基于ai智能图像的工控火电现场爆炸风险评估

对工控火电现场爆炸风险进行评估时，若采用人工识别现场图片信息的方法，容易导致现场图片特征信息采集不准确，存在评估耗时长、评估效率低和评估结果不准确的问题。针对该问题，提出1种基于ai智能图像的工控火电现场爆炸风险评估方法；通过自适应融合方法提取工控火电现场ai智能图像中的特征信息，根据特征信息对工控火电现场ai智能图像进行识别；结合层次分析法和问卷调查法，选取工控火电现场爆炸风险评估指标；在图像识别结果的基础上，通过风险等级集合、评估指标权重，建立工控火电现场爆炸风险评估模型，并与另外2种工控火电现场爆炸风险评估方法进行了对比。研究结果表明:所建方法能够缩短评估时间，且评估效率较高、评估结果准确率较高。

Assessment of explosion risk in industrial control thermal power field based on ai intelligent image

When assessing the explosion risk in the field of industrial control thermal power, the information of field image have been recognized manually, which results in the inaccurate collection of characteristic information in the field image, and there exists the problems of long assessment time, low assessment efficiency and inaccurate assessment results. Aiming at these problems, an assessment method of the explosion risk in the field of industrial control thermal power based on the ai intelligent image was put forward. The characteristic information of the ai intelligent image in the field of industrial control thermal power were extracted by using the adaptive fusion method, and the ai intelligent image was recognized according to the characteristic information. Combined with the analytic hierarchy process method and the questionnaire survey method, the assessment indexes of explosion risk in the field of industrial control thermal power were selected. On the basis of the image recognition results, an assessment model of explosion risk in the field of industrial control thermal power was established through the risk grade set and the weights of assessment indexes, then the assessment of explosion risk in the field of industrial control thermal power was completed. The results showed that the proposed method could shorten the assessment time, with a relatively high assessment efficiency and high accuracy of assessment results.