8results about How to "Realize automatic discrimination" patented technology

The present invention proposes a method and device for automatically constructing an evaluation operation template to improve the efficiency and accuracy of evaluating computer security. It is used to solve the problem that manual verification and operation configuration of computer system security in the prior art require a lot of time and energy, and the efficiency is often very low. At the same time, it solves the technical problem that experience and methods cannot be reused and the verification efficiency is low. The present invention proposes a method for automatically constructing an evaluation operation template. By automatically constructing an evaluation operation template, the test results are objectively classified, counted and analyzed. When the evaluation template itself can realize automatic judgment, or the evaluation template that can realize automatic judgment after manual correction is added to the template library, the existing experience can be used to improve the efficiency and accuracy of computer system evaluation, and automatic construction and detection can be realized.

This invention provides a method, system, and storage medium for discriminating surface electromyography (EMG) signals in chronic low back pain based on a Fourier analysis neural network. First, a dataset is acquired, containing several EMG signals and their corresponding ground truth labels. The EMG signals are preprocessed to obtain preprocessed EMG signals. These preprocessed EMG signals are then input into a constructed Fourier analysis-based neural network to obtain a predicted label for each EMG signal. A loss function is constructed based on the ground truth labels and predicted labels, and the Fourier analysis-based neural network is trained to obtain a trained Fourier analysis-based neural network. The EMG signal to be detected is then input into the trained Fourier analysis-based neural network to obtain the corresponding predicted label. This invention, by constructing and training a Fourier analysis-based neural network, aims to extract discriminative latent periodic features, achieving automated discrimination of abnormal patterns in EMG signals of chronic low back pain, thus achieving more robust, generalizable, and efficient discrimination.

The invention discloses a portable breather valve online detection system and method. The system comprises a signal acquisition module, a valve response monitoring module, a feature point identification module, a performance parameter evaluation module and a detection state output module. Signal quality is improved through continuous segment stability detection, a synchronous sudden change area is identified in dynamic data, a sudden change characteristic sampling point group is extracted, a traffic ratio threshold judgment mechanism is combined to realize accurate identification of an emergency state, and a rate change extreme point is compared with a fluctuation difference, a trigger node is calibrated, and a characteristic pairing value is extracted. A plurality of groups of flow pressure pairing sequences are formed in a test round and are compared with a standard interval to generate a compliance result, whether the inspiration and expiration state reaches the standard or not is automatically judged, and detection period label information and response state records with traceability are formed by performing unified archiving and identification processing on each detection period state. The recognition efficiency of abnormal opening and closing of the breather valve, the response speed of state feedback and the recording integrity of a detection result are improved.

This invention discloses an online dynamic monitoring method for magnetic field strength, belonging to the field of industrial non-destructive testing. The method includes: setting 8, 16, and 32 monitoring points at the end face, inner wall, shaft hole, and abrupt geometric changes, respectively, based on the workpiece's maximum size: less than 100 mm, 100 mm to 500 mm, and greater than 500 mm; deploying sensor nodes integrating Hall elements and wireless transmission modules at these points to collect magnetic field signals, encapsulate them into data frames, and wirelessly transmit them; receiving the data wirelessly and transmitting it to a host computer via a USB-to-serial converter, where it is digitally filtered and displayed in real time; comparing the magnetic field values ​​at each point with a safety threshold, triggering an alarm when the threshold is exceeded, and continuously receiving data until the magnetic field values ​​at all points are below the threshold. This invention achieves multi-point wireless online dynamic monitoring and closed-loop control, improving the comprehensiveness and real-time performance of the detection.

The present invention discloses a method for primary screening of onychomycosis based on an improved residual network, comprising the following steps: preparing an onychomycosis image dataset; inputting the image dataset into a feature extractor to extract features; integrating the features by a classifier; and calculating the difference between the current value and the true value. The present invention uses a feature extractor based on a lightweight attention mechanism to extract relevant features, inputs them into an improved classifier for classification, and uses a regularization loss function to normalize the output prediction of the network. The effective features in the onychomycosis image are learned and identified through forward and back propagation mechanisms to achieve automatic discrimination of the primary screening classification of onychomycosis.

The application discloses a kind of methods for automatically judging protection section limit point and turnout locking, it is to the laser survey data of trackside equipment collected to carry out processing, screen out the approachable signal with protection section limit point, identify its protection section limit point, and judge limit point type, then establish protection section limit point judgment model, carry out real-time difference comparison and update, judge whether protection section limit point meets design requirement;Again, turnout and warning post are analyzed, identify the axle counter near it, calculate the distance between each train after the direction of sliding and the axle counter near it, then establish turnout locking state judgment model, carry out real-time difference comparison and update, judge whether turnout locking state meets design requirement;Finally, obtain the judgment result.According to the application, only according to the collected laser survey data, the automatic update of protection section limit point and turnout locking state can be carried out, and whether it meets the design requirement is automatically judged.

The application is suitable for the technical field of communication and power safety monitoring, and provides a kind of optical cable identity recognition and illegal access detection method and system for smart grid, the method comprises the following steps: real-time acquisition vibration signal, when the amplitude of vibration signal is greater than the preset amplitude threshold, and its energy is greater than the energy threshold calculated based on dynamic baseline energy, it is determined as effective disturbance event;In response to effective disturbance event or according to the preset inspection plan, visible light image and infrared thermal image of target optical cable node are synchronously collected;Visible light image and infrared thermal image are spliced to form a fusion image;The fusion image is input into the lightweight target detection network, and the target detection result is output;According to the target detection result, the actual identity information of the current optical cable is extracted, and whether the actual identity information of the optical cable is legal and whether there is illegal access behavior is determined.The application provides a new generation of verifiable, traceable and closed-loop protection capability for the physical layer security of smart grid communication.

The invention relates to a distribution network protection constant value automatic checking method based on adaptive matching. The method comprises the following steps: step 1, establishing a constant value checking rule system; 2, determining the role of a distribution network protection switch; step 3, according to the distribution network protection switch role determined in the step 2, the distribution network protection switch adaptively matches a constant value checking scheme, and a constant value checking rule of each segment of current protection in the constant value checking rule system in the step 1 corresponding to the constant value checking scheme is obtained; step 4, automatically calculating a check value by the distribution network protection switch based on the check rule of the constant value of each section of current protection obtained in the step 3; and 5, based on the check value obtained in the step 4, judging a constant value check result. According to the distribution network protection switch role and the topological structure, the corresponding constant value checking scheme and the constant value checking position are adaptively matched to carry out constant value automatic checking.