442 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.

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 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.

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 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 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.

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 invention discloses a line loss reduction method and device based on three-phase load adjustment, equipment and a medium, and the method comprises the steps: collecting a three-phase load current corresponding to a power transmission line in response to a loss reduction request, and constructing a load square-time curve; creating a line loss change objective function according to a load square-time curve; calculating the minimum value of the line loss change objective function under the load constraint, and determining an adjustment load; and adjusting the three-phase load current according to the adjustment load to reduce the line loss of the power transmission line. Therefore, line loss calculation can be accurately carried out for continuous and changing three-phase load current, and the accuracy of line loss management and control is effectively improved.

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 landslide disaster early warning method based on an LSTM-SARIMA mixed data driving model. Global and local noise elimination is performed on radar displacement monitoring data by adopting a two-stage noise reduction method combining moving average and wavelet transform, so that the signal-to-noise ratio is effectively improved; the method comprises the following steps: decomposing slope displacement data into a trend term dominated by gravity and a periodic term influenced by the environment by utilizing a Hodry-Precott (HP) filtering method, and realizing differentiated analysis of a multi-factor action mechanism; a mixed prediction model combining a long short-term memory network (LSTM) and a seasonal autoregressive integrated moving average model (SARIMA) is provided, modeling and prediction are carried out on decomposed displacement components respectively, and results are fused to obtain a high-precision total displacement prediction value; an improved T-t curve is constructed based on a predicted displacement-time curve, a tangent angle index for landslide early warning is proposed according to a Saito three-stage theory, and quantitative and interpretable early warning criterion setting is realized.

The invention relates to the field of petroleum and natural gas engineering, in particular to a method for testing the oil and gas storage capacity of a tight sandstone reservoir in the exploration and development process. A tight sandstone reservoir oil and gas reservoir capacity testing method comprises the following steps: acquiring a pressure-time curve of a tight sandstone target reservoir section and an upper cover rock sample thereof; constructing a pressure drop standard function; respectively fitting the pressure-time curve of the target reservoir section rock sample and the pressure-time curve of the cover rock sample with a pressure drop standard function to obtain a target reservoir section pressure drop function and a cover pressure drop function; and calculating a reservoir physical property similarity coefficient according to the pressure drop function of the target reservoir section, calculating a cap layer physical property deviation coefficient according to the cap layer pressure drop function, taking an arithmetic square root of a product of the reservoir physical property similarity coefficient and the cap layer physical property deviation coefficient as an oil and gas reservoir index, and evaluating the reservoir capacity according to the oil and gas reservoir index. The method has popularization and application values.

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 a plasma thrust testing method and device, and the method comprises the steps: carrying out the calibration of a stepped force applied to a target plate, building a thrust-voltage linear model based on a voltage signal fed back by a displacement sensor, applying the instantaneous force of an analog pulse to the target plate, and carrying out the calibration of the thrust-voltage linear model. The dynamic response speed of the displacement sensor is verified, the propeller is triggered to discharge in a vacuum environment, the target plate swings after being impacted by plasma, the axial displacement of the target plate at different moments is obtained by the displacement sensor and converted into voltage signals at corresponding moments, and the voltage signals sent by the displacement sensor are collected based on an oscilloscope. The transient thrust of the plasma is inverted, and a transient thrust-discharge voltage-time curve is obtained through data fitting based on discharge parameters of the propeller at different moments. After step force is applied to the target plate for calibration, transient thrust is inverted through output voltage of the displacement sensor, and high-precision microsecond transient thrust inversion is achieved.

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 discloses a method for evaluating the service life of a rubber sealing material and application of the method, and the method comprises the following steps: obtaining the aging time t at a compression set critical value through a compression set rate-aging time curve of the rubber sealing material, and then evaluating the service life of the rubber sealing material through a fitting straight line of the aging time t and thermodynamic temperature. The evaluation method adopted by the invention is simple, the adopted compression set performance is matched with the actual use environment and use condition of the product and is closer to the real service life of the rubber sealing material, and the method adopts multiple groups of samples in the same batch to carry out tests for different times, and adopts a slow heating and cooling method, so that the test efficiency is greatly improved. The actual working environment of the product can be truly simulated, the data accuracy is ensured, and the problem that the test is stopped due to the damage of the sample can be avoided. Detection equipment is simple, personnel operation is convenient, and a reliable basis is provided for safe use of the rubber sealing material.

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.