592 results about "Time curve" patented technology

The invention discloses a device for measuring flowability of explosive modeling powder, which comprises a step-press-loading analogue unit, a timing and weighing unit and a computer control unit, wherein the step-press-loading analogue unit directly and indirectly drives a screw rod which extends into a blanking bin to rotate and perform reciprocating movements along an axial line and drives a pusher dog in the blanking bin to perform the reciprocating movements along an arc section through the combined action of a cylinder and a pneumatic reversal valve so as to ensure that the explosive modeling powder in the blanking bin falls into the timing and weighing unit, and the process more truly imitates an explosive conveying process of an explosive step-press process. The timing and weighing unit transmits a weighing value of the explosive modeling powder which falls in the timing and weighing unit to the computer control unit in real time, and the computer control unit calculates the instantaneous flow speed of the explosive modeling powder of a north side and generates a flow speed-time curve according to sampling data. The device can measure the flowability of the explosive modeling powder so as to provide an objective basis for choosing a proper explosive step-press process for the explosive modeling powder.

The invention relates to the technical field of power grid equipment management, in particular to a power grid equipment state intelligent evaluation and prediction method based on artificial intelligence. Through data acquisition and processing and a real-time monitoring and fault early warning mechanism, in the data acquisition stage, historical data are called, key electrical parameters and fault information are acquired in real time by means of a sensor, a data and fault association mechanism is established, and in the real-time monitoring link, the similarity between a real-time curve and a standardized curve is calculated, so that the fault early warning accuracy is improved. Once the similarity reaches a threshold value, the system quickly gives an early warning, preliminarily judges the fault position, more accurately detects the specific condition of the fault position, and meanwhile, performs troubleshooting according to the weight of the fault position, can quickly position the fault and deal with the fault in time, reduces the power failure time of the fault, guarantees the stable power supply of a power grid, and reduces the influence on the production and life of a user. The method is of great significance in improving the safe operation level of the whole power grid.

The invention discloses a blisk finish machining tool path compensation method, a medium and a program product, and relates to the technical field of tool path compensation, and the method comprises the steps: collecting historical blisk machining tool data, building a tool wear prediction model, estimating wear prediction values of a tool in different time periods according to the built wear model, fitting the predicted wear value with time, and drawing a tool wear time curve; and according to the influence of the tool wear on the finish machining of the blisk, the tool wear is divided into a plurality of time periods in combination with the tool wear time curve, machining compensation models of different time periods are established, and meanwhile, the current blisk is subjected to blade grouping. According to the method, the tool wear is accurately predicted and compensated, the tool compensation is corrected in combination with the product detection result, and the machining time period is reasonably divided, so that the machining precision and efficiency of the blisk can be effectively controlled and improved in different stages of the tool wear.

The invention discloses an egg quality detection system and method based on multi-sensor fusion, and relates to the technical field of multi-dimensional data process.The method comprises the steps that texture features are extracted from visible light images, and feature wavelengths are extracted from spectrums; pressure distribution and shell deformation in the pressing process are synchronously collected; recording a pressure-time curve and a deformation-time curve, extracting characteristic parameters, and constructing a three-dimensional dynamic model; performing wavelet transformation on the response curve of each sensor, extracting time-frequency domain characteristics, and generating a smell fingerprint spectrum; scanning the surface of the egg to excite resonance response, recording a sound pressure signal, and converting the sound pressure signal into frequency domain data through fast Fourier transform; and presetting a business rule, and generating a final decision by combining the model output with a rule matching result. The pressure feature extraction module, the smell feature extraction module and the crack degree quantification module are arranged to realize data depth association, and the quality inspection credibility is improved through an interpretable decision model.

The invention provides an oil seal press-fitting abnormity real-time detection method based on pressure displacement curve analysis, and relates to the technical field of oil seal assembly control. Pressure displacement data acquisition is executed and a real-time pressure displacement curve is fitted when press-fitting equipment is started; based on displacement progress threshold triggering stage switching of the time sequence displacement data, an association stage characteristic curve is called from the oil seal press-fitting reference template; comparing the characteristic curve in the association stage with the real-time pressure displacement curve to solve a real-time curve deviation vector; and according to the real-time curve deviation vector mapping physical failure abnormal mode, self-adaptive adjustment of oil seal press-fitting process parameters is triggered. The technical problems that in the prior art, a continuous press-fitting process is adopted for oil seal assembly, rubber stress concentration is caused, hydraulic locking is formed due to lubricant retention, and the press-fitting depth is out of control are solved. Physical failure prevention in the oil seal assembly process is achieved, it is guaranteed that the press-fitting depth meets the technological specification tolerance in the whole process, oil seal assembly defects are restrained, and the sealing reliability of an engine is improved.

A self-adaptive dynamic stratum recognition method based on multi-source drilling parameters comprises the steps that firstly, the drilling rate, the rotating speed and oil pressure parameters are collected through a sensor set, a drilling depth-time curve is constructed, time sequence data are segmented through a sliding window, and filtering, standardization and abnormal value processing are carried out; calculating a mean value, a standard deviation and skewness statistical characteristic of each parameter in the window, and constructing a nine-dimensional characteristic vector in combination with an energy ratio and a covariant coefficient; updating a stratum feature library based on an incremental learning algorithm, and dynamically optimizing a clustering center to realize autonomous evolution; a confidence coefficient threshold value is set according to the statistical characteristics and the clustering distance, and stratum type dual discrimination is completed; by comparing a real-time judgment result with manual sampling data, the generalization of a learning rate parameter optimization model is dynamically adjusted; and outputting a stratum type corresponding to the current drilling depth and a confidence degree evaluation result based on the optimized clustering model. According to the invention, by improving a data processing mechanism and an adaptive decision rule, high-precision and strong-generalization real-time stratum identification is realized.

The invention discloses a rapid imaging method and system for a multi-time-sequence magnetic resonance image group, particularly relates to the technical field of multi-time-sequence magnetic resonance image processing, and is used for solving the problems of low imaging speed and poor time sequence consistency. According to the method, sampling reference distribution is constructed in a frequency domain, the reconstruction difficulty is predicted by using graph convolution, a multi-scale under-sampling mask is generated, and sampling is distributed according to channel sensitivity, so that high information priority and sparse controllability are realized; sending the registered sparse data into a space-time-parameter three-domain network, extracting structural, dynamic and parameter characteristics, and obtaining an image group with a clear structure and a stable time sequence through cross-domain fusion, non-rigid body registration and wavelet domain artifact suppression; and forming a comprehensive score by using four indexes output by the quality scoring network, performing reinforcement learning feedback, adaptive adjustment of a sampling rate, a mask, a reconstruction parameter and closed-loop optimization, and finally outputting the comprehensive score together with a sequence parameter, a timestamp and a score, and generating a structure comparison diagram and a time curve to facilitate quality control and presentation.

The invention relates to the technical field of numerical control machining, in particular to an automatic input system and method for geometric parameters of a numerical control tool. The method comprises the following steps of obtaining point cloud data and material characteristics of a tool, removing abnormal points to clean the data, extracting the edge contour of the tool, performing geometric parameter mapping through the edge contour, determining geometric characteristics of the tool, reconstructing a tool framework, obtaining a numerical control machining task, and performing cutting load simulation on the reconstructed tool. Analyzing the initial wear data, performing heat effect prediction based on cutting load, calculating the thermal deformation degree of the cutter, performing deformation compensation on the initial wear data, generating geometric deformation data, drawing a deformation-time curve, performing time sequence tracking parameter compensation according to the change process of the cutter, and realizing real-time recording and updating. According to the method, the management efficiency and the machining precision of the numerical control tool are integrally improved, and the stability and predictability of the production process are enhanced.

The method for detecting the comprehensive working performance of the fresh concrete provided by the invention comprises the following steps: pouring the fresh concrete into a certain channel in a detection container which is provided with a plurality of channels and the bottoms of which are communicated with one another, and detecting the comprehensive working performance of the fresh concrete when the liquid level height of the fresh concrete in each channel is kept unchanged, measuring the liquid level height of the concrete in each channel and detecting the quality of the concrete in the container; a discharging opening in the bottom of the detection container is opened, the concrete in the detection container is discharged by means of self weight, in the discharging process, the mass of the discharged concrete or the discharging flow speed of the concrete is measured, and after discharging is completed, a concrete discharging mass-time curve or a concrete discharging flow speed-time curve is obtained; according to a measurement result, a series of indexes including the fluidity, viscosity, uniformity and apparent density of the concrete are obtained through arrangement and conversion and serve as a comprehensive evaluation result of the working performance of the fresh concrete. According to the method, multiple working performance indexes of the concrete can be given at a time, and mutual complementary interpretation can be carried out.

The invention discloses an ore pillar stability in-situ monitoring system which comprises a top plate grouting anchoring mechanism, a top plate settlement and weighting monitoring mechanism and an ore pillar circumferential deformation monitoring mechanism, and the system effectively fixes an upper structure on an ore body top plate through an air inflation pipeline, a grouting pipeline, an exhaust pipeline and a serial alarm circuit which are arranged in the system. Furthermore, real-time measurement of the stress variation and the self-degradation deformation of the pillar is realized through comprehensive cooperation of multiple sensors, a jack and a monitoring line, and a foundation is laid for the stability evaluation of the pillar. Based on the system, the invention further provides an in-situ assessment method for the stability of the jamb, the stable state of the jamb is divided into four grades of extremely high, high, medium and low risks according to a deformation-time curve and a stress-time curve of the jamb, multi-index comprehensive grading characterization of the stability of the jamb is realized, and a foundation is laid for differentiated treatment of a goaf jamb group. Reference and guidance are provided for avoiding goaf collapse accidents.

The invention discloses an auxiliary decision-making system for cognitive competence assessment of old people, which relates to the technical field of cognitive auxiliary decision-making and comprises an environmental noise acquisition and feature extraction module, a time sequence fluctuation analysis module, a dynamic threshold reconstruction and judgment module, a cross-domain consistency calibration module, a multi-modal synchronous verification module and a dynamic threshold regulation and control module. According to the method, the environmental noise is dynamically analyzed, so that the defects of a fixed noise suppression threshold and a static feature extraction model in the traditional technology are overcome. A sound field energy distribution model is constructed in real time and time sequence fluctuation analysis is combined so that a noise fluctuation interval can be identified, a voice starting point detection threshold value is dynamically adjusted and evaluation precision is enhanced. Through multi-mode synchronous verification combining a reaction time curve and a facial movement track, a time offset error is corrected, a judgment standard is adjusted in real time according to noise changes, misjudgment and virtual high risk early warning are avoided, and therefore the accuracy and reliability of cognitive ability assessment of the old are improved.

The invention relates to a fatigue driving monitoring method, and relates to the technical field of vehicle safety. The method comprises the following steps: collecting a first face image of a driver in a preset time period in real time after the driver gets on the vehicle, and determining a face behavior feature threshold value of the driver; a second face image of the driver is collected in real time in the driving process; calculating a real-time face behavior feature value corresponding to each frame of second face image; determining a facial behavior characteristic change rate time curve according to a facial behavior characteristic threshold value of the driver and the real-time facial behavior characteristic value corresponding to each frame of second facial image, determining a facial behavior characteristic jump value and jump duration within a preset duration range before and after each moment, and determining a facial behavior characteristic change rate of the driver according to preset facial behavior calibration data. Outputting a facial behavior judgment result of the driver; and the fatigue evaluation grade of the driver is determined according to the face behavior judgment result, the vehicle state collected in real time and the driving duration. The fatigue state of the driver can be recognized and reminded, and the driving safety is improved.

The invention discloses a method and a system for determining macro-micro unified constitutive model parameters of creep relaxation aging. The method comprises the following steps: firstly, respectively fitting creep-time curves under a single process condition, calculating a corresponding weighted average value and an arithmetic average value, and respectively fitting the creep-time curves under multiple groups of process conditions by using the weighted average value and the arithmetic average value to obtain a first fitting error and a second fitting error; and comparing the first fitting error with the second fitting error, and updating the range of each material parameter until the overall fitting error accords with a preset expected value, so that the optimal material parameter can be obtained. According to the scheme provided by the invention, the range of the material parameters is updated by the dichotomy, the fitting times can be greatly reduced, and the fitting time is shortened.

The invention discloses a method and a system for recovering power supply of a power distribution network after a fault. The method comprises the following steps: reconstructing to obtain a reconstructed topology network of a target power distribution network; acquiring real-time voltage response data of the reconstruction topology network for continuously changing power simulation, and calculating voltage sensitivity among nodes; modeling the acquired data to obtain a power supply recovery model; operating the power supply recovery model to obtain optimal power supply power-time curve data corresponding to each power resource unit; and controlling each power resource unit to perform power supply recovery on the target power distribution network after the fault according to the corresponding optimal power supply power-time curve data. According to the method, the power supply output time curve of each different-flexibility output power resource under the condition that the power supply recovery model gives consideration to the recovery speed and the voltage recovery stability is acquired, so that the power recovery resources can be utilized more fully and reasonably, the power fluctuation in the recovery process is balanced, and stable recovery and operation of the power distribution network are ensured.

The invention discloses an ultra wide band direction finding information extraction method based on a multi-input single-output delay superposition network. The method comprises the following steps: acquiring an antenna receiving signal and an attitude transformation matrix of an antenna; processing an antenna receiving signal to obtain a time point of a first peak leading edge detection threshold value and pulse sequence data in a complex form; carrying out 64-time up-sampling processing on the pulse sequence data in the plural form, and drawing an amplitude-time curve and a phase-time curve; determining a peak value corresponding to the adjacent antenna according to the peak value leading edge time point; calculating the peak values corresponding to the adjacent antennas to obtain the time difference of arrival and the phase difference of the adjacent antennas; and ultra-wideband direction-finding information positioning is realized. According to the invention, group delay can be carried out on the ultra-wideband pulse signal by adopting the delay line with the given length, and the ultra-wideband direction-finding information positioning precision is improved. The ultra wide band direction finding information extraction method based on the multi-input single-output delay overlay network can be widely applied to the technical field of ultra wide band positioning.

The invention discloses a bridge structure monitoring method based on multi-source data and digital twinning and a related device, and relates to the technical field of bridge engineering.The method comprises the steps that an initial finite element model of a target bridge is constructed based on a design drawing and structural parameters of the target bridge, and the initial finite element model of the target bridge is constructed based on the initial finite element model and preset load conditions; calculating to obtain simulation mechanical response data of each grid node of the target bridge; based on the simulation mechanical response data and the obtained actually measured mechanical response data of each grid node of the target bridge, obtaining a corrected finite element model; inputting the obtained traffic load data passing through the target bridge into a digital twinborn calculation model constructed based on the corrected influence line data for numerical calculation to obtain an overall structure response cloud picture and a structure response-time curve of the key monitoring point, and fusing the overall structure response cloud picture and the structure response-time curve with the obtained three-dimensional visualization model to obtain a three-dimensional visualization model; and obtaining the structural state of the target bridge. According to the invention, accurate monitoring and real-time state evaluation of the bridge structure are realized.

The invention relates to a load spectrum determination method and device, electronic equipment, a storage medium and a vehicle. The method comprises the steps that motion characteristic parameters of each historical driving cycle in at least one historical driving cycle of each vehicle in multiple vehicles of the same vehicle type are acquired; based on the motion characteristic parameters of each historical driving cycle of each alternative vehicle, determining at least one kinematics fragment belonging to different motion types from a plurality of kinematics fragments to obtain a plurality of typical kinematics fragments, the plurality of kinematics fragments being kinematics fragments corresponding to each historical driving cycle of each alternative vehicle, each kinematic fragment is used for indicating a speed-time curve of a corresponding historical driving cycle; splicing the plurality of typical kinematics fragments to obtain a road spectrum of a target time length; and inputting the road spectrum of the target duration into a whole vehicle dynamics simulation model of the target vehicle model, and performing simulation to obtain a load spectrum of a target rotating part of the target vehicle model.

The invention discloses a soft tissue constitutive parameter calibration method in a soft tissue-skeleton bird body model for bird strike simulation, and the method comprises the construction of a soft tissue-skeleton bird body finite element model and finite element reverse analysis based on flat bird strike. Dividing wing bones, leg bones and head and neck parts in the bones of the bird body into hexahedral unit grids, dividing wishbones, pecking bones, fossil protrusions and ribs into shell units, and dividing soft tissues into SPH particles; further obtaining bone elastic-plastic constitutive parameters through a static compression test, and endowing the bone units with the bone elastic-plastic constitutive parameters; an objective function is set as a mean square error between a flat plate center point pressure-time curve obtained by a real bird body impact flat plate test and corresponding curve data calculated by soft tissue-skeleton bird body impact flat plate finite element simulation, and soft tissue constitutive model parameters are inversely calibrated by adopting a genetic algorithm; and model and material parameter support is provided for bird strike simulation of a high-fidelity aircraft structure.

The invention provides an active power-assisted exoskeleton digital twinning sensing control system and method, and the system comprises an exoskeleton physical entity worn on a human body, a sensing feedback module which is used for obtaining the posture information of the exoskeleton physical entity, and an intelligent control module which is used for carrying out the data processing of the posture information. The digital twin module is used for receiving second data information processed by the intelligent control module, adjusting the posture of a virtual exoskeleton simulating an exoskeleton physical entity according to the second data information, and fitting the posture into a downloadable real-time curve for algorithm optimization iteration of the intelligent control module. The precision and the response speed of the identification and assistance algorithm are improved; according to the method, by combining mutual mapping and feedback control between the digital twin and the physical entity, reliable data information and optimization parameters are provided for production, design, debugging and use stages of the exoskeleton physical entity, and both wearing comfort and assistance efficiency of the exoskeleton physical entity are achieved.

A secondary disaster early warning method based on ground-based SAR monitoring of deformation data includes (1) real-time monitoring of a secondary disaster unstable area through ground-based SAR to obtain deformation monitoring data; (2) constructing a displacement-time curve generated by the secondary disaster unstable area over time; setting a monitoring period, and based on the displacement-time curve, constructing a displacement change triangular area model; (3) based on the displacement change triangular area model, constructing an area-time curve, and obtaining the area-time curve change trend and the displacement triangular area in the displacement-time curve according to the monitoring period; (4) dividing the secondary disaster development process into an initial deformation stage, a constant velocity deformation stage, and an accelerated deformation stage; (5) setting early warning levels corresponding to each stage for phased secondary disaster early warning; and (6) quickly and comprehensively identifying the secondary disaster development stage and deformation evolution trend.

The invention relates to the technical field of die detection, and discloses a stamping die detection and adjustment method and system based on use working conditions, and the method comprises the steps: obtaining a design drawing to create a stamping structure model, importing the stamping structure model into a physical field simulation platform, generating a stamping simulation model, and analyzing a standard power time curve of various stamping processing tasks; operation detection parameters of the stamping mechanism are obtained in real time, an actually-measured power time curve is drawn and compared with a standard power time curve, and stamping sub-action line segments with the power parameter deviation rate larger than a power deviation threshold value are recognized to generate resistance abnormal signals; a cooling suppression signal is generated based on the resistance abnormal signal and sent to a cooling assembly, and a temperature measurement sensor is controlled to detect abnormal temperature measurement data of the stamping structure; when the temperature deviation ratio of the abnormal temperature measurement data relative to the theoretical temperature data is greater than a temperature deviation threshold value, generating fault handling information; the method has the effect of improving the timeliness of stamping machining quality detection.

The invention relates to the technical field of landslide monitoring, and discloses a probability early warning method based on random fluctuation of a landslide deformation monitoring curve, and the method comprises the steps: obtaining landslide deformation monitoring data; establishing an accumulative displacement-time (S-t) curve to calculate the average deformation rate of the constant-speed deformation stage and the deformation rates vi of two adjacent measurements within the equal time interval; the dimensions of the vertical and horizontal coordinates of the S-t curve are subjected to consistent processing; if the improved deformation rate accords with normal distribution, calculating an improved rate mean value mu v and a standard deviation sigma v in equal time intervals; calculating a reliability index beta in equal time intervals; and calculating a damage probability according to the reliability index, and dividing a landslide early warning grade according to the damage probability. According to the scheme, the probability of landslide instability is reflected by monitoring the random change of the data, and the purpose of landslide monitoring and early warning is achieved; the tedious data processing of a traditional method is avoided, and the reliability and accuracy of early warning and forecasting are higher.

A method for thermomechanical testing of a test specimen, characterized in that the test specimen is subjected to a high-speed thermal mass flow and a force acting on the test specimen as a result of the exposure is continuously determined by a determination device and a force-time curve is determined therefrom. A test device for thermomechanical testing of a test specimen is also related.

The invention relates to an external multi-gap lightning arrester volt-second characteristic curve estimation method and device and a medium, and the method comprises the steps: selecting at least two different standard lightning pulses to carry out the lightning stroke test of an external multi-gap lightning arrester test system, and obtaining an initial initial voltage and a corresponding initial lightning stroke damage effect value; constructing each standard lightning pulse voltage-time curve, obtaining a damage effect integral function, and obtaining an initial external multi-gap lightning arrester voltage-time curve in combination with the initial initial voltage and the initial lightning damage effect value; based on the initial voltage-time curve of the external multi-gap lightning arrester, parameter optimization is carried out by utilizing a genetic algorithm, the voltage-time curve of the external multi-gap lightning arrester is obtained, and equipment and a medium are used for realizing the method. Compared with the prior art, the method has the advantages that the volt-second characteristic curve of the external multi-gap lightning arrester is directly estimated by using the genetic algorithm, and the characteristic curve capable of accurately reflecting the influence of the lightning stroke on the power distribution network is obtained through a simple estimation method.

The invention provides a construction method of a non-coupling blasting explosion load model and related equipment, and the method comprises the steps: describing non-coupling blasting explosion loads at different time stages through piecewise functions, and building a non-coupling blasting explosion load theoretical model; a pressure-time curve is collected through a non-coupling bursting pressure test, waveform analysis is carried out, and mechanical parameters are obtained; calibrating various parameters in the non-coupling blasting load theoretical model through mechanical parameters; various parameters in the non-coupling blasting explosion load theoretical model are input into a calculation program for calculation, and a non-coupling blasting explosion load model is obtained; the model provided by the invention can more accurately describe the action characteristics of the non-coupling blasting load, the peak values and the loading rates of the blasting shock waves and the blasting gas are directly controlled by respectively inputting the peak values and the rising time, so that the dynamic response of the structure under different peak values and loading rates can be conveniently researched, and the model has the advantages of simple model, high reliability and the like. The input parameters are few, and the applicability is wide.

The invention provides an etching end point detection method and semiconductor process equipment. The method comprises the following steps: collecting an etching progress signal capable of reflecting an etching process in an etching process; de-noising processing is carried out on the etching progress signal to obtain a curve of signal intensity changing along with time; filtering a false end point before a preset filtering time in the curve of the signal intensity changing along with the time; wherein the preset filtering time is a corresponding time point when the signal intensity rises or drops to a preset intensity threshold value after the set etching end point delay detection time; and obtaining a wave crest or a wave trough after the preset filtering time in the curve of the signal intensity changing along with the time, and carrying out extreme value verification on the wave crest or the wave trough to determine an etching end point. According to the invention, the accuracy of etching end point detection is improved, the influence of unstable etching end point detection on the key size of a product is avoided, and the stability of etching end point detection is improved.

The invention discloses an analysis and early warning method and device for tightening quality defects, and relates to the technical field of vehicle manufacturing, and the method comprises the following steps: collecting a torque and angle curve and a torque and time curve when a to-be-tightened point is tightened; based on the torque and angle curve and the torque and time curve, a real-time tightening curve is obtained through integration; and based on a preset abnormal tightening curve model corresponding to the to-be-tightened point, identifying a real-time tightening curve, and performing tightening quality defect early warning on tightening work. According to the method, the obtained real-time tightening curve is compared with the tightening abnormal curve model which is obtained through replacement and comprises the multiple tightening abnormal curves, so that tightening quality defect early warning is achieved, and the working efficiency is effectively improved on the premise that the early warning reliability is guaranteed.

The invention relates to a press machine fault early warning method, which comprises the following steps of: firstly collecting press machine processing data of different types of parts to obtain a plurality of sample data, further performing pressure value-time curve construction on all pressure data in each sample data, and then performing pressure value-time curve construction on all pressure data in each sample data; all the pressure value-time curves in each piece of sample data are fused into a coordinate system, and a fusion curve corresponding to each piece of sample data is obtained; cutting the fusion curve based on different working states of the press machine, calculating the change rate of the pressure corresponding to the press machine in different working states through the cut curve, and constructing and training a press machine wear model according to the change rate; and the prediction time of the wear fault of the press can be speculated by acquiring the real-time pressure data of the pressure.

The invention relates to the technical field of grouting tests, in particular to a three-dimensional high-pressure splitting grouting test method, which comprises the following steps: laying a rock mass sample in a large cubic test box, and applying a stable three-dimensional stress field to the sample in three directions by using a multi-hydraulic cylinder array; grout is injected in a stress maintaining state, grouting pressure, grouting flow and hydraulic cylinder data are synchronously collected to generate a pressure-flow-time relation curve, and meanwhile the grout diffusion process is directly observed through a visual window. According to the method, boundary interference is effectively reduced through a large-size sample and uniform loading, so that slurry is naturally diffused in a stress environment close to a real stratum. The dynamic stress compensation technology maintains boundary stability, and ensures that splitting expansion is not influenced by artificial constraint. A pressure-flow-time curve is combined with visual observation, and the diffusion rule of slurry in a three-dimensional stress field is clearly presented. According to the method, a test means closer to reality is provided for the underground engineering grouting process, and the reliability of grouting parameter design is remarkably improved.

The invention discloses a circuit breaker fault diagnosis system and method, and particularly relates to the technical field of circuit breaker diagnosis. According to the invention, through the root-mean-square value, kurtosis and zero-crossing frequency of the time-domain signal and the dominant frequency and high-frequency energy ratio parameters of the frequency domain, and by combining the stroke length, the average displacement speed and the root-mean-square error of the displacement time curve, the mechanical difference evaluation index of the circuit breaker is obtained, and the multi-dimensional evaluation of the mechanical state of the circuit breaker is realized. According to the method, initial similar cases are screened through early warning depth values, parameters are converted into coordinate points in a rectangular plane coordinate system, and the similarity between a current fault and an abnormal case is quantified through a line distance value and an Euclidean distance, so that subjective judgment errors are avoided, and the accuracy of abnormal reason estimation is improved; the problems that in the prior art, existing fault diagnosis mostly depends on single parameter analysis, and the fault of the circuit breaker cannot be rapidly positioned by combining a multi-parameter analysis result and historical data are solved.