Method and system for monitoring electrical installations

Abstract

A method for monitoring an electrical facility comprises the following steps: measuring (102) a current flowing through the facility and a temperature value at a predefined location in the facility while the facility is in operation; calculating (106) a numerical index representing a thermal characteristic of the facility based on a difference between the measured temperature value and a corresponding temperature value estimated from the measured current value using a pre-acquired numerical model; and detecting (110) a thermal anomaly when the calculated numerical index differs from a reference value.

Description

Technical Field

[0001] The present invention relates to a method and a system for monitoring electrical installations.

[0002] The invention relates more particularly to electrical distribution installations such as electrical cabinets and electrical switchboards, in particular in the low voltage field, although this example is not limiting and other applications are possible.

[0003] In practice, the present invention is applicable to any electrical installation. Background Art

[0004] In many commercial, domestic, and industrial settings, electricity from an energy supply is distributed to end users via one or more distribution facilities.

[0005] Typically, such facilities are the subject of regular inspection visits and preventive maintenance operations aimed at detecting and correcting any defects that may prevent the correct operation of the facility.

[0006] For example, during such visits, it is common practice to use specific measuring methods (such as infrared cameras) to search for thermal defects (such as hot spots) that may occur at connections between conductive elements through which high currents flow and could be the source of fire or major safety issues.

[0007] However, maintenance methods are not entirely satisfactory. On the one hand, the inspection intervals are usually separated in time and it is not possible to report sudden changes (such as failures) that may have harmful consequences in a very short time. On the other hand, these methods are sometimes lengthy and complex to implement.

[0008] Furthermore, such inspections require opening all or part of the electrical cabinet housing the electrical installation (it should be understood that the electrical installation is typically protected from direct environmental influences by normally closed doors or hatches), which introduces heat exchanges during the inspection that are not representative of actual operating conditions, complicating the interpretation of the measurement data.

[0009] Therefore, there is a need for a method and apparatus that can monitor electrical installations, particularly to continuously detect thermal anomalies during operation. Summary of the Invention

[0010] Thus, according to one aspect, a method for monitoring an electrical installation comprises:

[0011] When the facility is in operation, measuring over time a current flowing through the facility and a temperature value at a predefined location in the facility by means of a current sensor and a temperature sensor respectively arranged in the facility;

[0012] automatically calculating, by means of an electronic data processing device and using a previously acquired numerical model, a numerical index representing the thermal characteristics of the installation from the difference between the measured temperature values ​​and the corresponding temperature values ​​estimated from the measured current values ​​with the aid of said model;

[0013] When the calculated numerical index is different from the reference value, thermal abnormality is detected by the electronic processing device.

[0014] The ability to detect thermal anomalies in a facility allows for rapid identification of defects or situations that could lead to defects that could endanger the facility's safety. This detection occurs continuously while the facility is operating. This allows for a robust response and is simple to implement, without requiring the use of specially qualified personnel.

[0015] According to an advantageous but non-mandatory aspect, this method may combine one or more of the following features, alone or in any technically permissible combination:

[0016] The numerical model represents thermal characteristics of the electrical installation and is configured to relate current values ​​measured by the current sensor to temperature values ​​estimated at locations where the temperature sensor is located. The numerical model is pre-parameterized by learning the electrical installation.

[0017] The relationship between the temperature estimated at one of the locations and the current value measured in the facility is given by the following formula:

[0018] [Mathematical formula]

[0019]

[0020] where θ t i represents the estimated temperature at the location at a given moment, θ t-1 i denotes the temperature estimated for the same location at the previous moment, “n” is the statistical noise associated with the temperature sensors at that moment, “m” is the number of current sensors, “L” is the duration of the measurement window, “P” is the thermal power that depends on the measured current, and “α” and “β” are parameters of the numerical model.

[0021] The method comprises a preliminary step of parameterizing the numerical model, which includes the following operations:

[0022] When the device is in operation, a current flowing through a conductor of the facility and a temperature value at a predefined location in the facility are measured over time by means of a current sensor and a temperature sensor, respectively, arranged in the facility;

[0023] The parameters of the model are calculated based on the measured current and temperature values.

[0024] Calculating the parameters of the model includes the following operations: The operation consists of minimizing, for each pair of current and voltage sensors, the mean square error given by the following formula based on a training data set derived from the facility and where the facility has not experienced anomalies:

[0025] [Mathematical formula]

[0026]

[0027] Among them, θ t i represents the estimated temperature at the location at a given moment, θ t-1 i denotes the temperature estimated for the same location at the previous moment, “n” is the number of temperature sensors, “m” is the number of current sensors, “L” is the duration of the measurement window, “P” is the thermal power depending on the measured current, and α and β are parameters of the numerical model.

[0028] The method further includes the step of sending an alarm message when a thermal anomaly is detected.

[0029] The calculation of the numerical index and the detection of anomalies are performed by an electronic data processing device in a remote computer server, and wherein the method comprises the step of transmitting the measured data to the electronic data processing device via an electrical communication link.

[0030] The temperature sensor and the current sensor are coupled to a data concentrator configured to transmit the measured data to the electronic control device via an electrical communication link.

[0031] According to another aspect, the present invention relates to a monitoring system for an electrical installation, the system comprising a plurality of current sensors arranged in the installation and an electronic data processing device, the monitoring system being configured to implement a method comprising the following steps:

[0032] When the facility is in operation, measuring over time a current flowing through the facility and a temperature value at a predefined location in the facility by means of a current sensor and a temperature sensor respectively arranged in the facility;

[0033] automatically calculating, by means of an electronic data processing device and using a previously acquired numerical model, a numerical index representing the thermal characteristics of the facility from the difference between the measured temperature values ​​and the corresponding temperature values ​​estimated from the measured current values ​​with the aid of said model;

[0034] When the calculated numerical index is different from the reference value, thermal abnormality is detected by the electronic processing device.

[0035] According to another aspect, the invention relates to an electrical installation comprising a monitoring system as described above. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The invention will be better understood and further advantages will become more apparent from the following description of an embodiment of the method, given by way of example only, with reference to the accompanying drawings, in which:

[0037] Figure 1 is a block diagram of a power distribution facility including a monitoring device according to an embodiment;

[0038] Figure 2 is Figure 1 Block diagram of the model used by the monitoring equipment;

[0039] Figure 3 According to the embodiment Figure 1 Flowchart of the monitoring method implemented by the monitoring device. DETAILED DESCRIPTION

[0040] Reference Figure 1 , an electrical installation 2, such as a power distribution installation, is shown.

[0041] In this example, the installation 2 is arranged in an electrical cabinet 4 or container.

[0042] For example, the installation 2 comprises a set of busbars 6 comprising electrical conductors connected to each other by means of bolts, screws, connecting members or connectors.

[0043] The installation 2 may also comprise one or more electrical units, such as electrical protection units or switching units, or measuring units.

[0044] In this example, the installation 2 comprises four such units, which are referenced 8, 10, 12 and 14. This example is not limiting and many other configurations are possible.

[0045] For example, the unit may be a circuit breaker, a contactor, a fuse holder, a relay, a disconnector, a switch or any equivalent unit.

[0046] Generally, embodiments of the present invention may be implemented in any electrical installation, not just electrical distribution installations.

[0047] In the illustrated example, the first electrical conductor 16 carries power from an external source. The second electrical conductor 18 is connected to the first conductor 16 and third conductors 20, 22, and 24 to distribute power to appliances located downstream of the facility 2 via these third conductors 20, 22, and 24.

[0048] For example, protection unit 8 is associated with second conductor 18, and protection units 10, 12, and 14 are associated with third conductors 20, 22, and 24, respectively.

[0049] This example is not limiting, and many other architectures and configurations are possible herein.

[0050] The facility 2 also includes a monitoring system, and more specifically, the monitoring system is configured to detect thermal anomalies in the facility 2 .

[0051] For example, a thermal anomaly here means a temporal drift of at least one or several thermal characteristics of the installation 2 , which thermal characteristics can be temperature values ​​at precise locations of the installation 2 .

[0052] In practice, such thermal excursions usually indicate a defect of electrical origin, or a sudden failure of a component, or a defect of mechanical origin, such as a poorly connected electrical connection, for example a poorly tightened bolt or screw at an electrical connection, or any other defect that may be detrimental to the correct functioning of the installation.

[0053] Such thermal drift may also indicate a change in the behavior of an aging component, or a change in the heat exchange characteristics caused by the accumulation of foreign matter, such as dust, or the blockage of cooling holes.

[0054] In many embodiments, its components can be found in Figure 1 The monitoring system includes a plurality of current sensors, represented here as C1, C2, C3, C4 and C5, a plurality of temperature sensors, represented here as T1, T2, T3, T4, T5, T6, and an electronic data processing device 32. The number of temperature and / or current sensors is not limited and may vary without changing the principles of the present invention.

[0055] The current and temperature sensors can be based on conventional technology. For example, the current sensor is a measuring torii such as a Rogowski sensor. The temperature sensor can be a thermocouple or any other suitable sensor technology.

[0056] In the illustrated example, two current sensors C1 and C2 are placed on the first conductor 16 , upstream and downstream of the connection point with the second conductor 18 , and one current sensor C3 , C4 , C5 is associated with each of the third conductors 20 , 22 and 24 .

[0057] Still in the illustrated example, two temperature sensors T1 and T2 are associated with the first conductor 16, upstream and downstream of the connection point with the second conductor 18, a temperature sensor T3 is associated with the second conductor 18 upstream of the connection point of the third conductors 20, 22 and 24, and temperature sensors T4, T5, T6 are associated with the third conductors 20, 22 and 24, respectively.

[0058] This example is not limiting, and many other configurations are possible.

[0059] Optionally, the monitoring system may include a data concentrator 30 coupled to the temperature and current sensors, the function of which is to collect data measured by the temperature and current sensors and send these data to a processing device 32, particularly when the processing device 32 is placed away from the electrical cabinet 4 and / or is not directly connected to the sensors.

[0060] For example, the concentrator 30 comprises a first communication interface programmed to receive data from the sensor, for example via a wired link or a wireless link (preferably a short-range radio link). The concentrator 30 also comprises a second communication interface programmed to transmit the measured data to the processing device 32, for example via a wired link or a wireless link, for example via the Internet or a long-range radio link, or via a 3G, 4G or 5G type telecommunication network, or any other similar means.

[0061] In many embodiments, the processing device 32 includes a processor and memory. For example, the processor is a programmable microcontroller or microprocessor.

[0062] The memory is preferably a computer memory forming a computer-readable data storage medium. For example, the memory comprises ROM memory, RAM memory, non-volatile memory of the EEPROM type, flash memory or any equivalent means.

[0063] The memory comprises executable instructions and / or software codes which, when executed by the processor, implement the method for monitoring the installation 2 as described below.

[0064] As a variant, the processing device 32 may be implemented by a programmable logic component of the FPGA type or an application-specific integrated circuit configured to implement the monitoring method.

[0065] Typically, the monitoring system is specifically configured to implement a method comprising the following steps:

[0066] When the installation is in operation, measuring over time the current flowing through the installation conductors and the temperature values ​​at predetermined locations in the installation by means of current sensors C1, C2, C3, C4, C5 and temperature sensors T1, T2, T3, T4, T5, T6 respectively, previously arranged in the installation;

[0067] automatically calculating, by means of an electronic data processing device 32 and using a previously acquired numerical model, a numerical index representing the thermal characteristics of the installation from the differences between the measured temperature values ​​and the corresponding temperature values ​​estimated from the measured current values ​​by means of the model,

[0068] When the calculated numerical index is different from the reference value, thermal abnormality is detected by the electronic processing device.

[0069] Preferably, if Figure 2The numerical model denoted as M, schematically shown in FIG, represents the thermal characteristics of the electrical installation and is configured to convert the current values ​​measured by the current sensors C1, C2, C3, C4, and C5 (collectively referred to as I mes ) and the estimated temperature values ​​at the locations of temperature sensors T1, T2, T3, T4, T5, and T6 (collectively referred to as T est ) is associated with.

[0070] In other words, the model M is an estimate of the transfer function that links, for each instant, the temperature at the different locations of the installation with the current value at the same instant and with the temperature value at the immediately preceding measurement instant.

[0071] In a first approximation, the model M can be a linear model considering only a first-order heat exchanger, with higher-order nonlinear contributions due to convection, conduction or radiation phenomena possibly initially neglected.

[0072] Preferably, the measurement is performed repeatedly for a plurality of discrete moments in time or for a time window with a predefined duration.

[0073] The measurements may be repeated regularly or periodically with a predefined period.

[0074] According to a preferred embodiment, on the one hand, at a given time (time "t"), an estimated temperature θ at a location t i On the other hand, the relationship between the current value measured at this moment and the temperature value at the previous moment in the facility is given by the following formula:

[0075] [Mathematical formula]

[0076]

[0077] in:

[0078] θ t-1 i represents the temperature estimated for the same location at the previous moment (time “t-1”),

[0079] “n t ” is the statistical noise associated with the temperature sensor at that moment,

[0080] "m" is the number of current sensors,

[0081] "L" is the duration of the measurement window,

[0082] "P" is the thermal power that depends on the measured current, more specifically the square of the measured current,

[0083] "α" and "β" are parameters of the numerical model, and

[0084] "k" and "l" are the indices used for summation.

[0085] For example, the model M may be represented in the form of a matrix having n rows ("n" is the number of temperature sensors) and m columns, and its coefficients are numerical values.

[0086] Advantageously, the numerical model M is parameterized beforehand by learning the electrical installation. The appropriately parameterized model is then stored in a memory of the device 32 .

[0087] For example, before starting to monitor the installation 2, a preliminary step of parameterization of the numerical model is performed, which includes the following operations:

[0088] When the device is in operation, the current flowing through the conductors of the facility and the temperature values ​​at predefined locations in the facility are measured over time by means of current sensors C1, C2, C3, C4, C5 and temperature sensors T1, T2, T3, T4, T5, T6 respectively arranged in the facility;

[0089] The parameters of the model are calculated based on the measured current and temperature values.

[0090] For example, calculating the parameters of the model includes the following operation: the operation includes, for each pair of current sensor and voltage sensor, minimizing the mean square error given by the following formula based on a training data set derived from the facility and the facility has not experienced anomalies:

[0091] [Mathematical formula]

[0092]

[0093] in:

[0094] θ t i represents the temperature estimated at a given moment for the location indexed by index "i",

[0095] θ t-1 i represents the temperature estimated for the same location at the previous moment,

[0096] "n" is the number of temperature sensors,

[0097] "m" is the number of current sensors,

[0098] "L" is the duration of the measurement window,

[0099] "P" is the thermal power that depends on the current being measured, and,

[0100] "α" and "β" are parameters of the numerical model, and

[0101] "k" and "l" are the indices used for summation.

[0102] a k,l β k,l are the parameters of the numerical model, here corresponding to the coefficients of the matrix associated with the model M (e.g., the coefficients of the k-th column and the i-th row).

[0103] The ability to detect thermal anomalies in a facility, thanks to the present invention, allows for rapid identification of defects or situations that could lead to defects that could endanger the facility's safety. This detection occurs continuously while the facility is operating. This allows for a robust response and is simple to implement, without requiring the use of specially qualified personnel.

[0104] Because the numerical model is constructed using a learning phase performed on the facility, the method can be deployed on any type of facility without manual parameterization. Instead, during the learning phase, the model automatically adapts to the specifics of the facility. In other words, the learning phase allows the construction of a model based on an operating sequence used as a reference (since it is guaranteed that the facility did not experience any defects during that period), from which deviations from the norm can be identified.

[0105] refer to Figure 3 , an embodiment of a method for monitoring an installation 2 is described.

[0106] However, as a variation, these steps can be performed in a different order. Certain steps can be omitted. In other embodiments, the described examples do not exclude other steps combined with the described steps and / or other steps implemented after the described steps.

[0107] The method starts at step 100. For example, before step 100, a parameterized model M as a function of specific parameters of the installation 2 has been previously acquired.

[0108] In step 102, the current flowing through the conductors of the facility and the temperature values ​​at predefined locations in the facility are measured over time by means of current sensors C1, C2, C3, C4, C5 and temperature sensors T1, T2, T3, T4, T5, T6 respectively arranged in the facility. As mentioned above, the measurements can be repeated in time.

[0109] Optionally, in step 104 , the data measured by the sensors are transmitted to the electronic data processing device 32 via an electrical telecommunication link.

[0110] This step is performed, for example, when the device 32 is remote from the electrical cabinet 4 , for example when the device 32 forms part of a remote computer server.

[0111] In step 106 , the device 32 automatically calculates a numerical index representative of the thermal properties of the installation based on the difference between the measured temperature value and the corresponding temperature value estimated from the measured current value by means of the model.

[0112] For example, the index represents the difference between the temperature measured by the sensor at each instant and the corresponding temperature estimated for these instants by means of the model, the estimation being carried out from the measured current and the temperature estimated for the previous instant.

[0113] As an example for illustrative purposes, the numerical index is chosen to be equal to the product of the distance between the measured temperature and the estimated temperature, this distance being adjusted by the correlation estimated at the end of the parameterization phase and the correlation estimated on the validation signal after the learning phase. In other words, here, the model is built in the learning phase based on the main part of the measured data (for example, 75% of these data), and then the model is validated using data different from those used to build the model (for example, the remaining 25% of the data).

[0114] This example is not limiting and other numerical indices or scores or metrics may be chosen as alternatives.

[0115] In step 108 , the system 32 automatically compares the calculated numerical index or score to one or more reference values.

[0116] For example, thresholds that are considered to correspond to normal operation may be predefined.

[0117] If the calculated score lies outside the interval, the facility 2 is deemed to exhibit abnormal driving (step 110 ). The reference value or values ​​may be pre-stored in a memory of the device 32 .

[0118] As a variant, only one threshold value may be defined. If the calculated score is then above (or, in other examples, below) the threshold value, it is considered that an abnormal drift has occurred (step 110).

[0119] According to a variant, a comparison can be performed on the history of the calculated scores (step 108), and if the score remains outside the normal value range (or above or below a threshold value) for a sufficiently long period of time, it is considered that an abnormal situation has occurred, thereby avoiding false alarms due to sudden and unexpected changes.

[0120] Optionally, the method may include the step of sending an alarm message when a thermal anomaly is detected. In the example shown, the message is sent at step 110 .

[0121] If no anomaly is detected (step 112 ), the method continues, for example by repeating steps 102 to 108 described previously.

[0122] Any feature of one of the above-described embodiments or variations can be implemented in the other described embodiments and variations.

Claims

1. A method for monitoring an electrical installation (2), comprising the following steps: When the facility is in operation, measuring (102) over time the current flowing through the facility and the temperature values ​​at predefined locations in the facility by means of current sensors (C1, C2, C3, C4, C5) and temperature sensors (T1, T2, T3, T4, T5, T6) arranged in the facility, respectively; automatically calculating (106) by means of an electronic data processing device (32) and using a previously acquired numerical model (M) a numerical index representing the thermal characteristics of the installation from the difference between the measured temperature values ​​and the corresponding temperature values ​​estimated by means of the model from the measured current values; When the calculated numerical index is different from the reference value, a thermal anomaly is detected (110) by an electronic processing device, The numerical model (M) represents the thermal characteristics of the electrical installation and is configured to convert the current value (I mes ) and the estimated temperature value (T est ), said numerical model being pre-parameterized by learning the electrical installation, wherein the relationship between the temperature estimated for one of the locations and the current value measured in the facility is given by the following formula: [Mathematical formula] Among them, θ t i represents the estimated temperature at a given time for a location, θ t-1 i represents the temperature estimated for the same location at the previous moment, "n" is the statistical noise associated with the temperature sensors at said moment, "m" is the number of current sensors, "L" is the duration of the measurement window, "P" is the thermal power depending on the measured current, and "α" and "β" are parameters of said numerical model; The method further comprises a preliminary step of parameterizing the numerical model, which comprises the following operations: When the device is in operation, measuring over time the current flowing through the conductors of the installation and the temperature values ​​at predefined locations in the installation by means of current sensors (C1, C2, C3, C4, C5) and temperature sensors (T1, T2, T3, T4, T5, T6) arranged in the installation, respectively; Calculating the parameters of the numerical model based on the measured current and temperature values, Calculating the parameters of the numerical model includes the following operations: the operation includes, for each pair of current sensors and voltage sensors, minimizing the mean square error given by the following formula based on a training data set derived from the facility and in which the facility has not experienced anomalies: [Mathematical formula] Among them, θ t i represents the estimated temperature at a given time for a location, θ t-1 i denotes the temperature estimated for the same location at the previous moment, “n” is the number of temperature sensors, “m” is the number of current sensors, “L” is the duration of the measurement window, “P” is the thermal power depending on the measured current, and α and β are parameters of the numerical model.

2. The method according to claim 1, further comprising the step of sending an alarm message when a thermal anomaly is detected (110).

3. A method according to any one of the preceding claims, wherein The calculation of the numerical index and the detection of anomalies are performed by electronic data processing equipment (32) in a remote computer server, and wherein the method includes the step of transmitting the measured data (104) to the electronic data processing equipment via a telecommunication link.

4. The method according to any one of claims 1 and 2, wherein The temperature sensor and the current sensor are coupled to a data concentrator (30) configured to transmit the measured data to an electronic control device via a telecommunication link.

5. A monitoring system for an electrical installation, comprising a plurality of current sensors (C1, C2, C3, C4, C5) and a plurality of temperature sensors (T1, T2, T3, T4, T5, T6) suitable for being arranged in the installation, and an electronic data processing device (32), the monitoring system being configured to implement the method according to any of the preceding claims.

6. Electrical installation (2) comprising a monitoring system according to the preceding claim.

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