SBIR Phase I: Mobile inspection robot for industrial corrosion detection

小型企业创新研究(SBIR)第一阶段项目的更广泛影响/商业潜力是提高石化和其他制造设施管道腐蚀检测的准确性、安全性和效率。管道腐蚀是一个主要问题，估计耗费全球国内生产总值(GDP)的3.4%，如果不加以管理，可能会导致灾难性的安全和经济事故，如死亡或逃逸气体排放(仅石油和天然气每年就可能达到1300万吨/年)。目前检测管道腐蚀的方法昂贵、速度慢、人工操作，而且无法收集现场工程师要求的所有必要数据。建议的机器人解决方案通过以下方式解决这些问题：(1)通过改进的检查和本地化机制提高安全性和效率，(2)减少昂贵和危险的人工辅助检查任务，如脚手架建造和绝缘拆除，以及(3)报告大量分析数据，以改善腐蚀工程师的决策。这个小型企业创新研究(SBIR)第一阶段项目将使新的开发成为可能。高度自动化的机器人管道检测工具。目前的检测数据很难获得，而且需要大量的人工操作。一种新型的管道爬行机器人已经被创造出来，它能够对管道进行自动检查扫描，以寻找一个利基用例。车载传感器和空间定位的改进可能会使其得到广泛的商业应用。拟议的研究将提高机器人的车载传感器能力，以改善腐蚀检测用途，并创建人工智能驱动的定位系统，以改善移动、避障和数据完整性。目标1要求进行机械和电气研究，范围从物理设计挑战(包括遵守严格的净空、尺寸和重量要求)到数据处理实验和监管研究。目标2包括自主运动、避障和三维几何重建的研究。由此产生的机器人可能会为行业提供一种更安全、更便宜的检查关键管道基础设施的方法，从而防止潜在的灾难性安全和财务后果以及环境有害的泄漏。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve the accuracy, safety, and efficiency of pipe corrosion inspections for petrochemical and other manufacturing facilities. Pipe corrosion is a major issue, estimated to cost 3.4% of the global gross domestic product (GDP), and if left unmanaged, can result in catastrophic safety and economic incidents such as fatalities or fugitive gas emissions (which can total 13 million metric tons/year in oil and gas alone). Current methods to inspect pipe corrosion are expensive, slow, manual, and unable to collect all the necessary data requested by field engineers. The proposed robotic solution addresses these issues by: (1) improving safety and efficiency through improved inspection and localization mechanisms, (2) reducing the need for expensive and dangerous manual auxiliary inspection tasks such as scaffold construction and insulation removal, and (3) reporting significantly higher amounts of analytical data to allow improved decision making by corrosion engineers.This Small Business Innovation Research (SBIR) Phase I project will enable the development of a new. highly-automated, robotic pipe inspection tool. Current inspection data is both difficult and manually-intensive to obtain. A novel pipe crawling robot has been created that enables automated inspection scans of pipes for a niche use case. Improvements in both onboard sensors and spatial positioning may enable widespread commercial adoption. The proposed research will improve the onboard sensor capabilities of the robot for improved corrosion detection uses and create an artificial intelligence-driven positioning system to improve locomotion, obstacle avoidance, and data integrity. Objective 1 requires both mechanical and electrical research, ranging from physical design challenges (including adhering to strict clearance, size, and weight requirements) to data processing experiments to regulatory research. Objective 2 encompasses research in autonomous movement, obstacle avoidance, and three-dimensional geometry reconstruction. The resulting robot may provide the industry with a safer and cheaper method of inspecting critical piping infrastructure, thus preventing potentially catastrophic safety and financial consequences and environmentally-detrimental leaks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.