A non-electric quantity monitoring and diagnosis method and system for oil-immersed transformers

Abstract

A non - electrical quantity monitoring and diagnosis method for oil - immersed transformers. The monitoring and diagnosis method includes the following steps: S1: Use the non - electrical quantity information acquisition front - end in the non - electrical quantity monitoring and diagnosis system to collect the non - electrical quantity information of the oil - immersed transformer; S2: Collect the collected non - electrical quantity information to the collection terminal of the local control cabinet, and the collection terminal of the local control cabinet transmits the collected non - electrical quantity information to the server, and centrally monitors each non - electrical quantity information through the server; S3: Establish a non - electrical quantity database and calculate the non - electrical quantity health index H. Arrange a variety of collection terminals on the transformer body to form a centralized monitoring of each non - electrical quantity under a unified time scale, establish a non - electrical quantity monitoring operation database, based on the monitored historical data and statistical principles, match and search the monitoring data with the confidence interval under the confidence level, obtain the support degree of the specific non - electrical quantity for the normal operation of the transformer, and calculate the corresponding non - electrical quantity health index according to the weight to determine the state of the transformer.

Description

Technical Field

[0001] The invention belongs to the field of power equipment transformers, and particularly relates to a non-electric quantity monitoring and diagnosis method and system for oil-immersed transformers. Background Art

[0002] When low-energy faults such as slight inter-turn faults and partial discharges occur inside the transformer, as well as non-electrical faults such as core heating, the gas generated in the oil causes oil flow surges and pressure increases. The non-electrical quantity protection composed of fault characteristics such as gas, oil flow, and pressure has higher sensitivity to internal weak faults than electrical quantity protection. The accurate acquisition of non-electrical quantity information during the operation of the transformer can perceive the equipment status. The traditional method for collecting non-electrical quantity data of transformers is to regularly go to the site to read meters and conduct inspections. During peak summer or major events, more frequent on-site inspections are required to check the gas volume and the action traces of the pressure relief valve, etc. However, the changes in the light gas volume, pressure, and temperature of the transformer body during the interval between meter reading and inspection are unknown, which is likely to cause the problem of data gaps.

[0003] Currently, the parameters reflecting the transformer status involve multiple physical quantities such as gas, temperature, pressure, and oil flow. Although the existing sensing and acquisition technologies can also perform certain measurements, each monitoring terminal only displays the meters locally. Although the online monitoring technology for the light and heavy gas volumes has been piloted, its analysis of gas components and measurement accuracy of the heavy gas oil flow rate are insufficient, and the developed monitoring of the light and heavy gas volumes is carried out separately without unified integration, failing to meet the requirement of unified time scale for comprehensive analysis. When using non-electrical quantity information for transformer fault diagnosis, it is usually to take oil samples and conduct gas analysis for fault diagnosis after the transformer alarm action. This method takes a long time and the identification means are relatively single. Summary of the Invention

[0004] To solve the deficiencies in the prior art, the invention provides a non-electric quantity monitoring and diagnosis method and system for oil-immersed transformers. By establishing real-time centralized monitoring and status diagnosis of centralized multi-parameter non-electric quantities, early warning signals are sent out before serious faults occur, improving the perception ability of the transformer status, giving early warnings to possible faults, and eliminating potential safety hazards.

[0005] The invention adopts the following technical solutions:

[0006] A non-electric quantity monitoring and diagnosis method for an oil-immersed transformer, the monitoring and diagnosis method comprising the following steps:

[0007] S1: Use the non-electric quantity information acquisition front end in the non-electric quantity monitoring and diagnosis system to monitor and collect the non-electric quantity information of the oil-immersed transformer;

[0008] S2: Collect the non-electric quantity information and gather it at the local control cabinet aggregation terminal. Then, the local control cabinet aggregation terminal transfers the collected non-electric quantity information to the server, and the server conducts centralized monitoring on each non-electric quantity information.

[0009] S3: The server establishes a non-electric quantity database, calculates the non-electric quantity health index H, and conducts non-electric quantity monitoring and diagnosis on the oil-immersed transformer according to the non-electric quantity health index H.

[0010] As a preferred embodiment of the present invention, in the step S1, the non-electric quantity information of the oil-immersed transformer includes temperature, pressure, light gas volume, light gas components, and heavy gas oil flow rate.

[0011] As a preferred embodiment of the present invention, the temperature and pressure are monitored and collected through a temperature sensor and a first pressure sensor.

[0012] The light gas components are obtained through spectral analysis.

[0013] As a preferred embodiment of the present invention, the monitoring and collection method of the light gas volume is as follows:

[0014] The pressure is monitored by a second pressure sensor installed at the bottom inside the gas relay. When different volumes of gas are filled inside the gas relay, the liquid level height is different, and the pressure monitored by the second pressure sensor is different. Therefore, the gas volume can be calibrated by the pressure monitored by the second pressure sensor to achieve the monitoring and collection of the light gas volume.

[0015] As a preferred embodiment of the present invention, the specific process of calibrating the gas volume of the light gas by the pressure monitored by the second pressure sensor to achieve the monitoring and collection of the light gas volume is as follows:

[0016] Fill the gas relay, that is, the gas relay, with insulating oil, and then introduce gas until the liquid level drops to the scale one of the observation window and stop. At this time, the internal gas volume of the gas relay is V1, record the corresponding output value P1 of the second pressure sensor, continue to introduce gas until the next observation window scale two, at this time the internal gas volume of the gas relay is V2, and continue to record the corresponding output value P2 of the second pressure sensor until all the output values corresponding to the scales on the observation window are recorded, and establish a corresponding relationship set between the pressure collected by the second pressure sensor and the light gas volume. Based on this corresponding relationship set, the internal gas volume V of the gas can be mapped correspondingly according to the specific monitored pressure P of the second pressure sensor installed at the bottom of the gas relay.

[0017] As a preferred embodiment of the present invention, the heavy gas oil flow rate is monitored and collected by using the ultrasonic velocity measurement principle. Specifically:

[0018] An ultrasonic velocity detector is installed at the oil pipe between the conservator and the transformer, and the included angle between the ultrasonic transmitter and the horizontal direction of the oil pipe is θ. The frequency of the ultrasonic wave it emits is f1, and the frequency of the received reflected ultrasonic wave is f2. Then the oil flow velocity in the pipeline is:

[0019]

[0020] Where c is the propagation speed of ultrasonic waves in the pipeline fluid.

[0021] As a preferred embodiment of the present invention, in step S2, the NTP protocol is used to adjust the time synchronization between the non-electric quantity information acquisition front end and the server, and then the server centrally monitors each non-electric quantity information. The specific time synchronization steps are as follows:

[0022] S2.1: The non-electric quantity information acquisition front end sends an NTP data packet to the server, and adds the time stamp t1 when leaving the non-electric quantity information acquisition front end in the NTP data packet;

[0023] S2.2: The server receives the NTP data packet sent by the non-electric quantity information acquisition front end at time t2, sends the NTP data packet back to the non-electric quantity information acquisition front end at time t3, and adds the time stamp t2 and the time stamp t3 in the NTP data packet;

[0024] S2.3: The non-electric quantity information acquisition front end receives the NTP data packet sent by the server at time t4, and adds the time stamp t4 in the NTP data packet;

[0025] S2.4: Calculate the time difference τ according to t1, t2, t3, and t4:

[0026]

[0027] After calculating the time difference τ, the server uses its own T0 as a reference to perform time compensation processing on the data transmitted by the non-electric quantity information acquisition front end:

[0028]

[0029] In the formula:

[0030] is the i-th non-electric quantity information collected at time T0 in the server;

[0031] is the i-th non-electric quantity information at time T0 - τ transmitted from the front end;

[0032] i takes values from 1 to 5, respectively representing the volume of light gas, the composition of light gas, the heavy gas oil flow, temperature, and pressure.

[0033] As a preferred embodiment of the present invention, in step S3, the calculation steps of the non-electricity health index H are as follows:

[0034] S3.1: Establish a non-electricity database, and establish data sets for the non-electricity information monitored and operated in their respective dimensions to obtain a data set B = (B 1 , B 2 , B 3 , B i ), where i is the characteristic dimension of the non-electricity, and each dimension set is a subset of the non-electricity historical data within that dimension, that is n is the total number of data in the corresponding subset;

[0035] S3.2: According to statistics, the data set B conforms to a normal distribution, that is Among them, μ and respectively represent the mean and variance of the normal distribution. The calculation formulas for the mean and variance of the i-th dimensional non-electricity information are as follows:

[0036]

[0037] According to the variance and the mean, combined with the given confidence level, a specific confidence interval is obtained:

[0038]

[0039] Among them, when the confidence level is 90%, the parameter c is 1.64; when the confidence level is 95%, c is 1.96; when the confidence level is 99%, c is 2.58;

[0040] S3.3: Perform matching diagnosis on the monitored non-electricity. According to whether it falls within the confidence interval, obtain the support degree of the specific dimensional non-electricity for the normal operation state of the transformer. Match the non-electricity monitoring information of each dimension with the confidence interval. When it falls within the confidence interval, it is determined that the transformer state reflected by the non-electricity of this dimension at this moment is normal. The criterion formula is:

[0041]

[0042] The calculation rule for the support degree of the i-th dimensional non-electricity for the normal operation state of the transformer is: when the monitoring information of the i-th dimensional non-electricity satisfies the criterion, the support degree Wi of this non-electricity is 1; otherwise, Wi = 0;

[0043] S3.4: Calculate the non-electricity health index H reflecting the operation state of the transformer according to the specific non-electricity support degree:

[0044]

[0045] In the formula:

[0046] m is the total number of non - electrical state dimensions of the transformer used;

[0047] Wi is the support degree of the i - th non - electrical quantity;

[0048] Qi is the weight of the i - th non - electrical quantity, which takes a value in the range of (0, 1). The higher the value, the higher the support degree for the healthy operation state of the transformer when this non - electrical quantity is normal.

[0049] As a preferred embodiment of the present invention, in step 3, a health index limit value H set , is set. When the non - electrical health index H < H set , the non - electrical monitoring and diagnosis system issues an alarm of "non - electrical abnormality, suspected fault". When H ≥ H set , the diagnosis system determines that the transformer is in a "non - electrical normal" state.

[0050] A non - electrical monitoring and diagnosis system for an oil - immersed transformer, which is used to implement the above - mentioned monitoring and diagnosis method, includes: a non - electrical information acquisition front - end, a local control cabinet aggregation terminal, and a server; the non - electrical information acquisition front - end collects the non - electrical information of the oil - immersed transformer and hands it over to the local control cabinet aggregation terminal for aggregation. The local control cabinet aggregation terminal is connected to the server through an RS485 communication line and hands over the aggregated non - electrical information to the server for monitoring and diagnosis.

[0051] As a preferred embodiment of the present invention, the non - electrical information acquisition front - end includes a temperature monitoring module, a pressure monitoring module, a heavy gas oil flow monitoring module, a light gas volume monitoring and composition analysis module.

[0052] As a preferred embodiment of the present invention, the temperature monitoring module includes a temperature sensor.

[0053] As a preferred embodiment of the present invention, the pressure monitoring module includes a first pressure sensor;

[0054] As a preferred embodiment of the present invention, the heavy gas oil flow monitoring module includes an ultrasonic speed detector.

[0055] As a preferred embodiment of the present invention, the light gas volume monitoring and composition analysis module includes a second pressure sensor and a light gas composition analysis component.

[0056] As a preferred embodiment of the present invention, the light gas composition analysis component includes a main control unit, a gas sampling unit, and a gas detection unit.

[0057] As a preferred embodiment of the present invention, the gas sampling unit includes a waste oil tank and a gas collection box, and the waste oil tank and the gas collection box are connected through a third solenoid valve and a fourth solenoid valve.

[0058] As a preferred embodiment of the present invention, the gas collecting box is connected to the gas relay through the first solenoid valve.

[0059] As a preferred embodiment of the present invention, the gas collecting box is connected to the infrared spectrometer of the gas detection unit through the second solenoid valve.

[0060] As a preferred embodiment of the present invention, the main control unit is electrically connected to the gas relay and the infrared spectrometer respectively.

[0061] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0062] An oil-immersed transformer non-electrical quantity monitoring and diagnosis method and system disclosed by the present invention arranges a variety of acquisition terminals on the transformer body to form centralized monitoring of each non-electrical quantity under a unified time scale, which is more conducive to mastering the non-electrical quantity state of the overall operation of the transformer. In addition, a non-electrical quantity monitoring operation database is established. Based on the monitored historical data and statistical principles, the monitoring data is matched and searched with the confidence interval under the confidence level to obtain the support degree of the specific non-electrical quantity for the normal operation of the transformer, and the corresponding non-electrical quantity health index is calculated according to the weight to determine the state of the transformer. The present invention expands the use of parameters for non-electrical quantity protection in the secondary system and introduces them into transformer diagnosis. Considering the timeliness of monitoring information, an innovative method for unifying the time scale of each parameter is proposed, and the state of the transformer is judged by calculating the non-electrical quantity health index. The methods and data adopted are more comprehensive in terms of timeliness and scope. Description of the Drawings

[0063] Figure 1 is the overall architecture diagram of an oil-immersed transformer non-electrical quantity monitoring and diagnosis system of the present invention;

[0064] Figure 2 is the system diagram of the light gas component analysis module in an oil-immersed transformer non-electrical quantity monitoring and diagnosis system of the present invention;

[0065] Figure 3 is the time synchronization architecture diagram between the server and the non-electrical quantity information acquisition front end in an oil-immersed transformer non-electrical quantity monitoring and diagnosis method of the present invention. Detailed Embodiments

[0066] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. The embodiments described in this application are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the spirit of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0067] The present invention discloses a non - electrical quantity monitoring and diagnosis method for oil - immersed transformers. By arranging light gas, heavy gas, temperature, and pressure monitoring terminals on the transformer body, and uniformly transmitting them to the monitoring and diagnosis system through the aggregation terminal of the local control cabinet. The NTP protocol is applied to the monitoring and diagnosis system server and the non - electrical quantity acquisition front - end. By marking time and calculating the transmission time difference to adjust the time synchronization of each non - electrical quantity with the server, a centralized monitoring of non - electrical quantities under a unified time scale is formed. Based on the monitored historical data and statistical principles, the monitored data is matched and searched with the normal operation confidence interval obtained from the historical data, the support degree for the normal operation of the transformer is calculated, further weight distribution is carried out to obtain the corresponding non - electrical quantity health index, and the transformer status is determined by comparing with the set threshold.

[0068] The specific monitoring and diagnosis method includes the following steps:

[0069] S1: Use the non - electrical quantity information acquisition front - end in the non - electrical quantity monitoring and diagnosis system to monitor and collect the non - electrical quantity information of the oil - immersed transformer;

[0070] In step S1, the non - electrical quantity information of the oil - immersed transformer includes temperature, pressure, light gas volume, light gas composition, and heavy gas oil flow rate.

[0071] The temperature and pressure are monitored and collected through a temperature sensor and a first pressure sensor. Preferably, a pt100 temperature sensor and a MEMS pressure sensor are used.

[0072] The light gas volume monitoring is mainly used to monitor the volume of the gas accumulated inside the gas relay. By installing a second pressure sensor at the bottom inside the gas relay to monitor the pressure, and then calibrating the gas volume of the gas by the pressure value. When different volumes of gas are filled inside, the liquid level height is different, and the monitored pressure is different. The gas volume of the light gas is calibrated by the second pressure sensor at the bottom.

[0073] The method for establishing the relationship between the pressure P monitored by the second pressure sensor and the light gas volume monitoring is as follows:

[0074] The gas relay is filled with insulating oil, and then gas is introduced until the liquid level drops to the scale one of the observation window and stops. At this time, the internal gas volume of the gas relay is V1, and the corresponding output value P1 of the second pressure sensor is recorded. Continue to introduce gas until the next observation window scale two. At this time, the internal gas volume of the gas relay is V2, and continue to record the corresponding output value P2 of the second pressure sensor until all the output values corresponding to the scales on the observation window are recorded, and a set of corresponding relationships between the pressure collected by the second pressure sensor and the light gas volume is established. According to the specific monitored pressure P of the second pressure sensor installed at the bottom of the gas relay, the internal gas volume V of the gas can be mapped correspondingly.

[0075] The light gas components are analyzed by a light gas component analysis module, which includes a main control unit, a gas sampling unit, and a gas detection unit, and uses the spectral principle for analysis. The specific method is as follows:

[0076] Step X1: After the gas relay issues a light gas alarm signal or a heavy gas operation signal, the system starts to detect the free gas in the gas relay. The main control unit opens the first solenoid valve and the fourth solenoid valve, and the fault gas enters the gas collection box of the gas sampling unit from the gas relay. At the same time, the insulating oil in the gas collection box is discharged into the waste oil tank;

[0077] Step X2: When the oil level sensor in the gas collection box detects that the discharged insulating oil reaches 150 ml, the fourth solenoid valve is closed, and the second solenoid valve is opened. At this time, the fault gas in the gas relay passes through the gas collection box and enters the detection gas chamber of the infrared spectrometer in the gas detection unit, and the residual gas in the original detection gas chamber is discharged into the air through the one-way pneumatic valve at the air outlet;

[0078] Step X3: Under the action of the internal oil pressure of the transformer, the free gas in the gas relay is continuously squeezed into the gas sampling and detection device. After the free gas is exhausted, the insulating oil will enter the gas collection box through the same path. When the oil level sensor in the gas collection box detects that the remaining insulating oil rises from 50 ml to 100 ml, the first solenoid valve is closed, and the infrared spectrometer in the gas detection unit starts to detect the gas. After the detection is completed, the second solenoid valve is closed, the first solenoid valve and the third solenoid valve are opened, and the insulating oil enters the gas collection box. At the same time, the residual gas in the original gas collection box enters the waste oil tank under the action of pressure and is finally discharged into the air through the air outlet hole above the waste oil tank;

[0079] Step X4: When the oil level sensor in the gas collection box detects that the insulating oil is full, the first solenoid valve and the third solenoid valve are closed, and this gas sampling ends.

[0080] The monitoring of the heavy gas oil flow rate uses the ultrasonic velocity measurement principle. An ultrasonic velocity detector is installed at the oil pipe between the oil conservator and the transformer, and the angle between the transmitter and the horizontal direction of the pipeline is θ. The frequency it emits is f1, and the received reflected frequency is f2. Then the oil flow rate in the pipeline is:

[0081]

[0082] where c is the propagation speed of ultrasonic waves in the pipeline fluid.

[0083] S2: The non-electric quantity information collected is aggregated to the aggregation terminal of the local control cabinet, and the aggregation terminal of the local control cabinet transmits the collected non-electric quantity information to the server, and the server centrally monitors each non-electric quantity information;

[0084] The centralized monitoring part mainly conducts unified monitoring on various non - electrical quantity information collected in A. Considering that each piece of information is monitored in its own dimension and the time is not unified, it is necessary to synchronize them. The NTP protocol is used as the principle of clock synchronization between the non - electrical quantity acquisition front - end and the monitoring and diagnosis system server. Each non - electrical quantity acquisition front - end acts as a client, sending and receiving data packets with the server, and the server adjusts the unified time of the information according to the calculated time difference. The specific time - synchronization steps are as follows:

[0085] S2.1: The non - electrical quantity information acquisition front - end sends an NTP data packet to the server and adds the time stamp t1 when leaving the non - electrical quantity information acquisition front - end in the NTP data packet;

[0086] S2.2: The server receives the NTP data packet sent by the non - electrical quantity information acquisition front - end at time t2, sends the NTP data packet back to the non - electrical quantity information acquisition front - end at time t3, and adds the time stamp t2 and the time stamp t3 in the NTP data packet;

[0087] S2.3: The non - electrical quantity information acquisition front - end receives the NTP data packet sent by the server at time t4 and adds the time stamp t4 in the NTP data packet;

[0088] S2.4: Calculate the time difference τ according to t1, t2, t3, and t4:

[0089]

[0090] After calculating the time difference τ, the server takes its own T0 as the benchmark to perform time compensation processing on the data transmitted by the non - electrical quantity information acquisition front - end:

[0091]

[0092] In the formula:

[0093] is the i - th non - electrical quantity information collected at time T0 in the server;

[0094] is the i - th non - electrical quantity information at time T0 - τ transmitted from the front - end;

[0095] i takes values from 1 to 5, representing light gas volume, composition, heavy gas oil flow, temperature, and pressure respectively.

[0096] The time - synchronization architecture between the server and the non - electrical quantity information acquisition front - end is as Figure 3 shown.

[0097] S3: The server establishes a non - electrical quantity database, calculates the non - electrical quantity health index H, and conducts non - electrical quantity monitoring and diagnosis of the oil - immersed transformer according to the non - electrical quantity health index H.

[0098] The calculation steps of the non - electrical quantity health index H are as follows:

[0099] S3.1: Establish a non - electrical quantity database, and establish data sets for the non - electrical quantity information monitored and operated in their respective dimensions, obtaining a data set B=(B 1 , B 2 , B 3 , B i ), where i is the characteristic dimension of the non - electrical quantity, and each dimension set is a subset of the non - electrical quantity historical data within that dimension, that is n is the total number of data in the corresponding subset;

[0100] S3.2: According to statistics, the data set B conforms to the normal distribution, that is Among them, μ and respectively represent the mean and variance of the normal distribution. The calculation formulas for the mean and variance of the i - th - dimensional non - electrical quantity information are as follows:

[0101]

[0102] Based on the variance and the mean, combined with the given confidence level, a specific confidence interval is obtained:

[0103]

[0104] Among them, when the confidence level is 90%, the parameter c is 1.64; when the confidence level is 95%, c is 1.96; when the confidence level is 99%, c is 2.58;

[0105] Generally, the confidence level is taken as 95% or 99%;

[0106] S3.3: Conduct a matching diagnosis on the monitored non - electrical quantity. According to whether it falls within the confidence interval, obtain the support degree of the specific - dimension non - electrical quantity for the normal operation state of the transformer. Match the non - electrical quantity monitoring information of each dimension with the confidence interval. When it falls within the confidence interval, it is determined that the transformer state reflected by the non - electrical quantity of this dimension at this moment is normal, and the criterion formula is:

[0107]

[0108] The calculation rule for the support degree of the i - th - dimensional non - electrical quantity for the normal operation state of the transformer is: when the monitoring information of the i - th - dimensional non - electrical quantity meets the criterion, the support degree Wi of this non - electrical quantity is 1; otherwise, Wi = 0;

[0109] S3.4: Calculate the non - electrical quantity health index H reflecting the operation state of the transformer according to the specific non - electrical quantity support degree:

[0110]

[0111] In the formula:

[0112] m is the total number of non - electrical state dimensions of the transformer adopted;

[0113] Wi is the i - th non - electrical support degree calculated above;

[0114] Qi is the i - th non - electrical weight, which takes a value in the range of (0, 1). The higher the value, the higher the support degree of the normal operation of this non - electrical quantity for the health of the transformer operation state.

[0115] Set the health index limit value H set , when the non - electrical health index H < H set , the non - electrical monitoring and diagnosis system issues an alarm of "non - electrical abnormality, suspected fault". When H ≥ H set , the diagnosis system determines the "non - electrical normal" state of the transformer. The closer the non - electrical health index H is to 1, the more normal the non - electrical operation is, and the healthier the transformer state reflected is. The closer it is to 0, the more non - electrical abnormalities exist in the transformer, suspected of a fault.

[0116] The present invention also discloses a non - electrical monitoring and diagnosis system for an oil - immersed transformer, which is used to implement the above - mentioned monitoring and diagnosis method.

[0117] As Figure 1 shown, the monitoring and diagnosis system includes a non - electrical information acquisition front - end, an in - place control cabinet aggregation terminal, and a server.

[0118] The non - electrical information acquisition front - end acquires the non - electrical information of the oil - immersed transformer and hands it over to the in - place control cabinet aggregation terminal for aggregation. The in - place control cabinet aggregation terminal is connected to the server through an RS485 communication line and hands over the aggregated non - electrical information to the server for monitoring and diagnosis.

[0119] The non - electrical information acquisition front - end includes a temperature monitoring module, a pressure monitoring module, a heavy gas oil flow monitoring module, a light gas volume monitoring and composition analysis module.

[0120] The temperature monitoring module includes a temperature sensor; the pressure monitoring module includes a first pressure sensor; the heavy gas oil flow monitoring module includes an ultrasonic speed detector; the light gas volume monitoring and composition analysis module includes a second pressure sensor and a light gas composition analysis component.

[0121] As Figure 2 shown, the light gas composition analysis component includes a main control unit, a gas sampling unit, and a gas detection unit.

[0122] The gas extraction unit includes a waste oil tank and a gas collection box. The waste oil tank is connected to the gas collection box through a third solenoid valve and a fourth solenoid valve. The gas collection box is connected to the gas relay through a first solenoid valve, and the gas collection box is connected to the infrared spectrometer of the gas detection unit through a second solenoid valve. The main control unit is electrically connected to the gas relay and the infrared spectrometer respectively.

[0123] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0124] A non-electric quantity monitoring and diagnosis method and system for an oil-immersed transformer disclosed by the present invention arranges a variety of acquisition terminals on the transformer body to form centralized monitoring of each non-electric quantity under a unified time scale, which is more conducive to mastering the non-electric quantity state of the overall operation of the transformer. In addition, a non-electric quantity monitoring operation database is established. Based on the monitored historical data and statistical principles, the monitoring data is matched and searched with the confidence interval under the confidence level to obtain the support degree of the specific non-electric quantity for the normal operation of the transformer, and the corresponding non-electric quantity health index is calculated according to the weight to determine the state of the transformer. The present invention expands the use of the parameters for non-electric quantity protection in the secondary system and introduces them into the transformer diagnosis. Considering the timeliness of the monitoring information, an innovative method for unifying the time scale of each parameter is proposed, and the state of the transformer is judged by calculating the non-electric quantity health index. The methods and data adopted are more comprehensive in terms of timeliness and scope.

[0125] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: still can modify the specific implementation manners of the present invention or make equivalent replacements, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. A non-electrical quantity monitoring and diagnosis method for oil-immersed transformers, characterized in that: The monitoring and diagnostic method includes the following steps: S1: Use the non-electricity information acquisition front end in the non-electricity monitoring and diagnostic system to monitor and collect the non-electricity information of the oil-immersed transformer. The non-electricity information of the oil-immersed transformer includes temperature, pressure, light gas volume, light gas composition, and heavy gas oil flow rate. The monitoring and collection method of the light gas volume is as follows: Monitor the pressure through the second pressure sensor installed at the bottom inside the gas relay. When different volumes of gas are filled inside the gas relay, the liquid level height is different, and the pressure monitored by the second pressure sensor is different. Furthermore, the volume of the gas can be calibrated through the pressure monitored by the second pressure sensor to achieve the monitoring and collection of the light gas volume; The heavy gas oil flow rate is monitored and collected using the ultrasonic velocity measurement principle. Specifically: Install an ultrasonic velocity detector at the oil pipe between the oil conservator and the transformer, and the included angle between the ultrasonic transmitter and the horizontal direction of the oil pipe is θ. The ultrasonic frequency it emits is f1, and the received reflected ultrasonic frequency is f2. Then the oil flow rate in the pipe is: where c is the propagation speed of ultrasonic waves in the pipeline fluid; S2: Collect the collected non-electricity information to the collection terminal of the local control cabinet, and the collection terminal of the local control cabinet transmits the collected non-electricity information to the server, and the server centrally monitors each non-electricity information; S3: The server establishes a non-electricity database, calculates the non-electricity health index H, and performs non-electricity monitoring and diagnosis on the oil-immersed transformer according to the non-electricity health index H.

2. The non-electricity monitoring and diagnostic method of an oil-immersed transformer according to claim 1, characterized in that: The temperature and pressure are monitored and collected through a temperature sensor and a first pressure sensor; The light gas composition is obtained through spectral analysis.

3. The non-electricity monitoring and diagnostic method of an oil-immersed transformer according to claim 1, characterized in that: The specific process of calibrating the volume of the gas through the pressure monitored by the second pressure sensor to achieve the monitoring and collection of the light gas volume is as follows: Fill the gas relay, i.e., the Buchholz relay, with insulating oil, and then introduce gas until the liquid level drops to the scale one of the observation window and stop. At this time, the internal gas volume of the gas relay is V1, record the output value P1 corresponding to the second pressure sensor, continue to introduce gas until the next scale two of the observation window. At this time, the internal gas volume of the gas relay is V2, and continue to record the output value P2 corresponding to the second pressure sensor until all the output values corresponding to the scales on the observation window are recorded, and establish a corresponding relationship set between the pressure collected by the second pressure sensor and the volume of the light gas in the gas relay. Based on this corresponding relationship set, according to the specific monitored pressure P of the second pressure sensor installed at the bottom of the gas relay, the internal gas volume V can be correspondingly mapped.

4. The non-electricity monitoring and diagnostic method of an oil-immersed transformer according to claim 1, characterized in that: In step S2, the NTP protocol is used to adjust the time synchronization between the non-electricity information acquisition front end and the server, and then the server centrally monitors each non-electricity information. The specific time synchronization steps are as follows: S2.1: The non-electricity information acquisition front end sends an NTP data packet to the server, and adds the time stamp t1 when leaving the non-electricity information acquisition front end in the NTP data packet; S2.2: The server receives the NTP data packet sent by the non-electricity information acquisition front end at time t2, sends the NTP data packet back to the non-electricity information acquisition front end at time t3, and adds the time stamp t2 and the time stamp t3 in the NTP data packet; S2.3: The non-electricity information acquisition front end receives the NTP data packet sent by the server at time t4, and adds the time stamp t4 in the NTP data packet; S2.4: Calculate the time difference τ according to t1, t2, t3, t4: After calculating the time difference τ, the server takes its own T0 as the reference and performs time compensation processing on the data transmitted by the non-electric quantity information acquisition front end: In the formula: The i-th non-electric quantity information collected at time T0 in the server; is the i-th non-electric quantity information at the moment of T0-τ transmitted from the front end; i takes values from 1 to 5, respectively representing light gas volume, light gas composition, heavy gas oil flow, temperature, and pressure.

5. A non-electric quantity monitoring and diagnosis method for an oil-immersed transformer according to claim 4, characterized in that: In the step S3, the calculation steps of the non-electric quantity health index H are as follows: S3.1: Establish a non-electric quantity database, and establish data sets for the non-electric quantity information monitored and operated in their respective dimensions, to obtain a data set B = (B 1 , B 2 , B 3 …, B i ), where i is the characteristic dimension of the non-electric quantity, and each dimension set is a subset of the non-electric quantity historical data within that dimension, that is n is the total number of data in the corresponding subset; S3.2: According to statistics, the data set B conforms to the normal distribution, that is where μ, respectively represent the mean and variance of the normal distribution. The calculation formulas for the mean and variance of the i-th dimensional non-electrical quantity information are as follows: According to the variance and mean, combined with the given confidence level, a specific confidence interval is obtained: Among them, when the confidence level is 90%, the parameter c is 1.64; when the confidence level is 95%, c is 1.96; when the confidence level is 99%, c is 2.58; S3.3: Perform matching diagnosis on the monitored non-electric quantity. According to whether it falls within the confidence interval, obtain the support degree of the specific dimension non-electric quantity for the normal operation state of the transformer. Match the non-electric quantity monitoring information of each dimension with the confidence interval. When it falls within the confidence interval, it is determined that the transformer state reflected by the non-electric quantity of this dimension at this moment is normal. The criterion formula is: The calculation rule for the support degree of the i-th dimension non-electric quantity for the normal operation state of the transformer is: when the monitoring information of the i-th dimension non-electric quantity meets the criterion, the support degree Wi of this non-electric quantity is 1; otherwise, Wi = 0; S3.4: Calculate the non-electric quantity health index H reflecting the operation state of the transformer according to the specific non-electric quantity support degree: In the formula: m is the total number of dimensions of the non-electric quantity state of the transformer adopted; Wi is the support degree of the i-th non-electric quantity; Qi is the weight of the i-th non-electric quantity, which takes a value within the interval (0, 1). The higher the value, the higher the support degree of the normal operation state of the transformer when this non-electric quantity is normal.

6. A non-electric quantity monitoring and diagnosis method for an oil-immersed transformer according to claim 1, characterized in that: In step 3, set the health index limit value H set , when the non-electricity health index H < H set , the non-electricity monitoring and diagnosis system issues an alarm of "non-electricity anomaly, suspected fault". When H ≥ H set , the diagnosis system determines the "non-electricity normal" state of the transformer.

7. A non-electric quantity monitoring and diagnosis system for an oil-immersed transformer, characterized in that: The monitoring and diagnosis system is used to implement the monitoring and diagnosis method described in any one of claims 1 to 6, and includes: a non-electric quantity information acquisition front end, a local control cabinet aggregation terminal, and a server; The non-electric quantity information acquisition front end collects the non-electric quantity information of the oil-immersed transformer and hands it over to the local control cabinet aggregation terminal for aggregation. The local control cabinet aggregation terminal is connected to the server through an RS485 communication line and hands over the aggregated non-electric quantity information to the server for monitoring and diagnosis.

8. A non-electric quantity monitoring and diagnosis system for an oil-immersed transformer according to claim 7, characterized in that: The non-electric quantity information acquisition front end includes a temperature monitoring module, a pressure monitoring module, a heavy gas oil flow monitoring module, a light gas volume monitoring and composition analysis module; The temperature monitoring module includes a temperature sensor; The pressure monitoring module includes a first pressure sensor; The heavy gas oil flow monitoring module includes an ultrasonic speed detector; The light gas volume monitoring and composition analysis module includes a second pressure sensor and a light gas composition analysis component.

9. A non-electric quantity monitoring and diagnosis system for an oil-immersed transformer according to claim 8, characterized in that: The light gas composition analysis component includes a main control unit, a gas sampling unit, and a gas detection unit; The gas extraction unit includes a waste oil tank and a gas collection box, and the waste oil tank and the gas collection box are connected through a third solenoid valve and a fourth solenoid valve; The gas collection box is connected to the gas relay through a first solenoid valve; The gas collection box is connected to the infrared spectrometer of the gas detection unit through a second solenoid valve; The main control unit is electrically connected to the gas relay and the infrared spectrometer respectively.

Images