Potentiality of Transient Tests to Diagnose Real

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model for leakage detection and roughness calibration in pipe net- works.” J. Hydraul. Res., 41(5), 481–492. Lee, P. J., Vítkovský, J. P., Lambert, M. F., Simpson, ...
Potentiality of Transient Tests to Diagnose Real Supply Pipe Systems: What Can Be Done with just a Single Extemporary Test Silvia Meniconi1; Bruno Brunone; 2; Marco Ferrante; and 3; and Christian Massari4

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Abstract: In this paper, the reliability of a transient test-based technique as a powerful tool in the management of real supply pipe systems is shown. The pressure signal acquired during the first phase of the single completed test has been analyzed on the basis of the extensive research activity, that in the last years has been performed in the field of transient test-based techniques and refined on the basis of numerical and laboratory tests. Specifically, the Wavelet Transform, which allows the automatic detection of singularities also in noisy pressure signals, and a Lagrangian Model, which evaluates the causes of discontinuities, are efficiently coupled also for analyzing the pressure signal acquired in the described pipe system. As a result, the topology of such a system has been checked and its functioning conditions have been determined. Moreover, the unwanted status of an in-line valve—certified by the manager as fully open but actually partially closed—has been pointed out. DOI: 10.1061/(ASCE)WR.1943-5452.0000098. © 2011 American Society of Civil Engineers. CE Database subject headings: Pipes; Transient response; Diagnosis; Tests. Author keywords: Pipe system; Transient; Diagnosis.

Introduction In the management of pipe systems, the following issues are crucial: (1) the survey, to asses the geometrical characteristics of the system (diameter, length and material of branches, and position of connections); (2) the calibration, to determine reliable values of numerical model parameters ( pipe roughness and pressure wave speed); and (3) the diagnosis, to determine the status of devices and functioning conditions of connections and to detect leaks. The steady-state test-based techniques solve these issues sequentially to lead to increasingly efficient management. They need a labor-intensive field activity and a long sampling time to acquire both the discharge and the pressure in several measurement sections. Within such an approach, sophisticated models have been developed to find optimal locations of sensors. Such a problem is so complex from the theoretical and practical point of view that in literature the so-called “battle of sensors” has been taking place for some years (e.g., Ostfeld et al. 2008). 1

Assistant Professor, Dipartimento di Ingegneria Civile ed Ambientale, Università degli Studi di Perugia, Via G. Duranti 93, 06125 Perugia, Italy. E-mail: [email protected] 2 Professor, Dipartimento di Ingegneria Civile ed Ambientale, Università degli Studi di Perugia, Via G. Duranti 93, 06125 Perugia, Italy. E-mail: [email protected] 3 Associate Professor, Dipartimento di Ingegneria Civile ed Ambientale, Università degli Studi di Perugia, Via G. Duranti 93, 06125 Perugia, Italy. E-mail: [email protected] 4 Ph.D. Student, Dipartimento di Ingegneria Civile ed Ambientale, Università degli Studi di Perugia, Via G. Duranti 93, 06125 Perugia, Italy. Email: [email protected] Note. This manuscript was submitted on March 25, 2009; approved on May 17, 2010; published online on Month 00, 0000. Discussion period open until August 1, 2011; separate discussions must be submitted for individual papers. This paper is part of the Journal of Water Resources Planning and Management, Vol. 137, No. 2, March 1, 2011. ©ASCE, ISSN 0733-9496/0000/2-0–0/$25.00.

On the contrary, in supply systems using transient test-based techniques (TTBTs) that analyze pressure waves reflected by singularities solve these issues by means of short-duration tests and the measurement of only the pressure time-history, hereafter referred to as pressure signal h. As an example, if the geometrical characteristics are known, transient tests can point out unknown and illegal connections (Meniconi et al. 2009) to evaluate the pressure wave speed with high precision, to determine the condition of connections, and to detect leaks and partially closed in-line valves. To improve the efficaciousness of this approach, simple numerical models, such as the Lagrangian Model (LM) (Ferrante et al. 2009), and proper tools for the analysis of unsteady signals, such as the Wavelet Transform (WT), (e.g., Al-Shidani et al. 2003), can be used. This is not the case of the inverse transient analysis (ITA) where a detailed survey and a priori calibration are necessary before simulating transients by means of sophisticated numerical models (e.g., Ligget and Chen 1994; Kapelan et al. 2003). The main aim of the present paper is to show that TTBT, refined on the basis of numerical and laboratory tests (e.g., Brunone 1999; Mpeshaet al. 2001; Wanget al. 2005; Covaset al. 2005; Leeet al. 2005) can be reliably used for the calibration and diagnosis of real supply-pipe systems removing most of doubts about their applicability in practice.

Field Test The examined cast iron pipe system supplies the city of Rieti, Italy, and is managed by Sogea S.p.A. (Fig. 1(a)). The Madonna del Passo well-field supplies the pipe system and is connected to the two reservoirs: La Foresta and S. Mauro, by means of a Y junction. The main trunk, which spans node Y and the La Foresta reservoir, supplies a rink (node R) by means of branch 4, the fire hydrant system of the municipal swimming pool (node S) by means of branch 6, and the psychiatric hospital (node H) by means of branch 8. Furthermore, an in-line gate valve (LV) is placed very close to the junction J4 and the flow into La Foresta reservoir

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(a)

“MADONNA DEL PASSO”

S

H

R

1

6

4 Y

3

J4

8 section M

LV

J6

5

7

J8

9

V

2

very fast, all pressure changes are not as sharp as they should be to extract straightforwardly all information from the pressure signal; (3) since the pressure probe f.s. was too large compared to the maximum value of the pressure, the accuracy of the pressure signal is not as high as it could be, and (4) a higher frequency acquisition of the pressure signal would allow a more precise analysis. Notwithstanding these clear defects, results look very impressive in terms of knowledge of the system behavior, as will be shown below.

“LA FORESTA” RESERVOIR

Edge Detection in the Pressure Signal by Means of Wavelet Transform (WT)

“S. MAURO” RESERVOIR

100

(b) 90

pressure signal, h (m)

80 70 60 50 40 30 20 10

0

5

10

15

time, t (s)

Fig. 1. a) schematic representation of the Rieti supply-pipe system (the arrows indicate flow direction in steady-state condition); b) pressure signal at section M

and is regulated by means of a float-type valve (node V). Further characteristics of the system are given in Table 1, where L = pipe length, e = pipe thickness, and DN = nominal diameter. The transient test was generated by a total closure executed manually at valve V. Fig. 1(b) shows the pressure signal acquired with a frequency of 320 Hz by a piezoresistive transducer with a full scale (f.s.) of 16 bar. The measurement section, hereafter referred to as section M, is placed immediately upstream of valve V (Fig. 1(a)). The sound (available as Rieti_sound.wav file) recorded during the test gives an impressive idea of the pressure waves traveling along the pipe system. Since the test was carried out without a detailed program, some of the fundamental rules of TTBT were broken (Fig. 1(b)): (1) since the initial discharge was not measured, the overpressure was very high (about 70 m of water column); (2) since the maneuver was not

In this paper, because the pressure signal was acquired only at one section, the analysis of the pressure signal is limited to the first phase of the transient, where small amplitude pressure waves reflected by the singularities can be detected more reliably. Moreover, since the investigated system is quite complex with several branches and junctions, the number of reflected and transmitted pressure waves dramatically increases in time and this makes it more and more difficult to extract the effect of each singularity from the pressure signal. The selected time interval ranges from the end of the maneuver (about 4.5 s) to the arrival of the first wave reflected by the Y junction (about 6.2 s, as will be shown below). Consequently, the diagnosis of the system is focused on the main trunk and its connections up to node Y (Fig. 2(a)). Because of the unsteady nature of the phenomenon, the analysis of the pressure signal is performed by the WT. For further details about this method, see Mallat and Hwang 1992; Ferrante et al. 2007. In the selected time period, the WT points out discontinuities, indicated with dotted lines in Fig. 2(b), at the following time instants: t 1 ¼ 4:59 s, t 2 ¼ 4:90 s, t 3 ¼ 5:25 s, t 4 ¼ 5:52 s, t5 ¼ 5:59 s, t 6 ¼ 5:86 s, t 7 ¼ 5:97 s, and t 8 ¼ 6:13 s, with the subscript denoting the temporal sequence of pressure waves reaching section M.

Pressure Signal Analysis Coupling Wavelet Transform (WT) and a Lagrangian Model (LM) Interpretation of discontinuities pointed out by WT is made easier by comparison with the results of a simple and very fast LM. In fact, such a model is based on the solution of the differential equations governing frictionless transients in pressurized pipe systems (Swaffield and Boldy 1993). The omission of the friction term as well as the assumed instantaneity of the closure maneuver are not limiting since the aim of this work is not to simulate the transient, such as within ITA, but only to capture main characteristics of the pressure signal in order to evaluate the causes of its discontinuities.

Table 1. Characteristics of the Rieti Water Supply Pipe System Branch

Initialnode

Endnode

L (m)

e (mm)

DN mm

1 2 3 4 5 6 7 8 9

Well-field Y Y J4 J4 J6 J6 J8 J8

Y S. Mauro reservoir J4 R J6 S J8 H V

4274 1849 16 80 265 200 500 190 2450

5.1 5.1 4.9 2.9 4.9 2.9 4.9 2.9 4.9

400 400 200 40 200 90 200 90 200

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96

h (m)

94 92 90

(a) 4.6

4.8

5

5.2

5.4

5.6

5.8

6

wavelet scale, j

8 6

(b) 6 1

7

3

2

5

4

4

8

2 4.6

4.8

5

5.2

5.4

5.6

5.8

6

hLM (m)

100 Y

80 60

H and J6

40 J8 20 4.6

4.8

H

H

H

H S J4 and LV

(c)

J6

5

5.2

5.4

5.6

5.8

6

time, t (s)

Fig. 2. a) magnified vision of pressure signal of Fig. 1(b); b) corresponding WT; c) simulation of the pressure signal by the LM, in the case of: i) S closed, H closed, and LV fully open (solid line); ii) S closed, H open, and LV fully open (dotted line); iii) S open, H closed, and LV fully open (dashdot line); iv) S closed, H closed, and LV partially closed (dashed line)

As described in Ferrante et al. (2009), three steps can be identified in the LM approach. The first step is to define the topology of the system as a set of branches and external and internal nodes and the boundary condition at any node to evaluate the reflected, Δhr , and transmitted, Δht , waves for a given incident wave, Δhi . The second step is to follow the wave generated by the maneuver and the subsequent Δhr and Δht at any node, then record their paths and their arrival times at the nodes. Once the pressure change occurs at a node, it must be transferred to other nodes by means of the transfer function characteristic of the branches connected to that node, i.e., the time interval aL, with a = pressure wave speed being the only parameter of LM to be calibrated. The third step entails identifying which waves have passed section M and calculating the instant of passage. In the examined system, the external nodes are the S. Mauro reservoir, the well-field, the valve V, and the nodes R, S, and, H, whereas the internal nodes are the junctions, indicated by a hollow circle, and the in-line valve LV. For junctions, Δhr and Δht may be straightforwardly calculated from the characteristics of concurring branches (Swaffield and Boldy 1993). According to the statement of the manager, initially LV was assumed as fully open with Δhr ¼ 0 and Δht ¼ Δhi . With regard to the external nodes, at the valve V, when completely closed, Δhr ¼ Δhi ; at S. Mauro reservoir and the well-field, Δhr ¼ Δhi . Because the external nodes R, S, and H were not monitored during the test, their behavior has to be determined by means of a trial-and-error procedure by comparing the results of the LM with the pressure signal. Specifically, such nodes can be considered as a constant level reservoir (Δhr ¼ Δhi ) or a dead end (Δhr ¼ Δhi ). The evaluation of a in the main trunk is performed by considering that the first discontinuity pointed out by the WT is certainly due to junction J8 (Fig. 2(b)): given the length L9 ¼ 2; 450 m, the value of a9 ð¼ 2L9 =t 1 Þ is 1,068 m/s and the bulk modulus is 1:15 × 1011 Pa. Since the other pipes have the same material 2 and age, the value of a was obtained straightforwardly by means of the relationship for thin-walled pipes.

The results of the LM are shown in Fig. 2(c) for different behaviors not only of nodes S and H but also of LV, for reasons reported below. On the contrary, considering the position of section M, the behavior of node R can not be analyzed since its Δhr is hidden by the much larger one reflected by the Y junction. By comparing arrival times given by the LM and WT, the maximum relative error is about 1.4%, mainly due to a rough evaluation of a in branches and the duration of the maneuver. LM coupled with WT points out that the second and the third discontinuities are due to node H, which behaves as a dead end since at t 2 it gives rise to a sudden increase of the pressure (compare solid and dotted lines in Fig. 2(c)). According to system topology, the fourth and the fifth discontinuities are due to junction J6 and node H, respectively. The sudden increase at t 6 in the LM assumes that node S acts as a dead end (compare solid and dash dotted lines). The larger experimental pressure rise in the time interval t 7  t 6 with respect to the one at t2 can be simulated in the LM only by removing the hypothesis that LV was fully open. Specifically, it must be assumed that such a rise is due to the combined effect of both S and the partially closed LV (compare solid and dashed lines in Fig. 2(c)). Because of the lack of data about the hydraulic behavior of LV, its exact status can not be determined. Then, according to the followed approach, a positive Δhr has been assumed, to simulate the behavior of an in-line partially closed valve qualitatively (Contractor 1965; Meniconi et al. 2009).

Conclusions For supply systems, TTBTs are attractive for two main reasons: their very short duration, which significantly reduces both the interference with the regular functioning of the system and personnel costs, and the possibility of using only pressure measurements. Powerful tools to be coupled to transient tests are the WT, which allows the automatic detection of singularities also in noisy pressure signals, and the LM for evaluating the causes of discontinuities.

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In this paper, it is shown that a single transient test can be performed to locate singularities and to determine the functioning of a large part of a quite complex supply-pipe system by analyzing the pressure signal acquired at only one section. Moreover, the topology of the system is checked and the actual status of an in-line valve—certified by the manager as fully open—has been pointed out. More reliable results could be achieved by generating high quality and controlled pressure waves by means of a proper device, for example, the portable pressure waves maker (PPWM) (Brunoneet al. 2008); further measurement sections could allow a more extensive diagnosis. The proposed approach can be of great importance in the management of pipe systems since any further singularity, e.g., leaks, can be easily detected by analyzing the pressure signal or by comparing the present pressure signal with those acquired previously, if available. In our opinion, no other technique has the same performance in terms of economy and quickness of field tests for the diagnosis of real supply-pipe systems.

Acknowledgments This research has been jointly supported by the Italian Ministry of Education, University and Research (MIUR) under the Project of Relevant National Interest “Innovative criteria for the sustainable management of water resources in the water distribution systems”, and by Fondazione Cassa Risparmio Perugia. The support of Eng. E. Blasetti and Mr. G. Faraglia of Sogea S.p.A. and Eng. I. Brunelli in the execution of the field test is really appreciated.

Notation The following symbols are used in this paper: a = wave speed; DN = nominal diameter; e = pipe thickness; j = wavelet scale; h = pressure signal; L = length of the pipe; t = time; Δh = generic pressure wave. Subscripts

i = incident wave; r = reflected wave; t = transmitted wave.

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