基于神经网络的柴油机技术状况评估仿真方法

针对传统数学模型不能很好解决发动机结构参数和运转参数对发动机性能非线性影响的问题，提出应用人工神经网络建立S195型柴油机技术状态分析评估与仿真模型，利用神经网络的学习功能和非线性映射能力反映功率和油耗的实际情况，模拟仿真参数变化对发动机技术状况的影响，根据发动机的具体情况，找出影响发动机技术状况的主要参数，进行优化调整，为分析评估和改善S195型柴油机使用技术状态、节约能源提供了依据。

A New Approach to Appraising Working Condition of a Diesel Engine Based on Artificial Neural Networks

In the light of the shortcomings of traditional models on analyzing the relationship between technical states and system parameters of a diesel engine, a new method, based on artificial neural network(ANN), was proposed to analyze different factors influencing technical state of diesel engines. The main factors influencing the engine's technical state were worked out through analysis by using learning ability and no linearity reflection of ANN. The new inspecting and adjusting methods for the main factors, such as fuel delivering angle, were researched. The tests and practical use showed that this method was simple and effective to appraise technical state of S195 type diesel engines.