CN219800139U - Transformer fault monitoring device - Google Patents
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- CN219800139U CN219800139U CN202223594893.6U CN202223594893U CN219800139U CN 219800139 U CN219800139 U CN 219800139U CN 202223594893 U CN202223594893 U CN 202223594893U CN 219800139 U CN219800139 U CN 219800139U
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Abstract
The utility model relates to a transformer fault monitoring device, which comprises: a transformer body; the device comprises a cabinet, wherein a discharge monitoring unit, a gas monitoring unit, a current monitoring unit, a voiceprint and vibration monitoring unit and an upper computer are respectively arranged on the cabinet; the discharge monitoring unit is connected with the upper computer and is used for monitoring the discharge fault information of the transformer body; the gas monitoring unit is connected with the upper computer and is used for monitoring the fault gas content information in the transformer body oil; the current monitoring unit is connected with the upper computer and is used for monitoring current fault information of the transformer body; the voiceprint and vibration monitoring unit is connected with the upper computer and is used for monitoring mechanical fault information of the transformer body. The upper computer fuses the multidimensional sensor data such as electricity, gas, sound, machinery, light, temperature and the like, extracts the characteristics of multidimensional information of the transformer body, can diagnose faults of the transformer body, predicts the health state of the transformer and pre-warns potential faults.
Description
Technical Field
The utility model relates to the technical field of transformer on-line monitoring and diagnosis, in particular to a transformer fault monitoring device.
Background
In recent years, with the rapid development of economic construction in China, the load and the total power consumption of the power system are continuously increased. If a power failure accident occurs, the daily production and the daily life are greatly influenced and lost, so that the stable operation of facilities and equipment of the power system is ensured, and the power system becomes an important work of the power system.
In an electric power system, an electric power transformer is a core device for power transmission and conversion of an electric network, and the operation state of the electric power transformer is closely related to the overall safety and stability of the electric power system. In the long-term operation process of the power transformer, the power transformer is subjected to the comprehensive effects and influences of voltage stress, thermal stress, mechanical stress, operation conditions, meteorological environment and other factors, so that various physical and chemical changes can occur inside and outside the power transformer, and various faults such as partial discharge, partial overheating and the like are likely to occur, and therefore the operation state of the power transformer is comprehensively and accurately mastered, and potential faults of the transformer are found in time to be important work for monitoring the transformer.
Some transformer monitoring systems in the current market are devices with single monitoring functions, the integration level of the monitoring functions is not high, and the monitoring system cannot comprehensively monitor the state of faults such as partial discharge and overheating in the transformer. Therefore, it is necessary to find a comprehensive and comprehensive transformer fault diagnosis system, to monitor the transformer on line through the multidimensional sensor, to obtain the comprehensive state information of the transformer, to accurately judge and locate the transformer fault in real time and to early warn some potential faults, to judge the health condition of the transformer, to provide basis for equipment maintenance, so as to ensure the stable operation of the transformer.
Disclosure of Invention
The utility model aims to provide a transformer fault monitoring device which is used for detecting partial discharge, gas in oil, grounding current, voiceprint vibration, double-light imaging respectively, acquiring multidimensional information such as electricity, gas, sound, machinery, light, temperature and the like, transmitting the multidimensional information to an upper computer, fusing multidimensional sensor data such as electricity, gas, sound, machinery, light, temperature and the like, extracting the characteristics of the multidimensional information of a transformer body, diagnosing faults of the transformer body, estimating the health state of the transformer, early warning some potential faults and providing basis for equipment maintenance.
Embodiments of the present utility model are implemented as follows:
in a first aspect, the present utility model provides a transformer fault monitoring device, including: a transformer body; the device comprises a cabinet, wherein a discharge monitoring unit, a gas monitoring unit, a current monitoring unit, a voiceprint and vibration monitoring unit and an upper computer are respectively arranged on the cabinet; the discharge monitoring unit is respectively connected with the transformer body and the upper computer and is used for monitoring discharge fault information of the transformer body and transmitting the discharge fault information to the upper computer; the gas monitoring unit is respectively connected with the transformer body and the upper computer and is used for monitoring the content information of fault gas in the transformer body oil and transmitting the content information to the upper computer; the current monitoring unit is respectively connected with the transformer body and the upper computer and is used for monitoring current fault information of the transformer body and transmitting the current fault information to the upper computer; the voiceprint and vibration monitoring unit is respectively connected with the transformer body and the upper computer and is used for monitoring mechanical fault information of the transformer body and transmitting the mechanical fault information to the upper computer.
In one embodiment, the discharge monitoring unit includes: the sensors are connected with the transformer body and are used for collecting the discharge frequency information and the discharge amplitude information of the transformer body; and the signal acquisition subunit is connected with the plurality of sensors and the upper computer and used for transmitting the discharge frequency information and the discharge amplitude information to the upper computer.
In one embodiment, the gas monitoring unit comprises: the gas separation subunit is communicated with the transformer body through a first pipeline; the gas detection subunit is communicated with the gas separation subunit through a second pipeline and is also connected with the upper computer.
In one embodiment, the current monitoring unit includes: the grounding current transformer is connected with the transformer body; and the current acquisition subunit is connected with the grounding current transformer and the upper computer.
In one embodiment, the voiceprint and vibration monitoring unit comprises: the vibration sensor is connected with the transformer body and is used for collecting frequency information and amplitude information of mechanical fault vibration signals of the transformer body; the microphone is arranged on the transformer body and is used for collecting frequency information and amplitude information of mechanical fault sound signals of the transformer body; and the vibration and sound acquisition subunit is connected with the vibration sensor and the microphone and is used for transmitting the frequency information and the amplitude information of the mechanical fault vibration signals and the frequency information and the amplitude information of the mechanical fault sound signals to the upper computer.
In an embodiment, the transformer fault monitoring device further includes: and the double-spectrum imaging unit is connected with the upper computer and is used for monitoring the transformer body.
In one embodiment, the dual spectrum imaging unit comprises: the infrared detection module is connected with the upper computer by a wire and/or a wireless; the infrared detection module includes: an infrared detection assembly; and the infrared thermal imaging processing assembly is connected with the infrared detection assembly.
In an embodiment, the dual spectrum imaging unit further comprises: the visible light detection module is connected with the upper computer by a wire and/or a wireless; the visible light detection module includes: a visible light sensor; and the visible light imaging processing assembly is connected with the visible light sensor.
In a second aspect, the present utility model provides a transformer fault monitoring system, which comprises a transformer fault monitoring device according to any one of the embodiments of the first aspect of the present utility model and a fault handling device, wherein the fault handling device is connected with the transformer fault monitoring device through a wire and/or a wireless.
In one embodiment, the fault handling apparatus includes: the data processing module is connected with the upper computer through a wire and/or a wireless; and the fault evaluation and prediction module is connected with the data processing module through a wire and/or a wireless.
Compared with the prior art, the utility model has the beneficial effects that: in the transformer fault monitoring device, the upper computer fuses the multidimensional sensor data such as electricity, gas, sound, machinery, light, temperature and the like, extracts the characteristics of multidimensional information of the transformer body, diagnoses faults of the transformer body, predicts the health state of the transformer, early warns some potential faults and provides basis for equipment maintenance.
The transformer fault monitoring system acquires state information of a transformer body through the multi-dimensional sensor and the monitoring equipment, and the multi-dimensional sensor information is fused and analyzed, and the fused multi-dimensional sensor data is synchronously sent to the deep learning unit, so that the deep learning unit is trained according to the artificial intelligent model, and the iterative expert experience unit is continuously updated, so that the diagnosis, evaluation and prediction capabilities of the transformer health diagnosis equipment are continuously improved.
Additional features and advantages of the utility model will be set forth in the detailed description which follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present utility model, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present utility model and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structural diagram of a transformer fault monitoring device according to an embodiment of the present utility model;
fig. 2 is a schematic diagram of a detailed structure of a transformer fault monitoring device according to an embodiment of the present utility model;
fig. 3 is a schematic structural diagram of a transformer fault monitoring system according to an embodiment of the present utility model.
Icon:
1-a transformer fault monitoring system; 11-a transformer fault monitoring device; 100-a transformer body; 200-of a cabinet; 300-a discharge monitoring unit; 310-a sensor; 311-an ultrahigh frequency sensor; 312-high frequency sensor; 313-ultrasonic sensor; 320-a signal acquisition subunit; 400-a gas monitoring unit; 410-a gas separation subunit; 420-a first pipeline; 430-a gas detection subunit; 440-a second line; 500-a current monitoring unit; 510-a ground current transformer; 520-a current collection subunit; 600-voiceprint and vibration monitoring unit; 610-vibration sensor; 620-a microphone; 630-a vibration and sound acquisition subunit; 700-a dual spectrum imaging unit; 710-an infrared detection module; 711-an infrared detection component; 712-an infrared thermal imaging processing assembly; 720-a visible light detection module; 721-a visible light sensor; 722—a visible light imaging processing component; 800-an upper computer; 12-fault handling means; 121-a data processing module; 1211-expert experience unit; 1212-a deep learning unit; 122—fault assessment and prediction module.
Detailed Description
The terms "first," "second," "third," and the like are used merely for distinguishing between descriptions and not for indicating a sequence number, nor are they to be construed as indicating or implying relative importance.
Furthermore, the terms "horizontal," "vertical," "overhang," and the like do not denote a requirement that the component be absolutely horizontal or overhang, but rather may be slightly inclined. As "horizontal" merely means that its direction is more horizontal than "vertical", and does not mean that the structure must be perfectly horizontal, but may be slightly inclined.
In the description of the present utility model, it should be noted that, directions or positional relationships indicated by terms such as "inner", "outer", "left", "right", "upper", "lower", etc., are based on directions or positional relationships shown in the drawings, or directions or positional relationships conventionally put in use of the product of the application, are merely for convenience of describing the present utility model and simplifying the description, and are not indicative or implying that the apparatus or element to be referred to must have a specific direction, be configured and operated in a specific direction, and thus should not be construed as limiting the present utility model.
In the description of the present utility model, unless explicitly stated and limited otherwise, the terms "disposed," "mounted," "connected," and "coupled" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements.
The technical solutions of the present utility model will be clearly and completely described below with reference to the accompanying drawings.
Referring to fig. 1, the present utility model provides a transformer fault monitoring device 11, comprising: the transformer body 100, the cabinet 200, and the cabinet 200 may be a multi-layered vertical cabinet, and the discharge monitoring unit 300, the gas monitoring unit 400, the current monitoring unit 500, the voiceprint and vibration monitoring unit 600, and the upper computer 800 are installed in each layer of the cabinet 200. The cabinet 200 is installed near the oil intake port of the transformer body 100 and is fixed on a base built of concrete or cement material. The discharge monitoring unit 300 is connected to the transformer body 100 and the upper computer 800, and is used for monitoring discharge fault information of the transformer body 100 and transmitting the discharge fault information to the upper computer 800; the gas monitoring unit 400 is respectively connected with the transformer body 100 and the upper computer 800, and is used for monitoring the fault gas content information in the oil of the transformer body 100 and transmitting the fault gas content information to the upper computer 800; the current monitoring unit 500 is respectively connected with the transformer body 100 and the upper computer 800, and is used for monitoring current fault information of the transformer body 100 and transmitting the current fault information to the upper computer 800; the voiceprint and vibration monitoring unit 600 is connected to the transformer body 100 and the host computer 800, respectively, and is used for monitoring mechanical failure information of the transformer body 100 and transmitting the mechanical failure information to the host computer 800.
For example, the upper computer 800 may be connected to the discharge monitoring unit 300, the gas monitoring unit 400, the current monitoring unit 500, and the voiceprint and vibration monitoring unit 600 by cables. The connection or arrangement of the discharge monitoring unit 300, the gas monitoring unit 400, the current monitoring unit 500, the voiceprint and vibration monitoring unit 600 and the transformer body 100 will be described in detail below.
Referring to fig. 2, the discharge monitoring unit 300 includes: the plurality of sensors 310 are connected to the transformer body 100 and are used for collecting the discharge frequency information and the discharge amplitude information of the transformer body 100. The signal acquisition subunit 320 is connected to the plurality of sensors 310 and to the host computer 800, and is used for transmitting the discharge frequency information and the discharge amplitude information to the host computer 800. The signal acquisition subunit 320 and the plurality of sensors 310 may be connected by using cables, and the signal acquisition subunit 320 and the upper computer 800 may be connected by using cable wired connection or wireless network communication connection.
In an embodiment, the sensor 310 includes an ultrahigh frequency sensor 311, a high frequency sensor 312, and an ultrasonic sensor 313, where the ultrahigh frequency sensor 311, the high frequency sensor 312, and the ultrasonic sensor 313 are different types of partial discharge sensors, and they have different working principles and different frequencies of the collected signals.
By collecting various types of sensor information, the discharge monitoring unit 300 can accurately collect partial discharge phenomenon, and missing report of a single sensor is avoided. The discharge monitoring unit 300 monitors the transformer body 100 in real time, captures instantaneous frequency information and discharge amplitude information of partial discharge, and extracts characteristics of the frequency information and the discharge amplitude information of the partial discharge, thereby judging the type of the partial discharge. As an example, it can be judged that the types of partial discharge are mainly free metal particle discharge, floating potential body discharge, insulator internal air gap discharge, metal tip discharge, creeping discharge, and the like.
In this embodiment, the signal acquisition subunit 320 transmits the acquired partial discharge instantaneous frequency information and discharge amplitude information to the upper computer 800. The upper computer 800 records the accessed partial discharge instantaneous frequency information and discharge amplitude information data, displays the discharge information of the sensors, diagnoses faults of the transformer body 100, estimates the health state of the transformer by fusing various sensor acquisition data, pre-warns some potential faults, and provides a basis for equipment maintenance.
The ultrahigh frequency sensor 311 may be divided into an internal type and an external type, and an appropriate ultrahigh frequency sensor type may be selected according to actual requirements of the transformer fault monitoring device. The built-in ultrahigh frequency sensor 311 is generally installed at a reserved position when the transformer body 100 leaves the factory, and the external ultrahigh frequency sensor 311 is installed at a position with a sealing rubber gasket, such as a flange butt joint surface. The high frequency sensor 312 may be mounted to the transformer body 100 at the bushing end, core, clip, etc. The ultrasonic sensor 313 is attached to the oil tank surface of the important areas such as the sleeve lifting seat and the coil handle of the transformer body 100 by means of magnetic attraction, binding and the like.
Since the ultrahigh frequency sensor 311 is disposed inside the transformer body 100, the closer to the metal component inside the transformer body 100, the larger the discharge energy of the transformer body 100, the higher the sensitivity of the ultrahigh frequency sensor 311, the more accurate the detected discharge phenomenon, and the more definite the discharge type. The high frequency sensor 312 is located at a relatively low detection sensitivity as compared to the uhf sensor 311, which is located at a relatively long distance from the inside of the transformer body 100, but is also capable of detecting the discharge phenomenon of the core, clip, etc. inside the transformer body 100. The ultrasonic sensor 313 is disposed on the surface of the oil tank at a distance from the internal components of the transformer body 100, so that the detection sensitivity is lower, the ability to detect the discharge phenomenon near the oil tank is weaker, but the corresponding discharge type can be detected. Therefore, in the present embodiment, the corresponding discharge type is detected by providing sensors of different detection sensitivities at different positions of the transformer body 100.
The gas monitoring unit 400 includes: the gas separation sub-unit 410 and the gas detection sub-unit 430, the gas separation sub-unit 410 is communicated with the transformer body 100 through the first pipeline 420, the gas detection sub-unit 430 is communicated with the gas separation sub-unit 410 through the second pipeline 440, and the gas detection sub-unit 430 is also connected with the upper computer 800 through wired or wireless communication. The gas monitoring unit 400 may collect oil samples from a sampling valve at the lower portion of the transformer body 100, and may also collect oil samples at other advantageous locations of the circulation oil path.
Illustratively, the gas separation sub-unit 410 may include an oil inlet pipe, an oil-gas separation chamber, and an oil outlet pipe, wherein the oil inlet pipe is connected with the transformer body 100 through a first pipe 420, one end of the oil-gas separation chamber is connected with the oil inlet pipe, the other end of the oil-gas separation chamber is connected with the gas detection sub-unit 430 through a second pipe 440, and the oil outlet pipe is connected with the oil-gas separation chamber. The main function of the gas separation subunit 410 is to separate oil from gas in the oil in the transformer body 100 and dissolved in the oil in the transformer body 100, and send the gas to the gas detection subunit 430 for detection and analysis.
At present, two common technical methods for detecting the gas content exist, one is gas chromatography, and the other is photoacoustic spectrometry, and the two schemes are different in principle, but can all measure the content of fault characteristic gas so as to judge the fault of the transformer body 100. Illustratively, the gas detection subunit 430 may include a spectral measurement cavity having a light generating member disposed therein for emitting parallel monochromatic light. The spectral range of the light generating element is one of ultraviolet light region, visible light region or infrared light region. The main function of the gas detection subunit 430 is to detect the gas to be detected, and measure the content of the fault characteristic gas, where the fault characteristic gas has H 2 、CO、CO 2 、CH 4 、C 2 H 4 、C 2 H 2 、C 2 H 6 . Therefore, the gas monitoring unit 400 can determine that the fault of the transformer body 100 has oil overheating, partial discharge in oilpaper insulation, spark discharge in oil, arc discharge in oil, transformer wetting, and the like.
The current monitoring unit 500 includes: the ground current transformer 510 and the current acquisition subunit 520, the current acquisition subunit 520 is connected with the ground current transformer 510 and the upper computer 800 through a cable.
The core/clip in the transformer body 100 is typically led to the outside of the tank of the transformer body 100 via a bushing for grounding. The grounding current transformer 510 is a core-penetrating current transformer, and the grounding current transformer 510 is installed on an iron core grounding wire or a clamping piece grounding wire in a penetrating manner. When the iron core grounding current measuring device is installed, the grounding current transformer 510 is sleeved on the grounding sleeve, the grounding current transformer 510 senses the current of the grounding sleeve, the current is converted into a signal and is output to the current collecting subunit 520, and the current collecting subunit 520 carries out accurate test on the signal so as to calculate the iron core grounding current. The current monitoring unit 500 transmits the core grounding current to the upper computer 800 in real time, and alarms when the grounding current value exceeds the attention value, and when the grounding current is too large, the transformer body 100 may malfunction. Based on the above principle, the current abnormality of the transformer body 100 can be monitored in real time by the current monitoring unit 500.
The voiceprint and vibration monitoring unit 600 includes: a vibration sensor 610, a microphone 620, a vibration and sound collection subunit 630. The voiceprint and vibration monitoring unit 600 is able to identify some mechanical faults of the transformer, such as loosening of the housing, deformation of the windings, etc. For example, the common vibration sensor 610 has an acceleration sensor, and the vibration sensor 610 is arranged outside the oil tank of the transformer body 100 in a magnetic attraction and binding manner and is installed at the corresponding oil tank surface position of the side column and the upper iron yoke of the equipment.
The microphone 620 is divided into a contact type and a non-contact type, and the contact type microphone 620 is directly attached to the oil tank case of the transformer body 100. The non-contact voiceprint sensor is mounted at a distance from the transformer body 100.
The vibration sensor 610 is used for collecting frequency information and amplitude information of a mechanical fault vibration signal of the transformer body 100; the microphone 620 is disposed on the transformer body 100, and is used for collecting frequency information and amplitude information of mechanical fault sound signals of the transformer body 100. The vibration and sound collecting sub-unit 630 is connected to the vibration sensor 610 and the microphone 620 through cables for transmitting the mechanical failure vibration signal frequency information and amplitude information and the mechanical failure sound signal frequency information and amplitude information to the upper computer 800.
In this embodiment, the vibration sensor 610 can convert the sound signal into an electrical signal, the vibration and sound collecting subunit 630 collects the vibration and sound signal in real time, and can measure the amplitude information and the frequency information of the vibration and sound signal, and extract the signal characteristics at the same time, and through comparing with the fault characteristics, identify the possible fault of the transformer body 100.
In one embodiment, the transformer fault monitoring device 11 further comprises: the dual spectrum imaging unit 700 is connected to the host computer 800, and is used for monitoring the transformer body 100. Illustratively, the dual spectrum imaging unit 700 may be mounted on a pole located a distance from the transformer body 100, ensuring that the monitoring screen covers the entire transformer body 100. The dual-spectrum imaging unit 700 is used for real-time monitoring and high-temperature alarming of the temperature of the transformer body 100, and real-time safety monitoring and abnormality reminding of the site of the transformer body 100.
Wherein the dual spectrum imaging unit 700 includes: the infrared detection module 710 is connected to the host computer 800 through wired or wireless communication. Illustratively, the infrared detection module 710 includes: an infrared detection assembly 711 and an infrared thermal imaging processing assembly 712. The infrared detection component 711 is preferably an infrared detector that collects external infrared radiation and converts it into a video signal that is transmitted to the infrared thermal imaging processing component 712. The infrared thermal imaging processing component 712 generates a thermal map reflecting the surface temperature of the object based on the video signal and transmits the thermal map to the host computer 800.
In one embodiment, the dual spectrum imaging unit 700 further comprises: the visible light detection module 720 is connected to the host computer 800 through wired or wireless communication. Illustratively, the visible light detection module 720 includes: a visible light sensor 721 and a visible light imaging processing component 722. The visible light sensor 721 converts visible light as a detection target into a video signal, and transmits the video signal to the visible light imaging processing unit 722. The visible light imaging processing component 722 forms a visible light image according to the video signal, and transmits the visible light image to the host computer 800.
In summary, the discharge monitoring unit 300, the gas monitoring unit 400, the current monitoring unit 500, the voiceprint and vibration monitoring unit 600, and the dual spectrum imaging unit 700 respectively detect partial discharge, gas in oil, ground current, voiceprint vibration, and dual light imaging, acquire multidimensional information such as electricity, gas, sound, machinery, light, and temperature, and the like, the upper computer 800 diagnoses various fault problems occurring in the transformer body 100 by accessing discharge frequency information and discharge amplitude information (i.e., electric information), fault gas content information (i.e., gas information), abnormal current information (i.e., electric information), mechanical fault vibration signal frequency information and amplitude information (i.e., mechanical information) of the transformer body 100, mechanical fault sound signal frequency information and amplitude information (i.e., mechanical information) of the transformer body 100, imaging monitoring picture information (i.e., optical information), abnormal temperature information (i.e., temperature information) of the transformer body 100, and the like, and transmits the acquired multidimensional information data to the corresponding data processing module for processing. Specific data processing modules may be referred to the description of the fault handling apparatus 12 in the transformer fault monitoring system 1 of fig. 3.
Referring to fig. 3, a transformer fault monitoring system 1 includes a transformer fault monitoring device 11 and a fault handling device 12 as described in fig. 1 and 2, where the fault handling device 12 is connected to the transformer fault monitoring device 11 by a wire and/or wirelessly.
In one embodiment, the fault handling apparatus 12 comprises: the data processing module 121 and the fault evaluation and prediction module 122, the data processing module 121 and the upper computer 800 are connected by wire and/or wirelessly, and the fault evaluation and prediction module 122 and the data processing module 121 are connected by wire and/or wirelessly.
Illustratively, the data processing module 121 includes an expert experience unit 1211 and a deep learning unit 1212. The discharge monitoring unit 300, the gas monitoring unit 400, the current monitoring unit 500, the voiceprint and vibration monitoring unit 600 and the dual-spectrum imaging unit 700 respectively detect partial discharge, gas in oil, ground current, voiceprint vibration and dual-light imaging, acquire multidimensional information such as electricity, gas, sound, machinery, light, temperature and the like, and transmit the multidimensional information to the upper computer 800. The upper computer 800 displays and records the accessed multidimensional information, and simultaneously transmits the multidimensional information to the expert experience unit 1211, the deep learning unit 1212 and the fault evaluation and prediction module 122 of the upper computer 800. The expert experience unit 1211 analyzes the real-time data, extracts the characteristics of the multidimensional information of the transformer body 100, synthesizes the multidimensional information, and makes an expert decision to obtain an analysis result. The deep learning unit 1212 imports the history data, preprocesses and model analysis are performed on the data to obtain a state evaluation result, and then information fitting is performed to send the state evaluation result to artificial intelligence model training. The fault evaluation and prediction module 122 diagnoses the fault of the transformer body 100 according to the analysis result, fuses the multidimensional sensor, predicts the health state of the transformer, pre-warns some potential faults, and provides a basis for the maintenance of the transformer body 100. The deep learning unit 1212 sends the training result of the artificial intelligence model to the expert experience unit 1211, so as to continuously enhance the analysis and judgment capabilities of the expert experience unit 1211, and further continuously enhance the diagnosis, evaluation and prediction capabilities of the transformer health diagnosis device.
In summary, in the transformer fault monitoring device of the present utility model, the upper computer 800 fuses the multidimensional sensor data such as electricity, gas, sound, machinery, light, temperature, etc., extracts the characteristics of multidimensional information of the transformer body 100, diagnoses the fault of the transformer body 100, predicts the health state of the transformer, pre-warns some potential faults, and provides a basis for equipment maintenance.
The transformer fault monitoring system 1 acquires the state information of the transformer body 100 through the multi-dimensional sensor and the monitoring equipment, fuses and analyzes the multi-dimensional sensor information, and synchronously sends the fused multi-dimensional sensor data into the deep learning unit 1212, and the deep learning unit 1212 trains according to the artificial intelligent model, continuously updates the iterative expert experience unit 1211, and further continuously improves the diagnosis, evaluation and prediction capabilities of the transformer health diagnosis equipment.
It should be noted that the features of the embodiments of the present utility model may be combined with each other without conflict.
The above description is only of the preferred embodiments of the present utility model and is not intended to limit the present utility model, but various modifications and variations can be made to the present utility model by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present utility model should be included in the protection scope of the present utility model.
Claims (8)
1. A transformer fault monitoring device, comprising:
a transformer body;
the device comprises a cabinet, wherein a discharge monitoring unit, a gas monitoring unit, a current monitoring unit, a voiceprint and vibration monitoring unit and an upper computer are respectively arranged on the cabinet;
the discharge monitoring unit is respectively connected with the transformer body and the upper computer and is used for monitoring discharge fault information of the transformer body and transmitting the discharge fault information to the upper computer;
the gas monitoring unit is respectively connected with the transformer body and the upper computer and is used for monitoring the content information of fault gas in the transformer body oil and transmitting the content information to the upper computer;
the current monitoring unit is respectively connected with the transformer body and the upper computer and is used for monitoring current fault information of the transformer body and transmitting the current fault information to the upper computer;
the voiceprint and vibration monitoring unit is respectively connected with the transformer body and the upper computer and is used for monitoring mechanical fault information of the transformer body and transmitting the mechanical fault information to the upper computer.
2. The transformer fault monitoring device according to claim 1, wherein the discharge monitoring unit comprises:
the sensors are connected with the transformer body and are used for collecting the discharge frequency information and the discharge amplitude information of the transformer body;
and the signal acquisition subunit is connected with the plurality of sensors and the upper computer and used for transmitting the discharge frequency information and the discharge amplitude information to the upper computer.
3. The transformer fault monitoring device of claim 1, wherein the gas monitoring unit comprises:
the gas separation subunit is communicated with the transformer body through a first pipeline;
the gas detection subunit is communicated with the gas separation subunit through a second pipeline and is also connected with the upper computer.
4. The transformer fault monitoring device according to claim 1, wherein the current monitoring unit comprises:
the grounding current transformer is connected with the transformer body;
and the current acquisition subunit is connected with the grounding current transformer and the upper computer.
5. The transformer fault monitoring device of claim 1, wherein the voiceprint and vibration monitoring unit comprises:
the vibration sensor is connected with the transformer body and is used for collecting frequency information and amplitude information of mechanical fault vibration signals of the transformer body;
the microphone is arranged on the transformer body and is used for collecting frequency information and amplitude information of mechanical fault sound signals of the transformer body;
and the vibration and sound acquisition subunit is connected with the vibration sensor and the microphone and is used for transmitting the frequency information and the amplitude information of the mechanical fault vibration signals and the frequency information and the amplitude information of the mechanical fault sound signals to the upper computer.
6. The transformer fault monitoring device of claim 1, further comprising: and the double-spectrum imaging unit is connected with the upper computer and is used for monitoring the transformer body.
7. The transformer fault monitoring device of claim 6, wherein the dual spectrum imaging unit comprises: the infrared detection module is connected with the upper computer by a wire and/or a wireless;
the infrared detection module includes:
an infrared detection assembly;
and the infrared thermal imaging processing assembly is connected with the infrared detection assembly.
8. The transformer fault monitoring device of claim 6, wherein the dual spectrum imaging unit further comprises: the visible light detection module is connected with the upper computer by a wire and/or a wireless;
the visible light detection module includes:
a visible light sensor;
and the visible light imaging processing assembly is connected with the visible light sensor.
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| CN202223594893.6U CN219800139U (en) | 2022-12-30 | 2022-12-30 | Transformer fault monitoring device |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202223594893.6U CN219800139U (en) | 2022-12-30 | 2022-12-30 | Transformer fault monitoring device |
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