34 results about "Measurement uncertainty" patented technology

The invention provides a fault diagnosis method, device and equipment for a high-precision wide-range electric energy meter, and relates to the technical field of fault diagnosis. The method comprises the following steps: acquiring measurement error data of the electric energy meter under various test conditions; wherein each test condition comprises a changing electromagnetic environment condition and a temperature condition; based on the weight of each test condition, performing weighted fusion on the measurement error data to obtain comprehensive error data of the electric energy meter; if the comprehensive error data is not in the credible interval, determining that the electric energy meter has an integral fault, analyzing the source and contribution degree of the comprehensive error data based on an uncertainty evaluation model, and determining a fault component; wherein the uncertainty evaluation model is used for representing the contribution relation of each error source item to the total measurement uncertainty. According to the invention, comprehensive, accurate and efficient fault diagnosis of the high-precision wide-range electric energy meter can be realized, and the reliability and accuracy of electric power metering are guaranteed.

The invention relates to the technical field of geological exploration and three-dimensional modeling, and discloses a geological structure three-dimensional measurement system based on inertial navigation. According to the system, an inertial measurement data flow is processed through a resolving module, the instantaneous space attitude and the relative displacement vector of a measurement carrier are obtained, and a basic three-dimensional geologic structure model is constructed. The quantization module calculates the confidence coefficient of a resolving result in real time and generates a space-time uncertainty distribution field; and the model correction module performs error propagation analysis by using the distribution field, and performs iterative optimization of geometric morphology on a low-confidence region in the model. The system imports lithology, formation and structure interpretation data from the outside, and associates the data as attributes to the model. And the result packaging module packages the optimized model, the association attribute and the uncertainty distribution field into a composite three-dimensional geological survey result file. According to the method, dynamic quantification and visualization of measurement uncertainty are realized, the model can be autonomously optimized, and the reliability and precision of inertial navigation three-dimensional geological modeling are improved.

Aspects of the present disclosure include methods for identifying measurement uncertainty associated with light detected from a sample. Methods according to certain embodiments include introducing a sample into a flow cytometer, flowing the introduced sample in a flow stream, irradiating the sample in the flow stream with a light source, detecting light from particles in the sample flowing in the flow stream and, identifying measurement uncertainty associated with the detected light. In some embodiments, measurement uncertainty is identified corresponding to individual particles in the sample. In certain embodiments, measurement uncertainty is identified for individual parameters of detected light for particles in the sample. Methods according to some embodiments further comprise generating a quality score for each particle based on the measurement uncertainty for each particle. Systems, integrated circuit devices (e.g., a field programmable gate array) and non-transitory computer readable storage mediums for practicing the subject methods are also provided.

This application relates to the field of liquid level measurement technology, specifically to a high-precision automatic water level monitoring method and system. The method includes: setting measurement points in the monitored water area; analyzing the overall distribution characteristics of water level values ​​within a preset time window; determining the fluctuation frequency of each measurement point; combining the water surface fluctuations of all measurement points within the preset time window to obtain a fluctuation stability index; screening the measurement points to obtain valid measurement points; analyzing the dispersion of water level values ​​in the current time window of each valid measurement point; determining the fusion weight of each valid measurement point; using the fusion weight to weight representative water level values ​​to obtain a fused water level value; and correcting the fused water level value through measurement uncertainty to obtain the final water level measurement result. This application aims to improve the accuracy of water level measurement.

The invention discloses a differential transformer measurement precision uncertainty determination method and system, and the method comprises the steps: calculating a driving signal frequency influence quantity, determining a displacement-voltage conversion slope deviation caused by the coil mutual inductance coefficient change due to the signal frequency drift of a sensor driving coil, calculating a waveform transmission efficiency influence quantity, and determining the measurement precision uncertainty of a differential transformer. In consideration of differential transformer iron core eddy-current loss difference caused by non-sinusoidal waveform harmonic components and energy loss caused by a sampling system bandwidth threshold, full-travel interpolation errors caused by interpolation calculation of non-equally-divided calibration points are quantized by calculating a finite position linearity influence quantity, and the total-travel interpolation error is calculated by multi-aspect component estimation. And determining the field measurement uncertainty of the differential transformer principle sensor in combination with a multi-factor uncertainty model. Therefore, the uncertainty value of the physical quantity measured by the corresponding sensor under the field condition is obtained, and effective data support is provided for determining the precision of the sensor and the test and control precision.

The invention relates to a key uncertainty source identification method in five-axis on-machine measurement, which comprises the following steps of: preliminarily screening out uncertainty sources, introducing the uncertainty sources into a measuring head end, a workpiece end and a machine tool end for modeling, constructing a first-order five-axis on-machine measurement error sensitivity analysis model, identifying the key uncertainty sources in a measurement system by adopting an EFAST method, and determining the key uncertainty sources in the measurement system. The problem of difficulty in quantitative weight evaluation of the influence of an uncertainty source on the uncertainty of a measurement result in a measurement system is solved; the method is efficient in calculation and good in stability, can be popularized and applied to key uncertainty source identification in other multi-axis on-machine measurement systems, and facilitates improvement of on-machine measurement uncertainty evaluation precision.

The invention relates to a calibration method (100) of a gas pycnometer, said gas pycnometer comprising at least two containers, a reference container having a reference volumetric capacity, referred to as the first capacity, and a receiving container configured to hold a sample whose volume is to be determined, said receiving container having a test volumetric capacity, referred to as the second capacity, said gas pycnometer being configured to determine the volume v of a sample housed in the receiving container, characterized in that said gas pycnometer is characterized by a calibration function which depends on at least two modeling parameters: a sensitivity coefficient which is a predetermined value and a pycnometer-to-empty ratio which is a measurement value of said pycnometer when empty, the relative measurement uncertainty(s) of said pycnometer being determined as a function of the sensitivity coefficient and the pycnometer-to-empty ratio.Figure to be published with the abbreviation: none.

The invention discloses an electric vehicle charging out-of-tolerance measurement modeling method, system and device and a medium, and the method comprises the steps: obtaining vehicle end operation data, pile end operation data and cloud end operation data, and obtaining a measurement error prediction result of an electric vehicle charging facility through constructing a charging environment topological structure and analyzing an energy conservation relation of a charging area; the method comprises the following steps: obtaining a voltage estimation error and calculating measurement uncertainty in combination with a statistical theory to obtain a quantitative index set; the method comprises the following steps: inputting a quantitative index set as a feature into a Sheng differential equation model, and learning a differential rule of the input feature along with time evolution by using the Sheng differential equation model to obtain a matching result of a nonlinear dynamic characteristic of a metering error in a charging process; and inputting real-time operation data of the electric vehicle charging facility into the trained model to obtain an out-of-tolerance measurement result of the electric vehicle charging facility. According to the method, the metering accuracy and the error response rate under the complex working condition are remarkably improved.

The application discloses a device and method for measuring partial pressure of mixed gas in ultra-high vacuum based on cold atom technology. The application is based on the theory that the regularity attenuation of the cold atoms trapped in the potential well caused by the particle collision of the background gas can be used to reverse the density of the gas particles, and the characteristics that the velocity thermal average collision cross section of different gas particles and cold atoms has a certain and independent change trend with the depth of the potential well. A multivariate linear regression equation set of total collision loss rate about mixed gas density under different well depth conditions is constructed to analyze the change of the total loss rate of the cold atom group under different well depth conditions, so that the type and density of each component in the mixed gas are separated, and the partial pressure of each component is determined. The method avoids the measurement uncertainty caused by the effects brought by the ionization process of the traditional mass spectrometer, and has the advantages of no calibration, no disturbance to the measurement environment, high accuracy, reproducibility at different times and different places and the like based on the basic physical characteristics of the cold atoms.

The application discloses an advanced posterior Cramer-Rao lower bound considering target measurement uncertainty state correlation, comprising the following steps: step one, determining a target state equation of a target motion process and a measurement equation of a double-base radar when target tracking is performed; step two, after the target state equation and the sensor measurement equation are obtained, a Fisher information matrix of target state estimation of the target at time k is recorded as J k , and the lower bound of the target state estimation at time k is the inverse matrix of J k , that is, the advanced posterior Cramer-Rao lower bound; step three, calculating a conditional measurement information matrix; step four, substituting the calculated conditional measurement information matrix into the advanced posterior Cramer-Rao lower bound. The method focuses on the influence of target missed detection and measurement noise on the PCRLB under the influence of the target-radar geometric position under the basis of clutter interference. Simulation experiments verify that, compared with other PCRLB methods, the method of the patent can obtain a more accurate lower bound under the condition of highly uncertain double-base radar measurement information.

The invention relates to the technical field of thickness detection, and discloses a catenary dropper icing thickness monitoring and early warning method and system, and the method comprises the steps: obtaining a to-be-detected image of a catenary dropper, converting the to-be-detected image to an HSV and Lab color space, and generating a fusion edge feature map; segmenting a dropper icing area, and extracting a pixel width sample set; fitting the pixel width sample set to obtain initial icing thickness probability distribution, and extracting a measurement uncertainty factor; historical icing thickness prior distribution is constructed; determining a current measurement confidence coefficient, and calculating a fusion coefficient; performing conjugate updating on the initial icing thickness probability distribution and the historical icing thickness prior distribution to obtain icing thickness posterior probability distribution and distribution variance; acquiring a real-time environment wind speed, and calculating a safety thickness threshold value and an early warning probability threshold value; and when the cumulative probability of the icing thickness posterior probability distribution exceeding the safety thickness threshold is greater than the adjusted early warning probability threshold, outputting an early warning signal. According to the invention, the precision of icing thickness monitoring results is improved.

This invention provides a traceable uncertainty assessment method for dynamic wavelength calibration. First, it performs uncertainty source analysis based on Taylor series expansion, determining that the time-frequency relationship calibration uncertainty is mainly determined by the uncertainty of the local continuous time-frequency relationship. Then, it assesses the impact of peak location on uncertainty, the uncertainty of the standard interferogram, and the uncertainty of interference intensity under complex tuning conditions, quantifying the standard interferogram uncertainty and the measurement uncertainty generated by local normalized frequency interpolation. These are then combined to obtain the combined uncertainty of the normalized time-frequency relationship. Finally, the combined uncertainty of the normalized time-frequency relationship is multiplied by the free spectral range of the F-P interferometer to obtain the absolute uncertainty of the time-frequency relationship calibration. This invention enables the quantification and propagation analysis of each error component during nonparametric point-by-point calibration, establishing a systematic uncertainty assessment framework and providing a scientific basis for the reliability of the calibration results.

The present application relates to geological exploration and three-dimensional modeling technical field, disclose a three-dimensional measurement system of geological structure based on inertial navigation. The system includes through the processing of inertial measurement data stream by solving module, the instantaneous spatial attitude and relative displacement vector of the measurement carrier are obtained, and the basic three-dimensional geological structure model is constructed. The confidence of the solving result is calculated in real time by the quantization module, and the space-time uncertainty distribution field is generated; the model correction module uses the distribution field to carry out error propagation analysis, and the low confidence area in the model is iteratively optimized in geometric form. The system imports the lithology, stratum and structure interpretation data from the outside, and associates it to the model as an attribute. The optimized model, associated attribute and uncertainty distribution field are packaged into a composite three-dimensional geological measurement result file by the result packaging module. The present application realizes the dynamic quantification and visualization of measurement uncertainty, and can independently optimize the model accordingly, improves the reliability and precision of inertial navigation three-dimensional geological modeling.

Aspects of the present disclosure include methods for identifying measurement uncertainty associated with light detected from a sample. A method according to certain embodiments includes introducing a sample into a flow cytometer, flowing the introduced sample in a flow stream, irradiating the sample in the flow stream with a light source, detecting light from particles in the sample flowing in the flow stream, and identifying measurement uncertainty associated with the detected light. In some embodiments, measurement uncertainty is identified corresponding to individual particles in a sample. In certain embodiments, measurement uncertainty is identified for various parameters of detection light of particles in a sample. The method according to some embodiments also includes generating a mass fraction for each particle based on the measured uncertainty for each particle. Systems, integrated circuit devices (e.g., field programmable gate arrays), and non-transitory computer-readable storage media for practicing the subject methods are also provided.

The application discloses a kind of measurement threshold determination method, device, electronic equipment and medium, belong to electronic technical field.The method includes: obtaining multiple body SAR measurement data groups, each body SAR measurement data group includes the SAR measurement value of one sample at one frequency band and the SAR measurement value of body model at multiple distance values;Obtain multiple head SAR measurement data groups, each head SAR measurement data group includes the SAR measurement value of one sample at one frequency band and the SAR measurement value of head model at multiple relative position attitudes;According to multiple body SAR measurement data groups, determine first adverse factor;According to multiple head SAR measurement data groups and first body SAR value, determine second adverse factor, first body SAR value includes the SAR measurement value corresponding to zero distance in multiple body SAR measurement data groups;According to first adverse factor, second adverse factor and the system measurement uncertainty set, determine head SAR measurement exemption threshold.

The invention relates to the technical field of gear precision measurement and intelligent manufacturing automation control, in particular to a gear measurement center measurement process automation and intelligent scheduling system, which comprises a data acquisition module used for acquiring machining state characteristic parameters of a to-be-measured gear in a machining process; the first processing module is used for marking the physical index of the abnormal gear tooth unit as a high-risk area; the second processing module is used for decomposing the measurement program into a discrete measurement microtask set; the third processing module is used for resolving a process capability confidence index of the gear to be tested; the scheduling execution module is used for generating a hierarchical scheduling instruction: if the process capability confidence index is higher than a preset inspection-free threshold value, generating a direct release instruction and skipping residual measurement tasks; on the contrary, after the optimal cooling waiting time is over, the focusing scanning task is triggered to be executed; according to the method, the measurement uncertainty caused by processing residual heat is effectively eliminated, and the consistency of precision geometric quantity measurement results is guaranteed.

The invention relates to a shape and position integrated measurement method and system based on multi-sensor fusion, and relates to the technical field of optical measurement. The method comprises the following steps: calibrating internal parameters and external parameters of a sensor group; determining the measurement uncertainty corresponding to the sensors in the sensor group; performing parameter optimization on the sensor group in combination with the measurement uncertainty corresponding to the sensor; performing tight coupling on the measurement uncertainty corresponding to the sensor to obtain tight coupling uncertainty corresponding to the sensor and total measurement uncertainty corresponding to the sensor group; and combining the total measurement uncertainty to construct an integrated measurement model, wherein the integrated measurement model is used for simultaneously measuring the shape and the position of the polyhedral common optical element. The efficient multi-sensor measurement system is designed for solving the problem that the deflection measurement cannot effectively measure the surface shape and the pose at the same time. The precision of system calibration and workpiece positioning is effectively enhanced from the aspect of hardware, and then the surface shape and pose measurement capability of deflection measurement is improved.

The invention provides a gas turbine unit complete machine test measurement uncertainty evaluation method and device. The method comprises the steps that at least one constraint parameter of to-be-evaluated parameters in a gas turbine unit complete machine test is acquired; for any target parameter in the to-be-evaluated parameter and the at least one constraint parameter, adopting a plurality of measurement devices matched with the target parameter to obtain a plurality of target measurement values of the target parameter; determining a first uncertainty of the target parameter according to each target measurement value; determining a second uncertainty of the target parameter according to the basic uncertainty corresponding to each measurement device; and evaluating the uncertainty of the to-be-evaluated parameter according to the first uncertainty and the second uncertainty of each target parameter. By fusing the multi-device measurement values and the basic uncertainty, the uncertainty of the to-be-evaluated parameters is evaluated, errors caused by single measurement or simplified processing are effectively avoided, and the accuracy and reliability of uncertainty evaluation are improved.

A quantitative pooled-sample testing method and apparatus for chemical test items of consumer products are provided. The test method includes: calculating a maximum number of samples that can be pooled according to parameters such as regulatory limit requirements, measurement uncertainty, the number of pooled samples, a sample pooling ratio, and the like; establishing a searchable table according to a relationship between a qualified rate, the number of samples that can be pooled, and reduced workload; for various items to be tested, directly querying the table to acquire reduced workloads corresponding to different numbers of samples that can be pooled; and when the number of samples that can be pooled does not exceed a maximum value and corresponds to the most greatly reduced workload, determining that number of samples that can be pooled as an optimum number of samples that can be pooled, and performing pooled-sample testing.

The application discloses a method and device for evaluating the radiation emission level of power electronic equipment based on a reverberation chamber, a medium and equipment. The method comprises the following steps: obtaining a reverberation chamber radiation receiving power sample and a transmission coefficient sample; obtaining a radiation power calculation model of the power electronic equipment to be measured, constructing a radiation power function of the power electronic equipment to be measured, obtaining a probability density function of a radiation power estimation value based on the radiation power function of the power electronic equipment to be measured, and obtaining an uncertainty model; evaluating the first radiation emission level of the power electronic equipment to be measured based on the radiation power calculation model and the uncertainty model; and determining the second radiation emission level according to the radiation power function of the power electronic equipment to be measured. The method can accurately describe the statistical distribution characteristics of the electromagnetic field inside the reverberation chamber, quantitatively analyze the influence of the number of independent samples on the measurement uncertainty, and effectively evaluate the statistical characteristics and measurement uncertainty of the radiation emission of the power electronic equipment.

The invention relates to the field of power equipment fault prediction and health management, in particular to a transformer fault diagnosis method and device, equipment and a medium, and the method comprises the steps: verifying the effectiveness of each gas sensor corresponding to online monitoring gas when the transformer fault diagnosis is triggered; for any gas sensor, if the verification of the gas sensor is not passed, triggering an online calibration process to obtain a calibrated gas sensor; according to the calibrated gas sensor, gas concentration data corresponding to the online monitoring gas and measurement uncertainty corresponding to the gas concentration data are obtained; performing fault diagnosis on the transformer based on each gas concentration data and the measurement uncertainty corresponding to each gas concentration data to obtain a diagnosis result and a confidence level of the diagnosis result; and a diagnosis report is output according to the diagnosis result and the confidence level of the diagnosis result, and the credibility of transformer fault diagnosis is effectively improved by establishing quantitative correlation between data quality and a diagnosis conclusion.

The application discloses a method and system for evaluating measurement result uncertainty based on machine learning, and relates to the technical field of measurement data processing, comprising the following steps: constructing a basic non-consistency score based on the measurement prediction bias in the calibration sample, combining the prediction uncertainty to form a non-consistency score, extracting a confidence interval threshold according to the confidence level, implementing boundary correction on the prediction interval in the double-channel evaluation set to form an interval calibration data set; identifying boundary risk samples based on the distribution difference between online evaluation samples and training samples, performing interval expansion on the interval calibration data set, triggering a dynamic retest mechanism when the uncertainty after expansion is higher than the uncertainty threshold, performing interval update correction on the interval calibration data set, and outputting an uncertainty evaluation set. The application realizes adaptive correction under complex working conditions, thereby achieving the effect of more reliable and more robust measurement results.

The invention provides a flame light field imaging measurement uncertainty quantitative evaluation method, which comprises the following steps of: acquiring a light field original white image of a light field camera under an actual error condition and an ideal condition, and determining a central pixel block of each micro-lens sub-image area, the method comprises the following steps: acquiring an original light field image of a light field camera for imaging a target scene under an actual error condition, dividing a reference image and a to-be-measured image into corresponding sub-image pairs, sequentially calculating a local mean square error and a local structural similarity of each sub-image pair, sequentially calculating an overall mean square error and a structural similarity of a sub-aperture image under each view angle, and obtaining a sub-aperture image; according to the method, a quality evaluation system of a local sub-image and a multi-view sub-aperture image is established for a flame light field image from the angles of image intensity and structural distortion; therefore, the quantitative evaluation of the response uncertainty of the flame light field imaging measurement system under the given error input is realized.

The present application belongs to the technical field of large-size gear measurement, and particularly relates to a large gear tooth surface full-geometric information quantitative sampling method and application thereof. Under the constraint of measurement uncertainty set in different characteristic regions of a large gear tooth surface, an optimal critical value of sample size of each different characteristic is determined with the minimum total detection cost as the target, the total detection cost including total measurement cost and detection error cost, and the sample size being the total sampling point number covering the full tooth surface. The optimal critical value of sample size of a single tooth surface of a large gear or the optimal critical value of sample size of all tooth surfaces of the entire gear is determined, and the tooth surface of a gear standard is sampled according to the optimal critical value of sample size, and the full-geometric information of the tooth surface is fitted according to the sampling data to calibrate the measuring instrument. The present application can well balance the sampling accuracy and sampling cost, avoid blindly increasing the sampling points for pursuing the sampling accuracy, and greatly reduce the total cost consumption generated in the large-size tooth surface profile sampling process.

This disclosure relates to a method and system for calibrating the traction tension of nonwoven fabrics based on measurement uncertainty, comprising: constructing a measurement uncertainty model, wherein the measurement uncertainty model is constructed based on measurement data of minute traction tension; determining the likelihood function of the unknown parameters in the measurement uncertainty model based on the measurement uncertainty model; designing a calibration control scheme for adjusting the measurement error of the calibration system based on the error fitting state quantity in the measurement uncertainty model; and adaptively adjusting the control gain in the calibration control scheme based on the likelihood function and the calibration control scheme to calibrate the minute traction tension. This disclosure can achieve more accurate and consistent measurement of minute traction tension.

The invention relates to the technical field of metering testing, and discloses a laser interference type vacuum corrugated pipe micro-pressure calibration device and method. The device comprises an optical cavity, a vacuum corrugated pipe, a pressure controller, a laser interferometer and a data acquisition and processing system, the optical cavity is communicated with the vacuum corrugated pipe to form a fully-sealed variable-volume air chamber, and the motor driving mechanism controls the corrugated pipe to do axial reciprocating motion to generate sine dynamic pressure. The method comprises the following steps: firstly, performing static calibration by using a vacuum gauge to construct a physical mapping model of optical path difference and pressure, then synchronously collecting the optical path difference and a calibrated signal in a dynamic experiment, and obtaining standard dynamic pressure based on model inversion; and finally, the dynamic sensitivity and the frequency response characteristic of the calibrated sensor are calculated through contrastive analysis. According to the invention, a full-sealed structure is adopted to avoid gas leakage, pressure traceability is realized by using an optical interference principle, the defects of waveform distortion and response lag in micro-pressure dynamic calibration are overcome, and the measurement uncertainty is reduced.

The invention relates to the technical field of aero-engine measurement and evaluation, in particular to an aero-engine test measurement uncertainty dynamic evaluation and calibration method, which comprises the following steps of: acquiring a multi-channel calibration value and numbering, identifying jump according to a connection relationship and forming a paragraph, tracking a direction based on an offset paragraph and adjusting attribution. Connecting boundaries are identified, key drift channels are delimited, links are extended, cross-chain relations are classified, paths are merged, and uncertainty calibration labels are output. According to the method, a traceable structure is formed by jump points, trend features and cross-chain extension through combined processing of continuity, directivity and spatial association of multi-channel serial numbers, a drift aggregation relation is formed through direction tracking, link segmentation is achieved through boundary judgment, a cross-chain coherent path is obtained through extension association, and a labeling track is formed through position merging. Therefore, the drifting has traceability, the direction has distinguishability, and the cross-chain diffusion has a recognizable mode, so that the link division stability and the uncertainty evaluation consistency are improved.

This invention provides a method for evaluating the confidence level of underwater radiated acoustic field simulation results, by using the simulation uncertainty U S Measurement uncertainty U M Measurement results p M And simulation results p S The probability density distribution f of the difference between the measured expectation and the simulation expectation is calculated, and finally the confidence level of the error interval corresponding to the simulation result is obtained. The beneficial effects of this invention are: addressing the problem that current underwater acoustic simulation result evaluation methods do not incorporate measurement uncertainty, leading to incomplete evaluation results, this invention can provide a more comprehensive confidence evaluation result for underwater radiated sound field simulation results, providing a quantitative reference for improving underwater radiated sound field simulation, and has important implications for the development of underwater acoustic simulation technology.

The invention provides a high-precision measurement method for clearance change of a split cabin door of an airplane, which belongs to the technical field of airplane detection and specifically comprises the following steps: constructing a binocular stereoscopic vision measurement error transfer model; establishing a three-dimensional coordinate system; the measurement uncertainty of any point in the measurement view field is obtained through prediction based on the binocular stereoscopic vision measurement error transfer model, and parameters of the binocular stereoscopic vision measurement system are adjusted according to the predicted measurement uncertainty; a first target point is attached to a left cabin door of an airplane side-by-side cabin door, a second target point is attached to a right cabin door of the airplane side-by-side cabin door, and position changes of the first target point and the second target point after loading of the cabin doors are tracked through a binocular stereoscopic vision measurement system for measurement. According to the three-dimensional coordinate variable quantity of the first target point and the second target point, the gap width variable quantity and the order difference variable quantity of the split cabin door of the airplane are calculated. Through the processing scheme provided by the invention, non-contact, high-precision and high-resolution quantitative characterization of the gap morphology is realized.