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Cepstrum Analysis for Determining the Fundamental Frequency of Total Hip Replacement Acoustic Emissions

机译:倒频谱分析,用于确定髋关节置换总声发射的基本频率

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Acoustic emission (AE) monitoring of patients with total hip replacement (THR) implants has potential as a non-invasive and inexpensive diagnostic procedure for identifying and monitoring implant complications such as loosening and implant squeaking. AE signals that are generated from implant interactions can provide insight into implant condition and failure modes through signal characteristics such as frequency content. A substantial database of AEs has been collected from 107 THR patients using an AE monitoring prototype diagnostic device. This manuscript presents the use of the relatively unknown signal processing technique of cepstrum analysis as a method for identifying and comparing the frequency content of squeaking THRs from the AE database. It was observed that squeaking AE signals commonly exhibited frequency spectrums with strong harmonic content and fundamental frequencies that varied over time. Cepstrum analysis has the ability to isolate fundamental frequency content in signals that contain harmonics. The position and transient behaviour of the fundamental frequency content can then be used to correlate and categorise particular AE signals. The cepstrum results presented in this manuscript exhibits an ability to successfully isolate the fundamental frequency content for THR AE squeaks from separate patients. The usefulness of a cepstrum analysis for correlating and contrasting THR AE squeaks is demonstrated. However, the results also demonstrated that when strong harmonics were not present in the AE signals, the cepstrum isolated frequency content of no obvious significance and was even unable to simply identify the main frequency content reliably. Nevertheless, the cepstrum analysis is a promising technique to aid in the analysis of THR AE signals and can provide useful insight into the frequency behaviour of these emissions.
机译:使用全髋关节置换(THR)植入物的患者的声发射(AE)监测作为一种无创且廉价的诊断程序,具有潜在的潜力,可用于识别和监测植入物的并发症,例如松动和吱吱声。从植入物相互作用产生的AE信号可以通过信号特征(例如频率含量)提供对植入物状况和失效模式的洞察。使用AE监测原型诊断设备从107名THR患者中收集了大量AEs数据库。该手稿介绍了使用倒谱分析的相对未知的信号处理技术作为从AE数据库中识别和比较THR吱吱声的频率内容的方法。观察到,吱吱声的声发射信号通常显示出具有很强谐波含量的频谱以及随时间变化的基频。倒频谱分析能够隔离包含谐波的信号中的基频内容。然后,可以使用基频内容的位置和瞬态行为来对特定的AE信号进行关联和分类。本手稿中的倒谱结果显示出能够成功地从不同患者中分离出THR AE吱吱声的基本频率成分的能力。倒谱分析对于关联和对比THR AE吱吱声的有用性得到了证明。然而,结果还表明,当AE信号中不存在强谐波时,倒谱分离的频率成分没有明显的意义,甚至不能简单地可靠地识别主频率成分。然而,倒频谱分析是一种有前途的技术,可以帮助分析THR AE信号,并且可以提供对这些发射的频率行为的有用了解。

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