31 results about "Mathematical morphology" patented technology

The invention discloses a hydraulic pump fault detection method and device based on information fusion and a medium, and belongs to the technical field of hydraulic device fault detection. The method comprises the steps of collecting a vibration signal and a pressure signal of the hydraulic pump; processing the vibration signal and the pressure signal based on a mathematical morphology filtering algorithm to generate a de-noised vibration signal and a de-noised pressure signal; processing the signals through a convolutional neural network to generate a vibration feature map and a pressure feature map; generating a weighted vibration feature map and a weighted pressure feature map based on an attention mechanism; integrating the weighted vibration feature map and the weighted pressure feature map, and generating a comprehensive fault feature vector; generating normalized comprehensive features based on a normalization algorithm; and processing the normalized comprehensive features through a full connection layer and a Softmax classification layer of the convolutional neural network, and outputting a fault category diagnosis result. By means of the method, the technical effect of improving the accuracy and reliability of fault detection of the hydraulic pump is achieved.

The invention particularly relates to an AI auxiliary diagnosis method for oral cavity observation, which relates to the technical field of oral cavity medical AI and medical image security, and comprises the following steps: generating a Hash watermark by using patient information, and embedding the watermark into an intermediate frequency alternating current coefficient of a diagnosis core area by adopting a coefficient relation modulation method. According to the method, the local terminal is subjected to deterministic partitioning and frequency domain irreversible desensitization processing, rigid protection of biological privacy of a patient is achieved from the source, and the risk of privacy leakage in oral medical image transmission and storage is dealt with; color space conversion, threshold screening and mathematical morphology operation are completed at a local terminal, a diagnosis core area and a privacy sensitive area are accurately divided, and privacy processing can be completed without uploading an original image; the privacy sensitive area is subjected to combined processing of direct current component retention, medium and low frequency coefficient pseudo-random attenuation replacement and high frequency coefficient zero setting, a reverse mapping table and attenuation factors are not retained, irreversible blinding is achieved on the mathematical level, and biological characteristics such as cheilogramma and facial skin cannot be restored.

The application discloses a kind of offshore wind power dc collection line fault location methods based on travelling wave multiscale gradient analysis, S1.distinguishes that fault occurs;S2.sampling the voltage and current of positive pole and negative pole of fault collection line bus side, calculate 1 mode voltage reverse travelling wave;S3.based on mathematical morphology algorithm, 1 mode voltage reverse travelling wave is filtered, and filter signal is calculated;S4.the multiscale gradient of filter signal is calculated, and the transient abrupt point of waveform is identified, and the arrival time and wave head polarity information of fault voltage travelling wave are extracted;S5.calculating fault distance.The method of the application realizes fault location using fault voltage data in a short time after fault, and can quickly determine the specific fault position of collection line, and has important significance for accelerating fault clearing and guaranteeing the safe and stable operation of offshore wind power system.

The application discloses a kind of based on perception voxelization three-dimensional model generation and solidification method, it is related to artificial intelligence three-dimensional model generation technical field, comprising: S1, multi-modal three-dimensional asset input and analysis;S2, three-dimensional model surface sampling and color extraction;S3, three-dimensional space normalization and scale constraint;S4, three-linear weight sputtering based on voxel gridding;S5, voxel structure repair based on mathematical morphology;S6, internal cavity identification based on Flood Fill;S7, conservative solidification processing based on distance transformation;S8, color quantization based on perception color space;S9, sparse voxel data generation and model output.The application, through unified analysis interface, improves the compatibility and stability of multi-source three-dimensional asset conversion;Traditional attribution is replaced by three-linear weight sputtering, and sampling points are distributed to eight-neighborhood voxels according to distance, which reduces aliasing and ensures continuous expression of slender structures at low resolution.

The invention discloses a cable joint early fault detection method based on mathematical morphology, and belongs to the technical field of power line control, and the method comprises the steps: introducing a carbonization channel resistor and a water film resistor on a diode model, and obtaining a fault equivalent circuit model; building a cable network structure in the simulation software, setting a single-phase earth fault of the damped cable joint in the cable network structure, and performing fault simulation by using the fault equivalent circuit model; based on a fault simulation result, determining a zero-sequence voltage as an early fault detection signal, and enhancing and capturing fine distortion in a zero-sequence voltage waveform by using top-hat transformation to obtain a top-hat characteristic quantity; if the top cap characteristic quantity is greater than an amplitude safety threshold value and the duration greater than the amplitude safety threshold value is greater than a safety duration threshold value, judging that an early fault occurs; and determining the development stage of the early fault by using the top hat feature relative variance. According to the method, the early fault of the damped cable joint is accurately identified, the development stage of the damped cable joint is judged, and the detection sensitivity is improved.

This invention discloses a method for extracting moiré fringe phase information based on Morlet wavelet transform, comprising: converting a target moiré fringe image into a grayscale image; filtering the grayscale image to obtain a filtered binarized image; performing mathematical morphological denoising on the binarized image to obtain a processed image, wherein the mathematical morphological denoising includes erosion and dilation; convolving each column of the processed image using modulated Morlet wavelets and calculating the amplitude and phase of the wavelet coefficients; determining wavelet ridges based on the amplitude of the wavelet coefficients and extracting the phase of the scale coefficients and time coefficients corresponding to the wavelet ridge positions; and obtaining complete moiré fringe phase information based on the phases of all extracted columns. This method is highly accurate and easy to implement, making it suitable for further refractive index reconstruction and key parameter measurement of the measured flow field.

This invention relates to a method and apparatus for bright-field cell image segmentation in fluorescence microscopy. Combining an improved two-dimensional OTSU threshold segmentation algorithm, it filters out noise points in single-cell images during image preprocessing and further refines cell segmentation using binary image mathematical morphology. Then, it segments adhered cells using a label-controlled watershed segmentation algorithm based on cell nucleus images. This invention improves segmentation results through image enhancement and refines them using various segmentation methods, effectively addressing issues such as weak edges, poor contrast, irregular cell shapes, and cell adhesion in bright-field cell images. Therefore, the overall visual segmentation effect is quite good.

The application discloses a detection method, a storage medium and a device based on an OPENCV reagent cover opening angle, and the method comprises the following steps: (1) taking a picture of a hole plate area before each injection to obtain an image A; (2) pre-processing the image to obtain an effective range image B; (3) performing gray scale processing on the image by using the OPENCV to obtain a graph C; (4) performing binary processing on the image by using the OPENCV to obtain an image D; (5) performing mathematical morphology processing on the image to obtain an image E; (6) designing an elliptical detection area to obtain an image G; (7) selecting a detection area; (8) judging a reagent cover state; the application realizes automatic judgment on the opening and closing state of a reagent Tip head cover, calculates the opening and closing angle of the cover and makes angle marking, eliminates the cost of manual judgment, improves the reagent injection efficiency, and makes the stability and consistency of the whole production process higher.

The invention discloses a constant-resistance anchor cable supporting effect on-line monitoring method and system, particularly relates to the technical field of deformation state on-line monitoring, and is used for solving the problems that an existing method based on single-point monitoring cannot analyze multi-anchor cable collaborative response from a space-time correlation level, and a rock stratum activity energy release core area is difficult to position. The method comprises the following steps: acquiring and registering working data of an anchor cable network and geological structure information, implementing high-precision time synchronization and delay compensation on the working data of the anchor cable to form a networked time sequence data set, and identifying a time-space intensive response event cluster from the networked time sequence data set; coupling degree analysis is carried out on the response event cluster and the geological structure to confirm a multi-anchor-cable cooperative response event, then a space-time two-dimensional data field is constructed based on the space-time range of the event, multi-scale mathematical morphology gradient calculation is carried out on the data field online, and the multi-anchor-cable cooperative response event is obtained by tracking the space-time convergence area of the local maximum value of each scale gradient field. And finally, determining an energy release focus of the multi-anchor-cable collaborative response event.

This application discloses a bearing fault diagnosis method, equipment, medium, and product, relating to the field of fault diagnosis. The method includes: acquiring bearing information data; performing mode decomposition on the information data based on mathematical morphology and using an empirical wavelet transform spectral partitioning method to obtain a set of mode components; calculating the autocorrelation kurtosis of any mode component in the set; determining an autocorrelation kurtosis feature vector based on all autocorrelation kurtosis values; inputting the autocorrelation kurtosis feature vector into a fault diagnosis model and outputting a diagnosis result; the diagnosis result is either normal or a fault exists; the fault diagnosis model is trained based on a convolutional neural network. This application enables feature extraction and intelligent diagnosis of bearing faults.

The invention relates to the technical field of image recognition, and provides an intelligent food detection method and system based on image recognition, and the method comprises the steps: collecting a corn kernel image, and constructing a distance transformation diagram; all local maximum value points in the distance transformation diagram are screened out, a centroid height threshold value and a concave point height threshold value are set, mathematical morphology processing is carried out on the distance transformation diagram according to the centroid height threshold value and the concave point height threshold value, and centroid pixel points and concave points are obtained; determining adjacent centroids of the pits, and establishing a rigid mark graph according to the remaining pits and the positions of the adjacent centroids of the pits; image segmentation is carried out according to the rigid mark graph and the distance transformation graph, a segmentation label graph is obtained, areas corresponding to the corn kernels in the segmentation label graph are extracted, detection of the corn kernels is completed according to contour features of the areas corresponding to the corn kernels, and the corn kernels are divided into different quality types. According to the invention, the accuracy of corn kernel identification can be improved.

The application belongs to the technical field of fault line selection, and particularly relates to a small current secondary grounding fault line selection method and system based on mathematical morphology. Bus zero sequence voltage and each feeder zero sequence current are collected. The voltage signal is decomposed by using a mathematical morphology OCCO algorithm to extract transient and steady components. If the transient component exceeds a threshold value, voltage disturbance is determined and the fault time is recorded. If the effective value of the steady component exceeds the threshold value after the fault time, it is confirmed that a single-phase grounding fault occurs. According to the zero sequence current of each feeder after the voltage disturbance occurs, the transient component is obtained by using the OCCO algorithm, and the transient energy value of each feeder is calculated accordingly. The feeder with the maximum energy is selected as the suspected fault line. The instantaneous transient power of the transient component of the current and the transient component of the voltage of the line is calculated, and the fault type is determined according to the polarity. The OCCO algorithm adaptively extracts fault features, and the double criteria of transient energy and instantaneous power polarity can accurately identify single-phase grounding and secondary grounding fault lines.

This invention relates to the field of partial discharge pattern recognition technology, specifically to a partial discharge pattern recognition method based on adaptive mathematical morphology. The method first acquires partial discharge signal data from defective equipment and plots PRPD (partial discharge pattern recognition) maps. After grayscale and binarization processing, binary discharge images are obtained, and a dataset is constructed. Then, adaptive mathematical morphology parameter optimization is performed on the binary discharge images in the training set. The optimal results are applied to extract morphological change features and multi-dimensional morphological structure features from the binary discharge images in the entire dataset. Finally, the extracted features are weighted and fused, input into a radial basis function network for pattern recognition, and the recognition result is output. This invention effectively improves the accuracy of partial discharge pattern recognition through adaptive morphological parameter optimization and multi-dimensional feature fusion, and is suitable for insulation condition monitoring and fault diagnosis of power equipment.

The application discloses a seismic data interpolation method and system based on mathematical morphology theory. The selected structural elements and the shot gather waveforms in the selected dip range of the same phase axis are subjected to open operation to obtain a first point set; the selected structural elements and the shot gather waveforms in the selected dip range of the same phase axis are subjected to closed operation to obtain a second point set; the first and second point sets are subjected to amplitude balance calculation according to the amplitude balance principle of the mathematical morphology theory to determine the interpolated seismic data. The sparse sampling seismic data can be encrypted and interpolated, false high-frequency information caused by too large line spacing is avoided, the interpolation result can better reflect the actual geological conditions, the interpolation can be effectively and quickly performed without the need of transformation domain and any prior information or geological model constraint, the interpolation effect is better, the interpolation precision of the sparse sampling data under any complex geological conditions is higher, the required internal memory is lower, and the calculation speed and efficiency are higher.

The invention discloses a non-cooperative underwater sound pulse signal real-time reconnaissance method and device, a storage medium and a product. The method comprises the following steps: performing short-time Fourier transform on an underwater sound pulse signal received by a single hydrophone to obtain a time-frequency distribution diagram; extracting a noise trend according to the time-frequency distribution diagram, and whitening the signal time-frequency distribution diagram to obtain a noise-whitened time-frequency distribution diagram; carrying out closed operation on the time-frequency distribution diagram after noise whitening by utilizing gray mathematical morphology filtering, and further carrying out normalization processing; binarizing the normalized closed operation result by using a weighted adaptive threshold method to obtain a binarized time-frequency image; clustering analysis is carried out on the time-frequency features extracted through binarization by using a density clustering algorithm; detection result judgment is carried out according to the clustering result, each sub-pulse signal is extracted, and parameters are estimated. According to the method, the limitation that the performance of the complex pulse combination signal is reduced by a traditional detection method is overcome, and the real-time performance of reconnaissance is considered.

The invention provides a morphological method and device for removing noise of a ship and a medium, and belongs to the technical field of seismic exploration. The method comprises the following steps: step 100, inputting seismic shot gather data; step 200, determining a parallel minimum granularity unit by adopting an SPARK parallel framework, and forming a target set of morphological filtering calculation; step 300, constructing structural elements of morphological filtering, and then predicting noise; step 400, performing boundary noise process treatment; and step 500, separating interference noise of the large ship to obtain de-noised seismic shot gather data. According to the method, two-dimensional mathematical morphology filtering and boundary processing of bidirectional structure elements are combined for denoising calculation, interference noise can be accurately predicted, denoising is accurate, parallel calculation is adopted, the calculation amount can be greatly reduced, the calculation efficiency is greatly improved, and the calculation cost is saved.

The invention relates to the technical field of urban development, and discloses a development boundary demarcation method considering urban three-dimensional morphology, which comprises the following steps: according to urban land utilization data, constructing scenes including natural development, economic priority, ecological expression and coordinated development, and utilizing a multi-objective planning model to predict land utilization requirements under different scenes; setting an evaluation unit according to the target distance, and constructing land utilization simulation driving factors including natural environment factors, human activity factors and urban form factors; on the basis of land utilization requirements and land utilization simulation driving factors, a development boundary stipulation model is constructed in combination with a PLUS model and an iterative mathematical morphology algorithm, and land utilization simulation and urban development boundary demarcation are carried out. According to the method, a PLUS model and an iterative mathematical morphology method are combined, a development boundary demarcation model integrating multi-source features is constructed, and a decision basis is provided for urban planning and management, urban sustainable development and the like.

A mathematical morphology-based image recognition method for the icing thickness of an isolator switch, aiming to solve the problem of poor accuracy of existing edge detection methods in recognizing an image of the icing thickness of an isolator switch. The method comprises: acquiring an iced isolator switch image; performing image preprocessing on the iced isolator switch image to generate a grayscale enhanced image; using mathematical morphology to perform edge extraction on the grayscale enhanced image to obtain an edge image; performing edge selection on the edge image to obtain an extracted image of the iced isolator switch; and using acquired original edge data of an un-iced isolator switch and the extracted image of the iced isolator switch to perform comparison calculation to calculate the icing thickness of the isolator switch. The beneficial effect is that the icing thickness of the isolator switch can be accurately obtained.

The invention provides a clear sandy coastline extraction optimization method based on a water body index model. The method comprises the following steps: acquiring multispectral remote sensing image data at a coast in an area to be subjected to coastline extraction; preprocessing the multispectral remote sensing image data; respectively calculating a normalized difference water body index and an improved normalized difference water body index, and generating corresponding grayscale images; adopting a maximum between-class variance method to determine optimal thresholds of the gray level image generated by the normalized difference water body index and the gray level image generated by the improved normalized difference water body index, generating a binary image of each gray level image based on the optimal thresholds, and obtaining a preliminary water body mask image; introducing a mathematical morphology method to optimize the preliminary water body mask image to obtain an optimized water body mask image; and performing smooth reconstruction on the optimized water body mask image by adopting a sliding window polynomial fitting method to obtain a clear sandy coastline image.

The invention discloses a seismic data surface wave noise suppression method, electronic equipment, a storage medium and a device. The method comprises the following steps: inputting seismic data to be processed; setting time direction structural elements and space direction structural elements; and performing surface wave noise suppression on the seismic data by using mathematical morphology based on the time direction structural elements and the space direction structural elements. According to the method, the time direction structural elements and the space direction structural elements are set, the mathematical morphology is utilized to perform preliminary surface wave noise suppression along the time direction, the difference profile of the original seismic data and the preliminarily extracted noise profile is calculated, and the mathematical morphology is utilized to perform signal extraction on the difference profile along the space direction, so that effective noise suppression is realized; meanwhile, effective signals are protected, seismic data quality is improved, and the method has good application prospects in seismic signal processing.

The invention discloses an urban form ventilation potential assessment method and system based on rasterized spatial analysis and mathematical morphology, and belongs to the technical field of urban ventilation and thermal environment optimization. The method comprises the following steps: uniformly rasterizing a building and a road, and quickly calculating the windward area density by adopting a global rotation-block column extreme value-backfilling process; through multi-angle rotation and sliding window matching, pixel-level scoring of the downwind consistency of the road local is realized; extracting an opening width threshold value, a direction alignment degree and a shape factor of the semi-closed open space by using a multi-scale and anisotropic morphological opening operation; and superposing the indexes according to weights to generate a comprehensive ventilation potential map. According to the method, the calculation time consumption and memory occupation are effectively reduced while the calculation precision is ensured, the ventilation corridor, the high-resistance area and the local ventilation weakness can be accurately identified, and the method is suitable for urban planning, ventilation corridor special design, air quality simulation and microclimate optimization design.

The application relates to a small-scale moon surface impact crater extraction method based on image space domain and frequency domain features, which comprises the following steps: acquiring LROC NAC images, and performing impact crater seed detection by using mathematical morphology to obtain impact crater seed points; based on the impact crater seed points, impact crater candidate region extraction is performed by using space domain features and based on statistical morphology constraint path set; based on the impact crater seed points, impact crater candidate region extraction is performed by using frequency domain features and based on structure consistency constraint multi-path; cross verification of the impact crater candidate regions extracted based on the space domain and the frequency domain is performed based on a difference factor, false extraction impact craters are removed, and the final impact crater extraction result is determined. Compared with the prior art, the application has the advantages of high detection result accuracy.

The invention provides a low-voltage alternating-current system short-circuit selective protection method and system based on a CAN bus. The method comprises the steps that voltage / current digital signals are collected at high frequency, and mathematical morphology filtering is implemented; fitting the filtered data by adopting a least square algorithm, and calculating the voltage and current vector modulus length; and constructing a short-circuit early detection comprehensive criterion based on the vector modulus length, and triggering short-circuit fault diagnosis when a real-time calculation value exceeds a preset threshold value. According to the morphological filtering, electromagnetic noise interference is effectively suppressed on the premise that short-circuit characteristics are reserved; the voltage and current vector modulus length criterion is compatible with transient response characteristics of distributed photovoltaic power electronic equipment and the like, and the reliability and robustness of the criterion are remarkably improved; millisecond-level detection and selective breaking of a short circuit fault are realized through space-time cooperation of the rapid detection module and the protection decision terminal.

The invention relates to an electric power signal pulse noise filtering algorithm based on mathematical morphology and an electric power signal random noise filtering algorithm based on mathematical morphology. The electric power signal pulse noise filtering algorithm based on mathematical morphology comprises the following steps: S1, determining a maximum pulse width, namely the number of occupied points; and S2, carrying out opening operation and closing operation on the voltage and current digital signals. And S3, marking an area in which the positive and negative pulse noise amplitudes exceed a threshold value. And S4, continuously applying the odd positive integer width horizontal straight line structure elements to an area in which the positive pulse noise amplitude exceeds a threshold value and which is not overlapped with the area in which the negative pulse noise amplitude exceeds the threshold value to perform opening operation. And S5, continuously applying the odd positive integer width horizontal straight line structure elements to a region in which the negative impulse noise amplitude exceeds a threshold value and is not overlapped with a region in which the positive impulse noise amplitude exceeds the threshold value to perform closed operation. And S6, alternately performing opening and closing operation on the areas which exceed the threshold value and are overlapped by applying horizontal straight line structure elements.

The invention discloses an infrared picture strain clamp heating detection method based on a skeleton line temperature difference comparison method. According to the method, firstly, accurate positioning of a strain clamp is achieved through an algorithm, then the contour and skeleton lines of the strain clamp are accurately extracted through a segmentation network and a mathematical morphology method, and a strain side skeleton and a drainage side skeleton are automatically split innovatively through a direction change rate algorithm. And finally, the temperature characteristics of the two parts are accurately obtained by calling the large Xinjiang SDK, and temperature difference comparison analysis is carried out, so that intelligent and quantitative identification of the heating defect of the strain clamp is realized. The method has the beneficial effects that the high precision of target identification and segmentation is ensured, and the robustness of skeleton line extraction and splitting is also ensured; the treatment efficiency is high, and the good field application value is achieved; reliable technical support is provided for power transmission line unmanned aerial vehicle intelligent inspection, and the automation level of power system operation and maintenance and the accuracy of defect diagnosis are remarkably improved.

The invention discloses a tomography enhancement method based on diffracted wave fusion. The method comprises the following steps: 1, preprocessing original seismic data; 2, extracting a common offset gather; thirdly, diffracted waves and reflected waves are separated through mathematical morphology filtering; 4, diffracted wave and full wave field migration imaging processing; 5, optimizing an original diffracted wave imaging result in combination with amplitude envelope attributes; and 6, carrying out dynamic weighted fusion on the full-wave-field seismic data and the optimized diffracted wave field seismic data. According to the method, the imaging details of the fault and the associated fracture are remarkably enhanced while the macroscopic structure characteristics of the seismic data are reserved, the small fault energy can be effectively enhanced, the fault recognition precision is remarkably improved, and reliable technical support is provided for evaluation and development scheme optimization of oil and gas reservoirs in complex structure areas.

The invention provides a license plate positioning method and device, and the method comprises the steps: carrying out the Sobel vertical operator binarization of a license plate image; wherein the license plate image is a gray stretch image; determining license plate texture information of the binarized license plate image, and segmenting upper and lower boundaries of a license plate region based on the license plate texture information; extracting left and right boundaries of the license plate area through a median line recursive scanning method based on the license plate area with the upper and lower boundaries segmented; and determining a license plate area based on the upper and lower boundaries and the left and right boundaries, and determining whether the license plate area is qualified based on preset priori knowledge. In the mode, through Sobel vertical operator binaryzation, jump point statistics, median line recursive scanning and mathematical morphology processing, rapid and accurate positioning of the license plate in a complex environment is realized, and the method has the characteristics of high robustness, strong real-time performance and wide universality, and can be widely applied to the fields of intelligent traffic management, vehicle identification and the like.

The application relates to a kind of sea surface ship target fast detection methods based on remote sensing image, including through inorganic person shoots sea surface image of different height position, and image information is introduced into image processing system;Image processing system obtains image information after through two ways to sea surface ship image of different height shooting, through edge detection mode, ship and other objects are distinguished;Adopt the minimum circumscribed rectangle to frame the ship connected body, to read its length and width.Specifically, draw rectangle, carry out rectangular mark sequence, set rectangle length and width, display rectangle number.The sea surface ship target fast detection method based on remote sensing image of the application is based on remote sensing image, adopts threshold method, edge detection method, mathematical morphology and other methods, can guarantee under the premise of certain identification accuracy, quickly and effectively identify the target different from background in a short time, so as to realize the fast detection of water surface ship.

The invention discloses a laser radar point cloud spectrum filtering method based on mathematical morphology, electronic equipment and a storage medium. The method comprises the following steps: constructing two laser radar point cloud mathematical morphological profiles: an expanded morphological profile and an expanded multi-attribute profile; the expanded morphological profile and the expanded multi-attribute profile can effectively combine laser radar point cloud spatial spectrum information in a regional scale, solve the problem of laser point cloud local spectrum noise, improve the point cloud spectrum information quality and facilitate subsequent data processing.

The embodiment of the application discloses a kind of distribution network high resistance ground fault detection method and device.The method comprises: based on the zero sequence current of each line in distribution network, determine to be detected line;To the zero sequence current corresponding to the line to be detected and the other zero sequence current corresponding to each other line, cross wavelet coherence analysis is carried out, and cross wavelet power spectral density is obtained;Determine target scale coefficient based on cross wavelet power spectral density;Based on target structure operator, mathematical morphological transformation is carried out to the zero sequence current under target scale coefficient, and the target current signal after transformation is obtained;The estimation of fractal dimension under different time scales is carried out to the target current signal, and determines fractal dimension vector;High resistance ground fault detection is carried out based on mixed Gaussian model and fractal dimension vector, and the fault detection result corresponding to the line to be detected is determined.Through the technical scheme of the embodiment of the application, the accuracy of high resistance ground fault detection in distribution network can be improved.