WO2022204795A1

WO2022204795A1 - System and method for detecting at least one anomaly in a sealed enclosure, by measuring at least one physical parameter of a gas contained in said sealed enclosure

Info

Publication number: WO2022204795A1
Application number: PCT/CA2022/050459
Authority: WO
Inventors: Jocelyn Jalbert; Jean-Philippe Charest-Fournier; Mario Germain; Brigitte Morin; Serge Sarraillon; Marc-andré JOBIN
Original assignee: HYDRO-QUéBEC
Priority date: 2021-03-29
Filing date: 2022-03-28
Publication date: 2022-10-06
Also published as: CA3172306A1; CA3113421A1

Abstract

The invention relates to a system for detecting at least one anomaly in a sealed vessel of a specified volume and comprising a gas cushion. The system comprises at least one temperature sensor, to take temperature measurements of the gas cushion, and at least one pressure sensor, to take pressure measurements of the gas cushion. The system determines measurements of the volume of the gas cushion based on the temperature and pressure measurements taken in the gas cushion. The system detects an anomaly in the vessel from a variation in the volume, temperature and/or pressure measurements. The anomaly may be a leak in the vessel, or a defect in the equipment contained in the vessel.

Description

SYSTEM AND METHOD FOR THE DETECTION OF AT LEAST ONE ANOMALY IN A SEALED ENCLOSURE, BY MEASUREMENT OF AT LEAST ONE PHYSICAL PARAMETER OF A GAS CONTAINED IN SAID SEALED ENCLOSURE

TECHNICAL AREA

The invention relates to a system and a method for detecting at least one anomaly in an enclosure, by measuring at least one physical parameter of a gas contained in said enclosure. More particularly, the enclosure can be a sealed enclosure containing at least one gas blanket, and the physical parameters can include the temperature and the pressure of the gas blanket. Even more particularly, the sealed enclosure may be a sealed tank of an electrical transformer containing a liquid electrical insulator surmounted by the gaseous cushion, and at least one electrical device immersed in the liquid electrical insulator.

CONTEXT

[0002] The use of a liquid electrical insulator to insulate electrical equipment is well known in the field of electricity transmission. A tank, or container, preferably sealed, is often used to contain both the liquid electrical insulation and the electrical equipment, as is the case for example for electrical transformers on a base. This configuration can lead to leaks or spills, for example when the vessel experiences a physical failure and/or when its integrity is compromised. For example, in the case of electrical transformers, the tanks are generally filled with a liquid electrical insulator comprising an oil or a mixture of oils, and where appropriate, one or more additives.

[0003] A spill of such a liquid electrical insulator can cause significant damage to equipment resulting in significant economic losses (i.e. costs to repair/replace equipment, loss of productivity, etc.); and/or significant damage to the environment resulting in health and safety risks, significant costs related to decontamination of a dirty environment, etc.

[0004] Systems and methods exist to enable the detection of a leak of a liquid contained in a tank. The most common method for detecting leaks is to use a fluid level gauge. Other methods also exist, for example the use of installed cameras to visualize the level of liquid.

[0005] However, the existing systems and methods are not very precise since the level of liquid can fluctuate according to variations in the physical properties of the liquid, such as its temperature or its density, without there being a leak. in the system. In addition, existing systems and methods are generally intrusive, which can cause failures in the operation of electrical equipment. Also, some systems and methods installed outside the tank may be exposed to the weather and/or vandalism, for example.

[0006] There is therefore a need for a system and a method making it possible to accurately detect at least one anomaly in a sealed enclosure having a determined volume and containing at least one gas cushion.

[0007] Furthermore, when the sealed enclosure is a tank of an electrical transformer, there is a need for a system and a method making it possible to detect precisely, in the tank having a determined volume, at least one anomaly which may consist of a fault in the electrical equipment contained in the tank and immersed in a liquid electrical insulator which is surmounted by a gaseous cushion, and/or consist of a leak of the liquid electrical insulation and/or of the gaseous cushion, in particular of liquid electrical insulation.

[0008] In addition, there is a need to quickly detect at least one anomaly in a tank having a determined volume containing electrical equipment (e.g. an electrical transformer) allowing emergency maintenance to be carried out therein and/or avoid substantial leakage of the liquid electrical insulation.

[0009] In addition, there is a need for a system and a method which makes it possible to minimize potential intrusions into a tank having a determined volume containing electrical equipment (eg an electrical transformer) to reduce the risk of interference with the operation electrical equipment. SUMMARY OF THE INVENTION

Several aspects of the invention are described with reference to the following preferred embodiments [A] to [JJ]:

[A] A system for detecting at least one anomaly in a sealed tank containing a gaseous mattress, the system comprising: at least one pressure sensor adapted to perform pressure measurements of the gaseous mattress, said at least one pressure sensor being in contact with the gas mattress; at least one temperature sensor adapted to perform temperature measurements in the gaseous mattress, said at least one temperature sensor being in contact with the gaseous mattress; communication means configured to transmit data associated with the pressure measurements and the temperature measurements; and at least one computing device operatively connected to said at least one pressure sensor and to said at least one temperature sensor by the communication means, the at least one computing device comprising a data analysis module configured to: determine at least a value of a volume of the gas cushion from the data associated with the pressure measurements and the temperature measurements; and detecting the presence of said at least one anomaly in the tank from the at least one value of the volume of the gaseous cushion, the data associated with the pressure measurements of the gaseous cushion, and/or the data associated with the temperature measurements of the gas mattress.

[B] The system according to [A], in which the at least one computing device further comprises a data acquisition module configured to acquire the data associated with the pressure measurements and the temperature measurements transmitted by the communication means , and wherein the analysis module is operatively connected to the acquisition module. [C] The system according to [A] or [B], in which the at least one value of the gas cushion volume is calculated according to the following formula:

where P ₁ is a reference gas cushion pressure, V ₁ is a reference gas cushion volume and

is a reference temperature of the gas blanket; and where P ₂ is data associated with a pressure measurement of the gas cushion and T ₂ is data associated with a temperature measurement of the gas cushion.

[D] The system according to any of [A] through [C], wherein the at least one computing device is further configured to: determine a new value of the volume when new data associated with temperature measurements and pressure measurements are available; and detecting said at least one anomaly from a variation between the new volume value and at least one historical volume value previously determined.

[E] The system according to any one of [A] to [D], wherein the data analysis module further comprises a data smoothing module configured to attenuate noise in the at least one value of the volume, the noise being associated with pressure measurements and/or temperature measurements.

[F] The system according to [E], in which the noise in the at least one volume value includes a phase shift between the pressure measurements and the temperature measurements.

[G] The system according to [E] or [F], in which the data smoothing module is configured to use at least one method selected from a group consisting of: - an adjacent mean method,

- a Savitzky-Golay method,

- a percentile filter method, and

- an FFT filter method.

[H] The system according to any one of [A] to [G], in which the means of communication comprise a set of components, parts and/or electronic chips configured to: condition signals representative of the data associated with the measurements of temperature and pressure measurements; and transmitting the signals representative of the data associated with the temperature measurements and the pressure measurements to said at least one computing device.

[I] The system according to [H], in which the means of communication are further configured to transmit the signals representative of the data associated with the temperature measurements and the pressure measurements by wireless transmission.

[J] The system according to any of [A] to [I], wherein said at least one computing device further comprises an alert module configured to generate an alert following detection of said at least one anomaly.

[K] The system according to [J], wherein the alert module is further configured to generate an alert when at least one alert threshold is crossed, said at least one alert threshold being selected from a group consisting of :

- a minimum volume of the gaseous mattress,

- a maximum volume of the gaseous mattress,

- a minimum pressure of the gaseous mattress,

- a maximum pressure of the gaseous mattress,

- a minimum temperature of the gas blanket, and - a maximum temperature of the gas blanket.

[L] The system according to any of [A] through [I], wherein the system further comprises a user interface configured to perform at least one function selected from a group consisting of:

- a display function of at least one value of the volume of the gaseous mattress; and

- a functional management function comprising at least one start-up procedure and a shutdown procedure of said at least one pressure sensor and of said at least one temperature sensor.

[M] The system according to [J] or [K], wherein the system further comprises a user interface configured to perform at least one function selected from a group consisting of:

- a display function of at least one value of the volume of the gaseous mattress;

- an alert threshold management function; and

[N] The system according to any of [A] to [M], wherein said at least one computing device further comprises a deep learning module configured to:

- analyzing the at least one value of the volume of the gaseous mattress, the data associated with the temperature measurements of the gaseous mattress and/or the data associated with the pressure measurements of the gaseous mattress; and

- Automatically detect said at least one anomaly.

[O] The system according to any of [A] to [N], wherein the data associated with the pressure measurements and the temperature measurements comprises time indications indicative of a time when each of said pressure measurements and temperature measurements were made.

[P] The system according to any one of [A] to [O], in which said at least one computing device further comprises a database allowing storage of the at least one value of the volume, of the data associated temperature measurements and data associated with pressure measurements.

[Q] The system according to any one of [A] to [P], wherein said at least one temperature sensor is a thermocouple rod installed in contact with the gas blanket.

[R] The system according to any one of [A] to [Q], wherein said at least one pressure sensor is an absolute pressure sensor.

[S] The system according to any of [A] to [R], in which:

- the sealed vessel also contains a volume of a liquid, and

- at least a part of the gas cushion rests on at least a part of the volume of the liquid.

[T] The system according to any one of [A] to [S], wherein said at least one anomaly is a leak and/or a problem affecting the at least one value of the volume of the gas cushion, the measurements of gas mattress pressure, and/or gas mattress temperature measurements.

[U] The system according to [S], wherein said at least one anomaly is a liquid leak and/or an electrical problem of at least one piece of equipment at least partially submerged in the liquid, the electrical problem affecting the values of the mattress gas volume, mattress gas pressure measurements, and/or mattress gas temperature measurements.

[V] A method for detecting at least one anomaly in a sealed vessel containing a gas blanket, the method comprising: capturing, with at least one pressure sensor, pressure measurements of the gas blanket; capturing, with at least one temperature sensor, temperature measurements of the gas blanket; determining, by a processor, at least one value of a volume of the gas cushion from data associated with the pressure measurements and data associated with the temperature measurements; and detecting, by the processor, said at least one anomaly in the sealed vessel from the at least one value of the volume of the determined gas cushion, data associated with the pressure measurements, and/or data associated with the temperature measurements .

[W] The method according to [V], further comprising: transmitting, by means of communication, signals representative of the data associated with the pressure measurements and the data associated with the temperature measurements; and acquire, by an acquisition module operationally connected to the processor, the data associated with the pressure measurements and the data associated with the temperature measurements from the signals transmitted by the communication means.

[X] The method according to [V] or [W], in the at least one value of the volume of the gas cushion is calculated according to the following formula:

is a reference temperature of the gas blanket; and where P ₂ is a pressure measurement of the gas cushion and T ₂ is a temperature measurement of the gas cushion. [Y] The method according to any of [V] to [X], further comprising attenuating noise associated with pressure measurements and/or temperature measurements.

[Z] The method according to [Y], in which to attenuate noise comprises using a method selected from a group consisting of:

- an adjacent mean method,

- a Savitzky-Golay method,

- a percentile filter method, and

- an FFT filter method.

[AA] The method according to [W], in which transmitting signals comprises conditioning the signals representative of the data associated with the pressure measurements and the data associated with the temperature measurements.

[BB] The method according to any one of [V] to [Z] and [AA], further comprising generating at least one alert following the detection of said at least one anomaly in the sealed vessel.

[CC] The method according to any one of [V] to [Z] and [AA], further comprising generating at least one alert when at least one alert threshold is crossed, said at least one alert threshold alert being selected from a group consisting of:

- a minimum volume of the gaseous mattress,

- a maximum volume of the gaseous mattress,

- a minimum pressure of the gaseous mattress,

- a maximum pressure of the gaseous mattress,

- a minimum temperature of the gas blanket, and

- a maximum temperature of the gas blanket.

[DD] The method according to any one of [V] to [Z] and [AA] to [CC], further comprising at least one step selected from a group consisting of: visualize, with a user interface, a historical and/or real-time volume of the gas blanket; managing, with the user interface, said at least one pressure sensor and said at least one temperature sensor, or managing said at least one pressure sensor and said at least one temperature sensor comprises at least a start-up step and a stop step.

[EE] The method according to [CC], further comprising at least one step selected from the group consisting of: displaying, with a user interface, a historical and/or real-time volume of the gas cushion; manage, with the user interface, the thresholds of at least one alert; and managing, with the user interface, said at least one pressure sensor and said at least one temperature sensor, where managing said at least one pressure sensor and said at least one temperature sensor comprises at least a step of starting and a stop step.

[FF] The method according to any one of [V] to [Z] and [AA] to [EE], further comprising: analyzing, by a deep learning module, the at least one value of the volume of the gas blanket, data associated with temperature measurements and/or data associated with pressure measurements; and detecting, with the deep learning module, said at least one anomaly.

[GG] The method according to any of [V] to [Z] and [AA] to [FF], further comprising storing, in a database, the data associated with the temperature measurements and the pressure measurements .

[HH] The method according to any one of [V] to [Z] and [AA] to [GG], in which detecting said at least one anomaly comprises detecting at least one leak and/or a problem affecting the at minus a value of the volume of the mattress gas, the data associated with the pressure measurements of the gas cushion, and/or the data associated with the temperature measurements of the gas cushion.

[II] A use of the system defined in any one of [A] to [U] for the detection of at least one anomaly in a sealed vessel containing a gas cushion.

[JJ] A use of the system defined according to any one of [A] to [U] for the detection of at least one anomaly in a sealed tank of an electrical transformer containing a volume of a liquid and a gaseous cushion , at least a portion of the gas cushion resting on at least a portion of the volume of the liquid.

BRIEF DESCRIPTION OF DRAWINGS

The present invention will be better understood on reading the following description of non-limiting aspects of preferred embodiments of the invention.

[0012] FIG. 1 represents a photograph of an electrical transformer on a base, according to an example of the prior art.

[0013] FIG. 2 represents a schematic view of the electric transformer of the type illustrated in FIG. 1 and where appear in a sealed tank having a determined volume, a volume of liquid electrical insulation, a gaseous mattress and electrical equipment immersed in the volume of liquid electrical insulation.

[0014] FIG. 3 represents an electric transformer where appear sensors of a system according to the invention for the detection of at least one anomaly in an electric transformer.

[0015] FIG. 4 represents a schematic view of a system according to one of the possible embodiments of the invention, for the detection of at least one anomaly.

[0016] FIG. 5 shows some elements of the system of FIG. 4, partly positioned in a service cabinet (shown in the open position) of an electrical transformer. [0017] FIG. 6 shows an installation of the positioning of sensors of the system of FIG. 4.

[0018] FIG. 7 is a diagram showing the relationships between certain modules of the system of FIG. 4.

[0019] FIG. 8 represents the application of different smoothing methods to measurements obtained within the framework of the invention.

[0020] FIG. 9 represents the results of experiments of an embodiment of the system for detecting at least one anomaly in an electrical transformer.

DETAILED DESCRIPTION

In the description and the figures which follow, the same reference numbers refer to similar elements of the invention. In addition, in order not to unduly clutter the figures, it is possible that a figure does not contain all the reference numbers of the elements found therein. Also, it is possible that some elements are only referenced in a single figure. The elements thus referenced can be easily inferred in the other figures presented. The embodiments, geometric configurations, materials and/or dimensions shown in the figures or described in this disclosure are presented only as examples, and should not be interpreted as limitations of the invention.

[0022] In general, the following description will refer to preferred aspects of a system and a method allowing the detection of at least one anomaly in an electrical transformer which consists of a sealed tank having a determined volume and containing a volume of a liquid electrical insulator, a volume of a gas defining a gaseous cushion, and at least one electrical apparatus, said at least one apparatus being immersed in the liquid electrical insulator. The system comprises, among other things, a temperature sensor and a pressure sensor installed at least in part in the tank, at least one computing device, and communication means operatively connecting the temperature and pressure sensors to the computing device . Values of a volume of the gas cushion are determined from the temperature and pressure measurements obtained. The detection of the anomaly, which may be an electrical fault and/or a leak in the liquid electrical insulation, for example, is then based on the values of the volume of the gaseous mattress, the pressure measurements of the gas contained in the gas, and/or gas temperature measurements.

Of course, the detection system 21 according to the present disclosure can be adapted to any other field requiring the detection of defects in a sealed tank containing at least one volume of a gas or in a sealed tank closing a volume of a liquid and a volume of a gas forming a gaseous cushion above the liquid, either for example in the field of fuel or gas tanks/cisterns.

The detection system described makes it possible to reduce installation and operating costs, for example compared to current solutions including the use of an electrical insulating oil leak retention tank.

[0025] In Figs. 1 and 2 shows an existing pad-mounted electrical transformer known in the art.

The electrical transformer 1 on a base comprises at least one opening allowing access to a connection cabinet 3 (Fig. 5) and a sealed tank 5 in which there is an electrical device 7, as illustrated in FIG. 2. For example, electrical equipment 7 is an electrical transformer.

[0027] FIG. 2 shows details of internal constituents of the electrical transformer 1, namely the sealed tank 5 containing a volume of a liquid electrical insulator 9, a gaseous cushion 11 located above the liquid electrical insulator 9, and at least the electrical equipment 7 immersed in liquid electrical insulation 9.

[0028] Figs. 3-7 illustrate one aspect of a preferred embodiment of the invention.

[0029] FIG. 3 illustrates the sealed tank 5 on which are installed a temperature sensor 23 and a pressure sensor 25, the temperature 23 and pressure 25 sensors forming part of the system for detecting at least one anomaly 21, according to a preferred aspect 1 'invention. Specifically, the temperature sensor 23 and the pressure sensor 25 are installed so as to be in contact with the gaseous mattress 11. Thus, the sensors perform temperature and pressure measurements in the mattress 11. Thus, said detection system 21 is configured and adapted to detect anomalies in the tank 5, for example leaks of the liquid electrical insulation 9 or a defect in the electrical equipment 7, from the physical properties of the gas mattress 11.

[0030] Preferably, the gaseous cushion 11 comprises a volume of gas in contact with the top of the volume of the liquid electrical insulator 9. The gas constituting the gaseous cushion can be dry air or nitrogen, for example. Preferably, the liquid electrical insulator 9 is an oil or a mixture of oils, possibly containing one or more additives. For example, the liquid electrical insulator 9 may consist of a naphthenic-type mineral oil. It will however be noted that the constitution of the liquid electrical insulation and/or of the gaseous cushion may vary without departing from the present disclosure.

In a preferred embodiment, the electrical equipment 7 is an electrical transformer. For example, the detection system 21 can be installed on a Siemens brand ONAN (Oil Natural Air Natural) transformer, whose characteristics include a nominal power of 500kVA, a 25kV three-phase primary, a 600V three-phase secondary, and 995L of oil at as a liquid electrical insulator. However, this disclosure is not limited by the type of electrical equipment 7 contained in the sealed tank 5.

In some embodiments, the sealed vessel 5 having a determined volume may be provided with an overpressure valve (not shown) allowing part of the gaseous cushion to be evacuated in the event that the pressure of the latter reaches a critical value putting risks the integrity of the sealed tank. In these embodiments, the temperature sensor 23 and/or the pressure sensor 25 can be arranged differently from the embodiments shown in Figs. 3 to 7. For example, the pressure sensor 25 can be installed on a section of the suppression valve in contact with the gas cushion 11.

Still with reference to Figs. 3 to 7, the system for detecting at least one anomaly 21 is configured to detect an anomaly in the sealed tank 5 from pressure and temperature measurements in the gas cushion 11 contained in the sealed vessel 5. The temperature sensor 23 is suitable for taking temperature measurements and the pressure sensor 25 is suitable for taking pressure measurements. The temperature 23 and pressure 25 sensors are installed so as to be at least partly in contact with the gaseous mattress 11. The detection system 21 is thus configured to determine, using the law of ideal gases, volume values of the mattress gas 11 from the pressure and temperature measurements taken by the pressure sensor 25 and the temperature sensor 23, respectively.

[0034] According to a preferred embodiment of the invention, the detection system 21 is configured to detect variations in the physical properties of the gaseous cushion from the determined volume values, from data associated with the measurements of the pressure and/or data associated with the measurements of the temperature of the gas cushion 11, in order to detect, from these variations, an anomaly or a defect in the sealed tank 5. For example, the detection system 21 can determine the anomaly from data in real time associated with the temperature and pressure measurements, and/or using historical data, i.e. data associated with the temperature and pressure measurements having been carried out previously and having been stored by the detection system 21.

An anomaly may be, for example, an oil leak due to a loss of structural integrity of the tank. The decrease in the amount of oil causes a change in the physical properties of the gaseous mattress, for example a change in pressure and volume of the gaseous mattress. Since the pressure and the temperature are measured by the pressure sensor 25 and the temperature sensor 23, the anomaly detection system can then detect the anomaly in the gas cushion, from the data associated with the pressure and the temperature. temperature and/or the value of the corresponding volume determined. For example, the detection system 21 can detect the anomaly by comparing a volume value determined at a time t=x with a reference volume determined during the installation of the tank 5. Alternatively, the anomaly can be detected by comparing the volume value determined at time t=x with a volume value determined at time t=xy. The instants t=x and t=x-y correspond to instants or times when temperature and pressure measurements are taken, for example. [0036] Furthermore, according to a preferred embodiment of the invention, the detection system 21 can also be configured to detect an electrical problem in the electrical equipment 7 causing a variation in the physical properties of the gas cushion 11, in particular the volume, the pressure and/or the temperature of the gas cushion 11. The electrical problem can be an electric arc, a hot spot, or a partial discharge, for example.

Preferably, the volume of the gas cushion 11 is relatively small compared to the volume of the liquid electrical insulator 9. Thus, even a small variation in the volume of the liquid electrical insulator 9 will have an accentuated effect on the variation of volume pressure of the gas mattress. Thus, the detection system 21 is advantageously adapted to detect an anomaly from the physical properties of the gaseous cushion, increasing the probabilities of detecting relatively small leaks of the liquid electrical insulation 9.

[0038] Referring to FIG. 4, a schematic representation of the detection system 21 is illustrated. As already mentioned, this detection system 21 comprises a temperature sensor 23 and a pressure sensor 25. In certain embodiments, the detection system 21 can comprise several temperature sensors and several pressure sensors arranged on the sealed tank 5 and in contact with the gas mattress. The presence of several sensors makes it possible to determine average temperatures and pressures representative of the pressure and temperature in the entire gas cushion. In certain embodiments, the temperature sensor 23 and the pressure sensor 25 can be integrated into a single sensor, or common element.

The anomaly detection system 21 further comprises a data acquisition module 33 operatively connected to the temperature sensor 23 and to the pressure sensor 25 by communication means 27a and 27b, respectively. The communication means 27a and 26b are suitable for transmitting the data associated with the temperature measurements and the pressure measurements, for example in the form of wired or wireless signals. According to a preferred embodiment of the invention, the detection system 21 further comprises a computing device 31 and a database 35 which are operationally connected to the data acquisition module 33. Said acquisition module 33 is configured to transmit data associated with temperature measurements and pressure measurements to database 35 and computing device 31.

In certain embodiments of the invention, the communication means 27a and 27b are similar and can each comprise a set of components configured to condition, or process, the signals originating respectively from the temperature 23 and pressure 25 sensors, the signals being representative of temperature measurements and pressure measurements. The set of components of each of the communication means 27a and 27b can also be configured in certain embodiments to transmit said signals to the computing device 31, comprising an integrated data acquisition module, or to an acquisition module of data 33 physically separated from the computing device 31, as illustrated in the embodiment of FIG. 4. The component set may include electronic parts and/or electronic chips, for example. In addition, the communication means 27a and 27b can additionally be configured to power the pressure and/or temperature sensors, for example by integrating a power cable into the communication means.

[0042] Referring to FIG. 5, at least a portion 22 of the detection system 21 is installed in a wiring closet 3 of a transformer 1. The portion 22 of the system thus installed is easily accessible by authorized personnel. Such an installation also makes it possible to protect the portion 22 of the detection system 21 from bad weather or vandalism, for example.

[0043] It will be noted that the installation of the temperature sensor 23 and the pressure sensor 25, in limited contact with the gaseous cushion, makes it possible to reduce the probability of interference of the anomaly detection system 21 with the equipment. electric 7 since the presence of the detection system 21 is limited in the sealed tank 5. In addition, the temperature 23 and pressure 25 sensors are in contact with the mattress gas from the tank, also reducing the possibility of interference with electrical equipment 7.

[0044] In alternative embodiments, the detection system 21 can be installed in a different way, for example in a box external to the electrical transformer 1, as long as the temperature 23 and pressure 25 sensors are at least partially in contact with the gas cushion 11 of the sealed tank 5.

[0045] Referring to Figs. 4 to 6, a temperature sensor 23 and a pressure sensor 25 are installed at least partly in the tank 5, on a wall 6 of the sealed tank 5. The temperature sensor 23 is a type T thermocouple rod which is installed on the wall 6 towards the top of the tank 5, so as to be in contact with the gaseous cushion 11. Similarly, the pressure sensor 25 is installed on the wall 6 towards the top of the tank 5, so as to be in contact with the gas mattress 11.

[0046] In alternative embodiments, different types of temperature sensors can be used, such as resistance temperature detectors (RTDs) or thermistors, for example. The temperature sensor 23 can also be physically arranged differently in the tank, for example depending on the shape of the tank, as long as the sensor is in contact with the gaseous mattress in order to allow measurements of the temperature of the gaseous mattress. In certain embodiments, the temperature sensor 23 may require an electrical power supply, supplied by the detection system 21 or by an external system. Power supply wires or batteries, installed in the connection cabinet 3, can thus be connected to the temperature sensor 23, for example.

[0047] In some embodiments, the sealed vessel 5 includes a relief valve (not shown), and the pressure sensor is an absolute pressure sensor installed on the pressure relief valve above the oil in the gas cushion 11 Alternatively, various pressure sensors can be installed, depending on a certain accuracy or operating pressure range desired and depending on the type of vessel in which the detection system is installed. The pressure sensor 25 can be physically arranged differently in the tank, for example depending on the shape of the tank, as long as the sensor is installed at least partly in the gas cushion 11 to perform the pressure measurements of the gas cushion 11. In one of the preferred embodiments, the pressure sensor 25 may require an electrical power supply supplied by the system 21. Power supply wires or batteries, installed in the connection cabinet 3, can thus be connected to the pressure sensor 25, for example.

[0048] Referring now to FIG. 7, the computer device 31 comprises several modules configured for the detection of an anomaly in the tank. The temperature sensor 23 and the pressure sensor 25 are operationally connected by means of communication 27a and 27b to a data acquisition module 33 configured for an acquisition of the data associated with the pressure measurements and the temperature measurements in real time. . The communication means 27a and 27b, in one of the preferred embodiments, can be adapted for wired transmission of the data associated with the temperature measurements and the pressure measurements. The communication means 27a and 27b can alternatively or additionally be adapted to transmit the data wirelessly.

The data associated with the temperature measurements and the pressure measurements may include, in certain embodiments, the moment when each of the temperature or pressure measurements is taken (time stamp). For example, the data associated with the pressure and temperature measurements transmitted by the communication means 27a and 27b can include time data representative of the respective moment when each of the measurements transmitted is measured by one or the other of the pressure sensor 25 and the temperature sensor 23.

[0050] The data acquisition module 33, in a preferred embodiment, can be a module that is physically separate from the computing device 31. For example, a CompactRIO® can be used. However, in other embodiments, data acquisition module 33 may be integrated with computing device 31. Data acquisition module 33 may activate at regular intervals to collect temperature and pressure and to transmit the data associated with the measurements to the computer device 31 or to a database 35. According to another preferred embodiment of the invention, the acquisition module can also be activated prematurely in the event of of breakage or anomaly in order to transmit an alert indicative of the anomaly, for example. In some embodiments, the data acquisition module 33 may therefore have a data analysis and processing capability.

According to a preferred embodiment of the invention, the data acquisition module 33 is also operationally connected to the database 35 which is configured to record the data associated with the pressure measurements and the temperature measurements, and optionally timestamp values, ie data indicative of the moment when each of the measurements is carried out. Thus, the database 35 can be configured to store the data associated with the temperature measurements and the pressure measurements in a time series, thus creating a history of the temperature measurements, the pressure measurements, and the volume values associated with the temperature measurements and pressure measurements. In a preferred embodiment, the InfluxDB® database, a specialized database for time series, is used. However, it will be understood that several other databases can be considered for recording measurements.

[0052] Still with reference to FIG. 7, the data associated with the pressure measurements and the temperature measurements are additionally sent to a data analysis module 37. Alternatively, the data analysis module can be operatively connected to the database 35. The data analysis module The data analysis 37 is configured to determine values of the volume of gas in the gas cushion 11 from the data associated with the pressure measurements and the temperature measurements taken.

For example, the data analysis module 37 uses the following formula to determine the volume of air V ₂ :

In the previous equation, P is an initial or reference pressure, 7 is an initial or reference temperature, and V ₁ is an initial or reference volume of the gas cushion 11 in the tank 5, and P ₂ is data associated with the pressure of gas cushion 11 measured by pressure sensor 25 and T ₂ is data associated with the temperature of gas cushion 11 measured by temperature sensor 23. In a preferred embodiment, the initial pressure P and the initial temperature are reference values. For instance,

is set at 298K and is set at 101.325 kPa, and the initial volume V ₁ is calculated using the parameters indicated on the transformer tank. However, in alternative embodiments, the initial pressure and temperature can be measured by the pressure sensor 25 and the temperature sensor 23 at an initial instant, for example during the installation of the detection system 21 or during the tank installation 5. The volume can also be determined from the initial pressure and temperature measurements.

Still with reference to the above equation, the pressure P ₂ is a pressure measurement taken at a given time in the sealed vessel 5 and the temperature T ₂ is a temperature measurement taken at a given time in the tank 5. Preferably, the pressure and temperature measurements are taken at the same given time. It is thus possible to calculate a measurement of the volume V ₂ at said given time.

As described previously, the data analysis module 37 is also configured to detect the presence of an anomaly in the sealed vessel 5 from historical and/or current volume values, and associated historical/current data. to the temperature measurements and to the pressure measurements of the gas cushion 11. For example, the data analysis module 37 can be configured to detect or diagnose a number of anomalies according to one or more variations of the values of the volume, of the associated data pressure measurements, and/or data associated with the temperature measurements of the gas cushion 11.

For example, when the data analysis module 37 detects an increase in the volume of the gaseous cushion 11, for example by analyzing the fluctuations in the volume values of the gaseous cushion 11 from the historical values of the volume, said module data analysis 37 can determine the presence of an oil leak in the tank 5.

According to a preferred embodiment of the invention, still with reference to the embodiment of FIG. 7, the data analysis module 37 includes a data smoothing sub-module 41 configured to clean the data associated with the temperature and pressure measurements to allow analysis of the physical properties of the gas mattress in the tank 5. Indeed, a variation in the values of the volume of the gas cushion 11 is not necessarily indicative of an anomaly in the tank 5. This variation can come from the sensitivity as well as from the precision of the sensors temperature 23 and pressure 25, but also due to the fact that the temperature in the gaseous cushion varies differently from the contraction or expansion of the liquid caused by the change in temperature. A phase shift can thus be created between the pressure and temperature changes, thus creating a phase shift between the temperature measurements and the pressure measurements taken at a given time and consequently leading to variations in the values of the volume of the gaseous cushion 11 determined from data associated with pressure and temperature measurements. By phase shift, it is meant that the impact of a physical event, such as a leak, on the physical properties in the gaseous cushion is not necessarily simultaneous, and is therefore not detected simultaneously by the temperature sensor and the pressure sensor. The variation in the volume values caused by this phase shift between the pressure and temperature variations of the sealed vessel 5 can be characterized as noise and the data smoothing sub-module 41 makes it possible to at least partially reduce this noise on the volume values determined by the system 21.

To prevent this variation in volume, which is not indicative of an anomaly, from being interpreted as an anomaly in the tank, the data smoothing sub-module 41 can be configured to smooth the data, for example the values volume or data associated with temperature and pressure measurements, using a smoothing model suitable for smoothing data containing a certain amount of noise. Depending on the situation, the FFT filter method, the Savitzky-Golay method, the adjacent mean method, or the percentile filter method can be used. It will be understood that other methods of data smoothing may be considered without departing from this disclosure.

According to a preferred embodiment of the invention, the computing device 31 of FIG. 7 further comprises an alert module 43. This alert module, operationally connected to the data analysis module 37, is suitable for signaling the presence of an anomaly in a tank 5, for example in the form of a visual or audible alert sent to an operator. For example, when the module data analysis 37 detects an anomaly in a tank 5, an alert message can be sent to an operator.

According to a preferred embodiment of the invention, the computing device 31 also comprises a user interface 45. The user interface 45 is configured to allow functional management of the temperature sensor 23 and the pressure sensor 25, as well as other elements of the anomaly detection system 21. For example, the user interface can include functions for stopping and starting the anomaly detection system 21 , allowing the starting or stopping of the system and/or taking temperature and pressure measurements in the tank.

The user interface 45 is operationally connected to the alert module 43 and is further configured to control said alert module 43. In certain embodiments, the alert module 43 is further adapted to the generation of one when an alert threshold is crossed. These alert thresholds can be created or managed from the user interface 45. The alert thresholds can include: a minimum and/or maximum volume of the gas cushion 11, a minimum and/or maximum temperature of the gas cushion, and a minimum and/or maximum pressure of the gas cushion 11. Other alert thresholds can also be defined. Alert thresholds can be configured automatically or manually, depending on the achievements. For example, alert thresholds can be automatically generated when the detection system 21 is installed on a certain type of sealed tank 5.

[0064] Furthermore, according to a preferred embodiment of the invention, the user interface 45 is also configured to allow selection of the type of alert desired. For example, the user interface 45 allows configuration of audio and/or visual alerts, the visual alert being able to be displayed by the user interface 45, for example, and alternatively or additionally allows the configuration of textual alerts sent to a device cellular, in emails, or with various possible means of communication in order to inform a competent person of the triggering of the alert.

According to a preferred embodiment of the invention, the user interface 45 is also configured to allow historical and/or real-time visualization of the temperature, pressure and volume of the gas cushion 11 in the tank 5. Thus, the user interface 45 is operationally connected to the database 35, where the data associated with the temperature and pressure measurements and where the volume values are recorded, allowing access to this data for display/analysis.

In a preferred embodiment, the Grafana® user interface is used, this interface being configured for consulting data from the InfluxDB® database using a web interface. However, in other embodiments, a different user interface, for example using an application installed on the computing device, can be used without departing from the present disclosure.

In the preferred embodiment of Figs. 3 to 7, the data coming from the data acquisition module 33 are transmitted to the computing device 31 by additional wired and/or Wi-Fi® communication means. However, in other embodiments, several means of communication, such as a cellular network, a smart meter, or power line communication, can be used for the transfer of measurements and/or data between the various modules of the system. . Other means of communication can also be envisaged according to the needs related to the place of installation of the anomaly detection system 21, for example.

[0068] Still referring to Figs. 3 to 7, there will be described below a preferred method for detecting at least one anomaly in the sealed tank 5 containing a gaseous cushion 11, a volume of a liquid electrical insulator 9 and an electrical apparatus 7, at the help of the system for the detection of said at least one anomaly 21.

The method includes a step of capturing, as a function of time, pressure measurements of the gas cushion 11. For example, a pressure measurement can be captured at each interval of seconds, minutes or hours, or at a determined time. daily. The method also comprises capturing, preferably at times similar to the capture of the pressure measurements, temperature measurements of the gas cushion 11. The method then comprises determining at least a value of a volume of the gas cushion 11 from the associated data pressure measurements and temperature measurements. Thus, a volume value can be determined at each given time when a temperature measurement and a temperature measurement pressure are captured. The method then comprises detecting said at least one anomaly in the sealed vessel from any combination of data associated with pressure measurements, data associated with temperature measurements, and/or volume values of the step.

According to a preferred embodiment of the invention, the method further comprises a step of transmitting the data associated with the pressure measurements of the gaseous cushion 11, and a step of transmitting the data associated with the temperature measurements of the gaseous cushion 11, to the computer device 31 operationally connected to the temperature sensor 23 and to the pressure sensor 25 by the communication means 27a and 27b.

Experiment results

Some experiments were carried out in order to validate and verify the operation of the anomaly detection system 21. During one of these experiments, an anomaly detection system 21 was installed on an ONAN electrical transformer ( Oil Natural Air Natural) of the Siemens brand, having the following characteristics: nominal power 500kVA, primary 25kV three-phase, secondary 600V three-phase, volume of oil of 995L, and volume of the gas cushion of 248 L. As part of the experiment, an oil leak was deliberately induced to assess the operation of system 21. Detection system 21 was installed as shown in Figs. s 3 to 7.

[0072] Referring to Figure 8, a graph is presented containing the raw experimental data 51 , i.e. air volume values in the tank, to which the various smoothing methods described above are applied in order to obtain curves smoothed. In this test, the Siemens transformer tank is used, from which the oil is allowed to leak at the rate of 1.5 L/h. The curve obtained with the FFT method gives a good general trend, but is rather insensitive to particular events, such as the stoppage of a leak or the restarting of the leak. The curve obtained with the percentile mean method gives results similar to the FFT method while fluctuating more significantly at ends of a measurement period, either when the system is switched on or when it is switched off. The curve obtained with the adjacent mean method generally adequately follows the profile related to the various events that may occur, for example the start or stop of an oil leak, while also fluctuating at the ends of a period of measures. According to a preferred aspect, the curve obtained with the Savitzky-Golan method gives a good general trend.

In another test carried out according to the parameters defined previously, a valve present at the bottom of the tank is opened then closed to cause the flow of the oil contained in the tank. Temperature measurements and pressure measurements were captured periodically over a period of time. The anomaly detection system then determined values for the volume of the gas cushion in the tank for each periodicity during this same period, based on these measurements. Referring to FIG. 9, the raw experiment data 51 included a variation not indicative of the presence of an anomaly, and the data smoothing sub-module 41 applied a data smoothing method to enable detection of a variation of the volume resulting from a potential leak. Different smoothed curves are shown in Fig. 9, according to the smoothing methods presented above.

Initially, the smoothed curves are constant in a period 55 during which there is no oil leak. The smoothed curves then increase when the valve is opened and oil flows, which is expected. Indeed, a decrease in the volume of the oil has the effect of increasing the volume of the gas cushion in the tank. The smoothed curves also grow more pronounced when the leak rate is greater, i.e. during period 56 between 11:42 and 12:10 (flow rate of 775 ml/min), than when the leak rate is lower. , i.e. during period 58 between 12:17 and 13:07. In addition, the values of the volume of the gas cushion form a plateau when the valve is closed, i.e. during the period 57 between 12:10 and 12:17. The anomaly detection system therefore reacts well to transitions between a normal state and an abnormality.

[0075] Several alternative embodiments and examples have been described herein. These embodiments are given by way of example only. A person skilled in the art will be able to recognize that any combination of the accomplishments described could be provided. Moreover, it will be understood that the embodiments described here are not limiting and that other particular embodiments can be achieved without departing from the main characteristics of the invention described. The invention should therefore not be considered limited to the details given here.

[0076] In addition, it will be understood that some of the modules described above can be implemented in the form of applications or computer programs. In these embodiments, the system then comprises a non-volatile memory suitable for storing instructions that can be executed by a processor or a computer. The instructions, when executed by the process, perform steps associated with the modules described in this application.

Claims

1. A system for detecting at least one anomaly in a sealed tank containing a gaseous mattress, the system comprising: at least one pressure sensor adapted to perform pressure measurements of the gaseous mattress, said at least one pressure sensor being in contact with the gas mattress; at least one temperature sensor adapted to perform temperature measurements in the gaseous mattress, said at least one temperature sensor being in contact with the gaseous mattress; communication means configured to transmit data associated with the pressure measurements and the temperature measurements; and at least one computing device operatively connected to said at least one pressure sensor and to said at least one temperature sensor by the communication means, the at least one computing device comprising a data analysis module configured to: determine at least a value of a volume of the gas cushion from the data associated with the pressure measurements and the temperature measurements; and detecting the presence of said at least one anomaly in the tank from the at least one value of the volume of the gaseous cushion, the data associated with the pressure measurements of the gaseous cushion, and/or the data associated with the temperature measurements of the gas mattress.

2. The system according to claim 1, wherein the at least one computing device further comprises a data acquisition module configured to acquire the data associated with the pressure measurements and the temperature measurements transmitted by the communication means, and wherein the analysis module is operatively connected to the acquisition module.

3. The system according to claim 1 or 2, in which the at least one value of the volume of the gaseous cushion is calculated according to the following formula:

where P is a reference pressure of the gas cushion, V ₁ is a reference volume of the gas cushion and 7 is a reference temperature of the gas cushion; and where P ₂ is data associated with a pressure measurement of the gas cushion and T ₂ is data associated with a temperature measurement of the gas cushion.

4. The system according to any one of claims 1 to 3, wherein the at least one computing device is further configured to: determine a new value of the volume when new data associated with the temperature measurements and the pressure measurements are available; and detecting said at least one anomaly from a variation between the new volume value and at least one historical volume value previously determined.

5. The system according to any one of claims 1 to 4, wherein the data analysis module further comprises a data smoothing module configured to attenuate noise in the at least one volume value, the noise being associated with pressure measurements and/or temperature measurements.

6. The system according to claim 5, wherein the noise in the at least one volume value includes a phase shift between the pressure measurements and the temperature measurements.

7. The system according to claim 5 or 6, wherein the data smoothing module is configured to use at least one method selected from a group consisting of: an adjacent mean method, a Savitzky-Golay method, a percentile filter method, and an FFT filter method.

8. The system according to any one of claims 1 to 7, in which the communication means comprise a set of components, parts and/or electronic chips configured to: condition signals representative of the data associated with the temperature measurements and the measurements depression; and transmitting the signals representative of the data associated with the temperature measurements and the pressure measurements to said at least one computing device.

9. The system according to claim 8, in which the communication means are further configured to transmit the signals representative of the data associated with the temperature measurements and the pressure measurements by wireless transmission.

10. The system according to any one of claims 1 to 9, wherein said at least one computing device further comprises an alert module configured to generate an alert following detection of said at least one anomaly.

11. The system of claim 10, wherein the alert module is further configured to generate an alert when at least one alert threshold is crossed, said at least one alert threshold being selected from a group consisting by: a minimum volume of the gas cushion, a maximum volume of the gas cushion, a minimum pressure of the gas cushion, a maximum pressure of the gas cushion, a minimum temperature of the gas mattress, and a maximum temperature of the gas mattress.

12. The system according to any one of claims 1 to 9, wherein the system further comprises a user interface configured to perform at least one function selected from a group consisting of: a function for displaying the at least one value the volume of the gas mattress; and a functional management function comprising at least one startup procedure and one shutdown procedure of said at least one pressure sensor and of said at least one temperature sensor.

13. The system according to claim 10 or 11, in which the system further comprises a user interface configured to perform at least one function selected from a group consisting of: a function for displaying the at least one value of the volume of the mattress gaseous; an alert threshold management function; and a functional management function comprising at least one startup procedure and one shutdown procedure of said at least one pressure sensor and of said at least one temperature sensor.

14. The system according to any one of claims 1 to 13, wherein said at least one computing device further comprises a deep learning module configured to: analyze the at least one value of the volume of the gaseous cushion, the data associated with gas blanket temperature measurements and/or data associated with gas blanket pressure measurements; and automatically detecting said at least one anomaly.

15. The system according to any one of claims 1 to 14, wherein the data associated with the pressure measurements and the temperature measurements includes time indications indicative of a time when each of said pressure measurements and temperature measurements were carried out.

16. The system according to any one of claims 1 to 15, wherein said at least one computing device further comprises a database allowing storage of at least one volume value, data associated with temperature measurements and data associated with the pressure measurements.

17. The system according to any one of claims 1 to 16, wherein said at least one temperature sensor is a thermocouple rod installed so as to be in contact with the gas cushion.

18. The system according to any one of claims 1 to 17, wherein said at least one pressure sensor is an absolute pressure sensor.

19. The system according to any one of claims 1 to 18, wherein: the sealed vessel further contains a volume of a liquid, and at least a portion of the gas cushion rests on at least a portion of the volume of the liquid.

20. The system according to any one of claims 1 to 19, wherein said at least one anomaly is a leak and/or a problem affecting the at least one gas cushion volume value, the gas cushion pressure measurements , and/or the temperature measurements of the gas blanket.

21. The system according to claim 19, wherein said at least one anomaly is a liquid leak and/or an electrical problem of at least one piece of equipment at least partially submerged in the liquid, the electrical problem affecting the values of the volume of the gas mattress, the pressure measurements of the gas mattress, and/or the temperature measurements of the gas mattress.

22. A method of detecting at least one anomaly in a sealed vessel containing a gas blanket, the method comprising: capturing, with at least one pressure sensor, pressure measurements of the gas blanket; capturing, with at least one temperature sensor, temperature measurements of the gas blanket; determining, by a processor, at least one value of a volume of the gaseous cushion from data associated with the pressure measurements and data associated with the temperature measurements; and detecting, by the processor, said at least one anomaly in the sealed vessel from the at least one value of the volume of the determined gas cushion, data associated with the pressure measurements, and/or data associated with the temperature measurements .

23. The method according to claim 22, further comprising: transmitting, by means of communication, signals representative of the data associated with the pressure measurements and the data associated with the temperature measurements; and acquire, by an acquisition module operationally connected to the processor, the data associated with the pressure measurements and the data associated with the temperature measurements from the signals transmitted by the communication means.

24. The method according to claim 22 or 23, in the at least one value of the volume of the gas cushion is calculated according to the following formula:

where P is a reference pressure of the gas cushion, V ₁ is a reference volume of the gas cushion and 7 is a reference temperature of the gas cushion; and where P ₂ is a pressure measurement of the gaseous mattress and T ₂ is a temperature measurement of the gaseous mattress.

25. The method according to any one of claims 22 to 24, further comprising attenuating noise associated with pressure measurements and/or temperature measurements.

26. The method of claim 25, wherein noise attenuation comprises using a method selected from a group consisting of: an adjacent mean method, a Savitzky-Golay method, a percentile filter method, and an FFT filter method. .

27. The method of claim 23, wherein transmitting signals includes conditioning signals representative of data associated with pressure measurements and data associated with temperature measurements.

28. The method according to any one of claims 22 to 27, further comprising generating at least one alert following the detection of said at least one anomaly in the sealed tank.

29. The method according to any one of claims 22 to 27, further comprising generating at least one alert when at least one alert threshold is crossed, said at least one alert threshold being selected from a group consisting of a minimum volume of the gas mattress, a maximum volume of the gas mattress, a minimum pressure of the gas mattress, a maximum pressure of the gas mattress, a minimum temperature of the gas mattress, and a maximum temperature of the gas mattress.

30. The method according to any one of claims 22 to 29, further comprising at least one step selected from a group consisting of: displaying, with a user interface, a historical and/or real-time volume of the gas cushion; managing, with the user interface, said at least one pressure sensor and said at least one temperature sensor, or managing said at least one pressure sensor and said at least one temperature sensor comprises at least a start-up step and a stop step.

31. The method according to claim 29, further comprising at least one step selected from the group consisting of: displaying, with a user interface, a historical and/or real-time volume of the gas cushion; manage, with the user interface, the thresholds of at least one alert; and managing, with the user interface, said at least one pressure sensor and said at least one temperature sensor, where managing said at least one pressure sensor and said at least one temperature sensor comprises at least a step of starting and a stop step.

32. The method according to any one of claims 22 to 31, further comprising: analyzing, by a deep learning module, the at least one value of the volume of the gaseous cushion, the data associated with the temperature measurements and/or or data associated with pressure measurements; and detecting, with the deep learning module, said at least one anomaly.

33. The method according to any one of claims 22 to 32, further comprising storing, in a database, the data associated with the temperature measurements and the pressure measurements.

34. The method according to any one of claims 22 to 33, in which detecting said at least one anomaly comprises detecting at least one leak and/or a problem affecting the at least one value of the volume of the gas cushion, the data associated the pressure measurements of the gas blanket, and/or the data associated with the temperature measurements of the gas blanket.

35. A use of the system defined in any one of claims 1 to 21 for the detection of at least one anomaly in a sealed tank containing a gas cushion.

36. A use of the system defined in any one of claims 1 to 21 for the detection of at least one anomaly in a sealed tank of an electrical transformer containing a volume of a liquid and a gaseous mattress, at least one part of the gas cushion resting on at least part of the volume of the liquid.