Scrubbing Complex Sound Sources for Factory Situational Awareness

清理复杂声源以实现工厂态势感知

• 批准号: 10761362
• 负责人: Karen L Payton
• 金额: $ 29.57万
• 依托单位: SPEECH TECHNOLOGY/APPLIED RESEARCH CORP.
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10761362
• 关键词: Scrubbing; Complex; Sound; Sources; Factory

According to the CDC NIOSH website “Occupational hearing loss is one of the most common work-related illnesses in the United States.” This is due, in part, to the number of workers exposed to hazardous noise levels in the workplace who don’t use hearing protection devices (HPDs). A National Health Institute Survey estimated that over 22 million U.S. workers are exposed to hazardous noise levels at work annually. Another survey indicated over half of those workers reported non-use of HPDs. Non-use of HPDs on factory floors is often not due to the cost of such devices or lack of availability. In many cases, ear plugs and other HPDs can be seen hanging around a worker’s neck or stuffed in a pocket! The problem is that, in addition to blocking hazardous sounds, HPDs also block all other sounds in the environment but awareness of alarms is critical for physical safety and job performance in these industries. We propose a novel hearing protection system that provides enhanced access to “situational” sounds such as alarms, forklifts, and voices, while simultaneously suppressing hazardously loud noises. By overcoming the situational-awareness obstacle, we believe workers will be more willing to wear HPDs that include our system. Our solution uses innovative signal processing technologies to “scrub” hazardously loud machines, each of which has been “tagged” by adjacent microphones (mics), from the response mixtures of other, “situational” mics placed in more acoustically diverse locations in the workspace. This scrubbing process removes the tagged noises from the response signals of the situational mics, thereby enhancing the audibility of the other important sounds in the environment. Unlike existing products, this scrubbing is independent of the frequency or amplitude of the signal being scrubbed. Based on successful results scrubbing noise from small sources, this project focuses on two limitations of our current system: 1) Acoustic sensors used as tagging mics pick up situational sounds in addition to the unwanted noise. This tagger contamination makes it more difficult to scrub just unwanted noise from situational mics. We propose to investigate alternative sensor technologies to reduce contamination. 2) Noisy machines typically have multiple underlying noise sources (e.g. motors, pulleys, bearings) and relatively large shells encasing the noise sources. Successful scrubbing requires as many tagging mics as distinct noise sources. We propose to develop and test a procedure to identify the number and location of tagging mics needed to scrub a machine with multiple internal sources.

根据 CDC NIOSH 网站，“职业性听力损失是最常见的听力损失之一” 在美国患上与工作有关的疾病。”这部分是由于工人数量 在工作场所暴露于危险噪音且未使用听力保护装置的人 （HPD）。美国国家卫生研究院的一项调查估计，超过 2200 万美国工人 每年在工作中都会暴露在危险的噪音水平下。另一项调查显示，其中一半以上 工人报告未使用 HPD。工厂车间不使用 HPD 通常不是因为 此类设备的成本或缺乏可用性。很多情况下可以看到耳塞等HPD 挂在工人脖子上或塞在口袋里！问题是，除了 阻挡危险声音，HPD 还阻挡环境中除意识之外的所有其他声音 警报对于这些行业的人身安全和工作绩效至关重要。我们提出一个 新颖的听力保护系统，可以增强对“情境”声音的获取，例如 如警报、叉车和声音，同时抑制危险的大声噪音。经过 克服情境意识障碍，我们相信员工会更愿意佩戴 包含我们系统的 HPD。 我们的解决方案使用创新的信号处理技术来“清理”危险的声音 机器，每台机器都被相邻的麦克风（mics）“标记”，从响应 其他“情境”麦克风的混合，放置在声音更加多样化的位置 工作区。这个清理过程从响应信号中去除了标记的噪声。 情景麦克风，从而提高了其他重要声音的可听度 环境。与现有产品不同，这种擦洗与频率或 被擦洗信号的幅度。 基于消除小来源噪音的成功结果，该项目重点关注两个方面 我们当前系统的局限性：1）用作标记麦克风的声学传感器拾取情境 除了不需要的噪音之外的声音。这种标签污染使得更难 消除情景麦克风中不需要的噪音。我们建议研究替代传感器 减少污染的技术。 2) 嘈杂的机器通常有多个底层 噪声源（例如电机、皮带轮、轴承）和封闭噪声的相对较大的外壳 来源。成功的清理需要与不同噪声源一样多的标记麦克风。我们 建议开发和测试一个程序来识别标记麦克风的数量和位置 需要清洗具有多个内部源的机器。