Most petrochemical units run under extreme conditions, such as high temperatures, pressures, and speeds. Consequently, the equipment operators may commit errors because the startup and shutdown processes usually involve complicated operation steps; moreover, the operators may lack experience in handling abnormal situations. Misoperation can lead to accidents, including fires and explosions. Thus, risk analysis for process operations and the development of preventive measures have become an effective means of avoiding misoperation-related accidents. However, it is challenging to ensure the comprehensiveness of risk-analysis results. In this paper, we present a method for misoperation monitoring and early warning in the startup and shutdown processes of petrochemical units. The mechanisms of misoperation occurrence are summarized based on investigations of serious accidents in the recent past. Knowledge regarding the mechanisms of misoperation is crucial for the risk analysis of petrochemical units. The potential risk information, such as causes, adverse consequences, key monitoring parameters, and prevention control solutions, should be acquired and be employed to construct an early-warning knowledge database. Furthermore, misoperation judgment rules need to be formulated to identify misoperations. The data obtained from the monitoring module, misoperation judgment rules, and analysis results can aid in developing schemes to avoid possible abnormal situations. This paper reports a misoperation monitoring and early-warning system for a hydrogenation unit. As demonstrated, conducting risk analysis to determine the potential operational risks and formulating misoperation judgment rules to analyze the process data are essential for enabling early warning. The application of this method will contribute to operational guidance, economic loss reduction, and accident avoidance. 相似文献
Objective: The objective of this study is to develop a novel algorithm on a mobile system that can warn drivers about the possibility of a collision with a pedestrian. The constraints of the algorithm are near-real-time detection speed and a good detection rate.
Method: Histogram of gradients (HOG)-based detection is widely used in pedestrian safety applications; however, it has low detection speed for real-time systems. Hence, it has no direct usage for mobile systems. In order to achieve near-real-time detection speed, partial Haar transform predetections are applied to an image before HOG detection. The partial and HOG detections are merged and a score-based confidence level is defined for the final detection phase. In this way, the outcome is prioritized and different warning levels can be issued to warn the driver before a possible pedestrian collision.
Results: The proposed algorithm provides an increase in detection speed (from 46 to 76 fps) and detection rate (from 80 to 91%) with respect to HOG-based pedestrian detection. It also improves confidence of the results by multidetection merging and score assignment to detections.
Conclusions: Performance improvement of the algorithm is compared with respect to state-of-the-art detectors/algorithms. Based on the detection rate and detection speed performance, it can be concluded that the proposed algorithm is suitable to be used for mobile systems to warn drivers about the possibility of collision with a pedestrian. 相似文献
Objective: The objective of this study was to identify and quantify the motorcycle crash population that would be potential beneficiaries of 3 crash avoidance technologies recently available on passenger vehicles.
Methods: Two-vehicle crashes between a motorcycle and a passenger vehicle that occurred in the United States during 2011–2015 were classified by type, with consideration of the functionality of 3 classes of passenger vehicle crash avoidance technologies: frontal crash prevention, lane maintenance, and blind spot detection. Results were expressed as the percentage of crashes potentially preventable by each type of technology, based on all known types of 2-vehicle crashes and based on all crashes involving motorcycles.
Results: Frontal crash prevention had the largest potential to prevent 2-vehicle motorcycle crashes with passenger vehicles. The 3 technologies in sum had the potential to prevent 10% of fatal 2-vehicle crashes and 23% of police-reported crashes. However, because 2-vehicle crashes with a passenger vehicle represent fewer than half of all motorcycle crashes, these technologies represent a potential to avoid 4% of all fatal motorcycle crashes and 10% of all police-reported motorcycle crashes.
Discussion: Refining the ability of passenger vehicle crash avoidance systems to detect motorcycles represents an opportunity to improve motorcycle safety. Expanding the capabilities of these technologies represents an even greater opportunity. However, even fully realizing these opportunities can affect only a minority of motorcycle crashes and does not change the need for other motorcycle safety countermeasures such as helmets, universal helmet laws, and antilock braking systems. 相似文献