Mauricio Orozco-Alzate1, Carolina Acosta-Muñoz2 and John Makario Londoño-Bonilla2

<sup>1</sup>*Depto. de Informática y Computación, Universidad Nacional de Colombia Sede Manizales* <sup>2</sup>*Observatorio Vulcanológico y Sismológico de Manizales, INGEOMINAS Colombia*

#### **1. Introduction**

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Classifying seismic signals into their corresponding types of volcanic earthquakes is among the most important tasks for monitoring volcano activity. Such a duty must be routinely conducted —in a daily basis— and implies, therefore, a significant workload for the personnel. The discipline of pattern recognition (PR) provides volcanic seismology practitioners with theories and methods to design classification systems and, together with digital signal processing (DSP) techniques, has given rise to promising and challenging opportunities for the automated identification of volcanic earthquakes.

A wealth of recently published studies have demonstrated the applicability of PR tools to volcano-seismic monitoring; however, in spite of that, several cutting-edge approaches have not yet been applied to the problem; moreover, there is still a gap between research achievements reported in the literature and the deployment of custom solutions at the volcano observatories. This chapter introduces fundamental concepts regarding seismic volcanic signals and PR systems, reviews research contributions and case studies, and highlights open issues, future directions for research and challenges to bridge the gap in the transfer of prototype academic results into deployed technology.

In this preliminary section, important definitions and concepts from volcano seismology and PR are considered. First, fundamentals of measurement, data acquisition and telemetry are presented. This is followed by an overview of the different types of volcanic earthquakes, including concise explanations of their geophysical origin and importance for monitoring and forecasting volcanic activity. Advantages of using PR tools in the identification of seismic volcanic signals are discussed. Lastly, stages of a PR system —namely detection or segmentation, representation and generalization — are introduced.

#### **1.1 Measurement, data acquisition and data transmission**

The foundation of volcano monitoring is the collection of experimental physical data and their subsequent analysis and correlation with the associated underlying phenomena. Measuring volcanic earthquakes is particularly important, since seismic events are a first sign of renewed

Fig. 1. Seismic monitoring station installed by Observatorio Vulcanológico y Sismológico de Manizales (OVSM) at Nevado del Ruiz Volcano, Colombia.

volcanic activity (Chouet, 1996) and reveal processes such as transport of magma and gases or fracture of solid rock. Nowadays, seismic data collection is typically automated and telemetered. Both properties are required in order to guarantee (1) continuous —24 hours a day— records, (2) real time surveillance, and (3) data acquisition in remote areas where frequent visits to collect data are not feasible.

The automated collection of seismic volcanic data can be divided into three stages: measurement, data acquisition and data transmission. Measurement is performed by using sensing devices that convert ground motion into measurable output signals: electrical energies as voltages; data acquisition is composed, in turn, by several substages including signal conditioning, analog to digital (A/D) conversion and further signal processing; data transmission is performed by radio link systems, either analog or digital whether the A/D conversion is carried out after or before transmission. A standard seismic monitoring station —loosely thought of as being composed by a buried sensor, an electronics box, a solar panel and a Yagi antenna— is shown in Fig. 1. Further descriptions regarding sensors and telemetry are given below. For a general introduction to data measurement and analysis, the reader is referred to (Brown & Musil, 2004) and the classic book by Bendat & Piersol (2010).

#### **1.1.1 Seismic sensors**

Comprehensive book chapters on seismic instruments have been written by Havskov & Alguacil (2004, Chap. 2), Bormann (2009, Chap. 5) and Havskov & Ottemöller (2010, Chap. 3). In spite of that and for the sake of a self-contained presentation, brief discussions on physical principles, types and technical properties of seismic sensors —also known as seismometers are given below.

Seismometers are usually categorized into passive short period sensors and active broadband sensors, see Figs. 2(a) and 2(b) respectively. The former consist in a magnetic mass which is suspended in a spring and surrounded by a coil; as a result of the mass movement, an electric current is induced in the coil; the associated voltage is proportional to the velocity of the mass. In these sensors, the relationship between the induced signal and the actual velocity is linear in a bandwidth typically ranging from 1.0 to 100 Hz (Havskov & Ottemöller, 2010).

Active broadband sensors are based on the so-called *force balance accelerometer* principle. It roughly consists in extending the linear bandwidth response, down to about 0.01 Hz, by including a feedback coil that limits the motion of the mass in a desired range. The linear bandwidth of broadband sensors typically ranges from 0.01 to 50 Hz. Both types of sensors require corrections to reflect the actual ground motion in length-related units, namely corrections for the instrument response and phase shift. Such topics are note covered here but are well explained in the above cited references.

(a) Short period sensor. (b) Broadband sensor.

2 Will-be-set-by-IN-TECH

Fig. 1. Seismic monitoring station installed by Observatorio Vulcanológico y Sismológico de

volcanic activity (Chouet, 1996) and reveal processes such as transport of magma and gases or fracture of solid rock. Nowadays, seismic data collection is typically automated and telemetered. Both properties are required in order to guarantee (1) continuous —24 hours a day— records, (2) real time surveillance, and (3) data acquisition in remote areas where

The automated collection of seismic volcanic data can be divided into three stages: measurement, data acquisition and data transmission. Measurement is performed by using sensing devices that convert ground motion into measurable output signals: electrical energies as voltages; data acquisition is composed, in turn, by several substages including signal conditioning, analog to digital (A/D) conversion and further signal processing; data transmission is performed by radio link systems, either analog or digital whether the A/D conversion is carried out after or before transmission. A standard seismic monitoring station —loosely thought of as being composed by a buried sensor, an electronics box, a solar panel and a Yagi antenna— is shown in Fig. 1. Further descriptions regarding sensors and telemetry are given below. For a general introduction to data measurement and analysis, the reader is

referred to (Brown & Musil, 2004) and the classic book by Bendat & Piersol (2010).

Comprehensive book chapters on seismic instruments have been written by Havskov & Alguacil (2004, Chap. 2), Bormann (2009, Chap. 5) and Havskov & Ottemöller (2010, Chap. 3). In spite of that and for the sake of a self-contained presentation, brief discussions on physical

Manizales (OVSM) at Nevado del Ruiz Volcano, Colombia.

frequent visits to collect data are not feasible.

**1.1.1 Seismic sensors**

Fig. 2. Examples of seismic sensors installed in the field.
