fault diagnosis algorithm 中文意思是什麼
fault diagnosis algorithm
解釋
故障診斷演算法-
Study of fault diagnosis hybridized with genetic algorithm and bp algorithm
演算法的故障診斷方法的研究 -
One fault diagnosis model and corresponding algorithm was constructed based on neural network and evidence theory for taking a step forward diagnosis correct rate, which can cut down the imput dimension of neural network 、 improve classification ability 、 decrease the error classify rate of diagnosis system. then, the feasibility and effectiveness of this method was manifested by specific diagnosis example
為進一步提高診斷準確率，本文基於神經網路和證據理論，構建了基於決策層信息融合的故障診斷模型及其相應演算法，目的在於降低神經網路的輸入空間，提高其分類能力，降低診斷系統的誤分類，診斷實例表明了這種方法的可行性和有效性。 -
Abstract : in this paper, the significance of remote monitoring and fault diagnosis system for the pipe laying pump units in petroleum conveyance process is discussed. the communication principle and particular of remote monitoring and fault diagnosis system for pump units are analyzed. the hardware configuring and software algorithm of this system are constructed, and then, advantage and benefit out of this system are pointed out
文摘:論述了原油輸運過程中的加壓泵機組遠程監測及故障診斷系統的意義，分析了輸油泵機組遠程監測及診斷系統的通信原理和特點，建立了實現該系統的硬體結構和軟體體系，最後說明了採用該系統的優勢。 -
Neural network algorithm ' s application in fault diagnosis of aeromotor oiling system
演算法在滑油系統故障診斷中的應用 -
Next, the thesis carefully describes the definitions method and course of the mechanical fault diagnosis technology, and the structure ~ algorithm ~ trait and nature of ann model. and it relates the theoretical meaning of the research on the mechanical fault diagnosis technology based on ann theory. the thesis also points out that the peculiar structure and trait of ann have poured into new vitality, so it is possible that the mechanical fault diagnosis technology extricates itself from predicament
其次，本文系統介紹了機械故障診斷技術的定義、方法和過程以及人工神經網路模型結構、演算法、特點和性質，並在此基礎上闡述了人工神經網路理論應用於機械故障診斷技術研究的理論意義，指出人工神經網路獨有的結構和特點為機械故障診斷技術注入了新的生命力，從而很有可能使機械故障診斷技術走出困境。 -
In this paper, the power transformer interior fault diagnosis technique based on the dissolved gas in oil analysis and the principles of genetic algorithm are analyzed. the forecasting models for power transformer interior fault are proposed based on the grey prediction model. the genetic algorithm is applied to estimating optimum coefficients of this forecasting model
本文對基於變壓器油中溶解氣體分析（ dissolvedgasesanalysis ，簡稱dga ）技術的大型電力變壓器內部故障診斷技術和遺傳演算法原理進行了深入的分析，首次將灰色預測理論引入到大型電力變壓器內部故障預測工作中，運用遺傳演算法實現預測模型的優化，建立了基於遺傳演算法的變壓器內部故障改進灰色預測模型。 -
Rule reasoning, fuzzy decision and information fusion algorithm are merged, and the step fault diagnosis method is accomplished ; for different object, when necessary knowledge is given, a special fault diagnosis system will be automatically produced, and the diagnosis result will be given
將規則推理、模糊決策、多傳感器信息融合演算法融為一體，形成一階梯式故障推理機制；對不同的診斷對象，只要設置好必要知識模塊，就可自行生成一專用故障診斷系統，並能自動輸出診斷結果。 -
In the next place, an improved algorithm of grounding fault location for tree - type distribution system which is based on new fault function and criterion measure, is proposed in order to complete fault branch ide ntification, fault location and fault value. a lot of the simulation of fault diagnosis and location by computer demonstrate that the algorithm is effective
其次論文基於輻射狀饋線的任一分支線路發生接地故障，通過分析與推導，建構了配電線路單相短路點定位的故障定位函數和相應的故障判據，利用樹網單端信息完成故障分支識別、故障定位和過渡電阻定值。 -
A probabilistic algorithm of system - level fault diagnosis based on greedy principle
基於貪婪演算法的系統級故障的概率診斷 -
The number of the hidden layers of mul - tilayer perceptrons ( mlps ) is analyzed, and three - layer perceptrons neural network is adopted ; by analyzing the mechanism of the neural cells in hidden layer, a method for combining genetic algorithm and bp algorithm to optimize the design of the neural networks is presented, and it solves the defects of getting into infinitesimal locally and low convergence efficiently, it can also solve the problem that it can usually obtain nearly global optimization solution within shorter time through using genetic algorithm method lonely ; several examples validate that this algorithm can simplify the neural networks effectively, and it makes the neural networks solve the practical problem of fault diagnosis more effectively
對多層感知器隱層數進行了分析，確定採用三層感知器神經網路;通過對隱層神經元作用機理的分析，引入了遺傳演算法與bp演算法相結合以優化設計神經網路的方法，有效地解決了bp演算法收斂速度慢和易陷入局部極小的弱點，還可以解決單獨利用遺傳演算法往往只能在短時間內尋找到接近全局最優的近優解的問題;通過實例驗證了這種演算法能夠有效地簡化神經網路，使神經網路更加有效地解決實際的故障診斷問題。 -
2. study on knowledge - based fault diagnosis system systemeticly to find the causes of faults, maily include the following aspects : representation of symptoms and experience knowledge ; measurement of fuzzy symptoms ; inference algorithm of the inaccuracy diagnosis ; interface of acquisition of evidence and management of knowledgebase. 3
以詳細診斷故障原因為目的，系統的研究基於知識的故障診斷系統，主要包括：故障徵兆知識及經驗知識的形式化表示；故障徵兆知識的量化處理；不確定診斷問題的求解演算法；獲得診斷證據的介面及知識庫管理技術。 -
At last, the valid data based fast emd algorithm was proposed. chaper five aimed to the requirement of the emd based time - frequency analysis in the field of rotating machinery signal analysis and fault diagnosis. studied the method of rotatory speed prediction to improve the precision of complete period sampling of vibration signals in rotating machinery, then, discussed the phenomenon of mode fission in noise signal anlysis by emd and provided the filter method to weaken the phenomenon. after then, found a process to analysis the signals using emd - based method in the field of rotating machinery signal analysis and fault diagnosis
第五章針對旋轉機械信號進行emd時頻分析的要求，提出了提高整周期采樣精度的預測演算法和適合於單片機計算的近似公式；論述了模態裂解現象，並通過模擬信號和實際信號的研究，提出了使用濾波技術來減弱模態裂解現象的方法；給出了適合於旋轉機械振動信號基於emd時頻分析的工作步驟；研究了基於emd的旋轉機械振動信號自適應濾波技術。 -
Abstract : in order to process signal in depth and to extract the fault feature from original signal in machinery diagnosis ， the graphical display algorithm that can keep the data length of wavelet transform results the same as that of original signal is used. the fault diagnosis of a bend axial piston pump via b - spline wavelet that has linear phase is provided. the results of study demonstrate that the new method has excellent feature and the weak fault signal can be extracted from the strong vibration background of the pump
文摘:採用具有線性相位的b樣條小波，應用圖形顯示演算法並結合小波變換快速演算法將信號分解到不同的頻帶上，且分解結果和原信號長度保持一致，可對信號進行深層次的處理，克服了傳統的信號處理方法不易提取微弱信息的不足.通過對礦用斜軸式柱塞泵振動信號的分析，分離出了配流副磨損、球鉸松動、缸體及泵軸支撐軸承的故障特徵，為液壓泵的故障診斷提供了依據，並為信噪分離、微弱信號提取及設備的早期故障診斷提供了一條有效途徑 -
After researching the application of artificial neural network to fault diagnosis of transformer, the back propagation algorithm is improved observably. inducting chaos dynamics principium to create chaos neural network back propagation algorithm and using the pretreatment of training sample, the emulation program show that this method is effective
本文深入研究了人工神經網路在變壓器故障診斷中的應用，對目前最常採用的bp演算法做出了較大改進，在原有演算法中引入混沌動力學原理構造了混沌神經網路bp演算法，並提出了訓練樣本集的預處理方法，在模擬訓練中取得了滿意的效果。 -
Complete fuel cell condition monitoring and fault diagnosis soft and hardware system, adopting the fit fault diagnosis algorithm, through the verify of practice, basically satisfy prescriptive technique target, obtaining the favourable result
完成了燃料電池狀態監測與故障診斷系統硬體和軟體設計，採用了合適的故障診斷演算法，經過了實踐的檢驗，基本滿足了所規定的技術指標，取得了良好的效果。 -
For real - time monitoring the each work status of fuel cell, on time discovering every kind of equipment failure of, fuel cell of condition monitoring and fault diagnosis system adopts the usb bus system to set up the hardware platform, regarding neural network theory as foundation, creates fault diagnosis model and algorithm, and joining together both of the advantage, guarantees the safe and dependable running of fuel cell system
為了能夠實時監測燃料電池的各個工作狀態、及時發現各種可能出現的設備故障，燃料電池狀態監測與故障診斷系統採用usb總線系統搭建硬體平臺，以神經網路理論為基礎，建立故障診斷模型與演算法，把兩者的優點充分結合，保證了燃料電池系統安全可靠的運行。 -
Cluster - based fault diagnosis algorithm in ad - hoc networks
網路中一種基於簇的故障診斷演算法 -
Fault diagnosis algorithm for mobile hosts in hierarchical ad - hoc networks
網路中的一種移動節點故障診斷演算法 -
A fault diagnosis algorithm on application layer in hierarchical ad hoc networks
網路中的一種應用層故障診斷演算法 -
An improved fault diagnosis algorithm based on system - level diagnosis for satellite networks was proposed and its correctness was proved
在前面工作的基礎上，提出一種改進的基於系統級診斷的衛星網路故障診斷演算法，並給出診斷正確性的證明。
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