CN111784175A - Distribution transformer risk assessment method and system based on multi-source information - Google Patents
Distribution transformer risk assessment method and system based on multi-source information Download PDFInfo
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Abstract
The invention discloses a distribution transformer risk assessment method and system based on multi-source information, which can be used for monitoring a plurality of transformers simultaneously, acquiring related index data by numbering the monitored transformers, firstly obtaining a comprehensive health index by analyzing oil chromatographic data, and then obtaining the fault probability and the fault frequency of the transformers by an index fault rate model; then establishing an evaluation index set to obtain the risk severity grade of the transformer; the comprehensive risk grade of the transformer is obtained by synthesizing the frequency and the severity grade of the fault, and the potential risk of the transformer is subjected to multi-level alarm; the risk assessment method is used for carrying out risk assessment on the operation state and the environment of each transformer based on the fact that various index parameters related to the operation state of the transformer are acquired by various sensors, so that the reliability of the risk assessment is improved, maintenance personnel can find the transformer with the operation risk in time conveniently by adopting a multi-stage alarm mode, and the safe operation of the transformer is guaranteed.
Description
Technical Field
The invention belongs to the technical field of transformers, and particularly relates to a distribution transformer risk assessment method and system based on multi-source information.
Background
With the vigorous development of electric power utilities, the construction of smart power grids and ubiquitous power internet of things, a distribution transformer is used as important power transformation equipment in a power grid, and the operation reliability of the distribution transformer determines the stability of the power grid. Distribution transformers are high in accident rate due to their own structures and complex operating environments. In order to avoid huge economic loss and potential safety hazard caused by transformer accidents, the running state of the transformer needs to be evaluated, and the transformer accidents are prevented by effective monitoring and data analysis means.
At present, the transformer risk assessment technology at home and abroad is mainly designed for large transformers, historical operation data of the transformers are assessed, relevant fault rate models are established, fault rates of the transformers are obtained, risk consequences are quantized, and therefore risk assessment of the transformers is completed. The lack of real-time operational data of the transformer and the simplification of the evaluation state quantity lead to a large deviation of the risk evaluation result.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a distribution transformer risk assessment method and system based on multi-source information, which can be used for monitoring a plurality of distribution transformers simultaneously, analyzing the state information of the transformers for a long time, predicting the potential risks of the transformers, preventing the distribution transformers from faults and ensuring the safe operation of the distribution transformers.
In order to achieve the above object, the method for evaluating risk of a distribution transformer based on multi-source information includes:
the method comprises the following steps: the distribution transformers are numbered in a single way, and each transformer is connected to a main signal line through a secondary signal line to transmit signals to a host;
step two: detecting temperature and humidity data of the environment where each transformer is located by using a temperature and humidity sensor; detecting oil chromatographic data of each transformer by using an oil chromatographic analyzer; detecting winding hot spot temperature data of each transformer by using a winding thermometer; detecting the running current of each transformer by using a current transformer; detecting a vibration signal of each transformer by using a vibration sensor; detecting a partial discharge ultrasonic signal of each transformer by using an ultrasonic sensor;
step three: evaluating the real-time oil chromatogram monitoring data of the transformer to obtain the comprehensive health index of the transformer;
step four: calculating the fault probability and the fault frequency level of the transformer according to the comprehensive health index of the transformer and the adopted fault rate model;
step five: establishing a transformer risk consequence evaluation set to obtain the transformer risk severity grade; analyzing real-time monitoring data of winding hot spot temperature, vibration, iron core grounding current and local discharge ultrasonic signals of the transformer to obtain fault types of the transformer;
step six: obtaining the comprehensive risk grade of the transformer by combining the fault rate grade and the risk severity grade of the transformer; a buzzer is used for carrying out multi-stage alarm; and displaying the interface of the transformer risk evaluation system by using an LED display, displaying data information of the transformer, such as real-time environment temperature and humidity, an oil chromatogram, winding hot spot temperature, current, vibration signals, partial discharge ultrasonic signals and the like, and a risk value, a risk grade and a corresponding fault type of the transformer.
According to the scheme, in the second step, all the obtained detection data are transmitted to the host computer for storage and processing.
According to the scheme, in the third step, the method for evaluating the oil chromatogram real-time monitoring data of the transformer to obtain the comprehensive health index of the transformer comprises the following steps:
the absolute gas production rate calculation formula of the dissolved gas in the oil is as follows:
in the formula, gammaαIndicating the absolute gas production rate, mL/day; ci,2And Ci,1Respectively representing the concentration of a certain gas in the oil sampled for the second time and the first time, mu L/L; Δ t represents the actual running time in the time interval of two samplings, days; m represents total oil quantity of equipment, t; ρ represents the density of the oil, t/m3；
Calculating the absolute gas production rates of hydrogen, acetylene, total hydrocarbon, carbon monoxide and carbon dioxide to obtain corresponding state indexes, wherein the state indexes corresponding to the absolute gas production rates are shown in table 1;
TABLE 1 State index corresponding to Absolute gas production Rate
Hydrogen gas state index through transformer is denoted H1Acetylene state index H2The total hydrocarbon index means H3Carbon monoxide state index H4And carbon dioxide State index H5Obtaining the comprehensive health index H of the transformer, wherein the value range is [0,100 ]]：
Obtaining the comprehensive health index H of the transformer:
H＝(H1+H2+H3+H4+H5)α
wherein: α is an internal insulation state of the transformer, and the internal insulation state of the transformer is classified into 5 levels, i.e., a good state, a normal state, a degraded state, and a severe state, and is set to {0.15,0.4,0.6,0.8,1}, respectively.
According to the scheme, in the fourth step, according to the comprehensive health index of the transformer and the adopted fault rate model, the method for calculating the fault probability and the fault frequency level of the transformer comprises the following steps:
the mathematical model between the failure probability and the composite health index is:
p＝KeHC
k is a proportionality coefficient, C is a curvature coefficient, and the proportionality coefficient and the curvature coefficient are obtained through historical operation data of the transformer;
the failure probability of each part of the transformer can be obtained by calculation, and the failure frequency of the transformer is divided into 4 grades as shown in table 2.
TABLE 2 Fault frequency rating
| Frequency of failure | Probability of failure P |
| Can make it possible to | P≥0.15 |
| Occasionally, the patient is | 0.05≤P<0.15 |
| Is rarely used | 0.02≤P<0.05 |
| Can be ignored | p<0.02 |
According to the scheme, in the fifth step, a transformer risk consequence evaluation set is established, and the method for obtaining the transformer risk severity grade comprises the following steps:
set the evaluation index set U ═ U { U } of the severity of transformer risk1，u2，u3The assessment set is V ═ V, { asset loss, environmental impact, safety loss }, the assessment set is V ═ V }1，v2，v3As shown in table 3. Selecting the maximum grade v in the evaluation set according to the maximum membership rulejAs a transformer severity rating.
TABLE 3 severity rating
According to the scheme, in the fifth step, real-time monitoring data of winding hot spot temperature, vibration, iron core grounding current and partial discharge ultrasonic signals of the transformer are analyzed, and the fault type of the transformer is obtained by the following method:
(1) analysis of winding hotspot temperature: when the winding hot spot temperature detected by the winding thermometer exceeds 85 ℃, the system gives an alarm, and the fault type is winding fault;
(2) analysis of vibration signal: setting the maximum vibration value of the transformer in normal operation under the condition of maximum load as a threshold value, and when the vibration value of the real-time monitoring quantity is greater than the threshold value, giving an alarm by a system, wherein the fault type is an iron core fault or a winding fault;
(3) analysis of core grounding current: the system selects a sensor of the through permalloy to collect the grounding current of the iron core, when the grounding current of the iron core is more than 0.1A, the system gives an alarm, and the fault type is the grounding fault of the iron core;
(4) analysis of the local discharge ultrasound signal: and detecting an amplitude map with a partial discharge signal frequency band of 20-200 kHz, and giving an alarm by a system when the amplitude is greatly changed compared with the amplitude map in normal operation, wherein the fault type is an insulation medium fault.
According to the scheme, in the sixth step, the method for obtaining the comprehensive risk grade of the transformer by combining the fault rate grade and the risk severity grade of the transformer and combining the fault rate grade and the risk severity grade of the transformer comprises the following steps:
constructing a transformer risk evaluation matrix according to the fault rate grade and the severity grade, and finally obtaining the comprehensive risk grade of the transformer as shown in table 4;
TABLE 4 Transformer Risk assessment matrix Table
A, B, C and D represent the good, caution, abnormal and severe four operating states of the transformer, respectively;
good: no alarm is given;
note that: performing primary alarm to strengthen operation monitoring;
exception: performing secondary alarm, and timely arranging power failure maintenance;
severe: and carrying out three-level alarm and arranging power failure maintenance as soon as possible.
The invention provides a distribution transformer risk assessment system based on multi-source information, which is characterized in that a detection system comprises:
the power supply module is a 50Hz 220V alternating current power supply and a distributed power supply module and is used for supplying power to all devices and sensors in the plurality of transformer devices;
the signal detection module comprises a temperature and humidity sensor, an oil chromatographic analyzer, a voltage current transformer, a winding thermometer, a vibration sensor, an ultrasonic sensor and an anti-interference iron core;
the data processing module comprises sensor edge processing and host centralized processing, wherein the sensor edge processing is used for processing data acquired by each sensor on site and sending the processed data to the host, and the host centralized processing comprises risk calculation and fault type diagnosis;
the communication module comprises a wired communication module and a wireless communication module, the wired communication module is mainly used for one-to-many communication and field data reading of the signal bus and the signal auxiliary line, and the wireless communication module is used for real-time monitoring and background communication of the handheld terminal to realize remote monitoring and online risk assessment of the state of the transformer;
and the output module comprises a storage module and an alarm module, the storage module consists of a data memory and stores the operation data, the risk assessment result, the related oscillogram and the like, the alarm module comprises an LED display and a buzzer, the LED display is used for displaying the operation state of the sensor, and the buzzer is used for the graded alarm of the risk assessment of the transformer.
The invention has the following advantages:
the invention collects various index parameters related to the running state of the distribution transformer based on various sensors, including current, voltage, ultrasonic partial discharge, abnormal vibration, winding hot point temperature, vibration signal and other state information, can simultaneously monitor the running states and environments of the distribution transformers in real time, and can increase or decrease the number of the sensors according to the user requirements; according to the invention, the comprehensive health index is obtained by utilizing the oil chromatographic data and the insulation state, so that the fault probability and the fault frequency level of the transformer are obtained, and meanwhile, various monitoring data are analyzed to obtain the fault type; establishing a transformer risk consequence evaluation set, obtaining a transformer risk severity grade by adopting a multi-level fuzzy analysis method, and obtaining a transformer risk grade by combining a fault frequency grade and the risk severity grade; the buzzer is used for giving a multi-stage alarm to each transformer, so that the accuracy of risk assessment of the transformers can be improved, and effective help can be provided for actual engineering; the system has the advantages of high monitoring precision, strong compatibility and low economic cost, and is convenient for maintenance personnel to find the problems of the transformer in time and ensure the reliability of the operation of the transformer.
Drawings
FIG. 1 is a flow chart of a risk assessment method for a distribution transformer based on multi-source information according to the present invention;
FIG. 2 is a flowchart illustrating the operation of the risk assessment system of the present invention;
FIG. 3 is a schematic diagram of a risk assessment system according to the present invention;
the temperature and humidity sensor comprises a temperature and humidity sensor 1, a winding thermometer 2, an ultrasonic sensor 3, a vibration sensor 4, a terminal 5, an anti-interference iron core 6, a power bus 7, a buzzer 8, a LORA communication module 9, a host computer 10, an LED display 11, an oil chromatographic analyzer 12, a voltage current transformer 13, a distribution transformer body 14 and a data memory 15.
Detailed Description
The invention is described in further detail below with reference to the accompanying drawings and the detailed description;
the invention relates to a distribution transformer risk assessment method based on multi-source information, which comprises the following steps of:
the method comprises the following steps: a plurality of distribution transformers are numbered in a single way, and each transformer is connected to a main signal line through a secondary signal line to transmit signals to a host 10;
a plurality of distribution transformer singles are defined as 001, 002, 003, 004, 005, … ….
Step two: detecting temperature and humidity data of the environment where each transformer 14 is located by using the temperature and humidity sensor 1; detecting hot spot temperature data of each transformer winding by using a winding thermometer 2; detecting the running current of each transformer by using a current transformer 13; detecting each transformer vibration signal by using the vibration sensor 4; detecting a partial discharge ultrasonic signal of each transformer by using the ultrasonic sensor 6; detecting the oil chromatographic data of each transformer by using an oil chromatographic analyzer 12;
step three: evaluating the real-time oil chromatogram monitoring data of the transformer to obtain the comprehensive health index of the transformer;
step four: calculating the fault probability and the fault frequency level of the transformer according to the comprehensive health index of the transformer and the adopted fault rate model;
step five: establishing a transformer risk consequence evaluation set to obtain the transformer risk severity grade; analyzing real-time monitoring data of winding hot spot temperature, vibration, iron core grounding current and local discharge ultrasonic signals of the transformer to obtain fault types of the transformer;
step six: obtaining the comprehensive risk grade of the transformer by combining the fault rate grade and the risk severity grade of the transformer; a buzzer is used for carrying out multi-stage alarm; and displaying the interface of the transformer risk evaluation system by using an LED display, displaying data information of the transformer, such as real-time environment temperature and humidity, an oil chromatogram, winding hot spot temperature, current, vibration signals, partial discharge ultrasonic signals and the like, and a risk value, a risk grade and a corresponding fault type of the transformer.
Step three, the method for analyzing the oil chromatogram real-time monitoring data of the transformer to obtain the comprehensive health index comprises the following steps:
(1) calculating the absolute gas production rate of the dissolved gas in the oil
The absolute gas production rate calculation formula of the dissolved gas in the oil is as follows:
in the formula, gammaαIndicating the absolute gas production rate, mL/day; ci,2And Ci,1Respectively representing the concentration of a certain gas in the oil sampled for the second time and the first time, mu L/L; Δ t represents the actual running time in the time interval of two samplings, days; m represents total oil quantity of equipment, t; ρ represents the density of the oil, t/m3；
Calculating the absolute gas production rates of hydrogen, acetylene, total hydrocarbon, carbon monoxide and carbon dioxide to obtain corresponding state indexes, wherein the state indexes corresponding to the absolute gas production rates are shown in table 1;
TABLE 1 State index corresponding to Absolute gas production Rate
(2) Calculating a composite health index
Hydrogen gas state index through transformer is denoted H1Acetylene state index H2The total hydrocarbon index means H3Carbon monoxide state index H4And carbon dioxide State index H5Obtaining the comprehensive health index H of the transformer, wherein the value range is [0,100 ]]：
Obtaining the comprehensive health index H of the transformer:
H＝(H1+H2+H3+H4+H5)α
wherein: α is an internal insulation state of the transformer, and the internal insulation state of the transformer is classified into 5 levels, i.e., a good state, a normal state, a degraded state, and a severe state, and is set to {0.15,0.4,0.6,0.8,1}, respectively.
Step four, the method for calculating the fault probability and the fault frequency level of the transformer according to the comprehensive health index of the transformer and the adopted fault rate model comprises the following steps:
the mathematical model between the failure probability and the composite health index is:
p＝KeHC
k is a proportionality coefficient, C is a curvature coefficient, and the proportionality coefficient and the curvature coefficient are obtained through historical operation data of the transformer;
the failure probability of each part of the transformer can be obtained by calculation, and the failure frequency of the transformer is divided into 4 grades as shown in table 2.
TABLE 2 Fault frequency rating
| Frequency of failure | Probability of failure P |
| Can make it possible to | P≥0.15 |
| Occasionally, the patient is | 0.05≤P<0.15 |
| Is rarely used | 0.02≤P<0.05 |
| Can be ignored | p<0.02 |
Step five, establishing a transformer risk consequence evaluation set to obtain a transformer risk severity grade according to the following method:
set the evaluation index set U ═ U { U } of the severity of transformer risk1，u2，u3The assessment set is V ═ V, { asset loss, environmental impact, safety loss }, the assessment set is V ═ V }1，v2，v3As shown in table 3. Selecting the maximum grade v in the evaluation set according to the maximum membership rulejAs a transformer severity rating.
TABLE 3 severity rating
Analyzing real-time monitoring data of winding hot spot temperature, vibration, iron core grounding current and partial discharge ultrasonic signals of the transformer to obtain fault types of the transformer, wherein the method comprises the following steps:
(1) analysis of winding hotspot temperature: when the winding hot spot temperature detected by the winding thermometer exceeds 85 ℃, the system gives an alarm, and the fault type is winding fault;
(2) analysis of vibration signal: setting the maximum vibration value of the transformer in normal operation under the condition of maximum load as a threshold value, and when the vibration value of the real-time monitoring quantity is greater than the threshold value, giving an alarm by a system, wherein the fault type is an iron core fault or a winding fault;
(3) analysis of core grounding current: the system selects a sensor of the through permalloy to collect the grounding current of the iron core, when the grounding current of the iron core is more than 0.1A, the system gives an alarm, and the fault type is the grounding fault of the iron core;
(4) analysis of the local discharge ultrasound signal: in the embodiment of the invention, 3 transformer ultrasonic partial discharge sensors are arranged in the transformer risk evaluation system, ultrasonic signals acquired by each sensor are converted into an effective frequency band of 20-200 kHz to obtain an amplitude map, and when the amplitude is greatly changed compared with the amplitude map in normal operation, the system gives an alarm, and the fault type is an insulating medium fault.
Step six, the method for obtaining the comprehensive risk grade of the transformer by combining the fault rate grade and the risk severity grade of the transformer comprises the following steps:
constructing a transformer risk evaluation matrix according to the fault rate grade and the severity grade, and finally obtaining the comprehensive risk grade of the transformer as shown in table 4;
TABLE 4 Transformer Risk assessment matrix Table
A, B, C and D represent the good, caution, abnormal and severe four operating states of the transformer, respectively;
good: no alarm is given;
note that: performing primary alarm to strengthen operation monitoring;
exception: performing secondary alarm, and timely arranging power failure maintenance;
severe: and carrying out three-level alarm and arranging power failure maintenance as soon as possible.
The invention provides a distribution transformer risk assessment system based on multi-source information, which comprises:
the power supply module is a 50Hz 220V alternating current power supply and a distributed power supply module and is used for supplying power to all devices and sensors in the plurality of transformer devices;
the signal detection module comprises a temperature and humidity sensor 1, an oil chromatographic analyzer 12, a voltage current transformer 13, a winding thermometer 2, a vibration sensor 4, an ultrasonic sensor 3 and an anti-interference iron core 6;
the data processing module comprises sensor edge processing and host centralized processing, wherein the sensor edge processing is used for processing data acquired by each sensor on site and sending the processed data to the host, and the host centralized processing comprises risk calculation and fault type diagnosis;
the communication module comprises a wired communication module and a wireless communication module, the wired communication module is mainly used for one-to-many communication and field data reading of the signal bus and the signal auxiliary line, and the wireless communication module is used for real-time monitoring and background communication of the handheld terminal to realize remote monitoring and online risk assessment of the state of the transformer;
and the output module comprises a storage module and an alarm module, the storage module consists of a data storage 14 and stores the operation data, the risk assessment result, the related oscillogram and the like, the alarm module comprises an LED display 11 and a buzzer 8, the LED11 display is used for displaying the operation state of the sensor, and the buzzer 8 is used for the graded alarm of the risk assessment of the transformer.
The above-mentioned embodiments only express the embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent should be subject to the appended claims.
Example analysis
The analysis is carried out by taking a distribution transformer with the capacity of 800kVA of a certain oil-gas platform as an example. The operation test data are shown in Table 4, the data of the gas dissolved in the oil extracted one day before and after the operation test are shown in Table 5, the severity evaluation table is shown in Table 6, and the density of the transformer oil is 895kg/m3The total oil amount is 685kg, the internal insulation state is a good state, the proportionality coefficient K is 0.13069, the curvature coefficient C is-0.071, the asset loss when the transformer fails belongs to a major transformer equipment damage accident, the caused environmental impact is light pollution, and the safety loss is a general personal accident.
Table 4 distribution transformer data
TABLE 5 dissolved gas content in oil
The diagnostic procedure was as follows:
(1) calculating the absolute gas production rate:
hydrogen gas:
acetylene:
total hydrocarbons:
carbon monoxide:
carbon dioxide:
(2) comprehensive health index:
according to Table 1, the hydrogen state index H can be obtained1Acetylene state index H2The total hydrocarbon index means H3Carbon monoxide state index H4And carbon dioxide State index H5Respectively as follows: 3,8,3.5,6,7.8.
Combined health index H ═ H (H)1+H2+H3+H4+H5)α＝28.3*0.4＝11.32
(3) Failure probability and failure frequency:
p＝KeHC＝0.13069e11.32*0.071＝5.87％
according to Table 2, when P <0.15 is 0.05. ltoreq.P, the corresponding frequency of failure is occasional.
(4) Establishing an evaluation set to obtain a severity grade:
set the evaluation index set U ═ U { U } of the severity of transformer risk1，u2，u3The assessment set is V ═ V, { asset loss, environmental impact, safety loss }, the assessment set is V ═ V }1，v2，v3And f, according to the known evaluation set V, setting the final severity level as two levels according to the maximum membership rule.
(5) Analyzing the monitoring data to obtain possible fault types:
according to the national standard regulation and the normal operation parameter range of the transformer with the same model, the determined index threshold value is shown in the table 6.
TABLE 6 parameter threshold table
| Index (I) | Threshold value |
| Temperature of hot spot winding (. degree. C.) | 85 |
| Amplitude of vibration signal (V) | 2 |
| Ultrasonic signal amplitude (mV) | 30 |
| Iron core grounding current (A) | 0.1A |
The winding hot spot temperature detected by the winding thermometer does not exceed 85 ℃, and the normal operation is realized; the grounding current of the iron core is 0.07A less than 0.1A, and the normal state is realized; the amplitude of the ultrasonic signal is 3.47mV which is less than 30mV and is normal; the amplitude of the vibration signal is 2.1V and is larger than 2V, and the transformer may have iron core faults or winding faults;
in conclusion, the fault probability of the transformer is 5.87%, the fault frequency level is occasional, the severity level is second level, the possible fault types are iron core faults or winding faults, the comprehensive risk level is abnormal, the buzzer carries out second-level alarm, and power failure maintenance is arranged timely.
Claims (8)
1. A distribution transformer risk assessment method based on multi-source information is characterized by comprising the following steps:
the method comprises the following steps: the distribution transformers are numbered in a single way, and each transformer is connected to a main signal line through a secondary signal line to transmit signals to a host;
step two: detecting temperature and humidity data of the environment where each transformer is located by using a temperature and humidity sensor; detecting oil chromatographic data of each transformer by using an oil chromatographic analyzer; detecting winding hot spot temperature data of each transformer by using a winding thermometer; detecting the running current of each transformer by using a current transformer; detecting a vibration signal of each transformer by using a vibration sensor; detecting a partial discharge ultrasonic signal of each transformer by using an ultrasonic sensor;
step three: evaluating the real-time oil chromatogram monitoring data of the transformer to obtain the comprehensive health index of the transformer;
step four: calculating the fault probability and the fault frequency level of the transformer according to the comprehensive health index of the transformer and the adopted fault rate model;
step five: establishing a transformer risk consequence evaluation set to obtain the transformer risk severity grade; analyzing real-time monitoring data of winding hot spot temperature, vibration, iron core grounding current and local discharge ultrasonic signals of the transformer to obtain fault types of the transformer;
step six: obtaining the comprehensive risk grade of the transformer by combining the fault rate grade and the risk severity grade of the transformer; a buzzer is used for carrying out multi-stage alarm; and displaying the interface of the transformer risk evaluation system by using an LED display, displaying data information of the transformer, such as real-time environment temperature and humidity, an oil chromatogram, winding hot spot temperature, current, vibration signals, partial discharge ultrasonic signals and the like, and a risk value, a risk grade and a corresponding fault type of the transformer.
2. The multi-source information-based distribution transformer risk assessment method of claim 1, wherein: in the second step, all the obtained detection data are transmitted to the host computer for storage and processing.
3. The multi-source information-based distribution transformer risk assessment method of claim 1, wherein: step three, the method for analyzing the oil chromatogram real-time monitoring data of the transformer to obtain the comprehensive health index comprises the following steps:
the absolute gas production rate calculation formula of the dissolved gas in the oil is as follows:
in the formula, gammaαIndicating the absolute gas production rate, mL/day; ci,2And Ci,1Respectively representing the concentration of a certain gas in the oil sampled for the second time and the first time, mu L/L; Δ t represents the actual running time in the time interval of two samplings, days; m represents total oil quantity of equipment, t; ρ represents the density of the oil, t/m3；
Calculating the absolute gas production rates of hydrogen, acetylene, total hydrocarbon, carbon monoxide and carbon dioxide to obtain corresponding state indexes, wherein the state indexes corresponding to the absolute gas production rates are shown in table 1;
TABLE 1 State index corresponding to Absolute gas production Rate
Hydrogen state index through transformer indicates H1Acetylene state index H2The total hydrocarbon index means H3Carbon monoxide state index H4And carbon dioxide State index H5Obtaining the comprehensive health index H of the transformer, wherein the value range is [0,100 ]]：
H＝(H1+H2+H3+H4+H5)α
Wherein: α is an internal insulation state of the transformer, and the internal insulation state of the transformer is classified into 5 levels, i.e., a good state, a normal state, a degraded state, and a severe state, and is set to {0.15,0.4,0.6,0.8,1}, respectively.
4. The multi-source information-based distribution transformer risk assessment method of claim 1, wherein: step four, the method for calculating the fault probability and the fault frequency level of the transformer according to the comprehensive health index of the transformer and the adopted fault rate model comprises the following steps:
the mathematical model between the failure probability and the composite health index is:
p＝KeHC
k is a proportionality coefficient, C is a curvature coefficient, and the proportionality coefficient and the curvature coefficient are obtained through historical operation data of the transformer;
the failure probability of each part of the transformer can be obtained by calculation, and the failure frequency of the transformer is divided into 4 grades as shown in table 2.
TABLE 2 Fault frequency rating
5. The multi-source information-based distribution transformer risk assessment method of claim 1, wherein: step five, establishing a transformer risk consequence evaluation set to obtain a transformer risk severity grade according to the following method:
set the evaluation index set U ═ U { U } of the severity of transformer risk1，u2，u3The assessment set is V ═ V, { asset loss, environmental impact, safety loss }, the assessment set is V ═ V }1，v2，v3As shown in table 3. Selecting the maximum grade v in the evaluation set according to the maximum membership rulejAs a transformer severity rating.
TABLE 3 severity rating
6. The multi-source information-based distribution transformer risk assessment method of claim 1, wherein: the method for analyzing various monitoring data to obtain the fault type of the transformer comprises the following steps:
(1) analysis of winding hotspot temperature: when the winding hot spot temperature detected by the winding thermometer exceeds 85 ℃, the system gives an alarm, and the fault type is winding fault;
(2) analysis of vibration signal: setting the maximum vibration value of the transformer in normal operation under the condition of maximum load as a threshold value, and when the vibration value of the real-time monitoring quantity is greater than the threshold value, giving an alarm by a system, wherein the fault type is an iron core fault or a winding fault;
(3) analysis of core grounding current: the system selects a sensor of the through permalloy to collect the grounding current of the iron core, when the grounding current of the iron core is more than 0.1A, the system gives an alarm, and the fault type is the grounding fault of the iron core;
(4) analysis of the local discharge ultrasound signal: and detecting an amplitude map with a partial discharge signal frequency band of 20-200 kHz, and giving an alarm by a system when the amplitude is greatly changed compared with the amplitude map in normal operation, wherein the fault type is an insulation medium fault.
7. The multi-source information-based distribution transformer risk assessment method of claim 1, wherein: step six, the method for obtaining the comprehensive risk grade of the transformer by combining the fault rate grade and the risk severity grade of the transformer comprises the following steps:
constructing a transformer risk evaluation matrix according to the fault rate grade and the severity grade, and finally obtaining the comprehensive risk grade of the transformer as shown in table 4;
TABLE 4 Transformer Risk assessment matrix Table
A, B, C and D represent the good, caution, abnormal and severe four operating states of the transformer, respectively;
good: no alarm is given;
note that: performing primary alarm to strengthen operation monitoring;
exception: performing secondary alarm, and timely arranging power failure maintenance;
severe: and carrying out three-level alarm and arranging power failure maintenance as soon as possible.
8. A distribution transformer risk assessment system based on multi-source information, the detection system comprising:
the power supply module is a 50Hz 220V alternating current power supply and a distributed power supply module and is used for supplying power to all devices and sensors in the plurality of transformer devices;
the signal detection module comprises a temperature and humidity sensor, an oil chromatographic analyzer, a voltage current transformer, a winding thermometer, a vibration sensor, an ultrasonic sensor and an anti-interference iron core;
the data processing module comprises sensor edge processing and host centralized processing, wherein the sensor edge processing is used for processing data acquired by each sensor on site and sending the processed data to the host, and the host centralized processing comprises risk calculation and fault type diagnosis;
the communication module comprises a wired communication module and a wireless communication module, the wired communication module is mainly used for one-to-many communication and field data reading of the signal bus and the signal auxiliary line, and the wireless communication module is used for real-time monitoring and background communication of the handheld terminal to realize remote monitoring and online risk assessment of the state of the transformer;
and the output module comprises a storage module and an alarm module, the storage module consists of a data memory and stores the operation data, the risk assessment result, the related oscillogram and the like, the alarm module comprises an LED display and a buzzer, the LED display is used for displaying the operation state of the sensor, and the buzzer is used for the graded alarm of the risk assessment of the transformer.
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