12 results about "Multiple failure" patented technology

This invention relates to a method for early warning of the resilience margin of mountain roads during rainstorms and floods based on multiple failure mechanisms. The method includes: acquiring multi-source monitoring data in real time; preprocessing the data to obtain an extended state vector at the current moment; establishing resilience critical boundaries for different failure mechanisms based on pre-generated labels, forming a multi-failure mechanism resilience critical boundary model library; mapping the extended state vector to the multi-failure mechanism resilience critical boundary model library, calculating the resilience margin of each mechanism component, and obtaining the comprehensive resilience margin and the current candidate dominant failure mechanism based on the resilience margins of each mechanism component; determining the current warning level and the final dominant failure mechanism based on the resilience margins of the mechanism components and the comprehensive resilience margin, combined with set warning conditions; and outputting warning information and linkage control commands corresponding to the current warning level and the final dominant failure mechanism. Compared with existing technologies, this invention has advantages such as strong interpretability, high lead time, good stability, and strong linkage targeting.

The invention discloses an intelligent inspection method for hoisting equipment based on multiple failure modes, and relates to the technical field of health management of the hoisting equipment, and the method comprises the steps: carding the whole life cycle typical damage and failure modes of a port crane structure, mechanism and electric control system, and constructing a typical failure / failure mode library; and based on the typical failure / fault mode library, analyzing a fault causal chain, and constructing a multi-level failure / fault tree model covering the structure and the transmission and electric control system. Cooperative monitoring of a multi-system coupling damage mode is achieved by constructing a multi-level failure / fault tree model covering a structure, a transmission system and an electric control system, traditional routing inspection is only aimed at a single system and cross-system faults prone to missing detection, and then relevance of mechanical abrasion, hydraulic leakage and electrical faults is synchronously tracked through fault causal chain analysis, so that the fault detection accuracy is improved. Electric-mechanical-hydraulic full-chain diagnosis is formed, and the positioning precision of complex faults is remarkably improved.

The monitoring device includes: an operation record acquisition unit that acquires operation records for multiple failure cases; a threshold setting unit that sets a threshold; a loss rate acquisition unit that acquires a loss rate representing the degree of wear and tear on the device corresponding to operating time; a failure rate cumulative frequency acquisition unit that acquires the shift of the failure rate cumulative frequency for the multiple failure cases relative to the loss rate; an evaluation index calculation unit that calculates an evaluation index as a value obtained by integrating the failure rate cumulative frequency with the loss rate; and a notification unit that notifies the user that maintenance is required when the loss rate, derived from the relationship between the load rate or load change rate of the monitored device and the threshold, reaches a given management value determined based on the shift of the failure rate cumulative frequency for the failure cases, wherein the threshold setting unit sets the threshold such that the evaluation index is minimized.

The invention discloses a method and system for predicting the residual life of a redundant safety instrument system, and the method comprises the steps: carrying out the life test of a to-be-predicted safety instrument system, and obtaining the residual life of the to-be-predicted safety instrument system according to the life data obtained through the test; constructing a mixed Weibull distribution model used for representing fault occurrence probability distribution characteristics of each device forming the safety instrument system to be predicted; performing maximum likelihood estimation on the mixed Weibull distribution model to obtain a maximum likelihood estimation value of a mixed Weibull distribution parameter; and constructing a fault distribution function of the to-be-predicted safety instrument system based on the fault equipment distribution characteristics corresponding to the failure of the to-be-predicted safety instrument system so as to obtain a failure probability density function, and based on the failure probability density function, obtaining the residual life of the current safety instrument system in combination with the maximum likelihood estimation value. The problem that the service life prediction of the redundant safety instrument system is limited to a single fault type and the application range is small is solved, and accurate prediction of the residual service life of the safety instrument system with multiple fault types at the same time is achieved.

The present application belongs to the technical field of finite element analysis, and proposes a hammer pin articulated rotor probability life prediction method based on multiple failure modes: firstly, the hammer pin articulated rotor in the forage rubbing crusher is respectively subjected to deterministic fatigue life prediction, deterministic wear life prediction and deterministic vibration fatigue life prediction; secondly, the hammer pin articulated rotor is subjected to uncertainty analysis based on the deterministic fatigue life prediction result, the deterministic wear life prediction result and the deterministic vibration fatigue life prediction result of the hammer pin articulated rotor; then, the hammer pin articulated rotor is subjected to probability fatigue life prediction, probability wear life prediction and probability vibration fatigue prediction based on the uncertainty analysis result of the hammer pin articulated rotor. The present application can accurately predict the life of the forage rubbing crusher and similar machines.

The application discloses a kind of double-layer RVM system function material pipe reliability analysis methods combined with meta-model, and the sample point of gradually approaching importance sampling function is obtained according to iterative updating strategy by the thought of constructing adaptive RVM meta-important sampling model, and the initial RVM model and corresponding importance sampling sample point are obtained after iterative convergence, and the initial adaptive RVM model can effectively identify multiple failure domains and multiple maximum probability points, and generate the candidate sample points required by the second layer adaptive RVM based on MCS.The method of the application can effectively improve the calculation efficiency, and has important reference value and guiding significance for the system reliability engineering problem of multiple failure domains and multiple maximum probability points.

The invention relates to an electromechanical actuator multi-failure mode health state assessment method and a storage medium, and relates to the technical field of electromechanical actuator failure prediction and health management. Multi-source health factor data of EMA is collected, and statistics of failure mode data and historical state transition information is carried out; extracting a key health factor of each failure mode based on the multi-source health factor data and fitting an edge distribution function; joint distribution of all failure modes is constructed based on the edge distribution function of each failure mode to describe the multilevel dependency relationship of each failure mode, the state transition probability between any two failure modes is calculated based on the joint distribution and historical state transition information, and a state transition probability matrix is obtained; and calculating the health state value of each failure mode, determining the weight based on the state transition probability matrix, and fusing to generate a comprehensive health state. The complex dependency relationship and the dynamic migration probability of multiple failure modes can be accurately quantified, and high-precision real-time evaluation of the EMA comprehensive health state is achieved.

The application discloses a small failure probability evaluation method based on prior constraint integration and hierarchical correction sampling, relates to the technical field of uncertainty quantification, and comprises the following steps: firstly, an integrated surrogate model is constructed by fusing multiple types of prior constraints, and residual correction is performed by using high-fidelity anchor samples; then, soft failure weights are calculated based on the corrected surrogate model, and candidate samples are searched in layers to obtain a failure sample set according to the soft failure weights; next, the failure samples are clustered to identify multiple failure sample clusters, and a multi-scale mixed proposal distribution is constructed; thereafter, bridge sampling driven by the effective sample size is performed, a transition step is adaptively controlled, and stable initial failure probability estimation is obtained; finally, through inverse probability weighted unbiased correction, false negative risk priority high-fidelity review is performed on the bridge samples, the initial estimation is corrected, and the final failure probability is output. Under the condition that the high-fidelity evaluation times are strictly limited, high-precision, high-stability and statistically unbiased estimation of the small failure probability are realized.

The invention belongs to the technical field of finite element analysis, and provides a hammer pin articulated rotor probability life prediction method based on multiple failure modes, which comprises the following steps: firstly, respectively carrying out deterministic fatigue life prediction, deterministic wear life prediction and deterministic vibration fatigue life prediction on a hammer pin articulated rotor in a forage grass triturator; secondly, based on a deterministic fatigue life prediction result, a deterministic wear life prediction result and a deterministic vibration fatigue life prediction result of the hammer pin articulated rotor, performing uncertainty analysis on the hammer pin articulated rotor; then, probability fatigue life prediction, probability wear life prediction and probability vibration fatigue prediction are carried out on the hammer pin hinged type rotor based on the uncertainty analysis result of the hammer pin hinged type rotor. The method can accurately predict the service life of the forage grass triturating machine and the similar machinery.

The invention relates to a creep-corrosion-hydrodynamic fatigue coupled deformation calculation and life evaluation method and device for a prestressed beam bridge, and a storage medium. The method comprises the following steps: establishing a beam bridge hydrodynamic simulation model containing a time-varying creep constitutive structure and prestressed tendons; parameters such as concrete creep, prestress relaxation, prestressed tendon corrosion depth and hydrodynamic fatigue cracking depth are updated year by year, the failure area of prestressed tendons is determined based on a corrosion and fatigue competition criterion, and the interface bonding performance is calculated. Then hydrodynamic force and long-term effect coupling simulation is carried out, mid-span deflection, relative displacement of piers and prestress amplitude are extracted, and then the corrosion-hydrodynamic force fatigue life of the prestressed tendons is evaluated. And iteratively calculating until the mid-span deflection, the service life or the fatigue life reaches a critical value, and outputting a deformation time-history curve. Compared with the prior art, the method has the advantages that the hydrodynamic accumulated displacement fatigue effect and the multi-factor coupling effect are considered, the minimum service duration is determined through multiple failure modes, and the actual situation can be comprehensively represented.

The application discloses a kind of FPSO riser support system's failure prediction method and system, it is related to failure prediction technical field, obtain current failure data about FPSO riser support system failure state and obtain final failure type in combination with historical failure data, obtain maintenance importance coefficient, pollution coefficient and production reduction coefficient calculated according to each final failure type corresponding historical data;According to maintenance importance coefficient, pollution coefficient and production reduction coefficient, the key coefficient of each failure type is calculated, and the maintenance urgency of the failure type of each FPSO riser support system is judged according to the key coefficient;In this way, the failure of FPSO riser support system can be predicted at multiple levels, to ensure the accuracy of failure prediction;And in the case where multiple failures may occur simultaneously, it can accurately determine which failure is the most urgent and critical, and reasonably allocate resources for priority maintenance and processing.