# An Improved Hilbert-Huang Transform for Vibration-Based Damage Detection of Utility Timber Poles
## 1 Introduction  
Timber is a commonly used industrial material due to its accessibility and wide variety of mechanical and physical properties, such as higher strength to weight ratio, electrical, and heat insulation and having a simpler and faster installation process [1]. Timber poles are broadly used worldwide since they are environmental friendly and significantly cheaper than other alternative materials [1]. Currently, more than 5 million utility timber poles are used in Australia's infrastructure which represent 80% of the total poles [2]. Approximately 70% of these timber poles were installed before 1965 [3]. They will require maintenance and need replacement soon and related cost may reach up to AU$1.75 billion [3]. Routine inspections are carried out on a regular basis to monitor pole condition which deteriorates over time due to fungal and termite attacks and climate and soil condition. For maintenance and asset management, utility pole industry spends AU$50 million yearly to avoid pole failure and ensure reliability of energy network [3]. In addition, the current pole assessment techniques available in the market mainly rely on visual inspection, sounding, and drilling. However, first two techniques greatly depend on the skill of an asset inspector, which cannot provide consistent accuracy required for ensuring public safety, and drilling is commonly conducted at the ground level reflecting the local condition of the pole. However, damage can present in underground section or top part of the pole which is unreachableby the asset inspector and that often results into inaccurate prediction of the health state. Advanced methods like X-ray, ultrasonic tomography, and radiographic methods use cross-sectional evaluation and can yield highly accurate results. Nevertheless, access to the underground or overhead information remain a challenge. Additionally, use of these methods are limited due to high cost, limited computational efficiency, and complexity in the operation [4]. To overcome these limitations, variety of non-destructive testing (NDT) methods have been investigated and developed by the engineers and researchers in the past two decades to provide accurate information on the condition of timber pole/pile structures such as wave based, and vibration based, NDT methods. In case of vibration based method, timber pole is hit manually by a modal hammer and a broadband low frequency input signal is generated [5]. Because the input frequency is low, generated signal has long wavelength. When the wavelength of the signal gets bigger than the diameter of the pole, the induced stress wave creates a standing wave within the pole resulting into vibration of the whole pole [6]. Vibration based method has been utilised for non-destructive evaluation of timber poles to assess the underground and top part of the pole since it has higher propagating energies. This method has been successfully used by many researchers for timber poles [7; 8; 9; 10; 11], tree logs [12; 13; 14], and pile type structures [15; 16]. Table 1 demonstrates comparison of the reviewed NDT methods for this study. In this paper, vibration based method is adopted in order to investigate the condition of utility timber poles since this method can analyse the whole pole by utilizing its dynamic properties such as natural frequency, mode shapes, damping ratio [17]. Natural frequency is the most popular damage indicator in the early years of vibration-based damage detection as it is easy to determine and is generally less affected by ambient noise [18; 19; 20; 21; 22]. Natural frequency-based methods depend on the fact that damage in a structure reduces the structural stiffness which actually changes the resonance frequencies. Nonetheless, these methods are model based and need a mathematical model of the structure to obtain vibration frequencies. Another shortcoming is that changes in frequency caused by cracks is not very prominent and is often buried under operational and environmental conditions.