9 results about "Predictive failure analysis" patented technology

The invention discloses an intelligent photovoltaic grid-connected adaptive system based on multi-modal sensing and predictive analysis, and the system comprises a multi-modal sensing unit which is used for collecting the multi-source information of a photovoltaic system; the predictive fault analysis module is used for predicting potential system faults based on the multi-source data; the self-adaptive phase-frequency synchronous control unit is used for dynamically adjusting the output parameters of the photovoltaic inverter, so that the output of the photovoltaic inverter is matched with the parameters of the power grid; the comprehensive decision engine is used for generating a grid-connected or off-grid instruction; the self-repairing execution unit is used for generating a specific response scheme and controlling related equipment to execute based on the fault early warning and the strategy instruction of the comprehensive decision engine; and the remote monitoring and manual intervention interface is used for providing a monitoring interface. Through cooperative work of multi-modal data perception, predictive fault analysis and adaptive control, safe, efficient and intelligent grid connection of the photovoltaic system and the power grid is realized, and the reliability, safety and economical efficiency of the photovoltaic power generation system are improved.

A system and method for capturing, monitoring, and utilizing fugitive combustible gases from natural gas compressors and engines. The system comprises collection points for capturing gases from multiple sources, a filtration system, a control valve, a programmable logic controller for monitoring and control, and an engine air intake system for utilizing the gases as supplementary fuel. Advanced AI-driven monitoring capabilities transform sensor and emissions data into predictive maintenance insights, enabling early detection of equipment failures through pattern analysis. The system integrates FTIR analyzers, electrochemical sensors, and SCADA connectivity to provide comprehensive emissions monitoring and regulatory compliance documentation while optimizing operational efficiency through probability-based failure predictions.

A computational device determines whether a generated system event in the computational device is a critical error or a non-critical error. In response to determining that the generated system event is a critical error caused by a first field-replaceable unit (FRU), the critical error is processed to initiate tasks that lead to replacement of the first FRU in the computational device to eliminate the critical error. In response to determining that the generated system event is a non-critical error caused by a second FRU, operations are performed to proactively reserve a substitute FRU to replace the second FRU to eliminate the non-critical error, in anticipation of the second FRU failing at a future time to cause another critical error.

A predictive failure analysis system is operably connected with a data switch adapted to be operably connected with an electronics device to receive signals from sensors of the electronics device. The system performs the method steps of receiving signals from the sensor; tracking the signals to determine changes in the signals over time; determining the condition of the electronics device based upon the signals collected over time; and transmitting an alert when the condition of the electronics device has deteriorated to the point where the electronics device needs to be repaired or replaced.

A fault-tolerant architecture for wafer-scale all-silicon computing engines is disclosed, featuring "CREST" (Cyclic Redundant Spare Testing) and dynamic column substitution. The system integrates a massive array of processing elements with granular redundancy, such as spare columns and rows. A network of bypass multiplexers allows logical compute resources to be remapped to physical hardware dynamically. A redundancy controller performs background cyclic testing by pairing active columns with spares and comparing outputs, enabling run-time detection and repair of defects without system downtime. The architecture supports predictive failure analysis, secure configuration updates, and hierarchical fault management across vertically stacked dies and the wafer-scale substrate, ensuring high yield and reliability for zetta- scale inference workloads.

An information handling system may include at least one processor and a memory element. The information handling system may be configured to: determine a category for at least one software application running on the at least one processor, wherein the category is indicative of a degree to which the at least one software application utilizes the memory element; and based on the determined category, adjust a parameter associated with the memory element, wherein the parameter relates to predictive failure analysis of the memory element.

A computational device determines whether a generated system event in the computational device is a critical error or a non-critical error. In response to determining that the generated system event is a critical error caused by a first field-replaceable unit (FRU), the critical error is processed to initiate tasks that lead to replacement of the first FRU in the computational device to eliminate the critical error. In response to determining that the generated system event is a non-critical error caused by a second FRU, operations are performed to proactively reserve a substitute FRU to replace the second FRU to eliminate the non-critical error, in anticipation of the second FRU failing at a future time to cause another critical error.

The present application relates to the technical field of vehicle analysis, and especially relates to a vehicle intelligent analysis system based on Internet of Things, a detection device of an air conditioner compressor of a subway vehicle is connected through Internet of Things networking connection of a management platform and energy consumption analysis module, running state data is generated into a local energy consumption feature sequence through a data feature extraction model constructed based on an improved TCN of embedded data causality selection; an energy consumption prediction module generates compressor prediction data through an improved GRU constructed compressor efficiency prediction model based on embedded thermodynamic constraints; a dynamic adjustment module is used to dynamically adjust the model parameters of the data feature extraction model and the compressor efficiency prediction model through a feedback model constructed based on Adam; the compressor prediction data is input into an air conditioner simulation model to generate air conditioner device simulation parameters, and fault analysis and maintenance are carried out according to the air conditioner device simulation parameters. The present application realizes predictive fault analysis and maintenance based on Internet of Things.

The invention relates to the technical field of vehicle analysis, in particular to an intelligent vehicle analysis system based on the Internet of Things, which comprises a management platform, an energy consumption analysis module, an energy consumption analysis module and an energy consumption analysis module, generating a local energy consumption feature sequence from the operation state data through a data feature extraction model constructed by an improved TCN based on embedded data causal selection; the energy consumption prediction module is used for generating compressor prediction data from the local energy consumption characteristic sequence through a compressor efficiency prediction model constructed by an improved GRU based on embedded thermodynamic constraint; the dynamic adjustment module is used for dynamically adjusting model parameters of the data feature extraction model and the compressor efficiency prediction model through a feedback model constructed based on Adam; and inputting the compressor prediction data into the air conditioner simulation model to generate air conditioner part simulation parameters, and performing fault analysis and maintenance according to the air conditioner part simulation parameters. According to the invention, predictive fault analysis and maintenance based on the Internet of Things are realized.