344 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 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.

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 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 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 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 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.

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 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.

The embodiment of the invention discloses a stress relief effect evaluation method based on a hydraulic fracturing ground stress test. The stress relief effect evaluation method comprises the following steps: performing ground stress inversion on a to-be-relieved stress area according to hydraulic fracturing ground stress test data to determine an initial stress field; determining a stress concentration area in the excavation process of the stress to-be-relieved area according to the initial stress field; drilling a hole in the stress concentration area, carrying out a first hydraulic fracturing ground stress test in the drilled hole, recording a first pressure time history curve, and calculating the fracture surface stress before relieving; keeping the position of the packer in the first crustal stress test unchanged, continuously performing water injection fracturing, performing the hydraulic fracturing crustal stress test at the original position again, recording a second pressure time-history curve, and calculating the fracture surface stress after the second pressure time-history curve is relieved; and comparing fracture surface stress characteristic changes before and after fracturing, and evaluating the stress relief effect of the stress to-be-relieved area according to the fracture surface stress before and after relieving. The pain point that the stress relieving effect is difficult to quantitatively evaluate in the prior art is effectively solved.

The invention discloses a method for testing the impact resistance of a power battery and related equipment, and relates to the technical field of safety performance evaluation of the power battery, and the method comprises the steps: configuring the height parameters of a ball head and a falling ball in a falling ball impact test device based on the size of the power battery and a preset test standard; after a measurement module in the falling ball impact test device is calibrated, the ball head is released based on the falling ball height parameter; the data acquisition module is used for acquiring data to obtain a first time curve and a second time curve, the first time curve is used for representing a time-varying curve of dynamic impact force generated when the ball head impacts the power battery, and the second time curve is used for representing a time-varying curve of dynamic impact force generated when the ball head impacts the power battery. The second time curve is used for representing a curve that the deformation quantity of the surface of the power battery changes along with time under the impact action of the ball head; and obtaining a test result of the impact resistance of the power battery based on the first time curve and the second time curve.

The present invention discloses a method for correcting explosive initial conditions for numerical simulation of underwater explosions. The explosive is approximated as a sphere, and a computational model for a free-field spherically symmetric underwater explosion is established. Initial parameters of the explosive, including initial density and initial internal energy per unit mass of the explosive, are input into the JWL equation of state to obtain preliminary pressure-time curves at different spatial positions. The peak value of the shock wave pressure is extracted and compared with the results of an experiment or empirical formula. If the error does not exceed 5%, the initial internal energy per unit mass of the explosive is maintained unchanged; otherwise, the initial internal energy per unit mass of the explosive is adjusted until the error does not exceed 5%. The bubble pulsation period is determined and compared with the results of an experiment or empirical formula. If the error does not exceed 5%, the initial density of the explosive is maintained unchanged; otherwise, the initial density of the explosive is adjusted until the error does not exceed 5%. The present invention can accurately predict the peak value of the shock wave pressure and the bubble pulsation period, has the advantages of low cost and high efficiency, and can provide more accurate load input for the calculation of three-dimensional underwater explosion models.

The invention discloses a deep foundation bearing capacity characteristic value calculation method and system based on data fusion. The method comprises the steps that data collection is completed through a deep load test, and a load settlement curve and a settlement time logarithmic curve are formed; generating a smooth curve; identifying a slope mutation point of the curve by adopting a first-order derivative mutation method, wherein a load corresponding to the mutation point is a proportional limit load; if the slope abrupt change point is not recognized, the curve is set as a slowly changing curve; extracting the slope and the slope change rate of the curve under each level of load, and completing the judgment and correction of the limit load by fusing the multi-dimensional data of the two curves and combining preset thresholds including the settlement amount and the settlement stabilization time; and further calculating the bearing capacity characteristic value of the deep foundation by combining the numerical relationship between the ultimate load and the proportional limit load.

The invention relates to the technical field of pipeline safety monitoring, in particular to a long-distance pipeline risk event distinguishing monitoring system and method based on artificial intelligence. The artificial intelligence-based long-distance pipeline risk event distinguishing monitoring method comprises the following steps of S10, acquiring humidity time sequence data and anode output current time sequence data of soil in an area where a target pipe section is located, and respectively drawing a humidity time curve and a current time curve; acquiring a vibration signal acquired by the optical fiber sensing network; and S20, periodically fluctuating according to the current-time curve. According to the method, the relation between the regional self-adaptive humidity saturation interval and the corrosion rate is established, the huge cost for customizing a vibration analysis model for each region is avoided, the event recognition accuracy is improved under high-risk scenes such as coating damage by utilizing deep coupling of the corrosion state and vibration, and the event recognition efficiency is improved. And passive alarm is converted into active and accurate early warning based on humidity prediction.

The invention discloses an ant colony optimization energy focusing cable insulation damage positioning method and device, and relates to the technical field of cable detection engineering, and the method comprises the steps: generating a Gaussian envelope linear frequency modulation chirp detection signal, injecting the detection signal into a to-be-detected cable, and collecting an incident signal and an echo signal containing a reflection component; constructing a parameterized time-frequency analysis kernel function family under a Cohen type time-frequency distribution framework, and searching and optimizing kernel parameters by using an ant colony optimization algorithm; and calculating the time frequency distribution and energy-time curve of the signal based on the energy focusing time frequency analysis kernel function obtained through optimization, extracting the arrival time corresponding to an energy peak value, and realizing cable insulation damage positioning according to the reflection time delay and the propagation wave velocity. According to the method, energy peak focusing and peak position stability are enhanced while cross terms are restrained, defect positioning precision and robustness are remarkably improved, and the method is suitable for engineering online detection and automatic implementation of cable insulation damage.

The invention belongs to the technical field of data processing, and discloses a Mars probe temperature monitoring method and system based on time control factor optimization, and the method comprises the steps: obtaining simulated fire soil, and carrying out the screening processing and dense state preparation processing, and obtaining a plurality of relatively dense state samples; performing simulated temperature monitoring on the plurality of samples in the relatively dense state to obtain a plurality of temperature-time curves, and performing piecewise linear fitting to obtain thermal response characteristics of the simulated fire soil; performing optimal monitoring time period analysis and optimal monitoring duration analysis according to the thermal response characteristics to obtain an optimal passive monitoring time window and duration strategy; and determining target to-be-monitored fire soil, and performing real temperature monitoring on the target to-be-monitored fire soil according to the optimal passive monitoring time window and the duration strategy to obtain an optimal temperature monitoring result. According to the invention, the temperature of the fire soil to be measured can be accurately monitored, so that the assessment precision of the passing ability of the Mars rover is effectively improved, and the driving safety of the Mars rover is ensured.

The invention relates to a frame structure analysis method and system under the impact load effect, and the method comprises the steps: carrying out the modeling of a frame structure based on the basic information of the frame structure of a preset building unit, and obtaining a frame structure model; a load time history curve of the impact load acting on the preset building unit is constructed, and the load time history curve represents the change of the acting force of the impact load along with time; and based on the frame structure model and the load time history curve, solving a frame structure analysis result of the preset building unit under the action of the impact load. By means of the method, dynamic anti-explosion analysis combining the frame structure model and the load time history curve is achieved, the limitation of a traditional equivalent static method or a simplified dynamic model is broken through, the influence of key parameters on a structure damage mode can be quantified, transient nonlinear response under the action of shock waves can be accurately captured, and the anti-explosion effect is improved. The problem of how to accurately analyze the frame structure of the building under the action of the impact load is solved.

The invention discloses an elbow joint rehabilitation training evaluation method and system, and the method comprises the following steps: S1, collecting multi-cycle motion data and surface myoelectricity data when a patient executes a specified rehabilitation motion in a standard state through an inertia measurement unit and a surface myoelectricity sensor which are disposed on the upper limb of the patient, based on this data, establishing a personal motion baseline template comprising a standard angle-time curve and a standard muscle activation level; s2, in the rehabilitation training process, motion data and surface myoelectricity data are collected in real time, and the following operations are executed: S21, a joint motion range and a motion smoothness index are extracted from the motion data; s22, muscle activation intensity and collaborative shrinkage are extracted from the surface myoelectricity data; according to the method, individuation of evaluation standards, diversification of monitoring dimensions and dynamic weight adjustment are achieved, the accuracy and safety of rehabilitation training can be effectively improved, and the method has important clinical application value.

The invention relates to a control method for dynamically optimizing contact force distribution of a foot-type robot, belongs to the technical field of foot-type robots, and solves the problem that the foot end is easy to sink when the foot-type robot advances in a soft terrain in the prior art. The method comprises the following steps: acquiring real-time ground counter-acting force of each foot of the foot robot in a current gait cycle support phase and joint control information of each foot in a previous gait cycle support phase; based on the joint control information of each foot in the previous gait cycle support phase and the standard ground reaction force time curve, obtaining an expected ground reaction force time curve of each foot in the current gait cycle support phase; based on the expected ground reaction force time curve of each foot in the current gait cycle supporting phase and the corresponding real-time ground reaction force, a PID controller is used for obtaining the control torque of each foot at each moment, the control torque is applied to each joint motor of each foot, and the contact force distribution of each foot is optimized. The walking stability of the foot type robot in the unstructured terrain is achieved.

The invention discloses a temperature compensation parameter calculation method and system for a temperature controller, and the method comprises the steps: obtaining first measurement point experiment data, second measurement point experiment data and standard sensor data of the temperature controller under various different experiment conditions, and storing the data in a database for data cleaning; calculating a first measuring point temperature mean value, a second measuring point temperature mean value and a temperature compensation mean value under each experimental working condition, selecting a fitting curve equation according to a difference value between the first measuring point temperature mean value and the second measuring point temperature mean value, and calculating a coefficient of the fitting curve equation to obtain the fitting curve equation; and drawing an experimental curve and a real-time curve according to the experimental data in the database and the real-time data of the temperature controller, judging a fitting effect, and determining temperature compensation parameters of the temperature controller according to the fitting effect. The temperature compensation parameter calculated by using the method provided by the invention can effectively correct the measurement error of the temperature controller under different environmental conditions, so that the temperature measurement result is more accurate.

The invention discloses an influenza virus rapid preliminary screening detection method, and relates to the technical field of biological detection, and the method comprises the following steps: collecting fluorescence signal data of a detected sample, constructing a fluorescence signal time curve, dividing the fluorescence signal time curve into a baseline segment, an amplification segment and a platform segment, and adopting a weighted sliding difference curvature method to detect the influenza virus. Calculating a local curvature change rate of each center time point of an amplification section, constructing a dynamic curvature judgment reference based on noise characteristic parameters, further obtaining an amplification trend judgment result Boolean value, and generating a final preliminary screening conclusion by calculating a fluorescence fluctuation proportion and a fluorescence slope mean value of fluorescence signal data and judging an amplification termination behavior state. According to the method, the dynamic curvature judgment reference is constructed based on the baseline segment signal variance value and the maximum jump amplitude value, so that the curvature judgment threshold value can be flexibly adjusted along with the background noise level, misjudgment caused by fixed parameters is avoided, and stable amplification trend judgment under various noise conditions is realized.

A method for controlling a motion of a multi-jointed bionic dolphin relates to a technical field of damage detection using a bionic robot. The method comprises: constructing a three-dimensional model and a three-dimensional model in computational domain of the multi-jointed bionic dolphin, and performing pre-processing; importing the model file after the pre-processing into analysis software for computational fluid dynamics for the hydrodynamic simulation to obtain a thrust-time curve and a hydrodynamic curve under a specified underwater working condition, then finding a difference, and fitting to obtain velocity-resistance fitting curves; performing a kinetic analysis, and deducing a kinetic model; completing kinetic coupling to obtain kinetic parameters according to the kinetic model, the thrust-time curve, and the velocity-resistance fitting curves; and controlling output torques by a pulse width modulation (PWM) technique.

The invention discloses a nondestructive testing method for defects of a friction part based on pulse infrared thermal imaging. The method comprises the following steps: determining thermal physical parameters of each component material of the friction part with the defects through experimental measurement or material manual query; constructing a short-pulse infrared thermal imaging detection system and a long-pulse infrared thermal imaging detection system; a short pulse infrared thermal imaging detection system and a long pulse infrared thermal imaging detection system are respectively adopted to detect the friction part, and sequence infrared images and corresponding temperature data are synchronously obtained; in the collected sequence infrared images, selecting central areas and defect-free areas of different depth defects on the friction part as feature points, and extracting temperature data of each feature point to draw a temperature-time curve; performing data reconstruction and image enhancement processing on the acquired sequence image data; analyzing the image to obtain a detection result. According to the invention, accurate detection of different depth defects in the friction part is realized, the identification capability of the depth defects is improved, the cost is reduced, and the adaptability is high.

The invention discloses a pile forming form and inter-pile soil compactness evaluation method based on vibro-replacement gravel pile construction data. The method comprises the steps of finding a pseudo-residual vibration working section according to a real-time construction depth-time curve, determining a key stage according to a real-time construction filling amount-time curve, finally finding a time node of downward insertion / upward pulling of a gravel pile by a vibroflot according to an amplitude change rule of a real-time construction current-time curve, calculating a transverse extrusion and expansion range after reinforcement, and finally determining a reinforcement result. And the pile forming form is estimated, and the average compactness of the soil between the piles of the reinforced field is calculated. According to the method, evaluation of the pile forming form and the compactness of the soil between the piles is achieved through on-site construction data, and the method has the advantages of being high in evaluation speed, high in accuracy and the like and is suitable for reinforcing effect evaluation of the vibro-replacement gravel pile treatment foundation with the down-inserting and up-pulling construction technology.

This invention discloses a method, system, and self-moving device for multi-sensor clock synchronization. The method is applied to a self-moving device including a first sensor and a second sensor. The method includes generating a first rotational speed-time curve for the first sensor and a second rotational speed-time curve for the second sensor during the rotation of the self-moving device; determining the phase difference between the first and second rotational speed-time curves; and adjusting the clocks of the first and second sensors to be synchronized based on the phase difference. This method and system for multi-sensor clock synchronization more intelligently and effectively improves the efficiency of multi-sensor clock synchronization.

The invention discloses a method and a device for analyzing running exercise conditions. The method comprises the steps that inspection data and test data are collected through a sensor laid on a runway, the inspection data are used for obtaining a stiffness coefficient and a baseline offset, the test data are used for obtaining a plurality of accelerations, and an acceleration time curve is obtained; basic parameters are obtained, wherein the basic parameters comprise the weight, time and stride frequency of an athlete; according to the acceleration and the basic parameters, obtaining a step length, an acceleration change rate, a data relationship between the acceleration and the step length and a data relationship between the acceleration and a stride frequency; acceleration ability and dynamic performance are evaluated, and athlete ability is optimized. Through the method and the device, the problem of incomplete analysis of running conditions of athletes in related technologies is solved.