39 results about "Smoothing filter" patented technology

Described herein are apparatuses and methods to detect tachycardias and selectively reject false tachycardia detections due to T-wave oversensing or noise. An apparatus includes electrodes, a sensing circuit coupled to at least two of the electrodes and configured to sense a signal indicative of cardiac electrical activity, and a smoothing filter configured to filter to the sensed signal indicative of cardiac electrical activity to thereby produce a filtered signal indicative of cardiac electrical activity. The apparatus produces a difference signal indicative of cardiac electrical activity by determining a difference between the sensed and filtered signals indicative of cardiac electrical activity. The apparatus also includes at least one processor configured to detect a tachycardia, or to determine whether or not to reject a tachycardia detection, based on the difference signal. The smoothing filter and / or difference circuitry can be implemented by the at least one processor, and / or other circuitry.

This application discloses an adaptive control method and electronic device for PVD and micro-arc oxidation equipment. The method includes: constructing a parameter inversion model characterized by a forward mapping relationship between prior distributions of process parameters and physical constraints; establishing a causal topology based on the mapping relationship, and identifying anomaly types by calculating the joint probability density of the two hypotheses; executing different strategies according to the anomaly type: shielding faulty sensors and reconstructing signals when measurement anomalies occur, and calculating parameter corrections through online optimization when mechanistic anomalies occur; performing safety verification and smoothing filtering on the corrections based on safety constraint envelopes; and generating an interpretable report containing root causes, contribution levels, and maintenance guidelines. This application achieves accurate anomaly type differentiation and robust adaptive control through physical-data decoupling modeling and causal reasoning, significantly improving the stability, safety, and interpretability of processes in complex industrial environments.

This invention relates to the field of thermal management for new energy vehicles, specifically to an environmental temperature estimation system and method for range-extended electric commercial vehicles. The system acquires the current temperature values ​​of multiple available temperature sources for the entire vehicle in real time. Based on the current operating status of the vehicle, it dynamically assesses and filters the availability of each available temperature source. From the available temperature sources, it selects one or more temperature sources with high thermal inertia, no active heat source, or minimal thermal impact to form a candidate temperature set, and then performs a minimum value selection process, using the minimum value as the preliminary environmental temperature estimate. The preliminary environmental temperature estimate undergoes a rate of change rationality check and smoothing filter, outputting the final environmental temperature estimate. From the vehicle's existing temperature sensor network, it dynamically selects the signal closest to the actual environmental temperature as the estimation source, performs validity checks and data fusion, and finally outputs a reliable environmental temperature estimate, thereby completely replacing dedicated environmental temperature sensors and achieving hardware cost reduction.

The application provides a kind of nonlinear filtering method of pulse eddy current detection signal, belong to nondestructive testing technical field, can at least partially solve the problem that magnetic field decay voltage signal is greatly influenced by noise in pulse eddy current detection, traditional smoothing filter is easy to introduce signal distortion.The method is used for the pulse eddy current detection signal receiving processing of metal structure with cladding layer, comprising: collecting magnetic field decay voltage signal in pulse eddy current detection process;Nonlinear compression transformation is carried out on the time axis corresponding to the magnetic field decay voltage signal;Smooth filtering time window of preset length is set on the time axis after nonlinear compression, and the corresponding conventional time interval is determined;The magnetic field decay voltage signal falling into the conventional time interval is carried out smoothing filter processing, and the filtered pulse eddy current detection signal is obtained.The application makes the filtering process match the time characteristics of the magnetic field decay signal, improves the stability of signal processing, and is beneficial to subsequent wall thickness or state evaluation.

This invention relates to an adaptive correction method for multi-beam backscattering based on statistical change point detection, belonging to the field of marine acoustic detection and seabed sediment information processing technology. The method includes acquiring multi-beam data and constructing a proxy signal; adaptively grouping the proxy signal sequence using a bisection change point detection algorithm; statistically processing the backscattering intensity data within each group according to the beam incident angle; smoothing the average angle response curve using a smoothing filter; unsupervised partitioning based on curvature and clustering; and constructing a piecewise angle response reference model, using this model to calculate the correction value. This invention effectively weakens the central highlighting, edge attenuation, and striped structure caused by angle response effects, reduces the block effect or mosaic phenomenon common in fixed window methods, and effectively weakens the systematic correlation between backscattering intensity and incident angle, providing a more stable and reliable data foundation for subsequent seabed sediment classification, seabed geomorphological identification, and related marine survey applications.

The application provides a high-reliability anti-interference engine rotating speed measurement data processing method, including the following steps: generating a square wave interval time sequence based on a square wave time sequence, generating an interval time sequence multiset based on the square wave interval time sequence, and obtaining a calculated rotating speed through the interval time sequence multiset; performing abnormal value checking and replacement on the calculated rotating speed to obtain an optimized rotating speed; and performing smoothing filtering processing on the optimized rotating speed to obtain an output rotating speed. The method can reasonably divide and classify the time intervals collected by the rotating speed sensor, reduces effective data loss, improves rotating speed measurement accuracy, suppresses rotating speed jump, and calculates a more reasonable and reliable real-time rotating speed under a large amount of high-frequency noise, random interference, intermittent or continuous time sampling abnormality and the like.

The application relates to the technical field of industrial control, in particular to a control method and system of an insulating material production line. The method comprises the following steps: acquiring initial operation data of the insulating material production line in real time; calculating a transient specific energy index in combination with a standard plasticization reference absolute temperature; extracting a pressure change rate by performing smooth filtering on a time differential item of a head melt pressure; deducing a dynamic thinning coefficient in combination with the transient specific energy index, a value at a previous sampling moment, the pressure change rate and the head melt pressure; constructing a state matrix mismatch correction factor based on the dynamic thinning coefficient, a historical maximum thinning limit value of a sliding data window and a standard steady-state thinning reference value; and performing adaptive model predictive control to output an optimal control instruction by using the correction factor to target correct a discrete state space model system matrix. The application can effectively solve the mismatch problem of a static model under a nonlinear mutation condition, improve control precision and reliability, and guarantee stable and efficient operation of the production line.

This invention provides an intelligent inversion method for inflow based on multi-source error constraint fusion, belonging to the field of hydrological forecasting technology. The method includes: constructing physical constraints based on long-sequence water level observation data, measured outflow sequences, and reservoir capacity-water level curves; constructing a composite optimization function including a reservoir capacity time-varying error compensation term, inflow continuity regularization constraints, and a water level observation data assimilation module; deriving the analytical inversion solution of inflow based on the Lagrange multiplier method; and automatically optimizing key parameters such as constraint weights and smoothing coefficients using intelligent optimization methods such as grid search and cooperative search algorithms to perform adaptive high-precision inversion under different hydrological scenarios. This invention, by dynamically adjusting the error weight coefficients, directly generates physically consistent inflow sequences without relying on the prior assumptions of traditional smoothing filters, significantly improving the performance of negative value rate control, water balance, and flood peak characteristic preservation.

The application discloses a long-distance water delivery pipeline online water hammer tracing method based on negative pressure waves, comprising the following steps: obtaining a pipeline pressure signal of a long-distance water delivery pipeline; preprocessing the pipeline pressure signal of each key node; smoothing filtering the preprocessed signal through an S-G filter; taking the window length, polynomial order and derivative order of the filter as adjustable parameters; adaptively searching and adjusting the adjustable parameter combination; obtaining a filtering result; constructing a comprehensive score function based on the filtering result; screening an optimal parameter combination according to the comprehensive score function; performing difference operation and continuous same sign judgment on the filtering signal of the optimal parameter combination; obtaining a negative pressure wave arrival time; and obtaining a water hammer tracing result according to the negative pressure wave arrival time. The method utilizes adaptive filtering, continuous same sign criterion and the collaborative calculation of a multi-sensor pair, reduces the influence caused by the abnormality of individual sensors or local errors, and improves the real-time performance and reliability of water hammer tracing in long-distance water delivery projects.

This invention belongs to the field of non-destructive testing technology for material surfaces, and specifically to a material surface defect detection system based on optical spectroscopy. The system includes a defect scanning and spectral acquisition module, a spectral data cleaning module, a characteristic peak decomposition and defect encoding module, a pulsed neural network ignition module, a defect classification module, a 3D reconstruction module, and a report output module. These modules operate sequentially in series, with the output data of the previous module serving as the input data for the next, thus creating a closed-loop detection process from raw spectral acquisition to defect detection report generation. Through the linkage between the scanning and spectral acquisition module and the spectral cleaning module, a hardware trigger synchronously acquires spatial coordinates and spectral data, and sequentially performs energy normalization, curvature compensation, baseline subtraction, and smoothing filtering. This eliminates the cosine attenuation effect of spectral intensity caused by highly reflective surfaces, making low signal-to-noise ratio spectral data usable and providing a high-quality input foundation for subsequent defect identification.

This project proposes a low-cost, universal, and purely local gesture control scheme for mobile phone screen projection games. Users only need to place their phones in a common stand and use the front camera to recognize left and right gestures and screen projection functions in real time. This allows users to control screen projection games (small games created based on these two gestures) without touching the screen while driving, achieving lightweight interaction between the driver and the car. Unlike existing solutions that rely on vehicle-grade cameras, this project is completely based on local computing power and does not upload any data, ensuring privacy and security without the need for vehicle reconstruction. Moreover, the project adds vibration compensation and smoothing filters to effectively solve the problem of users being unable to accurately control the screen with gestures in a bumpy car, as well as using screen projection technology to reduce eye strain and motion sickness caused by small screens. Currently, this project has been implemented on Android phones such as OPPO and Huawei, with preliminary adaptation tests underway.

This application relates to the field of computer technology, providing a visual tracking method, apparatus, device, storage medium, and program product. The method includes: performing exposure compensation processing on the image to be processed based on the real illumination information at the time of shooting; performing smoothing filtering processing on the exposure-compensated image to be processed based on the illumination change rate at the time of shooting; wherein the illumination change rate is predicted before shooting the image to be processed; and performing target tracking based on the smoothed image to be processed. This application can effectively improve the accuracy of target recognition during target tracking, thereby improving the success rate of visual tracking in uneven lighting scenes.

The application discloses a minimally invasive spinal fusion system based on artificial intelligence, which comprises the following steps: after the deviation warning signal is obtained, the instrument trajectory data is subjected to smoothing filtering processing, the filtered trajectory sequence is obtained, and the filtered trajectory sequence is matched with the updated model grid; the dynamic path adjustment parameter is determined and is built into the surgical robot to adjust the vibration frequency parameter and improve the control experience level; the subsequent image data is processed by using the iterated model version, the temporary deviation caused by the instrument shaking is determined, and the temporary deviation is corrected through the path planning algorithm; the corrected navigation instruction sequence is generated, and the real-time feedback mechanism is applied to transfer the intuitive deviation information; the surgical instrument is driven to adjust the movement through the navigation instruction sequence, the adjusted trajectory data is obtained, and the deviation of the optimized path is compared and optimized in a cycle; if the deviation continuously falls below the threshold value, the current model is maintained, and the final navigation model is output to ensure reliable consistency.

The application provides a human-machine shared intelligent electric automobile lateral control system and method, relates to the technical field of intelligent automobile control, and comprises the following steps: obtaining a current steering wheel torque and its differential, a longitudinal vehicle speed, a yaw angular velocity and a desired front wheel turning angle; determining a driver intervention intention level according to the absolute value of the torque and determining an initial weight coefficient; constructing a steering quality coefficient by analyzing the time domain fluctuation characteristics of the torque and its differential, and simultaneously correcting the first target front wheel turning angle of automatic driving based on the vehicle speed and the desired turning angle; performing adaptive smoothing filtering on the torque according to the quality coefficient to generate a driver demand turning angle, and then weighting and fusing the first target turning angle and the driver demand turning angle according to the initial weight to obtain a second target front wheel turning angle of shared control and output execution, so that the comfort, smoothness and safety of human-machine shared driving are improved.

The present application relates to a kind of printing texture graph topology analysis and vectorization method, the described method includes the following steps:1) the initial image is preprocessed;2) by Sobel operator and LBFGS++ algorithm, the multi-vector field model of image foreground point is established;3) the curve connected by foreground point is established, and according to multi-vector field model, curve tracking is carried out, and topological graph is formed;4) according to topological graph result, each group of curve is fitted by Bezier interpolation, and smoothing filtering processing is carried out, and finally output svg format vector file with line skeleton as graph element information.Compared with prior art, the present application has the advantages of high vectorization accuracy, wide processing range, etc.

The embodiment of the application discloses a rotating equipment rotating speed estimation method based on hill peak identification and correlation analysis, belongs to the field of mechanical vibration signal processing, and comprises the following steps: collecting a vibration signal, using a Fourier transform method to calculate the frequency spectrum of the vibration signal, automatically identifying whether a hill peak exists in the frequency spectrum through a hill peak identification method, using a correlation analysis method to calculate the autocorrelation coefficient of an envelope signal or the vibration signal, using a smoothing filter to fit the autocorrelation coefficient to obtain a new autocorrelation coefficient, taking the two maximum value points in the new autocorrelation coefficient, obtaining two index position points corresponding to the two maximum value points, calculating the position difference of the two index position points, calculating the fundamental frequency according to the position difference, and calculating the rotating speed according to the fundamental frequency. The embodiment of the application can realize the rotating equipment rotating speed estimation based on the correlation analysis through the automatic identification of the modulation signal in the vibration signal waveform spectrum.

This invention relates to the field of visual AI technology, specifically to a high-precision assembly and quality traceability management system for KD (knock-down) components based on visual recognition and AI. In this invention, a dynamic point cloud acquisition and generation module generates point cloud flow data, and a normal field construction module establishes a surface normal vector distribution field. A dual-mode feature extraction module performs low-pass smoothing filtering to extract manifold surfaces to construct a flexible deformation compensation model, and performs high-pass residual filtering to extract random high-frequency normal disturbance data to generate microscopic quality fingerprint features. An adaptive assembly and traceability module generates an adaptive assembly trajectory based on the flexible deformation compensation model to control the assembly mechanism, achieving precise assembly that corrects physical deformation. The microscopic quality fingerprint features serve as a unique index to identify associated data and generate quality traceability files, thus realizing high-reliability assembly and label-free traceability of KD assembled parts.

This invention discloses an intelligent monitoring and prediction method for the setting strength of mine backfill bodies, belonging to the field of backfill strength monitoring technology. The method includes: S1 synchronously acquiring time-series signals of temperature, matrix suction, and conductivity to generate a multi-dimensional time-series signal matrix; S2 performing missing value imputation and smoothing filtering on the signals, extracting time-domain statistics and rate of change features to form a multi-dimensional feature vector; S3 constructing a neural network with dual LSTM hidden layers, training it with historical data, and outputting a predicted setting strength signal as input to the feature vector; S4 comparing the predicted signal with the target strength curve, calculating the deviation and rate of change, and generating a graded early warning signal based on a threshold. This invention solves the problem of the inability to predict the evolution trajectory of backfill strength in real time based on in-situ multi-physics field monitoring.

A method for processing tire longitudinal slip data based on data density and trend residual analysis belongs to the field of tire dynamics modeling and data processing. The method includes the following steps: Step 1, sorting the raw data according to slip ratio; Step 2, standardizing the sorted data and calculating the local density score and trend residual score respectively; Step 3, forming a comprehensive score based on a weighted combination of the local density score and trend residual score, and selecting high-quality data based on the comprehensive score; Step 4, performing a secondary smoothing filter on the selected high-quality data to obtain optimized longitudinal slip data curves. This invention significantly improves the usability and consistency of longitudinal slip data, reduces the interference of abnormal data on identification, and thus improves the fitting effect of semi-empirical models such as Pac and UniTire in longitudinal slip hysteresis and drive sections, thereby improving the tire model identification accuracy and the reliability of vehicle dynamics simulation and control applications.

Examples in the present disclosure relate to systems and methods for reducing noise in object tracking data. Images of an object are obtained via one or more cameras. The images are processed to obtain first pose data indicative of a pose of the object over time. The first pose data is represented in a camera space. The first pose data is transformed to second pose data represented in a world space. The second pose data is filtered using a smoothing filter to generate filtered pose data. The filtering includes, for each pose data item in a time series of the second pose data, using a rotation transformation between the world space and camera space to apply one or more camera space-specific filter parameters to the pose data item that is represented in the world space. The pose of the object is dynamically tracked based on the filtered pose data.

This application provides a smoothing filtering method, apparatus, electronic device, and storage medium for a fuel gauge, relating to the field of battery power technology. The smoothing filtering method includes: determining whether the battery is in a charging or discharging state; determining whether the actual battery charge at a later time is greater than the actual charge at a previous time; and determining whether the change in the actual battery charge at a later time is greater than a first preset threshold; if the change in the actual battery charge at a later time is greater than the first preset threshold, determining an adjustment step size based on the change in the actual battery charge, and adjusting the displayed charge of the fuel gauge according to the adjustment step size; if the change in the actual battery charge at a later time is less than or equal to the first preset threshold, adjusting the displayed charge of the fuel gauge proportionally. The method provided in this application satisfies the theoretical relationship F_SOC = F_RC / F_FCC while simultaneously achieving a smooth data transition perceived by the user.

The application provides a radar clock synchronization method, an electronic device, an electronic equipment and a readable storage medium, and relates to the technical field of laser radars. After an actual master-slave clock deviation of a laser radar relative to a master clock source at a current local time is obtained, the actual master-slave clock deviation is subjected to exponential smoothing filtering processing to obtain a target smoothed master-slave clock deviation, an adaptive PID controller is called based on actual PID parameters of the current local time, a target time synchronization control amount corresponding to the target smoothed master-slave clock deviation is calculated, and then the clock period count value of the local system clock signal of the laser radar is counted and adjusted according to the target time synchronization control amount to adjust the clock frequency of the laser radar, so that the laser radar can be synchronized with the master clock source, thereby effectively improving the radar time synchronization accuracy, meeting the real-time requirements of the radar, and improving the clock synchronization accuracy and the clock synchronization stability.

The application relates to the technical field of Internet of Things monitoring and environmental noise detection, and discloses a noise monitoring method and system based on the Internet of Things. The method comprises the following steps: collecting noise signal intensity and frequency distribution information of a target area and preprocessing to obtain a preliminary noise data set; obtaining a unified noise data set through feature quantization and multi-source data fusion; extracting noise space-time change characteristics and performing weighted analysis to obtain a main noise distribution mode, and performing smoothing filtering to obtain noise distribution characteristics; extracting noise source distribution rules, and when exceeding a preset threshold, performing triangular positioning, dynamic tracking and scene correction to obtain the final noise source position; and when the false alarm and missed alarm indicators meet the preset threshold through index analysis, outputting complete noise monitoring records. The method can realize intelligent noise monitoring and accurate tracing, effectively solves the problems of insufficient tracing accuracy and high false alarm and missed alarm rates, and significantly improves the sensitivity, tracing accuracy and scene self-adaptability of noise monitoring.

This invention discloses an adaptive positioning error compensation control method and system for a gantry machining center, comprising the following steps: synchronously collecting multi-source real-time working condition and position feedback data of the gantry machining center, constructing a multi-field coupled positioning error prediction model to calculate the comprehensive positioning error of each feed axis; dynamically correcting the model weights through an online recursive least squares algorithm with a forgetting factor, and generating a dynamic compensation quantity after amplitude constraint and smoothing filtering by combining a fuzzy PID algorithm, injecting the compensation quantity into the CNC system interpolation cycle to achieve command position pre-compensation; after compensation execution, collecting actual position data to verify the deviation, and feeding it back to the model to complete iterative optimization. This invention does not require modification of the original control logic of the CNC system or increase hardware costs significantly, and can significantly improve the dynamic positioning accuracy, working condition adaptability, and machining quality stability of the gantry machining center, while reducing the maintenance costs and accuracy decay rate of the machine tool during long-term service.

This invention relates to the field of steering system technology, specifically a torque smoothing control method for dual-redundant EPS fault shear. The method includes a data acquisition module, a torque sensor, a MasterECU, a SlaveECU, and a power steering motor. The outputs of the data acquisition module and the torque sensor are connected to the inputs of the MasterECU and SlaveECU, respectively. A fault detection module within the MasterECU and a fault detection module within the SlaveECU are bidirectionally connected. The output of the fault detection module within the SlaveECU is connected to the inputs of a switching control module and a filter coefficient adjustment module. The output of the filter coefficient adjustment module is connected to a smoothing filter module. The outputs of the MasterECU and the smoothing filter module are combined and connected to the power steering motor. Compared with existing technologies, this invention achieves precise and smooth control under different torque differences and vehicle speeds by dynamically adjusting the first-order low-pass filter coefficient, balancing switching smoothness and steering responsiveness.

This application discloses an immersive interactive control system and method for exhibition products in exhibition halls, relating to the field of interactive control technology. It includes: if the arousal difference is below a negative predetermined threshold, entering an activation loop: generating an incrementing instruction for the exhibition hall environment rendering parameters; if the arousal difference is above a positive predetermined threshold, entering a soothing loop: generating a stimulus reduction control instruction, pausing the currently running digital image rendering data stream, extracting and sending the spotlight coordinate guidance signal corresponding to the static physical exhibition product; exiting the current loop when the newly extracted arousal difference falls back to the target range; summarizing the control instructions generated when each loop exits, inputting the control instruction sequence into a state smoothing filter for time window cooling processing to suppress high-frequency oscillations of the instructions, and outputting a smoothed multimodal exhibition equipment drive data stream. This application has the effect of improving interactive control efficiency.

The application discloses a sparse unmixing method based on hypergraph denoising and superpixel weighting, and comprises the following steps: step 1, hypergraph smoothing filtering and denoising of a hyperspectral image; step 2, constructing a spatial weighting matrix based on superpixels; and step 3, weighted sparse unmixing of the hyperspectral image. The method combines hypergraph learning and hypergraph smoothing filtering and denoising to obtain a denoised image, and can effectively preserve the spatial structure of the original image; the denoised image is segmented by using the SLIC superpixel segmentation method, the superpixel structure of the image can be more accurately extracted, and the method has better robustness to Gaussian noises with various signal-to-noise ratios. Therefore, the application has the characteristics of strong practical application value and good reliability, and is suitable for promotion and use.

This invention discloses an algorithm for extracting structural deformation of high-speed railway bridges based on track inspection data, comprising the following steps: evaluating the mileage error of the track dynamic detection data and correcting data with mileage deviations; performing smoothing filtering on the corrected track irregularity data to identify bridge sections and locate the piers and mid-span positions of each span of a simply supported beam bridge; performing discrete wavelet transform multi-level decomposition on the preprocessed track irregularity data, selectively reconstructing coefficients containing the wavelengths of the target bridge structural deformation, and combining this with bandpass filtering to extract the pure bridge structural irregularity amplitude at the mid-span position; performing power spectral density analysis on the difference between the original irregularity, the extracted bridge structural irregularity, and the residual irregularity, and verifying the extraction effect of the bridge structural deformation by comparing the spectral characteristics of each component. The advantages of this invention are: high extraction accuracy, strong interference suppression capability, good preservation of time-frequency characteristics, and high computational efficiency.

The application is a liquid micro-leakage precision detection method based on liquid level pressure difference, and relates to the technical field of container leakage detection, comprising: removing outliers and smoothing filtering on the effective pressure difference time sequence to obtain an actual pressure difference sequence and a residual sequence, calculating an arithmetic mean and a standard deviation, and converting the standard deviation to obtain a pre-processed actual pressure difference sequence and a standardized theoretical pressure difference sequence.In the application, a thermodynamic quasi-steady state judgment mechanism can accurately identify the stable stage of the thermodynamic state of the container, avoid the influence of transient changes after pressurization on the detection result, and help shorten the detection period; through dynamic gas volume calculation and theoretical pressure difference decay sequence generation, the thermal expansion and cold contraction effect of the container and the liquid, the gas-liquid two-phase equilibrium, and the atmospheric pressure fluctuation and other factors are comprehensively considered, and the pressure difference change law under the condition of no leakage can be accurately simulated.

The application discloses a method for determining seismic quality factor with adaptive window length, which comprises the following steps: obtaining post-stack seismic data volume and interval velocity field of a target geologic body, and dividing the geologic body according to the interval velocity field; taking out a first seismic trace from the post-stack seismic data volume, processing the seismic trace by using short-time Fourier transform, calculating centroid frequency at each time sample, and performing smoothing filtering to obtain average centroid frequency of each layer; obtaining window length adjustment coefficient to adaptively determine the time window of each layer; performing time-frequency analysis on the seismic data by using generalized linear frequency modulation wavelet transform to obtain time-frequency spectrum of the seismic trace; calculating instantaneous energy spectrum of the seismic trace; extracting maximum peak energy at each time, and calculating seismic quality factor in the time domain of the seismic trace according to the relative attenuation amount of the maximum peak energy within a wavelength; sequentially extracting other seismic traces in the post-stack data volume, repeating the above steps, arranging the quality factors calculated for the seismic traces in sequence, and obtaining the seismic quality factor of the whole geologic body.