Centre for Advanced Imaging, The University of Queensland, Brisbane, Queensland, Australia.
Sci Rep. 2017 May 23;7(1):2269. doi: 10.1038/s41598-017-02099-z.
Air-core magnetometers are amongst the most commonly used magnetic field detectors in biomedical instruments. They offer excellent sensitivity, low fabrication complexity and a robust, cost-effective solution. However, air-core magnetometers must be tailored to the specific application to achieve high sensitivity, which can be decisive in the accuracy of the diagnoses and the time required for the examination. Existing methods proposed for the design of air-core magnetometers are based on simplified models and simulations using a reduced number of variables, potentially leading to sensitivity that is suboptimal. To circumvent this we chose a method with fewer assumptions and a larger number of decision variables which employed a genetic algorithm, a global optimisation method. Experimental validation shows that the model is appropriate for the design of highly sensitive air-core magnetometers. Moreover, our results support the suitability of a genetic algorithm for optimization in this context. The new method described herein will be made publicly available via our website to facilitate the development of less costly biomedical instruments using air-core magnetometers with unprecedented sensitivity.
空心磁强计是生物医学仪器中最常用的磁场探测器之一。它们具有出色的灵敏度、低制造复杂性以及稳健、经济高效的解决方案。然而,空心磁强计必须针对特定应用进行定制,以实现高灵敏度,这对于诊断的准确性和检查所需的时间至关重要。现有的空心磁强计设计方法基于简化模型和使用较少变量的模拟,可能导致灵敏度不理想。为了解决这个问题,我们选择了一种假设更少、决策变量更多的方法,该方法采用了遗传算法,这是一种全局优化方法。实验验证表明,该模型适用于设计高灵敏度空心磁强计。此外,我们的结果支持遗传算法在这种情况下进行优化的适用性。本文所描述的新方法将通过我们的网站公开提供,以促进使用具有空前灵敏度的空心磁强计开发成本更低的生物医学仪器。