CN111856169B - Transformer fault detection method and system - Google Patents
Transformer fault detection method and system Download PDFInfo
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- CN111856169B CN111856169B CN201910322718.5A CN201910322718A CN111856169B CN 111856169 B CN111856169 B CN 111856169B CN 201910322718 A CN201910322718 A CN 201910322718A CN 111856169 B CN111856169 B CN 111856169B
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- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
- Y04S10/52—Outage or fault management, e.g. fault detection or location
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Abstract
The invention provides a transformer fault detection method and a system, wherein the fault detection method is used for judging whether a tested transformer has a fault or not based on a preset fault numerical value range and a normal numerical value range, and comprises the following steps: judging whether the running state of the transformer is abnormal or not according to the first running parameter of the transformer, and controlling and adjusting the running state; judging whether the transformer fault is in the iron core or not according to the second operation parameter of the transformer; detecting fault positions and fault types; judging whether the fault of the transformer is a winding fault or not according to the leakage reactance parameter of the transformer; and judging the type of the winding fault through the analysis of the internal temperature of the transformer, the oil temperature and the oil pressure of the transformer and the vibration signal. Through one-by-one multi-stage detection of a plurality of parameters, a good prevention effect is achieved on the transformer which does not have a fault, and the fault probability is reduced; the transformer with the fault can be timely and accurately judged according to the fault position and type, so that maintenance personnel can maintain the transformer in a targeted manner, and the power operation maintenance management efficiency is improved.
Description
Technical Field
The invention relates to the field of transformers, in particular to a transformer fault detection method and system.
Background
The transformer is used as a component of power transmission and distribution of a power system, and the safety and the stability of the transformer have important significance for the development of national economy. Today, the breakdown of the power system caused by transformer accidents is more frequent, which is not only unfavorable for the rapid development of economy, but also seriously affects the normal life of residents. According to statistics, the number of accidents of 110kV and above power transformers in China is 284 from 1995 to 1999, the total capacity of the accidents is 21360MVA, and the failures of the transformers mainly comprise core failures and winding failures if the number of the accidents is divided according to the positions of the failures of the transformers. The core fault is mostly caused by the vibration of the transformer body, and the main reasons for causing the vibration of the transformer body are the vibration of the transformer body and the vibration of the cooling device. After the transformer is electrified and operated, current flows in the winding, and an electromagnetic field is generated in the iron core and the winding; the iron core silicon steel sheet material is subjected to magnetostriction under the action of a magnetic field, namely the size of atoms is subjected to micro deformation, so that the iron core vibrates. The probability that a transformer winding fault occurs among the fault types of all transformers is highest. And the fault possibility of transformer winding faults is many, and the faults include winding short circuit, winding deformation, insulation aging faults and the like.
At present, a method for detecting transformer faults in an electric power system is single, the types and the specific positions of the faults cannot be judged specifically, the severity of the faults cannot be judged effectively, negative influences are generated when field personnel know the internal deformation condition of the transformer, and development of next detection work is not facilitated.
Disclosure of Invention
In view of the above, the present invention is directed to a transformer fault detection method to solve the above problems.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a transformer fault detection method is used for judging whether a tested transformer is in fault or not based on a preset fault numerical range and a normal numerical range, and comprises the following steps:
step S1: judging whether the running state of the transformer is abnormal or not according to the first running parameter of the transformer, and controlling and adjusting the running state;
step S2: judging whether the transformer fault is in the iron core or not according to the second operation parameter of the transformer;
and step S3: detecting fault positions and fault types; judging whether the fault of the transformer is a winding fault or not according to the leakage reactance parameter of the transformer;
and step S4: and judging the type of the winding fault through the analysis of the internal temperature, the oil temperature and the oil pressure of the transformer and the vibration signal.
Further, the first operation parameter comprises internal temperature of the transformer, output current and/or output voltage, and the second operation parameter comprises internal temperature of the transformer, and vibration signal information of the transformer.
Furthermore, the temperature inside the transformer is detected through a temperature measurement sensing system, and the temperature measurement sensing system comprises a temperature processing module arranged on the outer wall of the transformer body and an infrared temperature measurement sensor extending into the transformer body.
Further, the step S1 includes:
step S11: starting the transformer to start running;
step S12: after the running time of the transformer reaches a first preset time, the detection device starts to detect the internal temperature T of the transformer;
step S13: judging whether the internal temperature T of the transformer detected by the temperature measurement sensing system is within a first preset temperature range delta T1 or not, and if so, continuing normal operation of the transformer; if the judgment result is no, executing the step S14;
step S14: executing a fault early warning detection program, warning workers to closely monitor the running condition of the transformer and detecting the output voltage of the transformer;
step S15: judging whether the output voltage is in a preset voltage range of the transformer, and executing an S2 fault judgment program when the judgment result is yes; if the judgment result is negative, it indicates that the temperature inside the transformer exceeds the first preset temperature range is caused by the overload of the transformer, and at this time, step S15 is executed to control the load reduction operation of the transformer.
Step S16: regulating transformer to reduce capacity and current limit I max . I.e. to limit the operation of the transformer not to exceed the current limit I max 。
Further, the step S2 includes:
step S21: detecting the internal temperature T of the transformer again;
step S22: judging whether the internal temperature T of the transformer is within a second preset temperature range delta T 2 If yes, indicating that the interior of the transformer is moderately overheated, and executing step S23; if the judgment result is no, executing the step S14;
step S23: sampling vibration information of the transformer according to set sampling frequency and sampling time, intercepting a vibration signal of the transformer in a whole period, performing wavelet denoising on the intercepted vibration signal, performing Fourier spectrum analysis, and simultaneously solving component amplitudes of the vibration signal at 50Hz, 150Hz, 100Hz and 200 Hz. Continuously detecting the oil temperature and the oil pressure of the transformer and sending detected signals to a control device;
step S24: judging whether the sum of the amplitudes of the frequency spectrum components of 50Hz and 150Hz is greater than a first preset threshold phi or not 1 If the fault is the iron core loosening fault, the fault of the transformer is judged, if the fault is not judged, the fault is the fault of other parts except the iron core, such as the winding fault, and the step S3 needs to be executed, so that the fault part and the fault type are further detected.
Further, the step S3 includes:
step S31: acquiring leakage reactance parameters after the short circuit of the transformer;
step S32: judging whether the obtained leakage reactance parameter value after the short circuit of the transformer is in a fault value range or not, if so, judging the fault of the transformer winding, executing the step S4, and judging the fault type of the specific transformer winding; if not, the transformer fault is a fault of other parts except the iron core and the winding, and a shutdown inspection alarm prompt is given, so that shutdown inspection is required.
Further, the step S3 includes:
step S41: acquiring the oil temperature and oil pressure change curve of the transformer, judging whether the oil temperature or oil pressure change curve of the transformer is in a continuously rising state, if so, judging that the transformer fault is a winding insulation aging fault, and giving an insulation aging alarm prompt. If not, it is determined that the transformer winding fault is not caused by insulation aging, and further determination is required, and step S42 is performed.
Step S42: the transformer internal temperature T is detected again.
Step S43: judging whether the internal temperature is in a third preset temperature range delta T 3 If yes, indicating that the interior of the transformer is severely overheated, and executing a step S44; if the judgment result is no, the transformer fault is the fault of other parts except the iron core and the winding, and the machine needs to be stopped for inspection.
Step S44: and detecting the vibration information of the transformer, and calculating the sum of the amplitudes of the spectral components at 100Hz and 200 Hz.
Step S45: judging whether the ratio of the sum of the amplitudes of the spectral components at 50Hz and 150Hz to the sum of the amplitudes of the spectral components at 100Hz and 200Hz is larger than a second preset threshold phi 2 If the fault is the winding deformation fault, the transformer fault is judged to be the fault of other parts except the iron core and the winding, and the machine needs to be stopped for inspection.
Further, the first preset temperature range Δ T1 is set according to temperature values of the winding and the iron core when the transformer is in a fault-free and normal operation state, and the first preset time is determined according to time from the startup of the transformer to the stable operation state.
Compared with the prior art, the transformer fault detection method has the following advantages:
according to the transformer fault detection method, through one-by-one multi-stage detection of a plurality of parameters, the transformer fault is accurately judged, and a corresponding alarm prompt is made in time, so that a good prevention effect is achieved on the transformer which is not in fault, and the fault probability is reduced; the transformer with the fault can be timely and accurately judged on the fault position and type, maintenance personnel can conveniently and pertinently maintain and replace the transformer, the workload of the maintenance personnel is reduced, and the power operation maintenance management efficiency is improved.
The invention also provides a transformer fault detection system, and by using the transformer fault detection method, the transformer comprises a transformer body and a detection system, wherein the transformer body comprises a transformer winding, a transformer iron core and a cooling device, cooling oil is stored in the cooling device, the detection system comprises a control device, an analysis module, a timer and a detection device, the timer is used for timing and analyzing the running time of the transformer, the detection device feeds detected data parameters back to the analysis module, the analysis module is used for analyzing and calculating the detected data and then transmitting the data to the control device, and the control device is used for controlling the alarm device to give corresponding alarm prompts.
Furthermore, the detection device comprises a temperature measurement sensing system, a vibration information detection device and a leakage reactance parameter measurement system, the temperature measurement sensing system comprises a temperature processing module installed on the outer wall of the transformer body and an infrared temperature measurement sensor extending into the transformer body, the vibration information detection device is a vibration sensor, the vibration sensor is arranged right above the middle position between the high-voltage winding and the low-voltage winding in the transformer, and the leakage reactance parameter measurement system comprises simulation software and a simulation transformer.
Compared with the prior art, the transformer fault detection system and the transformer fault detection method have the same advantages, and are not repeated herein.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate an embodiment of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a flowchart of a transformer fault detection method according to a first embodiment of the present invention;
FIG. 2 is a partial flowchart of a transformer fault detection method according to a second embodiment of the present invention;
fig. 3 is a flowchart illustrating a detection process of a fault location and a fault type in the transformer fault detection system according to the embodiment of the present invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments of the present invention may be combined with each other without conflict. The descriptions of "first," "second," etc. mentioned in the embodiments of the present invention are for descriptive purposes only and are not to be construed as indicating or implying relative importance or to implicitly indicate the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between the embodiments may be combined with each other, but must be based on the realization of the technical solutions by a person skilled in the art, and when the technical solutions are contradictory to each other or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present invention.
The present invention will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Example 1
As shown in fig. 1, a transformer fault detection method provided in an embodiment of the present invention is a flowchart, where the transformer fault detection method in this embodiment judges whether a tested transformer has a fault based on a predetermined fault value range and a predetermined normal value range, and specifically includes the following steps:
step S1: and judging whether the running state of the transformer is abnormal or not through the first running parameter of the transformer, and controlling and adjusting the running state.
Wherein the first operating parameter comprises a transformer internal temperature, an output current and/or an output voltage.
Firstly, each operation parameter of the transformer starts to be detected after the transformer operates for a period of time, and due to the limitation of the internal structure of the transformer, heat can be generated inside the transformer after the transformer starts to operate, so that the temperature is increased, but when the transformer operates normally and the state is stable, the temperature can be maintained within a normal range. Therefore, when the temperature inside the transformer is detected to be beyond the normal range, the transformer is indicated to be possible to have a fault or run in an overload mode.
Specifically, the internal temperature of the transformer is detected through a temperature measurement sensing system, and the temperature measurement sensing system comprises a temperature processing module arranged on the outer wall of the transformer body and an infrared temperature measurement sensor extending into the transformer body. For the traditional contact type temperature measuring sensor, because when the transformer operates abnormally, the winding and the iron core of the transformer are easy to generate sudden serious overheating, the damage to the sensor arranged inside the transformer is large, but if the temperature sensor is far away from the iron core and the winding, the temperature inside the transformer is easy to be detected inaccurately, and the temperature inside the transformer cannot be reflected effectively in time. In this embodiment, the infrared ray emitted by the temperature measuring probe of the infrared temperature measuring sensor performs non-contact continuous scanning temperature measurement on the transformer winding and the transformer core in the transformer body, and simultaneously transmits the detected temperature signal to the temperature processing module, the temperature processing module processes and calculates the temperature signal transmitted by the infrared temperature measuring sensor, and transmits the result to the control device, and the control device determines whether the running state of the transformer is normal or not according to the temperature value. If the temperature inside the transformer is detected to be abnormal, the operation is abnormal, and further detection and judgment are required. The temperature sensor is arranged as the infrared temperature sensor in the embodiment, non-contact detection with the iron core and the winding inside the transformer is achieved, and the service life of the sensor is prolonged.
The method comprises the steps of judging whether the temperature abnormality in the transformer is caused by transformer faults or overload by detecting whether the output voltage value and/or the current value of the transformer are abnormal, and if the temperature abnormality in the transformer is caused by the overload of the transformer, controlling the transformer to give an overload alarm prompt by a control device and enabling a worker to carry out load reduction operation on the transformer. If the abnormal temperature inside the transformer is judged to be caused by the transformer fault, a transformer fault detection program is executed, and the specific fault part and fault type of the transformer are detected, so that maintenance personnel can repair and replace the transformer in a targeted manner, the workload of the maintenance personnel is reduced, and the power operation, maintenance and management efficiency is improved.
Step S2: and judging whether the transformer fault is in the iron core or not according to the second operation parameter of the transformer.
The second operation parameter comprises the internal temperature of the transformer and the vibration signal information of the transformer.
When it is determined in step S1 that the temperature abnormality of the transformer is not caused by overload, the temperature inside the transformer needs to be further detected again, and if the transformer is moderately overheated, it needs to further determine whether the transformer fault is caused by the loosening of the iron core according to the vibration information of the transformer.
The vibration of the transformer body is mainly caused by the vibration of the transformer body and the vibration of the cooling device. The basic vibration frequency caused by the cooling device is lower and is obviously different from the vibration of the transformer body; the transformer body vibration includes vibration of the core and the winding. After the transformer is electrified and operated, current flows in the winding, and an electromagnetic field is generated in the iron core and the winding; the iron core silicon steel sheet material is subjected to magnetostriction under the action of a magnetic field, namely the size of atoms is subjected to micro deformation, so that the iron core vibrates. The vibration of the windings is caused by the interaction of currents in the windings under the influence of leakage inductance to generate electromotive force, which is proportional to the square of the current. And when the transformer is in no-load, the current of the winding is zero, the winding basically has no influence on the vibration of the iron core, and the vibration of the transformer mainly depends on the iron core.
And step S3: detecting fault positions and fault types; and judging whether the fault of the transformer is a winding fault or not according to the leakage reactance parameter of the transformer.
When the transformer fault detected in the step S2 does not belong to the core fault, further judgment needs to be made on the fault position and the fault type. Specifically, when the transformer enters a fault position and fault type detection program, whether the fault of the transformer is a winding fault is judged by judging whether the leakage reactance parameter after the transformer is short-circuited is within a preset numerical range.
Under the condition of a certain working frequency, the value of the leakage reactance parameter of the transformer is determined by the structure of a transformer winding, for a transformer, when the winding of the transformer is in a normal state, namely when the winding of the transformer does not have faults such as deformation or displacement, the value of the leakage reactance parameter after short circuit of the transformer is in a fixed value, and when the winding of the transformer is in a fault state, namely when the winding of the transformer has faults such as certain deformation or displacement, the value of the leakage reactance parameter after short circuit of the transformer is in another fixed value range, therefore, when detecting whether the winding of the transformer has faults, whether the winding of the transformer has faults can be judged by measuring the value of the leakage reactance parameter after short circuit of the transformer.
And step S4: and judging the type of the winding fault through the analysis of the internal temperature of the transformer, the oil temperature and the oil pressure of the transformer and the vibration signal.
When it is determined in step S3 that the fault of the transformer is caused by the winding fault, the type of the winding fault is further determined through analysis of the temperature, the oil temperature and the oil pressure of the transformer and the vibration signal. Common types of winding faults include winding insulation aging faults, winding deformation faults, and the like.
And when the oil temperature or the oil pressure of the transformer continuously rises, judging that the insulation aging of the winding of the transformer occurs. And meanwhile, when the internal temperature of the transformer is overheated, whether the winding deformation fault occurs is analyzed through a transformer vibration signal.
The transformer fault detection method provided by the embodiment can accurately detect whether the transformer runs abnormally or fails, prompt maintenance personnel to adjust the load of the transformer in time, and avoid the transformer from being burnt down due to long-time overload. Meanwhile, the fault type and the specific position of the fault of the transformer can be judged, so that maintenance personnel can repair and replace the transformer in a targeted manner, the workload of the maintenance personnel is reduced, and the power operation, maintenance and management efficiency is improved.
Example 2
The present embodiment further defines the transformer fault detection method based on embodiment 1. Specifically, the method comprises the following steps:
step S11: the starting transformer starts to operate.
Step S12: after the running time of the transformer reaches a first preset time, the detection device starts to detect the internal temperature T of the transformer.
Wherein the first predetermined time is determined according to the time from the startup of the transformer to the reaching of the stable operation state. When the running time of the transformer is less than the first preset time, the transformer does not enter a normal running state at the moment, and the detected temperature of the transformer is low, so that the judgment result is influenced. Therefore, the internal temperature of the transformer needs to be detected by the temperature measurement sensing system after the running time of the transformer reaches the first preset time, so that the internal temperature of the transformer is not too low, the judgment result is influenced, and the transformer is not burnt down due to too high temperature.
The temperature measurement sensing system is arranged on the temperature processing module on the outer wall of the transformer body and extends into the infrared temperature measurement sensor inside the transformer body. The infrared ray that infrared temperature measurement sensor sent carries out non-contact continuous scanning temperature measurement to transformer winding and transformer core in the transformer body, and the temperature processing module is carried out the temperature signal processing calculation with the temperature signal processing that infrared temperature measurement sensor transmitted simultaneously to carry the result to controlling means.
Step S13: judging whether the internal temperature T of the transformer detected by the temperature measurement sensing system is within a first preset temperature range delta T1 or not, and if so, continuing normal operation of the transformer; if the determination result is negative, step S14 is executed.
The first preset temperature range delta T1 is set according to the temperature values of the winding and the iron core when the transformer does not have faults and operates normally.
Step S14: and executing a fault early warning detection program at the moment, warning workers to closely monitor the running condition of the transformer and detecting the output voltage of the transformer.
Step S15: judging whether the output voltage is in a voltage range preset by the transformer, and executing an S2 fault judgment program when the judgment result is yes; if the judgment result is no, the fact that the temperature inside the transformer exceeds the first preset temperature range is caused by overload of the transformer is indicated, and at this time, step S16 is executed to control the load reduction operation of the transformer.
Step S16: regulating the transformer to reduce its capacity and current limit I max . I.e. limiting the operation of the transformer to not exceed the current limit I max 。
Through a series of judgments, the fault possibility of the transformer is discharged to a certain extent, the load of the transformer is reduced, the service life of the transformer is prolonged, on the other hand, the follow-up fault detection is facilitated, and the detection accuracy is improved.
Step S21: detecting the internal temperature T of the transformer again;
step S22: judging whether the internal temperature T of the transformer is within a second preset temperature range delta T or not 2 If yes, indicating that the interior of the transformer is moderately overheated, and executing step S23; if the determination result is negative, step S14 is executed.
Step S23: sampling vibration information of the transformer according to set sampling frequency and sampling time, intercepting a vibration signal of the transformer in a whole period, performing wavelet denoising on the intercepted vibration signal, performing Fourier spectrum analysis, and simultaneously solving component amplitudes of the vibration signal at 50Hz, 150Hz, 100Hz and 200 Hz. And simultaneously, the oil temperature and the oil pressure of the transformer are continuously detected, and detected signals are sent to the control device.
Step S24: judging whether the sum of the amplitudes of the frequency spectrum components of 50Hz and 150Hz is greater than a first preset threshold phi or not 1 If the fault is the iron core loosening fault, the fault of the transformer is judged, if the fault is not judged, the fault is the fault of other parts except the iron core, such as the winding fault, and the step S3 needs to be executed, so that the fault part and the fault type are further detected.
Analysis and calculation show that in vibration signal frequency spectrums in various winding fault states, the sum of the 50Hz and 150Hz component amplitudes is higher than the sum of the 50Hz and 150Hz components under normal conditions, and the difference is positively correlated with the fault degree, namely the more serious the winding fault is, the larger the difference between the two is.
Whether the fault part of the transformer is an iron core fault or not is accurately judged through orderly detection of temperature and vibration signals, and convenience is brought to maintenance of workers.
Step S31: and acquiring the leakage reactance parameters after the short circuit of the transformer.
Under the condition of a certain working frequency, the value of the leakage reactance parameter of the transformer is determined by the structure of a transformer winding, for one transformer, when the winding of the transformer is in a normal state, namely when the winding of the transformer does not have faults such as deformation or displacement, the value of the leakage reactance parameter after short circuit of the transformer is in a fixed value, and when the winding of the transformer is in a fault state, namely when the winding of the transformer has faults such as certain deformation or displacement, the value of the leakage reactance parameter after short circuit of the transformer is in another fixed value range.
Further, the transformer leakage reactance parameters are obtained through the leakage reactance parameters of the simulation transformer under the same conditions, and the simulation transformer is set according to the size, the structure and the performance parameters of the simulated actual transformer, so that the leakage reactance parameters obtained through the simulation transformer established by the simulation software can be used as the leakage reactance parameters of the simulated actual transformer.
Step S32: judging whether the obtained leakage reactance parameter value after the short circuit of the transformer is in a fault value range or not, if so, judging the fault of the transformer winding, executing the step S4, and judging the fault type of the specific transformer winding; if not, the transformer fault is indicated to be a fault of other parts except the iron core and the winding, and a shutdown inspection alarm prompt is given, so that shutdown inspection is required.
Specifically, if the measured value of the leakage reactance parameter after the short circuit of the transformer is within the fault value range, the winding of the transformer is judged to have a fault; on the contrary, if the value of the leakage reactance parameter after the short circuit of the transformer is measured is not in the fault value range, the winding of the transformer is not in the fault state, and the fault of the transformer can be judged to be the fault of other parts except the iron core and the winding.
Step S41: acquiring the oil temperature and oil pressure change curve of the transformer, judging whether the oil temperature or oil pressure change curve of the transformer is in a continuously rising state, if so, judging that the transformer fault is a winding insulation aging fault, and giving an insulation aging alarm prompt. If not, it is determined that the transformer winding fault is not caused by insulation aging, and further determination is required, and step S42 is performed.
Step S42: the transformer internal temperature T is detected again.
Step S43: judging whether the internal temperature is in a third preset temperature range delta T 3 If yes, indicating that the interior of the transformer is severely overheated, and executing step S44; if the judgment result is no, the transformer fault is the fault of other parts except the iron core and the winding, and the machine needs to be stopped for inspection.
Step S44: and detecting the vibration information of the transformer, and calculating the sum of the amplitudes of the frequency spectrum components of 100Hz and 200 Hz.
Step S45: judging whether the ratio of the sum of the amplitudes of the spectral components at 50Hz and 150Hz to the sum of the amplitudes of the spectral components at 100Hz and 200Hz is larger than a second preset threshold phi 2 If the fault is the winding deformation fault, the transformer fault is judged to be the fault of other parts except the iron core and the winding, and the machine needs to be stopped for inspection.
In the vibration signal frequency spectrum under the deformation fault state of various windings, the ratio of the sum of the frequency spectrum component amplitudes of 50Hz and 150Hz and the sum of the frequency spectrum component amplitudes of 100Hz and 200Hz is higher than the ratio of the sum of the frequency spectrum component amplitudes of 50Hz and 150Hz and the sum of the frequency spectrum component amplitudes of 100Hz and 200Hz in the normal state, and the difference is positively correlated with the fault degree, namely the more serious the winding deformation is, the larger the difference between the two is.
According to the transformer fault detection method provided by the embodiment, through one-by-one multi-stage detection of a plurality of parameters, the transformer fault is accurately judged, and a corresponding alarm prompt is made in time, so that a good prevention effect is achieved on the transformer which does not have the fault, and the fault probability is reduced; the transformer with the fault can be timely and accurately judged on the fault position and type, maintenance personnel can conveniently and pertinently maintain and replace the transformer, the workload of the maintenance personnel is reduced, and the power operation maintenance management efficiency is improved.
Example 3
As an embodiment of the present invention, the present embodiment further provides a transformer fault detection system. The transformer comprises a transformer body and a detection system, wherein the transformer body comprises a transformer winding, a transformer iron core and a cooling device, and cooling oil is stored in the cooling device.
The detection system comprises a control device, an analysis module, a timer and a detection device, wherein the timer is used for timing and analyzing the running time of the transformer, on one hand, the timer is used for prompting the fatigue state of the transformer, and on the other hand, the transformer is enabled to execute a detection program according to preset time.
The detection device feeds detected data parameters back to the analysis module, the analysis module analyzes and calculates the detected data and then transmits the data to the control device, and the control device controls the alarm device to give corresponding alarm prompts.
Furthermore, the detection device comprises a temperature measurement sensing system, wherein the temperature measurement sensing system comprises a temperature processing module arranged on the outer wall of the transformer body and an infrared temperature measurement sensor extending into the transformer body. The infrared temperature measuring sensor is connected with the temperature processing module, and the temperature processing module is connected with the control device. The sensor probe of the infrared temperature measurement sensor carries out non-contact continuous scanning temperature measurement on the interior of the transformer and transmits a measured temperature signal to the temperature processing module, and the temperature processing module analyzes and processes the received temperature signal and then transmits the processed temperature signal to the control device.
Furthermore, the detection device further comprises a vibration information detection device, the vibration information detection device is a vibration sensor, the vibration sensor is arranged right above the middle position between the high-voltage winding and the low-voltage winding in the transformer, and preferably, the vibration sensors are arranged in a plurality. The vibration information detection device is connected with the analysis module, and the analysis module analyzes and calculates the received vibration confidence and transmits the result to the control device.
Furthermore, the detection device further comprises a leakage reactance parameter measurement system, and the leakage reactance parameter measurement system comprises simulation software and a simulation transformer.
The transformer fault detection system provided by the embodiment can accurately detect data parameters of the transformer in various states, timely and accurately analyze and synthesize the parameters, provide a basis for a transformer detection method, ensure the smoothness of a detection flow, and facilitate maintenance personnel to repair and replace the transformer in a targeted manner.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the scope of the present invention, which is intended to cover any modifications, equivalents, improvements, etc. within the spirit and scope of the present invention.
Claims (6)
1. A transformer fault detection method is characterized in that whether a tested transformer is in fault or not is judged based on a preset fault numerical value range and a normal numerical value range, and the method comprises the following steps:
step S1: judging whether the running state of the transformer is abnormal or not through the first running parameter of the transformer, and controlling and adjusting the running state; the step S1 includes:
step S11: starting the transformer to start running;
step S12: after the running time of the transformer reaches a first preset time, the detection device starts to detect the internal temperature T of the transformer;
step S13: judging whether the internal temperature T of the transformer detected by the temperature measurement sensing system is within a first preset temperature range delta T1 or not, and if so, continuing normal operation of the transformer; if the judgment result is no, executing the step S14;
step S14: executing a fault early warning detection program, warning workers to closely monitor the running condition of the transformer and detecting the output voltage of the transformer;
step S15: judging whether the output voltage is in a voltage range preset by the transformer, and executing an S2 fault judgment program when the judgment result is yes; if the judgment result is negative, the fact that the temperature inside the transformer exceeds the first preset temperature range is caused by overload of the transformer is indicated, and step S15 is executed to control the load reduction operation of the transformer;
step S16: regulating the transformer to reduce its capacity and current limit I max (ii) a I.e. to limit the operation of the transformer not to exceed the current limit I max ；
Step S2: judging whether the transformer fault is in the iron core or not according to the second operation parameter of the transformer; the step S2 includes:
step S21: detecting the internal temperature T of the transformer again;
step S22: judging whether the internal temperature T of the transformer is within a second preset temperature range delta T 2 If yes, indicating that the interior of the transformer is moderately overheated, and executing a step S23; if the judgment result is negative, executing step S14;
step S23: sampling vibration information of the transformer according to set sampling frequency and sampling time, intercepting a vibration signal of the transformer in a whole period, performing wavelet denoising on the intercepted vibration signal, performing Fourier spectrum analysis, and simultaneously solving component amplitudes of the vibration signal at 50Hz, 150Hz, 100Hz and 200 Hz; continuously detecting the oil temperature and the oil pressure of the transformer and sending detected signals to a control device;
step S24: judging whether the sum of the amplitudes of the frequency spectrum components of 50Hz and 150Hz is greater than a first preset threshold value of 9811 1 If so, judging that the fault of the transformer is the iron core loosening fault, and if not, judging that the fault of other parts except the iron core is the fault of the other parts except the iron coreStep S3 needs to be executed to further detect the fault location and the fault type;
and step S3: detecting fault positions and fault types; judging whether the fault of the transformer is a winding fault or not according to the leakage reactance parameter of the transformer; the step S3 includes:
step S31: acquiring leakage reactance parameters after the short circuit of the transformer;
step S32: judging whether the obtained leakage reactance parameter value after the short circuit of the transformer is in a fault value range or not, if so, judging the fault of the transformer winding, executing the step S4, and judging the fault type of the specific transformer winding; if not, the transformer fault is a fault of other parts except the iron core and the winding, and a shutdown inspection alarm prompt is given to require shutdown inspection;
and step S4: judging the type of winding faults through the analysis of the internal temperature, the oil temperature and the oil pressure of the transformer and vibration signals; the step S4 includes:
step S41: acquiring an oil temperature and oil pressure change curve of the transformer, judging whether the oil temperature or the oil pressure change curve of the transformer is in a continuously rising state, if so, judging that the transformer fault is a winding insulation aging fault, and giving an insulation aging alarm prompt; if not, the fault of the transformer winding is not caused by insulation aging, further judgment is needed, and step S42 is executed;
step S42: detecting the internal temperature T of the transformer again;
step S43: judging whether the internal temperature is in a third preset temperature range delta T 3 If yes, indicating that the interior of the transformer is severely overheated, and executing step S44; if the judgment result is negative, the transformer fault is a fault of other parts except the iron core and the winding, and the machine needs to be stopped for inspection;
step S44: detecting vibration information of the transformer, and calculating the sum of the frequency spectrum component amplitudes of 100Hz and 200 Hz;
step S45: judging whether the ratio of the sum of the amplitudes of the spectral components at 50Hz and 150Hz to the sum of the amplitudes of the spectral components at 100Hz and 200Hz is greater than a second preset threshold value \981 2 If yes, the transformer fault is judged to be a winding deformation fault, and if not, the transformer fault is judged to be a winding deformation faultThe faults of the transformer are faults at other parts except the iron core and the winding, and the transformer needs to be stopped for inspection.
2. The transformer fault detection method according to claim 1, wherein the first operation parameter comprises a transformer internal temperature, an output current and/or an output voltage, and the second operation parameter comprises a transformer internal temperature, transformer vibration signal information.
3. The transformer fault detection method according to claim 2, wherein the temperature inside the transformer is detected by a temperature measurement sensing system, and the temperature measurement sensing system comprises a temperature processing module mounted on the outer wall of the transformer body and an infrared temperature measurement sensor extending into the transformer body.
4. The transformer fault detection method according to claim 1, wherein the first preset temperature range Δ T1 is set according to a temperature value of a winding and an iron core when the transformer is in a fault-free and normal operation state, and the first preset time is determined according to a time from power-on to a stable operation state of the transformer.
5. A transformer fault detection system is characterized in that the transformer fault detection method according to any one of claims 1 to 4 is used, the transformer comprises a transformer body and a detection system, the transformer body comprises a transformer winding, a transformer core and a cooling device, cooling oil is stored in the cooling device, the detection system comprises a control device, an analysis module, a timer and a detection device, the timer is used for timing and analyzing the running time of the transformer, the detection device feeds detected data parameters back to the analysis module, the analysis module is used for analyzing and calculating the detected data and then transmitting the data to the control device, and the control device is used for controlling the alarm device to give corresponding alarm prompts.
6. The transformer fault detection system of claim 5, wherein the detection device comprises a temperature measurement sensing system, a vibration information detection device and a leakage reactance parameter measurement system, the temperature measurement sensing system comprises a temperature processing module installed on the outer wall of the transformer body and an infrared temperature measurement sensor extending into the transformer body, the vibration information detection device is set as a vibration sensor, the vibration sensor is arranged right above the middle position between the high-voltage winding and the low-voltage winding in the transformer, and the leakage reactance parameter measurement system comprises simulation software and a simulation transformer.
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| CN113219378B (en) * | 2021-03-05 | 2024-04-09 | 国网江苏省电力有限公司徐州供电分公司 | Method for detecting insulation faults of dry-type transformer winding |
| CN113514783B (en) * | 2021-03-16 | 2023-12-15 | 国网江苏省电力有限公司南京供电分公司 | Method for detecting and judging mechanical state of transformer winding under no-load closing |
| CN113222447A (en) * | 2021-05-27 | 2021-08-06 | 南方电网数字电网研究院有限公司 | Automatic early warning and automatic dispatching inspection working system |
| CN113532535B (en) * | 2021-07-21 | 2024-03-15 | 国网江苏省电力有限公司宜兴市供电分公司 | Power transformer winding state judging method |
| CN114235053B (en) * | 2021-12-20 | 2022-07-01 | 国网山东省电力公司兰陵县供电公司 | Method for improving abnormity detection accuracy of voltage transformation equipment |
| CN114252724B (en) * | 2022-03-02 | 2022-06-17 | 山东和兑智能科技有限公司 | Intelligent detection method and detection system for transformer |
| CN116718952A (en) * | 2023-03-30 | 2023-09-08 | 青岛城市轨道交通科技有限公司 | Method and device for diagnosing overtemperature fault of dry type transformer |
| CN116561707B (en) * | 2023-07-11 | 2023-09-05 | 南京大全电气研究院有限公司 | Transformer fault checking and early warning method and system |
| CN116760196B (en) * | 2023-08-22 | 2023-12-26 | 国网浙江省电力有限公司宁波供电公司 | Control method and device for mobile box transformer substation vehicle and mobile box transformer substation vehicle |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102721464A (en) * | 2012-06-13 | 2012-10-10 | 江苏省电力公司南京供电公司 | Method and system for detecting winding deformation faults of power transformer |
| CN102721465A (en) * | 2012-06-13 | 2012-10-10 | 江苏省电力公司南京供电公司 | System and method for diagnosing and preliminarily positioning loosening faults of iron core of power transformer |
| CN102721897A (en) * | 2012-06-13 | 2012-10-10 | 江苏省电力公司南京供电公司 | Diagnosis method and system of turn-to-turn short circuit fault of power transformer winding |
| CN104316808A (en) * | 2014-11-17 | 2015-01-28 | 国家电网公司 | Method and system for detecting fault of transformer winding |
| CN106404078A (en) * | 2016-11-28 | 2017-02-15 | 山东科技大学 | Transformer online monitoring device |
| CN107247203A (en) * | 2017-07-10 | 2017-10-13 | 佛山杰致信息科技有限公司 | A kind of transformer fault detection method and device |
-
2019
- 2019-04-22 CN CN201910322718.5A patent/CN111856169B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102721464A (en) * | 2012-06-13 | 2012-10-10 | 江苏省电力公司南京供电公司 | Method and system for detecting winding deformation faults of power transformer |
| CN102721465A (en) * | 2012-06-13 | 2012-10-10 | 江苏省电力公司南京供电公司 | System and method for diagnosing and preliminarily positioning loosening faults of iron core of power transformer |
| CN102721897A (en) * | 2012-06-13 | 2012-10-10 | 江苏省电力公司南京供电公司 | Diagnosis method and system of turn-to-turn short circuit fault of power transformer winding |
| CN104316808A (en) * | 2014-11-17 | 2015-01-28 | 国家电网公司 | Method and system for detecting fault of transformer winding |
| CN106404078A (en) * | 2016-11-28 | 2017-02-15 | 山东科技大学 | Transformer online monitoring device |
| CN107247203A (en) * | 2017-07-10 | 2017-10-13 | 佛山杰致信息科技有限公司 | A kind of transformer fault detection method and device |
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