Automatic Full Weld Inspection System for High Speed Rail(TrackBot) Theme: 37

我们的铁路对于内部和跨境市场的顺利运作，以及可持续和清洁运输系统的发展至关重要。因此，建设现代化的、有竞争力的铁路网络正成为英国、中国和世界其他国家的首要任务。建设和维护安全的高速网络也带来了挑战。据《科学美国人》报道，大多数铁路事故都是由于铁轨断裂和焊接造成的。失效通常由焊接缺陷引起，如疲劳裂纹、死区和平点。尽管有这些令人担忧的统计数据，但中国等一些国家仍然主要依靠人工焊接检查，这是一种缓慢、不一致和不充分的方法，容易出现人为错误。对于钢轨的缺陷检测，最常用的方法是超声波和磁感应，这是缓慢的，缺乏检查焊缝全体积的能力。相控阵超声检测（PAUT）是一种先进的无损检测技术，能够检测焊缝中的任何缺陷。该联盟将开发TrackBot，这是一种先进的自动通用焊接检测系统，基于专利的PAUT技术和每个联盟合作伙伴开发的系统。TrackBot可以快速检测全焊缝中所有类型的缺陷，提高检测速度，并减少提供高效检测和铁路网络所需的熟练人员数量。在此过程中，财团合作伙伴将产生2260万英镑的总收入，并提供可观的（50倍的）投资回报。

Our railways are vital for the smooth operation of internal and trans border markets, and for the development of a sustainable and clean transport system. Building modern, competitive railway networks is therefore becoming a top priority for the UK, China and the rest of the world. To build and maintain safe high speed networks brings its own challenges. According to Scientific American, most rail accidents are due to broken rails and welds. Failure generally initiates from defects in the weld such as fatigue cracks, dead zones and flat spots. Despite these worrying statistics, some countries such as China still rely mainly on manual weld inspections, which is a slow, inconsistent and inadequate approach that is prone to human error. For defect detection in rail, the most common methods are ultrasonic and magnetic induction, which are slow and lack the ability to inspect the full volume of the weld. Phased array ultrasonic testing (PAUT) is an advanced NDT technique, with the capability to detect any faults within a weld. The consortium will develop TrackBot, an advanced automated universal weld inspection system that is based upon proprietary PAUT technology and systems developed by each of the consortium partners. TrackBot can rapidly detect all types of flaws in the full weld volume, increase inspection speeds, and reduce the number of skilled persons required to deliver efficient inspection and rail networks. In doing so, the consortium partners will generate combined revenue of £22.6million and deliver significant (>5x fold) return on investment.