WO2008059226A2

WO2008059226A2 - A sensor

Info

Publication number: WO2008059226A2
Application number: PCT/GB2007/004324
Authority: WO
Inventors: Bonniface Umaedi
Original assignee: University of Greenwich
Current assignee: University of Greenwich
Priority date: 2006-11-13
Filing date: 2007-11-13
Publication date: 2008-05-22
Anticipated expiration: 2009-05-13
Also published as: WO2008059226A3

Abstract

The invention relates to a remote sensor for use in detecting integrity in structures and more specifically pipes. Examples of existing sensors are able to detect so-called defect characteristics that are encountered in corrosion products that are found in pipelines and originate from pipe walls. In one embodiment the invention provides a sensor adapted to be located on a structure. The sensor comprises a sensing element capable of providing a signal to a microprocessor. The microprocessor is adapted to run software in order to evaluate signals in order to indicate a status of the structure. A communication device transmits a signal to a remote recipient. Energy for operating the sensor is derived from a vibration emission array which is in contact with the structure. Thus the sensor is able to detect vibration, temperature and other variables, convert these signals into recognisable data and alert a remote location in the event of a hazard or fault. The sensor is also able to perform other functions such as self-testing, remote interactive training and self-updating of upgraded software and control systems.

Description

A Sensor

Field of the invention

The present invention relates to a sensor and more particularly, but not exclusively, the invention relates to a remote sensor for use in detecting integrity in structures and more specifically pipelines, particularly oil and gas pipelines.

Background of the invention

Sensors for use in detecting movement, temperature and strain often include a piezoelectric element (PZT). An advantage with such PZT devices is that they are cheap, rugged, and reliable and may be integrated on a semiconductor substrate so as to provide a direct input signal to electronic circuits for processing.

One type of piezoelectric sensor, with on board processing capability, is often referred to as a "micro-sensor". Micro-sensors can include a number of devices and are capable of offering solutions to a wide range of problems by utilising integrated processing capabilities.

Particularly when integrated with other components such as micro-processors to produce so-called smart micro-sensors. T-he aforementioned sensors suffer from the fact that they are very delicate and prone to damage. This tends to reduce the ruggedness and versatility of such micro-sensors.

One environment where it is especially desirable to use such micro sensors and smart micro-sensors is in the monitoring of large structures such as buildings and pipelines.

Prior Art

Examples of existing sensors are able to detect so-called defect characteristics that are encountered in corrosion products that are found in pipelines and originate from pipe walls. These defect characteristics often give rise to an attenuation of a signal that is transmitted as a result of flow dynamics of the fluid that is being transported in the pipeline.

Whenever kinetic energy (from the fluid flow) is converted to mechanical energy, vibrations or movement occur due to interactions between fluids at the boundary layer or surface of a wall of the pipe, for example in an oil pipe with a steel wall. These vibrations or movements can occur at certain resonant frequencies. Where large amounts of energy is converted, for example where dynamic fluid interacts with resistive forces, the resonance forces encountered can give rise to severe vibrations, which in turn caused damage or led to corrosion. In situ sensors were developed in order to detect such vibrations and trigger an alarm warning of such a

A disadvantage with most corrosion detectors and systems has been that they require a power supply and often an alarm relay, for example that utilised a third party adaptor. Therefore existing systems have required two or three separate sensing systems to sense conditions or monitor integrity and report faults.

It is apparent therefore that existing sensors and systems for monitoring such structures as buried oil steel pipeline integrity were primarily static, vendor centric and bulky. Furthermore, on-going annual costs of maintenance licences, operation permits and renewal fees made communication to and from sites expensive in terms of time, energy, money and reliability. Therefore the cost of installing and maintaining the system had to be taken into account.

Another disadvantage is that existing sensor systems require a local power supply, which is reliable and does not need to be replaced, ideally for several years, because replacement is not always easy (as the sensors can be located in remote and hostile places); and replacement was expensive.

US Patent US 7 105 982 B1 (Hagood et al) discloses a system for harvesting, storing and transferring power generated by mechanical disturbances to an electrical load. The document discloses a system intended to provide an efficient means of harvesting energy from intermittent mechanical disturbances whilst storing this energy. International Patent Application WO 02/03856 A2 (Lockheed Martin) discloses a method for combining a plurality of miniature electro-mechanical devices, or Micro Electro-Mechanical Systems (MEMS). Particular combinations of MEMS are described in use in an aircraft and in the human body.

Published US Patent Application US 2004/0007942 A1 (Nishida) discloses self- powered micro system generators. These generators are arranged to be connected to a load or energy storage reservoir and were plurally provided to provide more than one resonant frequency. Such a system presented a more reliable method of generating electrical energy from vibration energy by providing back-up micro generators.

Published US Patent Application US 2004/0075363 A1 (Malkin) discloses an energy harvesting device. Multiple members worked simultaneously to create electrical energy. The device included a base attached to a vibrating structure and a plurality of cantilevered beams extended from the base. The mechanical resonance of the beams amplified imparted base vibrations.

The device is well-suited for use within an aircraft in association with an autonomous sensor, and also in avionic backup systems, cellular telephones, and/or handheld computers.

The aforementioned devices were all capable of deriving energy from a mechanically vibrating system, but did not disclose a sensor that was adapted for use in monitoring oil pipelines.

An object of the invention is to provide a sensor that incorporates an energy generation system and features for use in monitoring structures in situ, such as, for example buildings or buried pipeline systems.

Another object is to provide a sensor that incorporates a detection and assessment of vibrations which monitor and detect defect characteristics without third party intervention. Summary of the Invention

According to a first aspect of the invention there is provided a sensor adapted to be located on a structure, the sensor comprising: a sensing element capable of providing a signal to a microprocessor, said microprocessor being adapted to run software in order to evaluate said signal so as to provide a status of the structure and a communication device for transmitting a status signal to a remote recipient, characterised in that energy for operating the sensor is derived from an energy conversion device which is in contact with the structure.

Thus the sensor is able to detect vibration, temperature and other variables, convert signals into recognisable data and alert a remote location in the event of a probable, imminent or actual hazard or fault.

Ideally the vibration emission array includes a piezoelectric device or other similar crystalline material that generates an electric current when it distorts.

Other energy conversion devices may be used to generate an electric current, for example a thermocouple or a solar cell.

The invention thus overcomes problems of having to supply energy, for example via a battery supply and conductive element as it has effectively its own permanent energy source.

Preferably the communication device is capable of receiving a data signal and performing other functions such as self-testing, remote interactive training and self- updating of upgraded software and control systems.

Preferably the sensor is adapted to report changes in performance, (which may be transmitted in real-time); perform channel evaluation and scheming of optimum transmission parameters, such as bit-rate and bit error rate (BER) analysis. Ideally communication is by way of a radio signal and most preferably by way of a micro antenna and GSM (Global System for Mobile) communications.

Ideally the sensor records changes in acoustic transmission characteristics of a fluid as it interacts with inner surfaces of a pipe. The sensor, under control of the microprocessor, discriminates signals and determines their physical effect. The result is that the sensor is able to detect, predict and report problems or faults and relay this information to a remote base station. In addition vibration energy is used to generate an electric current needed to operate the sensor and/or the transmitter.

Preferably the sensor is miniaturised and this feature enables direct embedding, for example, beneath a coated surface of a pipeline. That is the sensor is capable of being placed between layers of protective coating and the surface of a steel pipe.

Ideally the sensor includes: an additional integrated relay to indicate a tamper condition. The relay in this instance is ideally microscopically integrated to an ultra micro-wire or connected to field panels via optical fibres. Advantageously four optical fibres are used; two for the tamper relay and two with a resistive network to differentiate between alarms. However, it will be appreciated that wireless communications could be used to indicate a tamper condition.

Another advantage is that sensors can be adapted to include an intelligent decision support capability. Thus the sensor not only is able to monitor and report changes in the state of components and their performance, but also is able to evaluate the impact that these changes have on the remaining life span and on the performance and/or integrity of a building, system or pipeline.

Ideally a neural network or artificial intelligence (Al) system is used to detect and identify most common and/or important faults and to trigger an alarm or perform a task corresponding to the priority of such faults.

Preferably a system including the sensor has electronic processing and data recording capability that: describes rules and variables used for performance assessment and diagnosis; and/or identifies degradation and failure modes; and/or conditions associated with each mode; and/or identifies a ranges of variables used to categorise events such as corrosion or performance. This is of particular importance when monitoring remote or inaccessible structures such as corrosion of buried oil or gas pipelines.

Ideally methods that automate sensor diagnostics, analysis and report protocols are included in such a system. These methods optionally include such features as: automated sensor/diagnoses and status reporting. The system ideally also has the capability to be self learning and capable of updating with new/improved software.

According to a second aspect of the invention there is provided a method of monitoring a structure, comprising the steps of: placing a sensing element in contact with the structure, deriving energy from the structure for powering the sensor, detecting vibrations in the structure, converting these to signals and processing the signals using a microprocessor, evaluating said signals so as to provide a signal indicative of the status of the structure and transmitting a status signal to a remote recipient.

Ideally the structure is an pipeline and energy is derived from a vibration emission array which is in contact with the pipeline.

Ideally the method categorises the signals according to defect types in the structure.

Preferably the method is used to monitor and to diagnose faults in an oil pipeline or similar structure and is able to determine from said signals, features representing the type and/or severity and/or nature of said defect.

Ideally data relating to the type of defect is derived from characteristics detected at or near the pipe wall. Once the characteristics have been detected a damage index for an entire structure or pipe wall can be compiled and a decision may be made on the basis of the type of defect. For example, if the defect is medium stage defect a warning can be triggered; if the defect is a severe defect an alarm is triggered; and if fatigue is suspected a shut down signal is tripped to avoid failure. Preferably there is provided a pipeline monitoring system comprising: a method and device for defect characterisation, whereby signals are obtained by a sensor, converted to digital signals and a Fourier transform is applied to said signals to derive data in order to characterise defects.

Alternatively wavelet transforms may be applied to sets of digitised data derived from the signals.

The system is ideally adapted to perform continuous monitoring of the condition of a pipeline system and performance dynamics and use changes in defect pattern (signature) to predict mean time to failure or failure events.

Ideally the method continuously monitors processes a pipeline system for defects in the form of: corrosion damage, cracks, holes or tears in the pipe wall. The method involves monitoring changes in condition and continual assessment of the state of the pipe.

Factors representing the configuration of each defect include: the size, location, shape and orientation of each defect.

The method preferably comprises the steps of; (a) monitoring defect characteristics in a pipe wall to obtain vibration data associated with a crack, hole or tear in the pipe wall (b) generating digital data representative of said defect characteristics; (c) determining the severity of said crack, hole or tear; and (d) obtaining a damage index for the pipe wall based upon the defect characteristics so as to determine whether or not to trigger an alarm based upon the damage index.

Preferably the damage index includes a probability weighting of whether a particular digital signature is likely to give rise to failure or rupture.

Ideally the method further comprises the steps of: comparing the defect characteristics with a reference signal, eg from a look-up table, and applying a transformation to the defect characteristic signals based upon the results of the comparison, thereby deriving a factor which is representative of the defect. Ideally the transformation comprises a Fourier-transform. Alternatively a wavelet- transform may be applied.

Preferably both Fourier-transform and wavelet-transforms may be applied.

By employing algorithms to analyse vibration data, the effects of vibration and other variables permit comparison of this data with stored data. Artificial intelligence (in the form of neural networks) may be used to interpret and make diagnoses based on corrosion characteristics, historical data and defect characteristics. Processing may be performed remotely or is ideally performed in-situ, so that individual remote sensors can assess local risk and report automatically to a central office or control station.

Preferred embodiments of the invention will now be described, by way of example only, and with reference to the Figures in which:

Brief Description of the Figures

Figure 1a is a block diagram illustrating key components of the sensor;

Figure 1b is a block diagram illustrating key components of the data acquisition and analog-to-digital conversion;

Figure 2 is a schematic showing a first embodiment of an integrated vibration sensor;

Figure 3a is a schematic showing a first, round button shaped circuit encasement capsule;

Figure 3b is a schematic showing a second, cylindrical shaped circuit encasement capsule;

Figure 4 shows a diagrammatical example of integrated device architecture; Figure 5 shows an example of a flow diagram of the architecture in Figure 4;

Figures 6a, 6b and 6c show graphs of resonance frequency of diesel-oil escaping under pressure from a pipeline (in mV/mS);

Figure 7 is an overall schematic showing a circuit board of a sensor which derives energy fm ambient surroundings;

Figure 8 shows a diagrammatic view of an ambient heat collection device for converting heat to electricity;

Figure 9 is a circuit diagram of the power scavenging device in Figure 7;

Figures 10 shows a diagram illustrating the principle of extracting electricity using p- type and n-type interleaved pellets; and

Figure 11 shows switch states for 'On' and 'Off' voltages of a thermo electric sensor.

Detailed Description of Preferred Embodiments of the Invention

Referring to the Figures generally, and Figures 1 and 2 in particular, there is shown a sensor 10 which is adapted for use with, for example a pipeline (not shown) through which oil is flowing. The sensor 10 comprises a metallurgical agitation piezoelectric transducer (PZT) 1 a central processing unit (CPU) 2 and a charge amplification device 3.

A wireless protocol, trigger and transmitter 4 is connected to a micro antenna 7 (in Figure 2) or a photo-diode or laser light emitting diode (LED) 70, as shown in Figure 1. Data is either transmitted via an optical link, eg fibre optic cable (not shown) using the photo-diode 70 or laser light emitting diode (LED) 70, or data is transmitted via a radio frequency (RF) channel, for example GSM or Radium (Trade Mark). Data transmitter receives control signals and data signals to be transmitted from CPU 2.

An energy scavenger system 5A is connected to a charge storage system 5B. Charge storage system 5B is in the form of first and second low powered chargeable/discharge/rechargeable batteries. A database index memory 6 is also shown in which Look-Up Tables, and other data is stored. Batteries 5A and 5B power the CPU 2 and wireless transmitter 4. The energy scavenger/storage system ideally comprises two rechargeable miniaturised size series-mounted batteries. For convenience, the rechargeable power source and charge storage system 5 will be referred to as a battery.

All the components are mounted on a solid substrate which provides mechanical strength and integrity and the sensor 10 is encapsulated in a waterproof encapsulant so that it is hermetically sealed from moisture.

The ability of the micro-sensor to integrate a sensing and artificial intelligence to monitor and report changes in performance of remote plant, structures and steel pipelines, without third party interference, is thus apparent.

In a preferred embodiment the CPU 2 includes a logic array that utilises a transposable wave pattern modifier to convert wave patterns into elements that designate towards higher integers, so as to generate signals and process and analyse these in-situ. Typically the memory has a 1-2 Megabyte capacity and each capsule is encoded with a unique digital identification (ID) number for identifying sensor/defective pipelines/location.

The energy scavenger 5A generates an electrical current to provide typically in excess of 1 μW power at +2.36 V (DC) to an electrical load. It achieves this by exploiting at least of the following: (a) cathodic protection connections and/or (b) fluid transmission properties and/or (c) temperature gradient, so as to provide a trickle current for recharging the batteries. The power supply for the sensor is therefore superior to existing lithium ion batteries that eventually need replacing. Ideally the sensor 10 is small and capable of being fitted to a building, structure, vehicle or pipeline. In a preferred embodiment it is in the form of a cuboid measuring 1mm x 0.5mm x 1mm.

The bandwidth of sensing elements of the PZT transducer 1 exceeds that of most vibration sensors. Use of a multi elements micro systems (MEMS), with the ability for high speed, broadband data acquisition, enables a detailed capture of the vibration signature form a pipeline. Sensor 10 therefore obtain signals from the transducer, sends them to the CPU 2 for processing so as to obtain an analysis of events for immediate processing and reporting and a status signal is transmitted in the event of a fault or 'non-standard' signal or series of signals being received..

Miniaturised wireless sensor 10, shown in Figure 2, is integrated with a radio frequency (RF) transmitter driver 20 shown in Figure 1a. The RF transmitter 20 may be of the type used in cellular telephones that enables the sensor to switch depending on transmission range. Alternatively a short range RF transmitter may be used for example in a HIPERLAN or Bluetooth (Trade Mark) protocols.

Brief reference will now be made to the remaining Figures, in particular Figures 4 and 5 which depict ways of achieving the microprocessor architecture required for operational logic sequence for use with the sensor 10.

Figure 5 shows an example of architecture of the integrated circuitry used in the sensor and how this integrates and synchronises processes, activities and operations of the microchip.

The sensor 10 may be used to gather and transmit data for characteristic analysis, signal processing and data analysis techniques that explore and, prospectively, improve upon the existing techniques of data handling. Raw data obtained from assessing a coated steel pipeline under transmission is traditionally copious in nature and not conducive to direct input into a data classifier. This has generally made it difficult to manipulate such data in order to reduce and or improve classification and analysis; whereas the present invention performs analog-to-digital (ADC) conversion of raw data locally then transmits it in a digital form which is readily handled, sorted and analysed.

These steps are shown in Figure 1 b which illustrates key components of the data acquisition and analog-to-digital conversion process. Proposed algorithms for manipulating and processing data include: an artificial neural network (ANN) which directly inputs data into a classifier. This assists with error detection during complex signal processing and enables faster reading of the results of the algorithm during data processing. A practical advantage of this is that data may be converted locally and sent for remote assessment/processing or it may be processed locally and a decision reached as to, for example the status or integrity of a pipeline.

Digital outputs and values that control the integrated-device sensors operations are stored in the memory of the CPU. Many degrees of freedom can be created by a suitable arrangement of coordinating the interoperability of the integrated-device-on- Nanochip solutions.

Output data may be generated by means of SHANNON - quantisation methods using analog-to-digital converters (ADC) to sample amplitudes of signal. Newly analysed parameters may be stored in memory 80 in order to eliminate changes in performance deviations from a pre-programmed or self learned system that is ideally stored in random access memory (RAM). Alternatively reports may be triggered in dependence upon certain threshold conditions being exceeded or not met. This helps to reduce the risk of fatigue failure that is, for example, initiated by corrosion damage.

Data acquired with the algorithms can also serve as a reference base for the evaluation of regulating parameters that control the monitoring logic, driver cycles and communication protocols of the sensor 10 when an alarm trigger occurs. The sensor ideally operates with low data redundancy and can be configured to correct itself in a self-adaptive manner. Therefore in a preferred embodiment the sensor 10 can provide an extensive method for the creation of an autonomous, self-organising algorithm that can be trained to recognise faults or risks from a map or set of learned data, as shown in Figures 4 and 5. Figure 5 illustrates an ANN (comprising an input, one hidden layer and an output layers encompassing nodes or neurons) identical to those which enable the generation of, and characterisation of sounds from defective pipe wall vibrations. This is achieved by comparing events signatures-learned and trends to current conditions in real time.

Quantification may be achieved through magnitude in both time and frequency envelopes; by use of mean values or errors in voltage peak frequencies processed using the depth of modulation m. Fast Fourier Transform methods may also be used. By associating frequencies with defective pipe characteristics, and also by analysing the amplitudes, it is possible to classify the defect patterns into classes, for example: tolerable (requiring maintenance), severe (requiring immediate assessment) or dangerous (requiring immediate shutdown to avoid failure).

According to one method modulation signals from an undamaged and damaged pipeline x (t) were determined in percentage using mean value of an envelope x (t), where x_maχ (t) and x_mj_n (t), are the maximum and minimum values of the enveloped signal, respectfully.

In contrast to cable supported systems, the integrated 'device-on-chip' solution permits a comparably large number of sensors to be located adjacent one other, typically every 100 - 120 metres to 1 kilometre on a buried oil steel pipeline system in situ. It is therefore necessary to acquire data from an available sensor in order to obtain a sufficiently accurate reference base for subsequent statistical analysis. Furthermore the configuration of such a system permits data to be processed at the device in a parallel manner.

A 'time of event' model using quantisation can be determined by the signal amplitude of the PZT sensor 1 (or receptor) in a defective pipe of a corresponding internal fluid flow, as a result of vibration sound emission (signal source). Alternatively events may be determined by an acoustic emission (AE) defect-wave signal amplitude directly coupled to fluid flow along several kilometres of pipe wall. Figures 6a, 6b and 6c show frequency spectra from a four-month simulation test conducted in a laboratory. The test established damage pipeline characteristics. The findings are that change in the condition of the steel pipeline, as a result of defects, triggered a sudden change in performance (cumulative crack growth reduces transmission-ability).

Referring to Figures 7 to 11 , in which like parts bear the same reference numerals as in Figures 1 and 2, there are shown further examples of sensor with batteries that do not need to be replaced, since their drive systems rely on rechargeable batteries and charging devices. The embodiment in Figures 7 to 9 show a charge amplifier that relies upon power scavenging that exists as a result of a thermal differential, for example in ambient conditions of an oil pipeline.

The self-powered integrated sensor, shown in Figures 7 to 9, has an on-board circuit with positive turn-on at low ambient body temperature. Charging occurs as a result of energy being derived from heated oil in a pipeline. The circuit, shown in Figure 9, includes a positive feedback loop which amplifies current flow rapidly to a predetermined level at which point energy flows from the charger to charge the batteries 5B.

Figure 8 shows a schematic view of an integrated thermoelectric/voltage powered sensor device, with a power module electrically interconnected to a sensor module. The sensor module has a ceramic heat current cell array that is in electrical connection with a charging circuit, (shown in Figure 9).

A power module utilises a power charging mode during general oil transmission. Thermal energy (in heated oil) and/or electric current from a cathodic protection system, is used to charge the battery array. When the sensor 10 is not transmitting data, energy is used to charge batteries 5B.

A programmed thermoelectric/voltage controller acquires a predetermined frequency, pulse width modulated charging current, to charge and regulate the battery 5B. The duty cycle of the charging current is controlled by alteration of a programmed thermoelectric/voltage and a sensed battery voltage. Therefore the required ambient voltage is achieved by controlling the ON and OFF thresholds of plural parallel-connected device, as shown diagrammatically in Figure 11.

Figure 9 shows Field Effect Transistors (FET) switches placed in series between a thermoelectric/PZT array and the battery. The duty cycle is regulated in discrete steps over the entire range of 0% to 100% and can be updated as often as required with battery voltage measurements in to provide highly accurate regulation. Charge current pulse rise time is selected to match the response time of the thermoelectric/PZT voltage array.

Fluid flow vibration induced kinetics gives rise to a quartz/crystal movement which is sufficiently constant to generate an electric charge to drive micro-processor 2. Piezoelectric, electrostatic and electro-magnetic energy harvesting technologies extract electrical energy from vibrations. Fluid Flow Vibration induced kinetics operate on the progressive principle of a dynamo powered by movement of fluid (oil/water) in a pipeline system.

In an alternative embodiment, vibrations from moving oil in a pipeline system on which the sensor is embedded causes a digitised-rotor to rotate coupling energy to a form of micro-gear train (not shown). The gear train multiplies the rotational speed by a factor of approximately 100. This is used to spin a power-generating micro- generator at ultra-high speed. Electric current generated by this micro generator charges batteries in-situ via a capacitive charger.

The capacitor in the charger supplies electricity needed to drive an integrated sensor circuit equipped with a controlled recharge of the rechargeable low voltage power source by thermoelectric voltage and/or fluid flow voltage sensors. The power scavenger 5A may have a small, high-performance generator that can be modified so that it produces electric current even when oil movements in the pipeline system are slow. An advantage of the device is that it is able to withstand rapid transients such as water-hammer events and movements.

The device can power an integrated sensor and therefore requires no battery replacement. The kinetic quartz technology charges its battery store by movements from the oil transmission and the vibration generated both internally and externally allows for the sensor battery life to be almost indefinite.

Energy saving options include: when the power supply of the kinetic charger runs low, (eg after a predetermined time for charging and discharging) such as only sensing every two seconds. This does not include processing and transmission or advancing data until the vibration/ambient heat increases to a level sufficient to charge again (kinetic auto relay).

Changes in conditions of the steel pipeline system also influence leakage that can also be associated with rapid change in fluid direction and pressure. It is these changes that produce pressure transients and affect vibration sound emissions, which are shown as a continuous block of wide frequency spectrum (1 kHz - 16Hz in the time domain) and are detected by the PZT sensor described above.

The invention has been described by way of exemplary example only and it will be appreciate that variation may be made to the embodiments described without departing from the invention.

Claims

1. A sensor adapted to be located on a structure, the sensor comprising: a sensing element capable of providing a signal to a microprocessor, said microprocessor being adapted to run software in order to evaluate said signal so as to provide a status of the structure and a communication device for transmitting a status signal to a remote recipient, characterised in that energy for operating the sensor is derived from an energy conversion device which is in contact with the structure.

2. A sensor according to claim 1 is adapted to convert vibration and/or temperature variations and charge a battery.

3. A sensor according to claim 1 wherein a solar array is provided for generating an electric current to charge a battery.

4. A sensor according to any preceding claim wherein the sensor has self- testing device.

5. A sensor according to any preceding claim wherein the sensor has a remote interactive device adapted to receive upgraded software and control systems.

6. A sensor according to any preceding claim wherein the sensor has means to report changes in performance.

7. A sensor according to any preceding claim has a radio communication device, preferably a micro antenna and GSM.

8. A sensor according to any preceding claim wherein the sensor has artificial intelligence software.

9. A sensor according to any preceding claim wherein the sensor is adapted to be embedded beneath a coated surface of a pipe.

10. A sensor according to any preceding claim wherein the sensor has a relay to indicate a tamper condition.

11. A sensor according to claim 8 wherein the artificial intelligence software is used to detect and identify most common and/or important faults and to trigger an alarm.

12. A system includes a sensor according to any claim 8 has processing means and data recording means that describes rules and variables used for performance assessment and diagnosis and/or identifies degradation and failure modes and/or conditions associated with each mode and/or identifies a ranges of variables used to categorise events such as corrosion or performance, whereby a status signal is output according to the condition of the structure.

13. A method of monitoring a structure, comprising the steps of: placing a sensing element in contact with the structure, deriving energy from the structure for powering the sensor, detecting vibrations in the structure, converting these to signals and processing the signals using a microprocessor, evaluating said signals so as to provide a signal indicative of the status of the structure and transmitting a status signal to a remote recipient.

14. A method of monitoring a structure according to claim 13 comprising the steps of continuously monitoring the structure; detecting signals in the structure characterised in that data representative of a defect is derived from said signals.

15. A method of monitoring according to claim 14 wherein the signals are categorised according to defect types in the structure.

16. A method of monitoring according to any of claims 13 to 16 wherein defect characterisation signals are obtained; by a sensor and a Fourier transform is applied to said signals to derive data in order to characterise defects.

17.A method of monitoring according to claim 16 wherein defect characterisation signals are obtained; by a sensor and a wavelet transforms is applied to sets of data derived from the signals.

18. A method of monitoring a pipeline comprising the steps of: (a) monitoring defect characteristics in a pipe wall to obtain vibration data associated with a crack, hole or tear in the pipe wall (b) generating digital data representative of said defect characteristics; (c) determining the severity of said crack, hole or tear; and (d) obtaining a damage index for the pipe wall based upon the defect characteristics so as to determine whether or not to trigger an alarm based upon the damage index.

19.A sensor substantially as herein described and with reference to the drawings.

20. A system substantially as herein described and with reference to the drawings

21. A method substantially as herein described and with reference to the drawings.