96 results about "System diagnosis" patented technology

The invention relates to a thermal power plant fault early warning and diagnosis method based on a nebula system, and the method comprises the steps: collecting the multi-dimensional operation time sequence data of a thermal power plant, carrying out the feature extraction and lexical element processing of the multi-dimensional operation time sequence data through an encoder, and obtaining a unified equipment state lexical element sequence; based on the equipment state lexical element sequence, constructing a dynamic star map representing the operation state of the whole power plant; inputting the dynamic star map into a space-time fusion backbone network; the space-time fusion backbone network performs iterative processing on the dynamic star map and generates a health degree attenuation trajectory; when the slope of the health degree attenuation trajectory exceeds a preset threshold value, dynamic early warning and system diagnosis are triggered, and a natural language diagnosis report containing a causal reasoning chain is generated; new multi-dimensional operation time sequence data are collected in real time, and an incremental learning algorithm is used to update the encoder and the space-time fusion backbone network online; compared with the prior art, the system can continuously adapt to working condition changes and has high self-optimization capacity.

A method for operating and diagnosing faults in a laboratory instrument comprising a plurality of subsystems can include conducting an analysis sequence and a set of diagnostic steps. Such a method can be conducted using diagnostic reagents that contain paramagnetic particles but lack an antibody component. Such a method can also include evaluating a set of instrument subsystems in an order that is opposite to the order in which the subsystems are used during an analysis.

The invention discloses a Fast DDS-based QNX system soft diagnosis method and system and electronic equipment, and relates to the field of system diagnos.The method comprises the steps that S1, a Fast DDS-based global data space is constructed and serves as a real-time communication bus between a QNX system and an Android system, and decentralized interaction of dual-system diagnosis data is achieved; s2, deploying a soft diagnosis service in the QNX system; the soft diagnosis service comprises four core function modules: a black screen detection and self-healing module, a resource dynamic monitoring module, a virtual machine monitoring module and a burying point analysis module; s3, a diagnosis agent service is deployed in the Android system; the diagnosis agency service receives the alarm and data issued by the QNX system through the Fast DDS client; the method comprises the following steps: reading a log packaging file and a tcpdump file stored in a QNX system through a shared directory; and summarizing the data and uploading the summarized data to a cloud platform to realize visual display of the diagnostic data.

A cloud-edge collaborative processing system includes: an edge computing system, an ICU diagnosis and treatment device, a service terminal device, and a cloud platform. The edge computing system collects multi-source heterogeneous medical data output from the ICU diagnosis and treatment devices and performs preprocessing, stores preprocessed data into an edge database, and connects to the cloud platform for data transmission and business interaction. The cloud platform connects to a plurality of edge computing systems to perform computation and processing of massive data. The medical-staff handheld terminals and the data terminals of wards are used to issue service instructions to the cloud platform to obtain the required third-party-business services.

The embodiment of the invention provides a visual analysis method for diagnosis and optimization of an urban drainage system and related equipment, and belongs to the technical field of smart city and data visualization. According to the method, a closed-loop analysis framework formed by collaboration of a map view, an analysis view and a comparison view is constructed. The map view integrates a hydrological and hydraulic model simulation result, visualizes a drainage system state and supports interactive modification; the analysis view is used for extracting a key drainage subsystem based on rules, and performing causal visualization by adopting an optimized mulberry-based graph integrated with terrain elevation information, so that overflow causes are accurately positioned; a comparison view is visualized through a parallel histogram and version inheritance relation, and multi-scheme comparison and iterative optimization management are supported. According to the method, the problems of difficulty in causal analysis, poor interpretability and lack of iterative optimization support in the prior art are solved, the whole-process integrated support from problem identification and diagnosis to optimization verification is realized, and the analysis efficiency and decision scientificity of the urban drainage system are remarkably improved.

The invention discloses a servo motor driver parameter management method and system, and relates to the technical field of motor parameter management, and the method comprises the steps: initializing a parameter database, and outputting a database initialization result; executing a state machine control flow based on a database initialization result; according to the state information of the state machine, executing a corresponding parameter synchronization strategy and outputting a parameter synchronization state; based on the parameter synchronization state and the state machine state information, performing hierarchical error detection and processing, identifying abnormity through a fault detection algorithm based on a time window, performing fault processing according to a hierarchical recovery strategy, and outputting a system health state; and executing system diagnosis and performance optimization according to the system health state and the parameter synchronization state, performing read-write optimization through the parameter cache layer, and implementing predictive maintenance to complete parameter management. Through unified storage and management of data parameters, the reliability of parameter management of the servo motor is improved, and the system has the advantages of high fault identification precision and remarkably improved system stability.

An inspection system includes a stage for positioning a substrate to be inspected, one or more reticle-based diagnostic targets positioned on the stage, and a reticle inspection sub-system having a field of view encompassing the stage. The system includes a controller configured to move the field of view between portions of the stage to selectively perform substrate and run time diagnostics (RTD) of predefined image quality metrics. In embodiments, the system may be an APMI system for EUV mask inspection and the diagnostic targets may be EUV reticle-based diagnostic targets having predefined EUV performance patterning. In embodiments, the diagnostic targets may be positioned adjacent to the mask to be inspected to permit contiguous scanning to perform inspection and RTD.

The invention discloses an IMA system fault diagnosis modeling tool based on a logic algebraic model, which comprises an ICD information management module and a fault diagnosis logic definition module, and is characterized in that the ICD information management module is used for realizing reading, analysis and data storage of an ICD file set and obtaining messages and parameters defined in ICD files; and the fault diagnosis logic definition module is used for defining various fault diagnosis logic algebraic models by defining variable names and logic operators according to the messages and parameters analyzed by the ICD information management module. According to the method, a visual and efficient logic modeling tool can be provided for IMA fault diagnosis function design and developers, and a diagnosis logic model is modified and solidified aiming at an object system, so that a high-adaptability agile design and development way is provided for the IMA system diagnosis function.

The application provides a kind of detection system of infectious pathogen type based on 5 markers, the 5 markers include: GSDMD, p-MLKL, IL-6, PCT, CRP, the system includes the following modules: (1) detection model: the GSDMD of detection sample, p-MLKL, IL-6, PCT, CRP content;(2) analysis module: based on random forest algorithm, neural network algorithm is analyzed to data, constructs diagnosis bacterial infection model;(3) diagnosis module: based on machine learning algorithm model is judged to bacterial infection to be diagnosed sample.The system provided by the application reaches 0.909, the diagnostic accuracy rate, the sensitivity, specificity, positive predictive value and negative predictive value of diagnosis are as follows: 0.95, 0.85, 0.90, 0.92.

The present disclosure provides a diagnostic method and device of a vehicle-mounted system and an electronic device, and relates to the field of vehicle-mounted system diagnosis. The specific steps are: establishing the connection between a diagnostic instrument and a vehicle controller through the diagnostic instrument interface of a vehicle; controlling the SOC corresponding to the vehicle-mounted system through the vehicle controller, so that the SOC enters a diagnostic mode; and diagnosing the SOC through the diagnostic instrument. The present disclosure controls the vehicle controller by connecting the diagnostic instrument to the diagnostic instrument interface of the vehicle, so as to diagnose the fault of the vehicle controller, realizes the diagnosis of the vehicle controller, avoids the disassembly and damage of the vehicle structure during diagnosis, and improves the diagnosis efficiency of the vehicle.

The invention belongs to the technical field of fault intelligent diagnosis and positioning, and discloses an optical cable fault intelligent diagnosis and positioning method and system based on multi-mode fusion. The system comprises a multi-modal feature extraction module, a fault type intelligent classification module, a precise positioning integration module and a fault diagnosis positioning instruction output module, input preparation processing is carried out based on a multi-source processing data sequence, feature extraction is carried out according to a deep learning model, a fusion feature vector is obtained, and a fault diagnosis positioning instruction is output. Fault type classification is carried out based on the fusion feature vector, fault type confidence is calculated, a preliminary fault diagnosis report is obtained, a final fault positioning report is obtained, strategy instruction matching is carried out based on the final fault positioning report, and a matching result is output. The method has the remarkable advantages of high multi-modal data comprehensive degree, good system diagnosis intelligent effect and high operation and maintenance decision integration capability.

A computer system and method for intelligent system diagnostics and management is provided. The system comprises at least one processor and a memory storing instructions which when executed by the processor configure the processor to perform the method. The method comprises receiving resource data and usage data, preprocessing the resource data and the usage data into operational data, training and updating a foresight model using the operational data, receiving a forecast generated by the foresight model, and sending a notification for a recommended action based on the forecast. The forecast may be associated with a future resource state or event associated with the operational data.

Methods, systems, and devices for host system diagnostic testing are described. A diagnostic tool including a diagnostic executable stored to an external memory may evaluate a system including a host subsystem and a memory subsystem. Upon initialization, the diagnostic executable may configure trace points in one or more layers (e.g., associated with an operating system) of the host subsystem based on dependencies (e.g., libraries) stored to the external memory, and may receive, from the host subsystem, first data collected at the trace points, directly from a host system buffer, or from the memory subsystem. Concurrent to the collection procedure, the diagnostic executable may perform processing operations on the first data to generate second data, which may be associated with one or more metrics of system performance. The second data is stored to the external memory, and may be utilized to evaluate the system.

The invention provides a staged progressive drainage pipe network system diagnosis method, which comprises preliminary diagnosis and detailed diagnosis: the preliminary diagnosis comprises the following steps of: constructing a pipe network basic data framework, quickly screening and accurately positioning a high-risk area by using detection equipment, and outputting a problem hotspot map; giving monitoring point distribution suggestions in the detailed diagnosis step according to the problem hotspot map; the detailed diagnosis comprises the following steps: deploying a multi-parameter water quality sensor and an electromagnetic flowmeter at a monitoring point position according to a monitoring point distribution suggestion in the preliminary diagnosis step; continuously collecting data in dry and rainy seasons, and generating an external water infiltration amount, a concentration attenuation curve and a pipe network health index according to the data; and generating an engineering decision support report according to the data, and defining a repair target region, a regulation and storage scale and risk control measures. The method effectively avoids the treatment dilemma that the pipe network is damaged after being repaired, improves the scientificity and effectiveness of pipe network treatment, and is especially suitable for pipe network diagnosis projects needing precise cost control and efficient promotion.

There are provided a medical image processing apparatus, an endoscope system, a diagnosis assistance method, and a program capable of coping with an erroneous determination while utilizing an observation completion determination in which image processing is used and of suppressing oversight of an observation target part by a doctor. The medical image processing apparatus includes at least one processor. The at least one processor acquires a medical image; makes, on the basis of the medical image, an observation completion determination as to whether observation is completed for a target part; performs display control for causing a determined result of the observation completion determination to be displayed on a display device, receives a user input including an instruction for correcting display content indicating the determined result of the observation completion determination, and causes corrected content based on the user input to be reflected in the display.

An endoscope system including a processor. The processor includes hardware and is configured to acquire an in-vivo image, input the in-vivo image to a first classifier to output first performance information, and input the in-vivo image to a second classifier to output second performance information. The first classifier and the second classifier are mutually different classifiers.

The application provides a multi-task system CPU diagnosis method and device, wherein when a CPU diagnosis instruction is acquired, all interrupts of the system are closed; a diagnosis event is determined based on the CPU diagnosis instruction and diagnosis is performed; when diagnosis is completed, a diagnosis result is generated and the closed interrupts are opened, so that the CPU diagnosis can be efficiently performed in the system running process. The application utilizes a clock interrupt service program to realize the CPU diagnosis in a single process mode under a multi-task real-time operating system, avoids the problem that interrupts and diagnosis processes interrupt the CPU diagnosis concurrently, and realizes the CPU diagnosis of the multi-task operating system.

The present application provides a kind of medical image processing device, endoscope system, diagnostic aid method and program, can be in the observation of using the determination of using image processing is completed at the same time processing error determination, can inhibit the oversight of physician to observation object site.Medical image processing device has at least one processor.At least one processor obtains medical image, based on medical image, whether observation of object site is completed observation completion determination, carries out the display control of the determination result of observation completion determination is displayed on display, accepts the user input including the instruction of the display content of the determination result indicating observation completion determination is modified, and the content modified by user input is reflected in display.

A method for heating, ventilation, and air conditioning (HVAC) system diagnostics includes, in response to determining that a triggering event has occurred, entering a filter diagnostics mode. A first instruction is sent to a thermostat to shut down an HVAC system. A user is instructed to locate and remove a filter. The filter is classified as acceptable or dirty. In response to classifying the filter as acceptable, the user is instructed to the turn on the HVAC system. In response to determining based on the triggering event that a desired mode is a cooling mode, a first value of a room temperature is determined. The user is instructed to set a temperature setpoint below the first value. A second value of the room temperature is determined. In response to determining that the second value is less than the first value, it is determined that the HVAC system operates properly.

The invention belongs to the technical field of power distribution network leakage current detection, and particularly relates to a CNN and FiLM-based leakage current type intelligent identification method. Comprising the following steps: S1, collecting real-time operation data of a typical power supply area, obtaining leakage current waveforms and related environment characteristic parameters under different working conditions, and constructing an original leakage current sample data set; s2, a CNN-based leakage current classification model is constructed, a FiLM condition modulation module is introduced, a multi-task learning framework is used at the tail of the network, a main task is leakage current type identification, and an auxiliary task is grounding system discrimination; s3, using a weighted cross entropy loss function to alleviate a class sample imbalance problem; an OneCycleLR dynamic learning rate scheduling strategy is introduced; s4, evaluating the performance of the model on the test set, and using the accuracy and the confusion matrix as evaluation indexes; according to the method, high-precision identification of multiple types of faults such as single-phase grounding, arc type electric leakage and direct current system electric leakage is realized, different grounding systems can be adapted, and the accuracy and robustness of system diagnosis are improved.

The invention discloses a traditional Chinese medicine tongue picture multispectral intelligent diagnosis system, and relates to the technical field of computer vision. Comprising a data acquisition and preprocessing interface, a self-adaptive spectrum super-resolution reconstruction module, a biological tissue optical inversion module, a multi-dimensional feature fusion analysis module, a traditional Chinese medicine syndrome deduction decision module and a result interpretation and visual interaction module, the system is deployed on a cloud server or a high-performance edge computing terminal, and is connected with a multispectral imaging module through a USB, GigE or wireless mode so as to access a multispectral acquisition device, so that integrated operation of multispectral acquisition and system diagnosis is realized. According to the invention, through introduction of the multispectral imaging technology, rich spectral information far beyond a common visible light image can be obtained from the tongue body, a data basis is provided for subsequent inversion of deep physiological and biochemical indexes, and the problem that traditional tongue diagnosis cannot deeply explore the microscopic physiological state of the tongue body is solved.

Method for analyzing a mechatronic system, wherein the mechatronic system has one or more functions, the functions comprising one or more hardware and / or software functions, and in the method - a first network (20) in the form of a tree graph with several hierarchy levels and nodes (201, 202, 203, 204, 205, 206) arranged in the hierarchy levels is provided, wherein the nodes (201-206) are each representative of one of the functions of the mechatronic system and are linked to each other via one or more logical operators, such that the tree graph represents dependencies between the functions represented by the nodes (201-206), wherein the top hierarchy level has a single node (201) as the initial node, - a node of the tree graph of the first network (20) is specified as the first trigger node, - Software network data is provided that is representative of the software functions of the mechatronic system and their dependencies, - depending on the first trigger node and the software network data, a second network (30) in the form of a tree graph with several hierarchy levels and nodes (301, 302, 303, 304, 305) arranged in the hierarchy levels is determined, wherein the nodes (301-305) are each representative of one of the software functions of the mechatronic system and are linked to each other via one or more logical operators, such that the tree graph represents dependencies between the software functions represented by the nodes (301-305), wherein the top hierarchy level has a single node (301) as the initial node, and - depending on the first network of action (20) and the second network of action (30), the mechatronic system is analyzed, wherein an analysis of the mechatronic system includes that - the first network (20) is extended by the second network (30) such that the first trigger node of the first network (20) corresponds to the initial node of the second network (30), and - the mechatronic system is analyzed depending on the extended first network of action (40), wherein the mechatronic system has one or more diagnostic functions that are representative of one or more software functions for diagnosing the mechatronic system, in which - a node of the tree graph of the extended first network (40) is specified as the second trigger node, - one of the diagnostic functions is specified and assigned to the second trigger node, - Diagnostic network data is provided that is representative of the diagnostic functions of the mechatronic system and their dependencies, - depending on the second trigger node and the diagnostic network data, a third network (50) is determined in the form of a tree graph with several hierarchy levels and nodes (501, 502, 503, 504, 505) arranged in the hierarchy levels, wherein the nodes (501-505) are each representative of one of the diagnostic functions of the mechatronic system and are linked to each other via one or more logical operators, such that the tree graph represents dependencies between the diagnostic functions represented by the nodes (501-505), wherein the top hierarchy level has a single node (501) as the initial node, such that the second trigger node of the extended first network (40) corresponds to the initial node of the third network (50), and - depending on the extended first network (40) and the third network (50) the mechatronic system is analyzed.

This application provides a unified management method and system for system diagnostic tools that adapt to heterogeneous plugins. The method includes: configuring a Seccomp filter for the target diagnostic process of the system diagnostic tool; obtaining the plugin identifier and operation parameters in the system call; querying whether corresponding cached diagnostic data exists in the BPF Map based on the plugin identifier and operation parameters; at the exit of the system call, the eBPF program detects whether the data write-through marker exists in the BPF Map; if it exists, the corresponding diagnostic data is read from the data cache of the BPF Map and written to the user buffer, and the return value register is modified to the data length in the data write-through marker. This method can achieve data path efficiency that matches the plugin backend processing speed while maintaining non-intrusive unified management of multiple heterogeneous plugins.

A fault diagnosis procedure for detecting faulty components in a vehicle, wherein, for at least one identifiable fault cause of a faulty component, a system parameter of the vehicle that is influenced by the fault cause is determined and compared with a target value of the system parameter, and a determined signal deviation between the determined system parameter and the target value of the system parameter is compared with a stored fault characteristic signal deviation, and if the determined signal deviation matches the fault characteristic signal deviation, the fault cause and / or faulty component associated with the fault characteristic signal deviation is uniquely identified, wherein the entire development process for the fault diagnosis procedure essentially consists of the following six individual steps, which are executed sequentially: - Selection of faults to be diagnosed, whereby in this first step the various components of the vehicle are analyzed in such a way that the possible causes of faults are listed for each component; - Structural analysis, whereby in this second step it is checked whether there is a possibility in principle of model-based diagnostics of the system; - Creation of a nominal model, whereby in this third step, so-called nominal models are created for those system parameters that are used and evaluated for the identification of a faulty system component, in which a normal operation of the system component is depicted; - Sensitivity analysis, in which, in this fourth step, defined causes of failure are imprinted into the system and their effects on the relevant system size(s) are considered using the nominal model, thereby identifying a unique assignment of a cause of failure or a faulty system component to its effect on the relevant system size; - Creation of fault models, whereby in this fifth step the knowledge about the effect is stored in a reference source onboard in the vehicle, whereby, based on this reference source, a statement can be made at any time valid for the diagnosis as to whether this cause of fault is present or not and - Integration into a diagnostic system, whereby in this sixth step the developed diagnostic procedure is transferred to a corresponding target control unit in the vehicle.

The presented invention relates to a method (100) for diagnosing a tank system (200), wherein the method (100) comprises: - Issuing (101) a command to close tank valves (207) of respective tanks (201) of the tank system (200), - Determining (103) a differential pressure between a first pressure in a respective tank (201) and a second pressure in a piping system (211) of the tank system (200), after a specified waiting period, - Adjusting (105) the differential pressure with a predetermined differential pressure threshold value, - Output (107) an error message reporting a severe leakage of the tank system (200) if the differential pressure differs from the differential pressure threshold.

The present application belongs to the technical field of PH detection, particularly relates to sauce PH detection technology, and specifically discloses a PH value on-line detector based on artificial intelligence, which realizes simultaneous monitoring of sauce distribution uniformity in the sauce pH detection process, and implements vibration control based on the feedback of sauce distribution uniformity, so that the detection is ensured to be in a fully mixed state, the pH measurement accuracy is significantly improved, and through linkage analysis of pH mutation identification and uniformity state, process disturbance and probe failure can be effectively distinguished under continuous monitoring conditions, false alarms and invalid maintenance are avoided, the intelligent level of system diagnosis is improved, stable and reliable on-line pH detection is realized, and when vibration control is implemented based on the feedback of sauce uniformity, liquid level offset monitoring is introduced, vibration adjustment is carried out in combination with the dynamic coupling relationship between the uniformity index and the liquid level offset, stirring is ensured to run within the structural safety range, excessive vibration is avoided, and the system stability and operation safety are improved.

The application belongs to the field of data processing, and provides an intelligent diagnosis and repair method and device for a business system to solve the problem of high complexity of current business system diagnosis and poor user experience. The intelligent diagnosis and repair method for the business system comprises determining milestone nodes and obtaining expected return information of each milestone node; reproducing problems of a business process, comparing the consistency of actual return information of the business process running to each milestone node with corresponding expected return information layer by layer, and finding a first problem node; finding an abnormal configuration position and its cause according to the generation logic of the expected return information of the first problem node, matching a corresponding abnormal repair strategy to perform abnormal repair; after the first problem node is repaired, the business process is continued to be run, the next problem node, the abnormal configuration position and its cause are found, and the corresponding abnormal repair strategy is matched, until all problem nodes are repaired. It can conveniently and accurately locate the root cause of the problem and improve user experience.

The invention belongs to the technical field of fire-fighting equipment, and particularly relates to an online state monitoring and fault intelligent diagnosis system for a fire-fighting robot. The system comprises an edge computing terminal, a communication signal collector, a vibration signal collector, a vibration signal sensor, a cloud server and a user terminal. Wherein the edge computing terminal is used for receiving data uploaded by the communication signal collector and the vibration signal collector, and a fault diagnosis algorithm, an EMD (Empirical Mode Decomposition) and a Bayesian optimized SVM (Support Vector Machine) fault diagnosis model are deployed in the edge computing terminal; the fault diagnosis algorithm is used for preprocessing the vibration signal, then an EMD decomposer is used for extracting the internal mode of the signal, and multi-dimensional features such as statistics, an envelope spectrum and instantaneous frequency are fused; and finally, through SVM fault diagnosis, the state of the robot transmission system is intelligently judged, and a state monitoring and fault analysis report is generated and uploaded to a cloud server. The system is high in diagnosis precision, high in real-time performance and high in operation and maintenance efficiency.

The application relates to a bearing fault diagnosis method and system based on a deep adaptive network under small samples. The diagnosis method comprises the following steps: collecting vibration signals in the bearing operation process and storing the vibration signals in a server; pre-processing the vibration signals, carrying out one-dimensional vibration signal two-dimensional image gray valueization, and storing the vibration signals in a database; extracting image data in the database, carrying out data enhancement based on a deep convolutional generative adversarial network, and constructing a database for fault diagnosis; and using a deep adaptive network to carry out small sample fault diagnosis. The diagnosis system comprises a preprocessing module, a data enhancement module and a diagnosis module. The deep convolutional generative adversarial network and the deep adaptive network are combined for use, training of the network can be completed under unfamiliar working conditions by using a small amount of labels, the training time and the training cost of the network are reduced, the portability of the model is enhanced, and the model has good robustness for small sample working conditions.

An information handling system including a processor and a memory coupled to the processor. The processor may be configured to monitor the information handling system to detect whether an information handling system is in a low power state. If the information handling system is in the low power state, then power consumption of the information handling system may be monitored. If the power consumption of the information handling system deviates from an expected power consumption of the information handling system, then a diagnostic routine may be performed.