in combination with coherence indexes, a key measuring point deformation sequence is collected, an InSAR result is calibrated based on stable reference points, data consistency is improved, a projection correction coefficient is constructed by using a dam body three-dimensional structure model, the sight line displacement is inversely solved into structural normal displacement, and the accuracy of the dam body three-dimensional structure model is improved. Obtaining an initial deformation value of the real structure meaning; according to the method, a spatial coupling map of measuring points and InSAR pixels is constructed for a shielding failure area, deformation compensation of the failure area is completed based on an edge weight, finally the deformation compensation result is remapped to a three-dimensional structure model, measuring point data restoration is performed on a high arch dam, and structural plane-level deformation visualization and trend analysis are realized more quickly and more accurately.

The invention is suitable for the technical field of semiconductor testing, and provides a data acquisition method and device based on a DDIC chip, and testing equipment, and the data acquisition method comprises the steps: receiving a test pattern, controlling the DDIC chip to output a corresponding gray scale voltage signal, and achieving the comprehensive testing of the response capability of the chip in a full gray scale range; secondly, a target acquisition link composed of functional units including impedance conversion, single-ended to differential conversion, programmable gain amplification, filtering, analog-to-digital conversion and the like is utilized, so that the signal driving capability and the anti-interference capability are effectively improved, meanwhile, high-frequency noise and nonlinear distortion are reduced, and the basic quality of sampled data is guaranteed; on the basis, sampling optimization processing is carried out on the sampling data based on the FPGA unit, and the data stability is improved. According to the scheme, through high-precision transmission of the signal link, the data acquisition precision of the DDIC chip is improved, and then the technical requirements of high-precision DDIC chip testing are met.

The invention discloses a method for determining the demulsification speed of emulsified asphalt, and relates to the technical field of online detection and intelligent monitoring of road engineering materials, and by integrating a lightweight time sequence prediction model and a self-adaptive processing mechanism, the practicability and reliability of the determination of the demulsification speed of the emulsified asphalt are remarkably improved; in the aspect of portability, an edge model based on a gating circulation unit structure is adopted, so that the dependence on computing resources is reduced, the method can be operated on handheld equipment, the problem that traditional laboratory equipment is heavy is avoided, and construction personnel can conveniently and quickly deploy the equipment on site; the real-time performance is enhanced, the adaptive sliding window dynamically adjusts the window length and step length according to the data stability to ensure that the inference frequency is matched with the demulsification process, and the model can immediately respond to environmental changes such as temperature fluctuation and output a demulsification speed estimated value without obvious delay in combination with an online learning mechanism, so that the paving and compacting opportunities are guided; and construction interruption is reduced.

The invention discloses a charging pile thermal runaway intelligent protection method and system based on edge calculation, and relates to the technical field of charging pile thermal runaway protection. Comprising the following steps: S1, collecting thermal runaway multi-mode sensing data in real time, and carrying out data preprocessing; a charging pile thermal runaway multi-mode abnormal state is judged, and an abnormal feature data packet is generated; s2, multi-modal abnormal feature vectors are constructed, the thermal runaway risk probability is evaluated, and thermal runaway risk grading protection of the charging pile is carried out; s3, the response effect of thermal runaway risk grading protection is quantified, and thermal runaway risk grading protection is adjusted; and S4, monitoring and feeding back the thermal runaway risk, and optimizing algorithm parameters and a thermal runaway risk grading protection strategy. The problems that an existing charging pile thermal runaway protection system is difficult to adapt to complex working conditions, multiple in false alarm and missing alarm, lagging in response and insufficient in protocol compatibility and data stability, and consequently the thermal runaway risk is difficult to recognize and protect timely and accurately are solved.

The invention relates to the technical field of cloud data synchronization, in particular to a diabetes management-oriented cloud data synchronization method, which comprises the following steps: based on a blood glucose monitoring record, unifying a time zone and verifying a device serial number, generating a terminal version identifier, comparing a cloud version to screen missing entries, and identifying time abnormality and a device source. And forming a version difference mark, judging a missing range and a conflict identifier, updating a synchronization state after sorting, and counting the number of synchronization entries. According to the method, the problems of additional recording of historical data and version conflicts in data synchronization are effectively solved by introducing a dynamic rollback mechanism and timestamp difference comparison, clock differences between devices are automatically detected and adjusted in the synchronization process, timely updating and consistency of data are ensured, invalid synchronization operations are reduced through an intelligent conflict resolution mechanism, and the synchronization efficiency is improved. The accuracy and timeliness of data in diabetes management are ensured, and the data stability and consistency in a multi-terminal environment are improved.

The invention discloses a data processing method and system of a chromatographic instrument, and relates to the technical field of data processing, and the method comprises the following steps: collecting whole-course original detection signals and external interference signs generated in a chromatographic analysis process, carrying out time alignment under a unified time scale, generating an interference rhythm index, and calculating the interference rhythm index; the reference is used as a unified reference for subsequent signal comparison; and based on the interference rhythm index, performing phase drift comparison on the acquired signal, calculating the phase difference between the detection signal and the interference signal, drawing a beat frequency wandering graph, extracting candidate signal segments of pseudo-period interference according to beat frequency change, and generating a pseudo-period candidate segment list. According to the invention, by establishing the interference rhythm index and comparing the interference rhythm index with the phase drift, the time decoupling of the detection signal and the interference signal is realized, and the sampling anti-interference capability is improved; and through dynamic control of a false peak characteristic fingerprint draft and a misjudgment reason table, signal rhythm correction and peak identification optimization are completed, so that the detection accuracy and the data stability are improved.

The invention discloses a data fusion dynamic operation state evaluation method and device, and relates to the technical field of operation state evaluation methods, and the method comprises the steps: collecting original data from a plurality of sensors, monitoring equipment or an external system, and carrying out the normalization processing and abnormal value elimination operation of the collected original data, obtaining a preprocessed standardized data sequence; based on the preprocessed standardized data sequence, the dynamic confidence value of each data source at the current moment is calculated, the dynamic confidence value is comprehensively determined by three factors of historical consistency, environmental adaptability and data stability of the data sources, and a dynamic weight value corresponding to each data source is obtained; based on the dynamic weight value, performing weighted fusion operation on the standardized data sequence in a set time window, introducing a time decay factor to enhance the attention on recent data, and obtaining a fused state feature vector; and taking the fused state feature vector as an input.

The invention relates to the technical field of fault detection, in particular to an ultralow-temperature refrigerator refrigeration fault detection method. Information is collected through the information sensing layer, external sensing data and refrigerating system data are output, and the defect of a single external sensor is overcome; the external sensing unit and the refrigeration sensing unit respectively perform targeted acquisition, and when an external sensor is abnormal, fault detection can be realized through refrigeration system data, so that the stability and reliability of detection are improved, and the problem of detection failure caused by sensor faults is avoided; according to the method, the data stability index is obtained by identifying the external sensing data, the data health signal is obtained by performing health assessment on the data stability index, the external sensing abnormal total value and the refrigerating system abnormal total value are comprehensively analyzed, abnormal levels are divided, the corresponding fault alarm strategy is generated, the fault severity degree can be matched, and the fault alarm accuracy is improved. False report and missing report are reduced, and safe operation of the refrigerator is guaranteed.

The invention relates to the technical field of air pollution detection, in particular to a flue gas detector and a calibration detection method thereof, and the flue gas detector comprises a concentration fluctuation analysis module, an abnormal data screening module, an error interval collection module, a parameter trend analysis module and a period stability judgment module. According to the method, abnormal data and equipment drift influence are dynamically screened, an error change interval is actively collected, and through linkage comparison of multi-source parameter trends and separation of working condition disturbance, instrument abnormality and periodic offset signals, automatic screening of concentration data and operation parameters under multiple links is achieved, feature recognition and abnormal partition are associated, and the accuracy of the system is improved. The sampling effectiveness, the data stability and the instrument parameter change trend under the continuous detection working condition are managed in a layered mode, a traceable dynamic calibration chain is formed, the smoke detection consistency and the data exception handling capacity in the complex emission environment are remarkably improved, and an intelligent judgment mechanism of data grading rejection and trend aggregation is perfected.

The invention belongs to the technical field of medical image processing, and provides a multi-modal medical image analysis system, medium and equipment for gastrointestinal disease recognition, and the technical scheme is as follows: extracting multi-scale texture features and structural features of a gastrointestinal endoscopy color image and a gastrointestinal endoscopy OCT depth image respectively, and fusing to obtain a cross-modal feature sequence; based on the feature sequence added with the position code, learning a spatial corresponding relation of different modal data on blood vessel morphology and gastrointestinal tract wall interlayer structure; obtaining a multi-scale global context feature sequence and a local detail feature sequence based on the aligned cross-modal blood vessel and gastrointestinal tract wall interlayer structure features, and fusing the multi-scale global context feature sequence and the local detail feature sequence to obtain fused multi-modal features; obtaining an adjusted dense deformation field based on the fused multi-modal features; and performing coarse registration and fine registration based on the adjusted dense deformation field to obtain a registered gastrointestinal endoscopy color image and a registered gastrointestinal endoscopy OCT depth image. The anti-interference capability is strong, and the data stability is high.

The invention discloses a measurement system and method based on dynamic distance measurement adjustment, and belongs to the technical field of three-coordinate measurement, and the system comprises a three-coordinate machine main body, a dynamic distance measurement module, a data fusion module, a coordinate system calibration module and a data processing module. The dynamic distance measuring module divides data and adjusts measuring head parameters, the data fusion module outputs accurate data after preprocessing and denoising, the calibration module selects three points to establish a system, and the processing module monitors data fluctuation and generates a result; starting a system to collect initial contour, distance and shaft speed data of the workpiece; classifying, associating and analyzing the data; dynamically adapting sampling parameters; performing multi-source data fusion optimization; selecting a reference point, establishing a system and calculating coordinates of a to-be-measured point; monitoring data stability, and generating a three-dimensional model and a measurement result of the workpiece; according to the method, errors are reduced by dynamically adjusting parameters, optimizing data fusion and reliably calibrating.

The invention discloses a data recovery method and electronic equipment, and relates to the technical field of storage systems.The data recovery method comprises the steps that a virtual disk array is created according to virtual disks, and the virtual disks in the virtual disk array are divided into data disks and verification disks; writing the write-in data of the write-in request into a data disk, obtaining verification information according to the data written into the data disk, and writing the verification information into a verification disk; and if the abnormal data exists, performing data reconstruction on the abnormal data according to the data except the abnormal data in the virtual disk array and the verification information to obtain repaired data. The problems that a data error correction mode of a storage system is single, only underlying data processing abnormity can be sensed, but abnormal data cannot be recovered can be solved. According to the method, when any virtual disk in the virtual disk array has abnormal data, the abnormal data can be recovered and corrected by means of data reconstruction, and the data stability and data security of a storage system are guaranteed.

The invention relates to the technical field of image recognition control, in particular to a linear motion module accurate control method and system based on AI vision, and the method comprises the following steps: obtaining an interference fringe image and extracting a gray path, analyzing central point displacement to generate a coordinate sequence, repairing an interference feature position, and aligning the image and a control time sequence to generate a synchronization time table. The mapping structure response forms a set of control output configurations. According to the method, a peak path is constructed through interference fringe gray scale information in an image frame, central point pixel displacement is extracted, a coordinate migration sequence is constructed, fine-grained capture and tracking of an execution state are realized, an external interference area is identified according to image gradient change, vector repair is carried out, and image data stability and feature reliability are guaranteed. And aligning the repaired image response with a control instruction time sequence, constructing an impulse response lag statistical mechanism, realizing accurate mapping adjustment of the control frequency, and improving the control precision and response consistency in high-frequency displacement execution.

The invention relates to the technical field of automatic control, in particular to a trace oxygen analyzer multi-node cooperative verification system which comprises a disturbance recognition module, a pressure flow correction module, a node scheduling module, a response evaluation module and a performance trend module. And combining the flow change of the mass flow meter to sort time sequence data in a partitioned manner. According to the method, the disturbance performance of each node is summarized in real time by relying on dynamic acquisition of disturbance characteristic factors, node pressure and flow parameters are actively linked, scheduling optimization is executed according to the real-time response performance of the node, collaborative serial number distribution is realized by analyzing node response interval sequence fluctuation, and the scheduling optimization is realized by means of a periodic stability comparison rule. Cooperative degradation trend indexes are extracted and monitored in time, continuous observation of physical disturbance and performance trend of verification nodes is enhanced, and verification accuracy, early warning capability and data stability in a multi-equipment-node scene are improved.

The invention discloses a nonvolatile memory device based on CrMoGe2S6 / Ga2O3 heterostructure tensile strain and a construction method, and belongs to the technical field of nonvolatile memory devices. Comprising the following steps: vertically stacking a single layer of Ga2O3 and a single layer of CrMoGe2S6, and constructing two kinds of CrMoGe2S6 / Ga2O3 heterostructures; performing biaxial tensile strain on the CrMoGe2S6 / Ga2O3 heterostructure, calculating a magnetic ground state and an energy band of the CrMoGe2S6 / Ga2O3 heterostructure under different strains, and screening out the CrMoGe2S6 / Ga2O3 heterostructure which is represented as a ferromagnetic state; and on the basis of the screened CrMoGe2S6 / Ga2O3 heterostructures, two CrMoGe2S6 / Ga2O3 heterostructures with the same tensile strain are selected to construct the nonvolatile memory device. Ferroelectric Ga2O3 is introduced to serve as a switch, the electronic property of CrMoGe2S6 is controlled by the polarization state of Ga2O3, the Ga2O3 which is electrically polarized upward P does not change the semiconductor characteristic of CrMoGe2S6, and the Ga2O3 which is electrically polarized downward P enables the CrMoGe2S6 to present semimetallic property; therefore, the non-volatile electric control of the CrMoGe2S6 between the antiferromagnetic semiconductor and the semimetal is indirectly realized; the characteristic is especially important for a memory device, and can significantly reduce energy consumption and improve data stability.

The utility model discloses a rapid satellite alignment device based on a Beidou compass, which comprises a main control module, a double-receiving mechanism, a signal fusion processing module, an angle adjusting mechanism and a mounting bracket, and is characterized in that the angle adjusting mechanism and the main control module are mounted on the mounting bracket; the double-receiving mechanism and the signal fusion processing module are installed on the angle adjusting mechanism, and the master control module is provided with a signal processing unit and a control unit. According to the method, errors possibly caused by a single signal can be reduced by providing redundant data, so that the accuracy of beam pointing is improved, interference can be effectively eliminated by double receiving of the same satellite signal, the anti-interference capability of a system in a complex environment is enhanced, and data stability is ensured.

The present application provides a kind of spun yarn product elongation at break detection method, comprising the following steps: sample preparation and pretreatment step carries out sample form measurement and mathematical modeling step;Stretching test equipment calibration and parameter setting step;Stretching test execution and data acquisition step;Elongation at break calculation and preliminary analysis step;Stress, strain relationship analysis step;Data stability analysis step;Outlier detection and processing step;Result comprehensive analysis and report generation step;The present method realizes the accurate analysis of yarn form and stress, strain relationship, improves the accuracy of test result;Data stability and outlier detection analysis are carried out, ensure the reliability and stability of test data;For the performance evaluation and improvement of yarn provides strong support.The present method has feasibility and practicality, can significantly improve the efficiency and accuracy of spun yarn product elongation at break detection.

The application discloses a posture and force monitoring device for a wheel-step type mechanized operation platform, which comprises a wheel-step type chassis body, an embedded inertia detection assembly, a composite force detection assembly, a data transmission module and a central control module. The embedded inertia detection assembly is arranged in a rotary base and is used for collecting a posture angle and acceleration. The composite force detection assembly comprises a shaft pin type multi-dimensional force sensor and a pin shaft load sensor, which in-situ replace a mechanical pin shaft, collect wheel leg ground contact force and support force of a support claw, and each component is connected to the central control module through the data transmission module. The application breaks through a blind area of a single sensor through multi-source sensing fusion, accurately identifies a virtual leg and a posture anomaly, does not change an original structure to guarantee strength, relies on box protection, heat insulation and shock absorption design to ensure data stability in a complex environment, optimizes posture estimation precision through a weighted fusion algorithm, and improves operation safety and environmental adaptation capability of the platform in a severe working condition through double logic early warning.

The invention provides a dynamic LOD road model generation method and system based on ADAS data stability evaluation, and the method comprises the following steps: obtaining ADAS data collected by an ADAS system for road sampling points in a vehicle driving process, and carrying out the frame budget-based adaptive framing processing of the ADAS data to obtain framed ADAS data; calculating road data information of the road sampling points based on the framed ADAS data; wherein the road data information comprises curvature stability, gradient compliance and road continuity; performing stability evaluation on the ADAS data based on the road data information to obtain an ADAS road stability score; deciding the LOD level of each road section based on the ADAS road stability score and the real-time position of the vehicle; and based on the road data information of the road sampling points and the LOD level, generating a three-dimensional road model of which each frame synchronously updates the LOD level once. The LOD level is determined in combination with the ADAS road stability score and the vehicle real-time position, model updating is driven through frame budget, and vehicle-mounted end computing resources are effectively saved.

The application discloses an environmental monitoring data analysis method and related device, relates to the technical field of environmental monitoring, obtains the standard sample data consistent with the attribute of the to-be-analyzed environmental monitoring data, calls a density-based clustering algorithm to process the two kinds of data, obtains a clustering result, and in the case that a turning point in a K-distance graph of the to-be-analyzed environmental monitoring data does not satisfy a preset turning point condition, determines a reference turning point by using a sliding window algorithm, so that the clustering result is more accurate; when the clustering result satisfies a condition, multi-dimensional quality analysis is performed on the to-be-analyzed environmental monitoring data, and the efficiency and accuracy of environmental monitoring data analysis are further improved; when the to-be-analyzed environmental monitoring data is subjected to multi-dimensional quality analysis, at least data stability and correlation of the to-be-analyzed environmental monitoring data are analyzed, so that the accuracy of an analysis result obtained by multi-dimensional analysis is greatly improved, and the accuracy of application of the analysis result to other scenes, such as data quality evaluation, is further improved.

The invention provides an apparent resistance correction method and system based on a resistivity method, a medium and equipment, and relates to the technical field of electric field detection. According to the technical scheme provided by the invention, the intra-group control scheme is generated by matching the preset optimization target corresponding to the attribute tag, adjustment is performed according to the inter-group influence factors to form the target control scheme, and the measurement strategy can be adaptively adjusted according to the geologic features. After the vector receiving voltage is acquired, vector synthesis is performed on the initial apparent resistance according to the horizontal included angle to obtain the target apparent resistance, so that the problem that a single component signal is weak and is easily interfered by noise in a traditional resistivity method is effectively solved. When component signals in a certain direction are particularly weak or abnormal, negative apparent resistivity can be avoided by adopting a vector synthesis mechanism, and the data stability is improved. The convergence of the inversion algorithm and the stability of the solution are obviously improved by improving the quality of the final input data and fully utilizing the vector information, vector synthesis can be carried out on component signals, and the inversion effect of the resistivity method is improved.

The application provides a resistivity-based apparent resistivity correction method, system, medium and equipment, and relates to the technical field of electric field detection. The technical scheme provided by the application generates an in-group control scheme by matching a preset optimization target corresponding to an attribute label, adjusts a target control scheme according to inter-group influencing factors, and can adaptively adjust a measurement strategy according to geological characteristics. After collecting a vector receiving voltage, the initial apparent resistivity is vector synthesized according to a horizontal angle to obtain a target apparent resistivity, effectively solving the problem that a single component signal is weak and susceptible to noise interference in the traditional resistivity method. When a certain direction component signal is particularly weak or abnormal, the vector synthesis mechanism can avoid the appearance of negative apparent resistivity, improving data stability. The improvement of the final input data quality and the full use of vector information significantly improve the convergence of the inversion algorithm and the stability of the solution, can perform vector synthesis on the component signal, and improve the inversion effect of the resistivity method.

The invention relates to the technical field of cloud platform computing, in particular to a waste weighing association method and system based on time sequence and data stability, and the method comprises the steps: collecting a pressure signal flow of a weighing sensor, and recognizing a putting behavior feature according with a preset putting mode through monitoring the pressure gradient change rate of the pressure signal flow, anchoring an effective putting time window; acquiring an identity recognition event triggered by the identity recognition module, performing delivery affiliation verification on the identity recognition event and the effective delivery time window, and calculating a business association degree; obtaining visual contour information of a weighing platform material, calculating a material projection area according to the visual contour information, carrying out weight-to-volume ratio verification in combination with a pressure stable value in an effective putting time window, and judging the authenticity of current weighing data; and in a stationary period after a single association task is finished, after no residue of the weighing platform is confirmed according to the visual contour information, the deviation value is updated to a follow-up zero compensation value, and the measurement reference maintenance of the system reference is completed.

The invention relates to a field programmable gate array (FPGA) method for increasing communication distance and communication data stability, which relates to the technical field of communication and comprises the following steps: firstly, acquiring a clock signal and a data signal corresponding to serial data; then, according to a plurality of clock sampling points corresponding to the clock signal, obtaining a filtered clock signal; in response to the detected rising edge of the filtered clock signal, starting data latching, and determining a plurality of data sampling points corresponding to the rising edge in the data signal; obtaining filtered data signals according to the numerical values corresponding to the plurality of data sampling points; and finally, carrying out self-synchronization coding on the filtered clock signal and the filtered data signal to obtain coded serial data. According to the scheme, the data signals are filtered through the data sampling points corresponding to the rising edges in the clock signals, the coded serial data are obtained through self-synchronization coding, interference in the serial data is reduced, and the reliability of the serial data is improved.

The invention relates to the technical field of laser control circuit design, in particular to a multifunctional laser control device and method.The multifunctional laser control device comprises a main control board, a signal isolation module used for enhancing information stability is arranged on one side of the middle of the upper surface of the main control board, and a digital-analog information conversion module is arranged on the other side of the middle of the upper surface of the main control board; according to the multifunctional laser control device, an integrated control method and a single-chip microcomputer technology are utilized, a human-computer interaction interface can be unified upwards, laser control can be unified downwards, customized operation of laser welding and laser cutting in different application scenes is greatly reduced, and data stability of a control system matched with the multifunctional laser control device can be improved through direct connection between plates.

The invention discloses an optical fiber partition layout method for roadway roof deformation monitoring, and relates to the technical field of roadway surrounding rock safety monitoring, and the method comprises the following steps: (1) partition: a roadway with faults and wrinkles is a geological structure region, and a roadway without faults and wrinkles is a conventional condition region; and (2) arranging optical fibers, namely arranging one optical fiber on a row of anchor rods or anchor cables along the trend of the roadway in a zigzag manner in a conventional condition area, and respectively arranging one optical fiber on at least three rows of anchor rods or anchor cables along the trend of the roadway in a geological structure area in a zigzag manner. The method has the beneficial effects that the accuracy of deformation monitoring of the roadway roof under complex conditions is improved, the problems that differential deformation is not considered and the applicability of key areas is insufficient in the prior art are solved, and the defects that the monitoring precision is insufficient due to inconsistent exposed lengths, and the reliability of the system is improved are overcome. And the data stability is enhanced.

This invention relates to the fields of smart city and machine learning technology, specifically a method for continuous self-optimization of urban governance models based on data closed-loop feedback. The scheme involves: acquiring raw waveform data and operating condition reference signals from vibration sensors of urban lifeline facilities; generating a time-frequency energy spectrum matrix through time-frequency transformation; decomposing this matrix into slow-changing and fast-changing components using a machine learning model; removing slow-changing components correlated with long-term operating conditions; labeling the remaining slow-changing components as the first component and the fast-changing components as the second component; generating a frequency-related compensation curve based on the difference between the first component and the historical energy spectrum; performing multiplicative correction; and simultaneously calculating a coupling health index, triggering a calibration work order and updating the historical energy spectrum when the index falls below a threshold. This invention achieves closed-loop optimization of sensor coupling state self-sensing, self-compensation, and self-calibration, significantly improving the long-term data stability and accuracy of urban lifeline monitoring systems.

The invention provides a high earth and rockfill dam core wall pore water pressure test method, and belongs to the technical field of indoor soil mechanics tests. According to the method, the structure of a traditional compression consolidation apparatus is improved, a sealing steel barrel which is provided with a double-layer sealing ring and can lead out a wire harness is adopted, and a high-precision osmometer, a soil pressure meter and a high-frequency data acquisition system are combined, so that the compression consolidation apparatus can be fully sealed under the conditions of complete sealing and high pressure; and the generation and change rule of pore water pressure in the filling process of the core wall of the high earth-rock dam can be accurately simulated. The method comprises the steps of soil sample preparation, saturation treatment, instrument burying, graded loading, data acquisition and the like, and can be used for researching the influence of different water contents, loading rates and clay content on the pore water pressure. Test results show that the method can still keep good sealing and data stability under the condition of 5 MPa high pressure, has high precision, high repeatability and high reliability, and can provide scientific basis for high earth and rockfill dam core wall design and construction safety.

This invention discloses a method for testing the crosslinking degree of hard carbon precursors and a method for predicting the capacity of hard carbon, belonging to the technical field of performance evaluation of battery anode materials. The method includes the following steps: preparing a control sample and a test sample of the precursor; collecting infrared spectral data of the control sample and the test sample under the same conditions; extracting the peak area of ​​characteristic functional groups in the infrared spectral curves using peak fitting; calculating the crosslinking degree of the hard carbon precursor according to a formula; verifying the accuracy of the detection method using conventional dynamic mechanical thermodynamic analysis; and establishing a mathematical relationship between the crosslinking degree of the precursor sample and the specific capacity of the derived hard carbon. This allows for the measurement of the crosslinking degree of the precursor sample and the prediction of the sodium storage capacity of the hard carbon anode material. Compared with existing technologies, this invention has stronger universality, simpler operation, quantitative analysis, and better data stability, making it an advanced detection technology for hard carbon anode materials.