Patent Application: US-201314072205-A

Abstract:
leak detection apparatus for deployment in a pipe . the apparatus includes a carrier disposed for motion along the pipe and a detector connected to move with the carrier in an axial direction . the detector comprises a drum mounted for rotation about pitch and yaw axes . a flexible material is mounted on , and extends from , the drum and at least two sensors responsive to drum rotation are provided . the flexible material will be drawn into contact with a wall of the pipe at a leak location , thereby producing a torque on the drum , causing the drum to rotate , and the at least two sensors to generate signals from which leak location is determined .

Description:
in this application we introduce pipeguard , a name adopted by the inventors herein for a new system able to detect leaks in pipes in a reliable and autonomous fashion ( fig1 ). the idea is that the apparatus disclosed herein is inserted into the network via special insertion points , e . g ., fire hydrants in water networks . the system inspects the network and sends signals wirelessly via relay stations to a computer [ 16 ]. leak signals stand out clearly on occurrence of leaks , eliminating the need for user experience . the latter is achieved via a detector that is based on identifying a clear pressure gradient in the vicinity of leaks . the proposed detection concept and the proposed detector design are now discussed . pipeguard is able to detect leaks in a reliable and robust fashion because of the fundamental principle behind detection . more specifically , the detection principle is based on identifying the existence of a localized pressure gradient ∂ p /∂ r this pressure gradient appears in pressurized pipes in the vicinity of leaks and is independent of pipe size and pipe material . it also remains relatively insensitive to the fluid medium inside the pipes , which makes the detection method widely applicable ( gas , oil , water pipes , etc ). the detection concept is based on the fact that any leakage in a pipeline alters the pressure and flow field of the working medium . our group studied , characterized and quantified the phenomenon in detail [ 17 ]. the main conclusion is that the region near the leak that is affected is small . this region is characterized by a rapid change in static pressure , dropping from phigh , inside the pipeline , to plow in the surrounding medium outside ( fig2 ). this local phenomenon is an important feature in the disclosed leak detection scheme . the rapid change in pressure ( radial pressure gradient ) due to existence of leaks essentially represents a “ suction region ”. numerical studies showed that the radial pressure gradient close to the leak is large in magnitude ( o ( δp = p high − p low )) and drops quickly as distance increases . this is shown in fig3 . more details are reported in [ 17 ]. identifying leaks based on this radial pressure gradient proves to be reliable and effective as shown in this paper . directly measuring the pressure at each point in order to calculate the gradient is not effective and should be avoided . however , as a leak can happen at any angle around the circumference , full observability would require a series of pressure sensors installed around the circumference of the pipe . to avoid the complexity of such an attempt , we introduce a more efficient mechanism to be discussed below . we propose a detection concept for the identification of the radial pressure gradient in case of leaks . the main requirement is that the system should be able to detect leaks at any angle φ around the circumference of the pipe . a schematic of the proposed detection concept is shown in fig4 . to achieve full observability around the circumference a circular membrane is utilized . the membrane is moving close to the pipe walls at all times conforming to diameter changes and other defects on the walls , e . g . accumulated scale . the membrane is suspended by a rigid body , called a drum ( fig4 [ a ]). the drum is allowed to rotate about its center point g ( about any axis ) by design . the latter is allowed by a gimbal . in case of a leak the membrane is pulled towards it . this happens because the membrane is pulled by the radial drop in pressure ∂ p /∂ r described earlier ( fig4 [ b )). upon touching the walls , pressure difference δp is creating the normal force f on the membrane . we can write that : where a leak stands for the cross - sectional area of the leak , which can be of any shape . as pipeguard continues traveling along the pipe , a new force is generated ( f z ). this force is a result of friction between the membrane and the pipe walls . f z is related to the normal force , f , by an appropriate friction model , say f z = g ( f ). the analytic form of function g is not discussed in this patent application . by using eq . ( 1 ) we can see that f z depends on the pressure difference , since f z = g ( δpa leak ). then f z generates an equivalent force and torque on the drum , m , a key fact that is discussed further below . as a result , m pushes the drum to rotate about some axis passing through its center , while orientation of the axis depends on the angle φ of the leak around the circumference ( fig4 [ c ]). the effects of m can be later sensed by force and / or displacement sensors mounted on the detector . f z vanishes only when the membrane detaches from the leak and the drum bounces back to the neutral position ( fig4 [ d ]). we now describe the detailed design of a mechanism that uses the concept presented here to effectively identify leaks in pipes . the disclosed system can identify a leak by measuring forces on the drum . essentially , the problem has switched from identifying a radial pressure gradient ( at any angle φ ), to measuring forces ( and / or deflections ) on a mechanism . a 3d solid model of the disclosed detector is shown in fig5 . the exploded view of the design is presented in fig6 . the drum is suspended by a wheeled system and remains always in the middle of the pipe . a key fact with this design is the gimbal mechanism consisting of two different parts ( parts [ b ] and [ c ] in fig6 ). this mechanism allows the drum to pivot about two axes and thus respond to any torque , m , about any axis passing through its center point g . moreover , the system dimensions are such that the membrane leaves a small clearance (& lt ; 2 mm ) from the walls of the pipe . whenever a leak exists , a torque m is generated about some axis on the drum depending on the leak angle φ , as described earlier . m is sensed by appropriate sensors on the back plate on the carrier . very small motions on the drum are allowed in this specific embodiment . springs ( not shown ) are used in order to push the drum back to the neutral position after detection is completed ( fig4 [ d ]. in this embodiment three linear springs are used and they are omitted in all figures for simplicity . we now present the forces acting on the drum and justify the placement of sensors on the detector . in addition we propose a detection algorithm for effective leak detection and identification . we discussed earlier that a force f z = f z ê z , is generated at leak positions . here we use ê z to represent the unit vector along axis z and similar notation will be followed . this force is then generating a torque about point g , the center of the gimbal mechanism , which is equal to : the drum is supported by three points , namely point a , b and c ( fig7 ). the distance between each of these points and the center of the gimbal g is the same and equal to r . we mention at this point that three points of support is the minimal support that is needed to fix the gimbal mechanism in position in such a design . in addition , those points are 2π / 3 away from each other . we need to mention at this point that the three points do not contribute to the support of the drum at the neutral position . when the drum tends to move from neutral position each support creates a corresponding normal force ( f a , f b , f c ) to counterbalance torque m stemming from f z . we can write : m x =[ f a r −( f b + f c ) r sin ( π / 6 ) ê x ( 3 ) m y =[ f b − f c ] r cos ( π / 6 )] ê y ( 4 ) we assume here that the drum is only allowed to perform small movements and , thus , static analysis is accurate to first order . to complete the analysis we need to equilibrate the torques and forces acting on it . to do this we need to set m support = m , using eq . ( 2 , 5 , 3 , 4 ). in addition , since the drum is only allowed to move very little , we can assume that f z is balanced by the support provided by the axes of the gimbal at point g . then the sum of the three support forces discussed here is approximately equal to zero : one can solve the system of equations for the three unknown support forces . solution to system of equations yields : for the purpose of this work we built a prototype that has the following dimensions : and the detector is designed to operate in 100 mm as discussed later . by installing two force sensors on the supports we are able to measure the corresponding forces directly . the idea here is to measure the support forces as a results of the leak force f z , instead of measuring the leak pressure gradient directly . to avoid “ blind spots ” and to be able to detect leaks at any angle around the circumference the system needs to perform at least two force measurements . the latter statement needs to be proven via observability analysis , which is outside the scope of this application . however , one can think of the simple case of a single leak at φ = 0 °. in such case a force sensor installed on point a would not give any measurement ( f a = 0 ). however , another sensor placed on either point b or c can measure forces due to the leak and can eventually identify it . in this embodiment we install force sensors on points b and c without loss of generality . in addition we propose the use of the following metric in order to effectively trigger alarms in case of leaks : j ( t , t )=∫ t - t t √{ square root over ( f b ( τ ) 2 + f c ( τ ) 2 )}{ square root over ( f b ( τ ) 2 + f c ( τ ) 2 )} dτ ( 10 ) where t is the integration period . whenever j ( t , t )& gt ; c , where c is a predefined constant , a leak is identified . c needs to be selected in such a way to neglect noise and avoid false alarms . at the same time large values of c will lower the sensitivity of the detection . this metric proves to be effective in identifying leaks in pipes as shown below where we present experimental results . in order to validate the concepts we developed a prototype that will now be discussed . pipeguard is evaluated in a real gas pipe . details of the experiments and results are shown below . for this work pipeguard is designed to operate in 4 ″ ( 100 mm ) id gas pipes . however , all concepts discussed herein can be scaled and slightly altered accordingly to accommodate pipes of different sizes and perform leak inspection in other fluid media , e . g . water , oil , etc . in this embodiment pipeguard consists of two modules , namely the carrier and the detector ( fig8 ). the detector design and concepts have been discussed in detail earlier . the carrier assures the locomotion of the system inside the pipe . the module is carrying actuators , sensors , power and also electronics for signal processing and communications . a 3d solid model of the carrier with explanations on its main subsystems is presented in fig9 . the module &# 39 ; s locomotion is provided via a pair of traction wheels ( od = 1 3 / 16 ″ ) ( fig9 ). those two wheels are touching the lower end of the wall . in addition , the system is suspended by 4 legs with passive wheels from the upper walls as shown in the same figure . each suspension wheel has a spring loaded pivot . the angle θ sus of each pivot point on each suspension wheel is regulated in a passive way and is providing required compliance to the carrier . that compliance is very important , since it enables the module to align itself properly inside the pipe , overcome misalignments or defects on the pipe walls or even comply with small changes in the pipe diameter . the main actuator of the module is a 20 w brushed dc motor from “ maxon ” ( 339150 ). the motor is connected to the traction wheels via a set of gears with ratio 5 : 1 . in order to regulate speed , an incremental rotary encoder ( 50 counts ) from “ us digital ” is used and the speed loop is closed . both disk and hub are shown in fig9 . finally , all electronics , communication modules and batteries are stored inside the carrier module . derived from our design requirements , the robot should be able to perform the following tasks : move and regulate speed in pipes identify leaks by measuring signals from two force sensors at relatively high sampling rates ( f s & gt ; 150 hz ). communicate with the command center wirelessly pipeguard &# 39 ; s architecture is developed to meet these requirements and is shown in fig1 . to perform the aforementioned tasks two micro - controllers are used . micro - controller # 1 is dedicated to speed regulation and micro - controller # 2 is performing real - time leak sensing . the workflow is the following : the user specifies a motion command on the computer . the computer sends out the motion command including desired speed and desired position to pipeguard . after the wifi transceiver on the robot receives the command , it delivers the command to micro - controller # 2 . micro - controller # 2 performs closed loop speed control in order to regulate speed of the carrier . at the same time it calculates speed ( by measuring the signal from the encoder ) and commands the system to stop if it reaches the end of the pipe section ( or any other point along the pipe as specified by the operator ). parallel to micro - controller # 2 , micro - controller # 1 is responsible for leak detection and for sending out sensor data to the wifi transceiver . this micro - controller receives signals from the two force sensors installed on the detector . at the same time it receives the measured position from the encoder mounted on the carrier . it compiles the correlating force sensor data with position data and sends them out through the wifi transceiver . the wifi receiver on the command center then receives the data , decomposes them and supplies them to the user via the graphical user interface on the computer . in this embodiment of pipeguard , the wifi transceiver selected is an xbee pro 900 mhz rp module . we use two arduino pro mini 328 5v / 16 mhz and the motor driver used is the vnh5019 from polulu . the whole system is powered by a 11 0 . 1 v 350 mah 65 c li - polymer battery . finally , we use two fsr 400 force sensors for leak detection from “ interlink electronics ”. the latter ones are powered at 5v and a resistor of 8 kω is used for the necessary voltage division . we now evaluate pipeguard in an experimental setup we built in our lab . the setup consists of a straight 4 ″ id and 1 . 40 m long pvc pipe . the system is deployed in the pipe and performs leak detection in a pressurized gas environment . artificial leaks have been created on the pipe walls in the shape of circular 2 mm openings . those openings can be considered small for the general case and such small leaks fail to be detected by most state - of - the - art systems available . a picture of pipeguard inside the experimental setup is shown in fig1 . pipeguard moves along the pipe from [ start ] to [ end ] and its job is to identify the leaks . in fig1 leak # 1 is covered and leak # 2 is opened . initially we let the system run in the pipe at low speeds . we command pipeguard to move at ω d = 2 h z . which is equivalent to ν d = 0 . 19 m / s . at this speed the system is able to traverse the distance from [ start ] to [ end ] in approximately 5 sec . the signals captured by the two force sensors are shown in fig1 . a clear change in the signals reveals the existence of a leak in the pipe . note here that for this experiment the line pressure was selected to be equal to 15 psi . in the same figure the evolution of the proposed metric from eq . 10 is shown . a clear peak above the noise level is indicating the existence of a leak at t = t * when j ( t *, t = 0 . 2 sec )& gt ; 0 . 025 . as pipeguard approaches the leak , the signals from the two force sensors do not show any large variations from the dc value . noise can occur but is much smaller in amplitude than the leak signal ( fig1 ). detection occurs in four phases . initially pipeguard approaches the leak . then the membrane is moving towards the leak because of the effect of the radial pressure gradient . the latter small movement results in a small change in the signals ( undershoot in this case ). afterwards and when the membrane touches the wall at the leak position a force f z is generated , resulting in the torque m on the drum . the latter torque pushes the drum to move and thus signals of the two sensors change significantly . signals continue to increase up to a certain point when the membrane detaches from the leak . at this point the drum bounces back to the neutral position and signals return to their dc values . successful detection is performed when both leaks along the pipe are opened . again pipeguard is commanded to move at ν d = 0 . 19 m / s . the detector passes by the two consecutive leaks and the signals captured are presented in fig1 . signal magnitude for leak # 1 is smaller than the magnitude for leak # 2 . this is expected , as line pressure at the position of leak # 1 is reduced , because of the existence of leak # 2 . by carefully selecting corresponding thresholds c , one can trigger alarms at times t * i when j ( t * i , t )& gt ; c . in this case , again , c = 0 . 025 is selected in order to avoid false alarm ( neglect noise ) and effectively trigger alarms at leak locations . by carefully observing fig1 we can see that signals captured as pipeguard is passing by the first leak are in phase , while the signals at the second leak are out of phase . this occurs because the two leaks are at a different position on the circumference of the pipe ( φ 1 ≠ φ 2 ). by designing appropriate algorithms one can estimate the position of the leak on the circumference , but such discussion is outside the scope of this application . this specific version of pipeguard is able to move inside the pipes at relatively high speeds . experimentation showed that pipeguard &# 39 ; s motor is saturated at approximately ω d = 9 . 23 h z , which is equivalent to ν d = 0 . 875 m / s . at this speed pipeguard is able to inspect pipes at a rate of more than 3 km per hour . even at these speeds pipeguard is still able to inspect pipelines and detect leaks in a very reliable fashion . by carefully selecting the triggering thresholds one is able to trigger alarms only when leaks are present and avoid false alarms . example leak signals captured at those high speeds are shown in fig1 . in this case noise magnitude is higher , but still leak signals stand out significantly . in this case c = 0 . 025 , but one would probably try to increase the threshold . the latter would enable the sensor to neglect higher noise levels at the cost of reducing the sensitivity of the detection . the numbers in square brackets refer to the references listed herein . the contents of all of these references are incorporated herein by reference in their entirety . it is recognized that modifications and variations of the present invention will be apparent to those of ordinary skill in the art , and it is intended that all such modifications and variations be included within the scope of the appended claims . hunaidi o ., chu w ., wang a . and guan w ., 1999 . “ leak detection method for plastic water distribution pipes ”. advancing the science of water . fort lauderdale technology transfer conference , awwa research foundation , pp . 249 - 270 . fuchs h . v . and riehle r ., 1991 . “ ten years of experience with leak detection by acoustic signal analysis ”. applied acoustics , 33 , pp . 1 - 19 . 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