10 results about "Intermittent fault" patented technology

The invention provides an industrial sensor intermittent fault detection method and device and a medium. The method comprises the following steps: acquiring a process input vector of a target industrial process at a current moment and a process output measurement value measured by a sensor to be measured; determining a process output predicted value according to the process input vector and the virtual sensor model; calculating a current residual between the process output measured value and the process output predicted value; if the current residual error exceeds a target early warning threshold value, marking an early warning signal, and generating a first fault mark under the condition that the continuous triggering times of the early warning signal on a time sequence reach a first preset times; based on the residual sequence from the historical starting moment to the current moment, the posterior probability that the sensor to be detected is in a fault state at the current moment is calculated through a hidden Markov model, and a second fault mark is generated under the condition that the posterior probability is larger than or equal to a preset probability threshold value; and if at least one of the first fault mark and the second fault mark is established, determining that the to-be-detected sensor has an intermittent fault.

The invention discloses an airborne integrated task processor I / O interface module fault diagnosis method and system, and relates to the technical field of avionics equipment fault diagnosis. The method comprises the following steps of: acquiring partial analog quantity and digital quantity information from an I / O (Input / Output) interface module of an airborne integrated task processor, and acquiring corresponding temperature and vibration information through a temperature sensor and a vibration sensor; after preprocessing and labeling, constructing a combined model based on an attention network and a depth separable convolution strategy; and training the combined model, and performing real-time fault diagnosis on the I / O interface module. Hardware protection is triggered for a permanent fault, and replacement of a fault module is prompted; for intermittent faults, fault types and occurrence time are recorded, a degradation trend report is generated, and follow-up key monitoring is facilitated; according to the invention, additional acquisition equipment is reduced, the fault diagnosis accuracy of the I / O interface module of the IMP is improved, accurate fault positioning and targeted processing are realized, and the reliability and maintainability are improved.

The invention relates to the technical field of power equipment fault diagnosis, in particular to a fault detection method and system for an electric energy metering box, and aims at solving the problems that in the prior art, fault detection of the electric energy metering box faces intermittent fault missing detection for a long time, root positioning is fuzzy, and environmental adaptability is insufficient. According to the method, multi-modal time sequence data and environment characteristics are fused, dynamic parameter aggregation is realized by adopting an attention enhancement federation VAR model, intermittent faults are captured in combination with a dual-condition triggering mechanism, and bidirectional reasoning traceability is realized by constructing a multi-modal knowledge graph. The problems that a traditional method is insufficient in dynamic fault detection capability, deficient in root analysis means and poor in environmental adaptability are effectively solved, and the method has the advantages of improving fault detection sensitivity and positioning precision.

The application discloses a strategy for extracting fault features of electronic circuit systems, named as SSEST strategy, which is used for perceiving global information and paying attention to notable local information, and mining important local information means realizing expression of intermittent fault features of electronic circuit systems, specifically, first, S transformation is performed on a circuit output time sequence signal to acquire time-frequency domain features, then a squeeze and excitation network attention module is used to distribute channel weights, subsequently, input into a Swin Transformer framework, and pay attention to local information related to faults from global signals, and deep mining is performed on fault features, and two electronic circuits are taken as experimental circuits, the proposed diagnostic strategy realizes rapid and high-precision diagnosis, and shows that the proposed multiple attention mechanism is efficient for feature mining of intermittent faults of electronic circuit systems.

This application belongs to the field of interconnection network reliability and fault diagnosis technology, and discloses a method for intermittent fault diagnosis of low-bandwidth long interconnection networks based on graph attention mechanism. Targeting the hierarchical recursive structure and high connectivity of the network, under the PMC fault diagnosis model, a multi-round testing strategy is used to obtain test symptoms within the node's neighborhood. A feature vector is constructed for each node using local statistical feature extraction methods, and preprocessed using zero-padding and noise enhancement techniques. Finally, a graph attention network model is constructed, and the importance weights of neighboring node test results are dynamically learned using the attention mechanism to achieve accurate diagnosis of node fault states in the network. This application leverages the powerful local information aggregation capability of graph attention networks to overcome the diagnostic limitations of traditional algorithms, maintaining high diagnostic accuracy and robustness even with high fault rates, incomplete test symptoms, and large network sizes.

This invention relates to the field of equipment testing solutions, and discloses an intelligent generation system and method for equipment testing solutions based on feature data recognition. By extracting fault features that characterize immediate equipment anomalies and health status features that depict long-term performance baselines and aging trends, as well as performance degradation and deviation indicators based on health status features, the remaining service life of hardware components can be quantitatively predicted. This predicted value is then used as prior information to input a causal association model, and probabilistic reasoning is performed in conjunction with fault features. This significantly improves the sensitivity of progressive fault perception and the accuracy of root cause localization for intermittent faults, thereby generating more accurate equipment testing solutions. This effectively simplifies the testing process, reduces the average fault repair time, and decreases the reliance on the experience of senior experts, providing intelligent operation and maintenance support with predictive and adaptive capabilities for the stable operation of critical information infrastructure equipment.

The application belongs to the technical field of interconnection network reliability and fault diagnosis, and discloses a low-wrapping-length interconnection network intermittent fault diagnosis method based on a graph attention mechanism. Aiming at the hierarchical recursive structure characteristics and high connectivity characteristics of the network, under the PMC fault diagnosis model, the test signs in the node neighborhood are obtained through a multi-round test strategy. A local statistical feature extraction method is used to construct a feature vector for each node, and a zero padding and noise enhancement technology is used for pretreatment. Finally, a graph attention network model is constructed, the importance weight of the neighbor node test result is dynamically learned by using the attention mechanism, and the accurate diagnosis of the node fault state in the network is realized. The application uses the powerful local information aggregation capability of the graph attention network, breaks through the diagnosis degree limitation of the traditional algorithm, and can still maintain high diagnosis accuracy and robustness under the condition of high fault rate, incomplete test signs and large network scale.

The invention provides a ball grid array packaging device installation intermittent fault detection method and related equipment. The method comprises the following steps: acquiring an installed ball grid array packaging device and determining a part of test positions in the ball grid array packaging device; installing the ball grid array packaging device to a detection system, and applying a temperature cycle and random vibration environment; collecting the resistance value variation of the test position, wherein the collection frequency is nanosecond level; and when the resistance value variation is greater than or equal to a first preset resistance value variation and the duration is greater than or equal to a preset time, judging that the intermittent fault occurs at the test position. The ball grid array packaging device installation intermittent fault detection method and the related equipment provided by the invention are simple and convenient, can effectively identify the intermittent fault of the device, and are high in reliability.

The application discloses a kind of airborne integrated mission processor I / O interface module fault diagnosis method and system, it is related to avionics fault diagnosis technical field.First, part of analog quantity and digital quantity information is obtained from the I / O interface module of airborne integrated mission processor, and corresponding temperature and vibration information is obtained through temperature sensor and vibration sensor;After pre-processing and labeling, a combined model based on attention network and deep separable convolution strategy is constructed;The combined model is trained and used for real-time fault diagnosis of I / O interface module.The application triggers hardware protection for permanent fault, prompts to replace the fault module;For intermittent fault, record fault type and occurrence time, generate degradation trend report, facilitate subsequent key monitoring;The application reduces additional acquisition equipment, improves the fault diagnosis accuracy of I / O interface module of IMP, realizes accurate positioning and targeted processing of fault, and improves reliability and maintainability.