## 1 Introduction  
The efficiency of urban water distribution networks is limited by significant leakage issues, which result in large water losses possibly exceeding 30% of the input volume [1; 2; 3]. Hence, the implementation of proper policies to control water leaks represents a challenging but essential target for all the utilities involved with drinking water supply. Many approaches for leak detection and location have been investigated in order to implement effective Leakage Management strategies (e.g., thermography, Ground Penetrating Radar, tracer gas techniques, noise and vibration monitoring, Electrical Resistivity Tomography, Time Domain Reflectometry, etc.) [4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14]. This paper focuses on Acoustic Emission (AE) methods, which belong to the family of techniques based on vibro-acoustic phenomena. According to the ASTM E1316 Standard [15], the term _Acoustic Emission_ defines _\"the class of phenomena whereby transient elastic waves are generated by the rapid release of energy from localized sources within a material, or the transient waves so generated\"_. In particular, AE refers to vibro-acoustic phenomena in the sonic and ultrasonic frequency range (up to 1 MHz) which propagate in solid materials. Monitoring of AE is a highly non-intrusive nondestructive testing and evaluation method, which is applied to several processes identified as sources of AE (e.g., crack formation and growth). In general, AE methods are based on the analysis of the parameters that characterize the waveforms of the measured AE signals. Some of these parameters are [15]: (i) _Hit--\"any signal that exceeds the threshold and causes a system channel to accumulate data\"_; (ii) _Counts--\"the number of times the Acoustic Emissionsignal exceeds a preset threshold during any selected portion of a test\";_ (iii) signal _Amplitude--\"the peak voltage of the largest excursion attained by the signal waveform from an emission event\"._ AE methods were originally developed for pressure vessels, both to inspect them during pressure testing and to detect leakages (e.g., loss of coolant in nuclear reactor vessels). Also, water flows leaking from pipelines generate AE, which propagate along the pipe walls. Indeed, AE methods for leak detection have been successfully applied also to water pipelines, in particular, for medium/large-diameter distribution pipes made of steel or plastic or prestressed concrete [16; 17; 18; 19], even if the technique's effectiveness may be considerably affected by the specific boundary conditions of the system under investigation [20]. In general, better detection capabilities could be achieved by applying procedures for artificially amplifying the leak noise (e.g., gas injection or fluid pressure variation) [14; 18]. It is worth mentioning, however, that such procedures may be unsuitable for practical use in some existing pipeline networks, since they require significant modifications of the system working conditions (which are not always allowed during normal operation, as in the case considered in this study). This work investigates the detection of water leaks occurring in polyethylene (PE) small-diameter service pipes of water supply networks, by means of AE measurements. Indeed, this class of pipes represents a significant percentage of the service pipes installed in the distribution network managed by the Italian multi-utility that promoted the research, namely a network that supplies about 3 \(\times\) 10\({}^{8}\) m\({}^{3}\) per year of drinking water to 237 municipalities (total population of about 4 million), through 35,150 km of water mains. In particular, PE pipes have been used over roughly the last two decades for all the new connections. Furthermore, all the leaks currently detected in service pipes are repaired by completely replacing the old pipes with new PE ones. Leaks in customers' connections are generally characterized by low flow rates but long total runtime (i.e., the total period from the leak initiation to the burst repair).