中国舰船研究
中國艦船研究
중국함선연구
CHINESE JOURNAL OF SHIP RESEARCH
2013年
5期
91-96
,共6页
舱室%火灾%判别要素%优先级%神经网络%BP算法
艙室%火災%判彆要素%優先級%神經網絡%BP算法
창실%화재%판별요소%우선급%신경망락%BP산법
cabin%fire%diagnostic feature%priority%neural network%BP algorithm
舱室是船舶的重要组成部分。当某舱室发生火灾时，其相邻舱室极易引发连锁性起火，此时如果报警系统不能及时、准确、可靠地给出各舱室的关联报警信息，就会对整个船舶造成严重危害。为了增加船舶火灾报警系统的早期预警与关联报警功能，分析了通常情况下典型船舶舱室的火灾报警判别要素并对其进行量化，建立舱室火灾报警优先级BP神经网络评估模型，运用LM算法对该评估模型进行学习训练，并通过测试样本验证该船舶舱室火灾报警优先级评估模型的可行性与准确性。该方法有助于提高报警系统对各舱室火灾探测报警的准确性，从而可降低由于舱室关联起火而导致发生船舶重大损失的概率。
艙室是船舶的重要組成部分。噹某艙室髮生火災時，其相鄰艙室極易引髮連鎖性起火，此時如果報警繫統不能及時、準確、可靠地給齣各艙室的關聯報警信息，就會對整箇船舶造成嚴重危害。為瞭增加船舶火災報警繫統的早期預警與關聯報警功能，分析瞭通常情況下典型船舶艙室的火災報警判彆要素併對其進行量化，建立艙室火災報警優先級BP神經網絡評估模型，運用LM算法對該評估模型進行學習訓練，併通過測試樣本驗證該船舶艙室火災報警優先級評估模型的可行性與準確性。該方法有助于提高報警繫統對各艙室火災探測報警的準確性，從而可降低由于艙室關聯起火而導緻髮生船舶重大損失的概率。
창실시선박적중요조성부분。당모창실발생화재시，기상린창실겁역인발련쇄성기화，차시여과보경계통불능급시、준학、가고지급출각창실적관련보경신식，취회대정개선박조성엄중위해。위료증가선박화재보경계통적조기예경여관련보경공능，분석료통상정황하전형선박창실적화재보경판별요소병대기진행양화，건립창실화재보경우선급BP신경망락평고모형，운용LM산법대해평고모형진행학습훈련，병통과측시양본험증해선박창실화재보경우선급평고모형적가행성여준학성。해방법유조우제고보경계통대각창실화재탐측보경적준학성，종이가강저유우창실관련기화이도치발생선박중대손실적개솔。
When fire breaks out in a ship cabin,the adjacent cabins may also suffer from chain effects and catch fire. In that case,if the fire alarm system does not provide accurate and reliable information concern-ing the afflicted cabins timely,the entire ship could be seriously damaged. In order to improve the early warning and alert correlation function of the ship fire alarm system,this paper analyzes the diagnostic fea-tures of typical cabin fires quantitatively and establishes a BP neural network evaluation model regarding the fire alarm priority. The model is then trained via the LM algorithm. In order to validate the proposed evaluation model,several testing samples have been employed. The results show that the method signifi-cantly improves the accuracy of the fire alarm system and lowers the chance of catastrophic losses due to cabin chain fires.
