Dry-type transformer intelligent monitoring system based on electronic voltage transformer

Abstract

The invention discloses a dry-type transformer intelligent monitoring system based on an electronic voltage transformer, and relates to the technical field of dry-type transformers, the dry-type transformer intelligent monitoring system comprises a dry-type transformer body, the dry-type transformer body is provided with a data acquisition device used for monitoring transformer parameters, one side of the dry-type transformer body is provided with an industrial control all-in-one machine, and the industrial control all-in-one machine is provided with a power supply. A data processing analysis module, a control execution module and a man-machine interaction module are configured in the industrial control all-in-one machine; the data acquisition device comprises a high-voltage side electric quantity acquisition unit, a low-voltage side electric quantity acquisition unit, a temperature control acquisition unit, an insulation state monitoring unit, an environment monitoring unit, a video monitoring unit, a vibration monitoring unit and a smoke acquisition unit, and the units communicate with one another through a network. By monitoring parameters such as temperature, voltage, current, power factor and the like in real time, omnibearing monitoring of the operation state of the transformer is realized, remote diagnosis is realized, a multi-parameter weighted scoring model and historical data can be combined, and the field inspection frequency is greatly reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of dry-type transformers, in particular to an intelligent monitoring system for dry-type transformers based on an electronic voltage transformer. Background Art

[0002] In recent years, dry-type transformers refer to transformers whose cores and windings are not immersed in insulating oil. They are cooled by air convection, etc. Dry-type transformers are widely used in high-rise buildings, subways, railway stations, airports, hospitals, petrochemical enterprises and mines due to their advantages such as flame retardancy, flame retardancy, fire resistance, explosion resistance and environmental protection. During the use of dry-type transformers, they need to be monitored.

[0003] Current dry-type transformer monitoring generally uses a transformer temperature controller to achieve dry-type transformer monitoring effects. Platinum thermal resistors embedded in the dry-type transformer windings are used to detect and display the temperature rise of the transformer windings. The system can automatically start and stop the cooling fan for forced air cooling of the windings, and implement over-temperature alarm and over-temperature trip control outputs to avoid transformer failures caused by excessively high temperatures, thereby ensuring that the transformer operates in a safe state and extending the transformer's service life. However, this monitoring method can only monitor the dry-type transformer's temperature, and cannot fully monitor the transformer's electrical power, insulation performance, environment, vibration and other parameters, nor can it comprehensively evaluate the transformer's health and lifespan.

[0004] Based on this, an intelligent monitoring system for dry-type transformers based on electronic voltage transformers is now provided, which can eliminate the drawbacks of existing technical solutions. Summary of the Invention

[0005] The object of the present invention is to provide an intelligent monitoring system for dry-type transformers based on electronic voltage transformers, so as to solve the problem of limited transformer monitoring parameters in the background art.

[0006] To achieve the above object, the present invention provides the following technical solutions: An intelligent monitoring system for dry-type transformers based on an electronic voltage transformer includes a dry-type transformer body, a data acquisition device for monitoring transformer parameters mounted on the dry-type transformer body, an industrial control all-in-one computer disposed on one side of the dry-type transformer body, and a data processing and analysis module, a control execution module, and a human-computer interaction module configured within the industrial control all-in-one computer. Data transmission and communication are achieved between the data acquisition device, the dry-type transformer body, and the industrial control all-in-one computer via the control execution module. The data acquisition device includes a high-voltage side power acquisition unit, a low-voltage side power acquisition unit, a temperature control acquisition unit, an insulation status monitoring unit, an environment monitoring unit, a video monitoring unit, a vibration monitoring unit and a smoke acquisition unit, and each unit communicates with each other through a network; The industrial control all-in-one computer is used to receive and integrate data transmitted by the data acquisition device, and to conduct a comprehensive evaluation and diagnosis of the operating status and health status of the dry-type transformer body in combination with the design parameters, structural parameters, test data and historical operation data of the dry-type transformer body; The data processing and analysis module is used to evaluate the health status of the dry-type transformer; The control execution module is used to implement data transmission and communication operations; The human-computer interaction module is used to set and modify various fixed values ​​and parameters, and view the monitoring data of each sensor in real time through a visual interface; The high-voltage side power collection unit includes an electronic voltage transformer, an electronic current transformer and high-voltage supporting instruments, which are used to collect phase voltage, phase current, zero-sequence current, phase-to-phase voltage and frequency parameters on the high-voltage side; The low-voltage side power collection unit includes a low-voltage side current transformer and a three-phase multi-function digital display meter, which is used to collect the phase voltage, phase current, zero-sequence current, phase-to-phase voltage and frequency parameters of the low-voltage side; The temperature control and acquisition unit includes a dry-type transformer optical fiber temperature controller for real-time online monitoring of the temperature of the dry-type transformer body; The insulation status monitoring unit is used to monitor the partial discharge amount and insulation resistance of different parts through a plurality of partial discharge sensors; The environmental monitoring unit includes a temperature and humidity controller and a temperature measuring probe, which are used to monitor the humidity, winding temperature, core temperature and ambient temperature inside the dry-type transformer body; The video monitoring unit uses a camera with flame detection function to perform video monitoring; The vibration monitoring unit is used to monitor the vibration acceleration of the dry-type transformer body through a vibration sensor; The smoke collection unit uses a smoke sensor to collect smoke concentration; The data processing and analysis module adopts a multi-parameter weighted scoring model, and each parameter is provided with a real-time status label, which includes four levels: normal, caution, abnormal and dangerous; The data processing and analysis module also integrates a fault prediction model. The fault prediction model is based on historical operation data and real-time monitoring data. It analyzes parameter change trends through machine learning algorithms, generates health status reports, and predicts potential fault types and occurrence probabilities.

[0007] Preferably, one side of the dry-type transformer body is equipped with a fire extinguishing device for automatically receiving smoke sensor monitoring data and automatically updating fire monitoring perception based on the monitoring data. The starting mode of the fire extinguishing device is two or more of constant temperature start, hot start and electric control start. The starting mode specifically includes: a combination of constant temperature start and electric control start, a combination of constant temperature start and hot start, and a combination of constant temperature start, hot start and electric control start. The fire extinguishing device and the smoke collection unit are linked through a control execution module. When the smoke concentration exceeds a threshold, the fire extinguishing device automatically starts.

[0008] Preferably, the temperature and humidity controller adopts a pre-buried and attached installation method, and the temperature and humidity controller is installed at the core temperature measuring point of the dry-type transformer body.

[0009] Preferably, the control execution module includes an input and output submodule and an alarm submodule. The input and output submodule is used to receive remote control instructions and realize the linkage function with the external switch. The alarm submodule is used to issue early warning, alarm and tripping signals according to the set alarm thresholds. The alarm thresholds include power parameter thresholds, temperature thresholds, humidity thresholds, partial discharge and insulation status thresholds, vibration and noise thresholds, and smoke and video monitoring abnormality thresholds.

[0010] Preferably, the electronic voltage transformer in the high-voltage side power collection unit adopts an insulator structure, and the electronic current transformer adopts a cable through-hole structure.

[0011] Preferably, the data acquisition device also includes a noise monitoring unit, which monitors the noise level of the dry-type transformer body during operation through a noise sensor. The noise sensor is installed above the dry-type transformer body, and the monitoring data of the noise sensor is transmitted to the data processing and analysis module through the network for comprehensive judgment of the equipment status in combination with the vibration parameters.

[0012] Preferably, the sensors of each unit of the data acquisition device all adopt an anti-electromagnetic interference structure.

[0013] Compared with the prior art, the present invention has the following beneficial effects: Compared with the traditional monitoring method that relies on a single sensor, this dry-type transformer intelligent monitoring system based on electronic voltage transformer achieves comprehensive monitoring of the transformer's operating status through real-time monitoring of parameters such as temperature, voltage, current, power factor, and insulation status, realizes remote diagnosis, significantly reduces the frequency of on-site inspections, and reduces labor costs. It can combine multi-parameter weighted scoring models and historical data to conduct a comprehensive assessment of the transformer's health status and lifespan, provide early warning of potential faults, and reduce power outage losses caused by equipment failures. Through temperature control and load management, it can reduce no-load and load losses, thereby achieving energy conservation. By monitoring the equipment status over a long period of time, the system can formulate a scientific maintenance plan, avoid excessive or insufficient maintenance, and extend the service life of the dry-type transformer itself. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a front view of the dry-type transformer body shell of the present invention.

[0015] Figure 2 It is a side view of the dry-type transformer body shell of the present invention.

[0016] Figure 3 It is a structural diagram of the dry-type transformer intelligent monitoring system of the present invention.

[0017] Figure 4 It is a structural schematic diagram of the data acquisition device of the present invention.

[0018] Figure 5 It is a structural schematic diagram of the industrial control all-in-one machine of the present invention.

[0019] Figure 6 It is a schematic diagram of the internal structure of the dry-type transformer body of the present invention.

[0020] Figure 7 For the present invention Figure 6 side view.

[0021] Notes on the accompanying drawings: dry-type transformer body 100, data acquisition device 200, high-voltage side power acquisition unit 210, low-voltage side power acquisition unit 220, temperature control acquisition unit 230, insulation status monitoring unit 240, environment monitoring unit 250, video monitoring unit 260, vibration monitoring unit 270, smoke acquisition unit 280, noise monitoring unit 290, industrial control all-in-one machine 300, data processing and analysis module 310, control execution module 320, input and output sub-module 321, alarm sub-module 322, human-computer interaction module 330, fire extinguishing device 400. DETAILED DESCRIPTION

[0022] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments.

[0023] In this embodiment, if Figure 1 - Figure 7 As shown, an intelligent monitoring system for dry-type transformers based on an electronic voltage transformer includes a dry-type transformer body 100. The dry-type transformer body 100 is a type of power transformer. Partial discharge reflects the presence of different insulation defects in it and can be continuously monitored in real time. A data acquisition device 200 for monitoring transformer parameters is installed on the dry-type transformer body 100. An industrial control all-in-one computer 300 is provided on one side of the dry-type transformer body 100. The industrial control all-in-one computer 300 is internally configured with a data processing and analysis module 310, a control execution module 320, and a human-computer interaction module 330. The industrial control all-in-one computer 300 also stores a body database. Data transmission and communication are achieved between the data acquisition device 200, the dry-type transformer body 100, and the industrial control all-in-one computer 300 through the control execution module 320. The system supports wireless and wired communication methods, including RS485, Ethernet, and LORA communication methods, and can realize automatic networking, facilitating data interconnection and sharing. The data acquisition device 200 includes a high-voltage side power acquisition unit 210, a low-voltage side power acquisition unit 220, a temperature control acquisition unit 230, an insulation status monitoring unit 240, an environment monitoring unit 250, a video monitoring unit 260, a vibration monitoring unit 270, and a smoke acquisition unit 280. Each unit communicates with each other via a network. The industrial control all-in-one computer 300 is used to receive and integrate the data transmitted by the data acquisition device 200, and to perform a comprehensive evaluation and diagnosis of the operating status and health status of the dry-type transformer body 100 based on the design parameters, structural parameters, test data, and historical operating data of the dry-type transformer body 100, and store the data in a local database according to the timestamp; The data processing and analysis module 310 is used to evaluate the health status of the dry-type transformer; Specifically, if Figure 4 and Figure 5 As shown, the data processing and analysis module 310 adopts a multi-parameter weighted scoring model, and each parameter is provided with a real-time status label, which includes four levels: normal, caution, abnormal, and dangerous; Specifically, health status assessment is mainly achieved through multi-parameter comprehensive analysis, graded label determination, and prediction model assistance. The assessment integrates multi-dimensional parameters. The data is collected by the corresponding monitoring unit, including: phase voltage, phase current, zero-sequence current, frequency, harmonic distortion (THD), power factor, etc. on the high-voltage side or low-voltage side; winding temperature, core temperature, ambient temperature; partial discharge, insulation resistance, polarization index (PI); humidity, vibration acceleration, and noise level inside the dry-type transformer body 100; smoke concentration, and video anomalies; harmonic distortion (THD) is the ratio of the effective value of each harmonic to the effective value of the fundamental wave, calculated by the harmonic analysis function of the high-voltage side power collection unit 210. The total score calculation formula is: , For the The weight of each parameter, the sum of all weights is 100%, For the The individual scores of each parameter are calculated based on the degree to which the parameter deviates from the normal range. For the total score, The total number of parameters involved in the scoring is divided into real-time status according to the scoring results. The input of the multi-parameter weighted scoring model is the real-time monitoring data from each unit and the historical baseline data stored in the local database of the industrial control all-in-one computer 300. The output is the health score, status label (normal / caution / abnormal / dangerous), and a list of key abnormal parameters; Specifically, the parameter weight distribution example of the multi-parameter weighted scoring model is as follows: temperature (25%), partial discharge (20%), insulation resistance (20%), power (15%), humidity (10%), and vibration (10%). Each parameter is deducted based on the degree of deviation from the normal range (e.g., a 0-100 point scale). The total score is weighted and calculated. If the score is above 90 points, the health level is excellent; if the score is between 80 and 90 points, the health level is good; if the score is between 60 and 79 points, the health level is medium; if the score is below 60 points, the health level is poor. The weight distribution is based on the IEEE Std C57.91-2011 standard. Temperature rise has the greatest impact on insulation life, partial discharge reflects insulation defects, and insulation resistance measures insulation performance. The remaining parameters can be adjusted according to actual operating data. Specifically, each parameter involved in the scoring (such as temperature, partial discharge, noise level, etc.) is based on dry-type transformer design standards, industry specifications and historical operating data. The specific threshold and normal range can be adjusted through the human-computer interaction module according to the equipment model, insulation level and operating environment. The single score adopts a 100-point system, and points are deducted in a step-by-step manner based on the degree to which the actual measured value of the parameter deviates from the normal range. The single score calculation method is as follows: If the actual value of the parameter is within the normal range and the change trend is stable, then For example, if the winding temperature is 90°C, taking the dry-type transformer body 100 as F-class insulation, the winding temperature should be lower than 155°C, then the winding temperature is within the normal range, which is recorded as point; If the actual value is within the warning threshold range, points will be deducted according to the deviation ratio. For example, if the winding temperature is 120°C, the warning is 110°C, and the alarm is 130°C, the deviation ratio is: The full score is 100 points. After exceeding the warning level, the maximum deduction is 50 points. The deduction can be adjusted according to actual needs. point; If the parameter exceeds the alarm threshold but does not reach the danger threshold, a maximum of 80 points will be deducted. The deduction can be adjusted according to actual needs. For example, if the partial discharge is 15pC, the warning is 10pC, and the alarm is 20pC. The deviation ratio is: ,but point; If the parameter reaches the dangerous threshold, point; Each acquisition unit acquires parameters in real time through an anti-electromagnetic interference sensor and transmits them to the industrial control all-in-one machine 300 via a cable. After pre-processing, the data processing and analysis module 310 has a built-in computing engine. It combines the local database historical baseline and storage content to adjust the parameter range and threshold, and calculates the single score through an algorithm. The input is the current parameter value and the preset threshold, and the output is the single score. , and then the total health score can be calculated; Specifically, the real-time status labels are divided into the following categories: if all parameters are within the threshold and the trend is stable, the real-time status label is set to normal; if one parameter exceeds the warning threshold but does not deteriorate, the real-time status label is set to caution; if more than two parameters alarm or a single parameter continues to deteriorate, the real-time status label is set to abnormal; if an emergency alarm is triggered, the real-time status label is set to dangerous; Specifically, parameter "deterioration" means that after a single parameter exceeds the warning threshold, its value shows a trend of continuous increase, increased fluctuation, or deviation from the normal range. The specific judgment rules are based on the dynamic comparison of real-time monitoring data and historical baselines. The thresholds and preset ranges need to be adjusted according to the normal range of different parameters. Examples are: Perform linear trend analysis on the interval sampling of continuously collected parameter values. If continuous sampling and sampling points all show an upward trend, and the cumulative increase exceeds the threshold, it is judged as "deterioration"; Calculate the standard deviation of the parameter over a period of time to reflect the degree of fluctuation. If the current standard deviation exceeds the preset range compared to the average standard deviation in the past hour, it is judged as "deteriorating"; Compare the current value of the parameter with the historical baseline for the same period. If the deviation ( ) If the temperature exceeds the preset range for a long time, it is judged as "deterioration"; In this application, the real-time analysis of parameter deterioration is completed by the data processing and analysis module and the control execution module in collaboration. The industrial control all-in-one computer 300 has a built-in local database that stores the normal operating range of the parameters and can compare the current parameter value with the historical baseline of the corresponding period in real time. The data processing and analysis module 310 has a built-in calculation engine that combines the local database historical baseline with the stored content to perform trend calculation, standard deviation calculation, and deviation calculation. If the calculation result shows the above situation, it will be marked as "deterioration"; The control execution module 320 is used to implement data transmission and communication operations; The human-computer interaction module 330 is used to set and modify various fixed values ​​and parameters, and view the monitoring data of each sensor in real time through a visual interface. The human-computer interaction module 330 supports multiple operation permission management and can set corresponding operation permissions according to different user roles (such as administrators, operation and maintenance personnel, general viewers, etc.), including the permission to modify system parameters, the permission to view data, and the permission to execute control instructions, etc., to ensure the security and standardization of system operations.

[0024] Among them Figure 4 and Figure 7 As shown, the high-voltage side power collection unit 210 includes an electronic voltage transformer, an electronic current transformer and high-voltage supporting instruments, which are used to collect the phase voltage, phase current, zero-sequence current, phase-to-phase voltage and frequency parameters of the high-voltage side. The electronic voltage transformer in the high-voltage side power collection unit 210 adopts an insulator structure, replaces the original high-voltage insulator, and is directly fixed to the dry-type transformer body 100 bracket. The electronic current transformer adopts a cable through-core structure and is installed on the high-voltage cable. The output signal is transmitted to the industrial control all-in-one computer via a shielded cable. The electronic voltage transformer is made based on the principle of resistance voltage division. The output signal is a voltage quantity that is proportional to the voltage of the measured system. There is no magnetic saturation phenomenon in the entire measurement range. The output is linear and has high measurement accuracy, which complies with GB / T 20840.7-2007 and IEC According to the 60044-7:2002 standard, the appearance of the electronic voltage transformer is similar to that of a traditional insulator. It can be installed with a bracket to replace the original insulator of the high-voltage incoming line fixed copper busbar. The voltage detection circuit of the high-voltage supporting instrument is designed according to the secondary side voltage of the electronic voltage transformer to meet the measurement accuracy requirements. The low-voltage side power collection unit 220 includes a low-voltage side current transformer and a three-phase multi-function digital display, which are used to collect the phase voltage, phase current, zero-sequence current, phase-to-phase voltage and frequency parameters of the low-voltage side. The low-voltage side current transformer is installed on the low-voltage side outgoing copper bus of the dry-type transformer body 100, and the three-phase multi-function digital display is installed in the local control box. The three-phase multi-function digital display can collect the three-phase phase voltage through direct access or voltage transformer. The phase-to-phase voltage can be calculated based on the phase voltage. Some instruments can also be directly measured, depending on the wiring method. The temperature control and acquisition unit 230 includes a dry-type transformer optical fiber temperature controller for real-time online monitoring of the temperature of the dry-type transformer body 100. Designed specifically for real-time online temperature monitoring of dry-type transformers, the dry-type transformer optical fiber temperature controller provides four-channel (A, B, C phases and iron core) temperature measurement and display functions, as well as alarm linkage output functions, in a strong electromagnetic environment. It utilizes a plug-in interface and can be used in conjunction with other products using the standard Modbus RTU protocol to implement functions such as cloud storage of real-time monitoring data. The insulation status monitoring unit 240 is used to monitor the partial discharge amount and insulation resistance of different parts through a number of partial discharge sensors. The partial discharge sensors are installed at the bottom of the high-voltage winding using magnetic adsorption. The environmental monitoring unit 250 includes a temperature and humidity controller and a temperature probe, which are used to monitor the humidity, winding temperature, core temperature, and ambient temperature inside the dry-type transformer body 100. The winding temperature adopts domestic multi-channel optical fiber temperature measurement technology. The temperature and humidity controller adopts pre-embedded and attached installation methods. The pre-embedded method means that a PT100 platinum resistor or thermocouple is embedded in the winding during the manufacture of the dry-type transformer body 100, which is more accurate. The attached method means that the temperature and humidity controller is fixed to the surface of the winding, and close contact must be ensured. Specifically, the temperature and humidity controller is installed at the core temperature measurement point of the dry-type transformer body 100, avoiding installation at locations with large vibration, strong magnetic field interference or poor heat dissipation. The core temperature measurement points include: the top of the low-voltage winding, the iron core or high-voltage winding, and the air inlet and outlet. The temperature and humidity controller is usually installed at the hot spot (the hottest area) of the low-voltage side winding of the transformer, which can directly reflect the winding temperature. An auxiliary temperature measuring probe can be installed on the high-voltage side or the iron core. The winding temperature measuring probe is installed in the reserved installation position between the winding turns. The air inlet and outlet can monitor the ambient temperature and the heat dissipation airflow temperature. Specifically, for the dry-type transformer body 100, taking common Class A insulation as an example, the winding temperature should be lower than 110°C, and the ambient temperature should be lower than 40°C. The fan is usually started at 80°C and stopped below 70°C. The specific values ​​can be adjusted according to the design. Class B insulation corresponds to a temperature of 130°C, Class F insulation corresponds to a temperature of 155°C, and Class H insulation corresponds to a temperature of 180°C. Transformers with different insulation materials have different allowable temperatures, which must be set according to the manufacturer's specifications. The video monitoring unit 260 uses a camera with flame detection function for video monitoring. It has a built-in infrared pyroelectric flame detector that can sense changes in infrared signals around the flame. The monitoring range can cover the front and back of the dry-type transformer body 100. The unit uses a high-definition network camera with flame detection function, which is installed on both sides and the top of the dry-type transformer body 100. The monitoring range covers the entire equipment and the surrounding environment. The camera has a built-in infrared pyroelectric flame detector that supports automatic switching between day and night modes. The video stream collected by the camera is transmitted to the industrial control all-in-one computer 300 via Ethernet and is processed by the data processing and analysis module 31 0 performs real-time intelligent analysis, using infrared pyroelectric sensors to capture the unique infrared radiation signals of flames, and combining image recognition algorithms to identify the dynamic contours and temperature distribution of flames. When an open flame or a high-temperature point is detected, it is marked as "flame abnormality". After the above abnormality is confirmed, the emergency alarm signal of the alarm submodule 322 is immediately triggered, and the video screen pop-up window is linked to the visual interface of the human-computer interaction module 330. The analysis results are simultaneously incorporated into the multi-parameter weighted scoring model and jointly participate in the health status assessment with parameters such as temperature and vibration to ensure that the monitoring of "noise level" and "video abnormality" is consistent with the overall diagnostic logic of the system; The vibration monitoring unit 270 is used to monitor the vibration acceleration of the dry-type transformer body 100 through a vibration sensor; The smoke collection unit 280 uses a smoke sensor to collect smoke concentration and detect whether a fire has occurred; Specifically, the data acquisition device 200 also includes a noise monitoring unit 290, which monitors the noise level of the dry-type transformer body 100 during operation through a noise sensor. The noise sensor is installed above the dry-type transformer body 100, and the monitoring data of the noise sensor is transmitted to the data processing and analysis module 310 through the network for comprehensive judgment of the equipment status in combination with the vibration parameters. The unit adopts a noise sensor with an anti-electromagnetic interference structure, which can effectively resist the interference of the strong electromagnetic environment of the transformer. The original sound pressure signal collected by the noise sensor is converted and transmitted to the data processing and analysis module 310 through the network. After feature extraction, deviation value calculation, and fusion analysis with the vibration acceleration data of the vibration monitoring unit 270, if the noise level increases compared to the baseline and is accompanied by abnormal vibration in a specific frequency band, the "attention" or "abnormal" status label is triggered according to the multi-parameter weighted scoring model.

[0025] like Figure 3As shown, one side of the dry-type transformer body 100 is equipped with a fire extinguishing device 400 for automatically receiving smoke sensor monitoring data and automatically updating fire monitoring perception based on the monitoring data. The starting mode of the fire extinguishing device 400 is two or more of the fixed temperature starting, hot starting and electric control starting modes. The starting modes specifically include: a combination of fixed temperature starting and electric control starting, a combination of fixed temperature starting and hot starting, and a combination of fixed temperature starting, hot starting and electric control starting. The fire extinguishing device 400 and the smoke collection unit 280 are linked through the control execution module 320. When the smoke concentration exceeds the threshold, the fire extinguishing device 400 automatically starts. The fire extinguishing device 400 can be used The ultra-fine dry powder automatic fire extinguishing device does not require the installation of a large number of pipelines and ancillary facilities. It only needs to hang and fix the fire extinguishing device 400 on one side to effectively play the role of fire extinguishing. The priority and linkage rules are as follows: hot start > constant temperature start > electric control start. Constant temperature start means that when the temperature probe detects that the ambient temperature exceeds the preset threshold (such as 120℃), the fire extinguishing is immediately triggered. Hot start means that the open flame is identified by the infrared pyroelectric flame detector. Electric control start means that the control execution module 320 of the industrial control all-in-one computer 300 is remotely triggered for manual emergency intervention. The three methods are independent of each other. Fire extinguishing can be started when any condition is met to ensure redundancy and reliability.

[0026] Among them Figure 4 and Figure 5 As shown, the control execution module 320 includes an input and output submodule 321 and an alarm submodule 322. The input and output submodule 321 is used to receive remote control instructions and realize the linkage function with the external switch. The system is equipped with a four-way digital input submodule for accepting remote control, such as remote start and stop of the cooling fan, and a four-way digital output submodule for interlocking with the external switch, such as the need to cut off the power supply due to a transformer failure. The alarm submodule 322 is used to issue early warning, alarm and trip signals according to the set alarm thresholds. The alarm thresholds include power parameter thresholds, temperature thresholds, humidity thresholds, partial discharge and insulation status thresholds, vibration and noise thresholds, and smoke and video monitoring abnormality thresholds; Specifically, the alarm threshold setting includes: Electricity parameter threshold: If the current or voltage parameters are unbalanced, the threshold can be set according to the set phases. If the set phase difference exceeds ±5%, an alarm state is triggered, and ±10% triggers a trip state. The harmonic distortion rate threshold can be set according to the total harmonic distortion rate. According to the IEEE 519 standard, if it exceeds 5%, a warning state is triggered, and if it exceeds 10%, an alarm state is triggered. If the power factor parameter is lower than 0.9, it is in a lagging state, and if it is higher than 1.0, it is in a leading state. Both states will trigger an alarm. Temperature threshold: The alarm threshold of the winding temperature is set according to the insulation grade. If the insulation grade is F (155°C), it is set to trigger the warning state when it exceeds 110°C, and the alarm state when it exceeds 130°C. It can be adjusted according to the load rate and actual environmental requirements. If the ambient temperature exceeds 40°C, the high temperature alarm is triggered. Humidity threshold: If the relative humidity of the cabinet exceeds 75%, an alarm state is triggered to prevent condensation. If the humidity exceeds 60% when the temperature drops suddenly, a warning state is triggered. Partial discharge and insulation status thresholds: Combined with historical baselines, if the partial discharge exceeds 10pC, a warning state is triggered, and if it exceeds 20pC, an alarm state is triggered. If the polarization index of the insulation resistance is lower than 1.5 or the insulation resistance value drops by 50%, an alarm state is triggered; Vibration and noise thresholds: If the vibration acceleration exceeds twice the baseline value or the absolute value is higher than 0.5m / s², an alarm state is triggered. If the noise level increases by 10dB(A) above the normal value, a warning state is triggered. Smoke and video monitoring abnormalities: If smoke particles are detected, an emergency alarm state is immediately triggered. If the video identifies that the cabinet door of the dry-type transformer body 100 is abnormally opened, foreign objects are intruded, or an arc flash is detected, an emergency alarm state is triggered.

[0027] Among them Figure 4 As shown, the sensors of each unit of the data acquisition device 200 all adopt an anti-electromagnetic interference structure and can adopt a metal shielding layer + filter circuit design to adapt to the strong electromagnetic environment of the transformer.

[0028] Among them Figure 4 As shown, the data processing and analysis module 310 is also integrated with a fault prediction model. The fault prediction model is based on historical operation data and real-time monitoring data. It uses a machine learning algorithm to analyze parameter change trends, generate health status reports, and predict potential fault types and occurrence probabilities. Specifically, the fault prediction model integrated in the data processing and analysis module 310 is implemented based on machine learning algorithms such as LSTM neural networks, random forests, or support vector machines. Outliers in historical operating data are eliminated, and Min-Max normalization processing is performed on the historical operating data to eliminate dimensionality effects. Then, a sliding window method is used to extract time series features. Key features include: temperature change rate, partial discharge trend, vibration spectrum energy, and insulation resistance polarization index. Dimensionality reduction is combined with principal component analysis, and the principal component contribution rate is adjusted according to actual environmental requirements. The model is trained using labeled historical fault data. The historical fault data contains at least five typical fault cases, and each case has ≥100 samples. The learning rate and number of iterations are optimized, and the optimizer is Adam. Finally, monitoring data and historical trend data are input in real time, and the fault type (such as insulation aging, winding overheating), fault phenomenon, occurrence probability (0%~100%), and possible causes are output. The model is linked to a local database so that a health status report can be generated based on the prediction results and maintenance measures can be provided. Specifically, the fault prediction model integrated by the data processing and analysis module 310 outputs possible causes of faults by combining a local database with feature recognition and extraction. The local database pre-stores annotated historical fault cases, each of which may include fault type, key characteristic parameters, fault cause, and maintenance records. An example is: "Insulation aging fault; associated features are: partial discharge continuously exceeding 20pC, insulation resistance polarization index <1.5; corresponding fault causes include: natural aging of insulation materials, performance degradation caused by long-term high-temperature operation." After extracting key features from the real-time input monitoring data, the fault prediction model matches the feature vectors of historical fault cases using a cosine similarity algorithm, and selects the top three historical cases with the highest similarity. The corresponding fault causes are the possible causes of the predicted output. The possible causes are weighted according to the matching similarity, and combined with the changing trends of the real-time parameters, a sorted list of fault causes is output. The model is regularly retrained based on newly added fault cases to update the local database. An example is: Assume the temperature display is abnormal: the fault phenomenon is display value drift, no display, or jump. The possible causes are sensor disconnection or short circuit, signal line interference or poor contact, or thermostat circuit board failure. Maintenance measures include: checking the sensor resistance, shielding the signal line, or replacing the thermostat. If the scenario is a false alarm or missed alarm, the possible causes are incorrect alarm threshold settings, loose or offset sensor installation, or excessively high ambient temperature. Maintenance measures include recalibrating parameters and checking sensor mounting and heat dissipation conditions. If the fan fails to start, possible causes include a damaged thermostat output relay, a fan power failure, or a stuck motor. Maintenance measures include testing the relay output and manually starting the fan for inspection.

[0029] When in use, the various units in the data acquisition device 200 work together. The high-voltage side power acquisition unit 210 collects parameters such as high-voltage side phase voltage and phase current through insulator-type electronic voltage transformers, cable-through-type electronic current transformers, etc. The low-voltage side power acquisition unit 220 obtains relevant power parameters of the low-voltage side with the help of low-voltage side current transformers and three-phase multi-function digital displays. The temperature control acquisition unit 230 uses an optical fiber temperature controller to monitor the temperature. The insulation status monitoring unit 240 captures the partial discharge amount and insulation resistance through a partial discharge sensor. The environmental monitoring unit 250 relies on a temperature and humidity controller and a temperature probe to grasp environmental parameters such as humidity and winding temperature. The video monitoring unit 260, vibration monitoring unit 270, smoke acquisition unit 280 and noise monitoring unit 290 also collect relevant data through corresponding sensors respectively. Each unit realizes data intercommunication through the network. The industrial control all-in-one machine 300 receives and integrates the data transmitted by the data acquisition device 200. Various types of data, combined with the design parameters, structural parameters, test data and historical operation data of the dry-type transformer body 100, are used by the data processing and analysis module 310 to evaluate the health status of the transformer using a multi-parameter weighted scoring model, and divided into four levels: normal, caution, abnormal and dangerous. The input and output submodule 321 of the control execution module 320 receives remote control instructions to achieve linkage with external switches. The alarm submodule 322 issues early warning, alarm and trip signals based on the set alarm thresholds. When the smoke collection unit 280 detects smoke, the fire extinguishing device 400 automatically receives the data and updates the fire monitoring perception based on this, and starts fire extinguishing through various methods such as constant temperature, hot start, and electronic control. The human-computer interaction module 330 supports users to set and modify fixed values ​​and parameters, and displays the monitoring data of each sensor in real time through various visual interfaces such as the monitoring overview screen and the input and output line parameter detection screen, making it convenient for users to understand the operating status of the transformer.

[0030] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. An intelligent monitoring system for dry-type transformers based on an electronic voltage transformer, comprising a dry-type transformer body (100), wherein a data acquisition device (200) for monitoring transformer parameters is installed on the dry-type transformer body (100), an industrial control all-in-one machine (300) is provided on one side of the dry-type transformer body (100), and the industrial control all-in-one machine (300) is internally configured with a data processing and analysis module (310), a control execution module (320) and a human-computer interaction module (330), and data transmission and communication are achieved between the data acquisition device (200), the dry-type transformer body (100) and the industrial control all-in-one machine (300) via the control execution module (320); It is characterized by: The data acquisition device (200) comprises a high-voltage side power acquisition unit (210), a low-voltage side power acquisition unit (220), a temperature control acquisition unit (230), an insulation status monitoring unit (240), an environment monitoring unit (250), a video monitoring unit (260), a vibration monitoring unit (270), and a smoke acquisition unit (280), and the units communicate with each other via a network; The industrial control all-in-one machine (300) is used to receive, integrate and store data transmitted by the data acquisition device (200), and to perform a comprehensive evaluation and diagnosis of the operating state and health state of the dry-type transformer body (100) in combination with the design parameters, structural parameters, test data and historical operating data of the dry-type transformer body (100); The data processing and analysis module (310) is used to evaluate the health status of the dry-type transformer; The control execution module (320) is used to implement data transmission and communication operations; The human-computer interaction module (330) is used to set and modify various fixed values ​​and parameters, and to view the monitoring data of each sensor in real time through a visual interface; The high-voltage side power collection unit (210) comprises an electronic voltage transformer, an electronic current transformer and high-voltage matching instruments, and is used to collect phase voltage, phase current, zero-sequence current, phase-to-phase voltage and frequency parameters on the high-voltage side; The low-voltage side power collection unit (220) comprises a low-voltage side current transformer and a three-phase multifunctional digital display meter, and is used to collect phase voltage, phase current, zero-sequence current, phase-to-phase voltage and frequency parameters of the low-voltage side; The temperature control and acquisition unit (230) comprises a dry-type transformer optical fiber temperature controller, which is used for real-time online monitoring of the temperature of the dry-type transformer body (100); The insulation state monitoring unit (240) is used to monitor the partial discharge amount and insulation resistance of different parts through a plurality of partial discharge sensors; The environmental monitoring unit (250) comprises a temperature and humidity controller and a temperature measuring probe, and is used to monitor the humidity, winding temperature, core temperature and ambient temperature inside the dry-type transformer body (100); The video monitoring unit (260) uses a camera with a flame detection function to perform video monitoring; The vibration monitoring unit (270) is used to monitor the vibration acceleration of the dry-type transformer body (100) through a vibration sensor; The smoke collection unit (280) uses a smoke sensor to collect smoke concentration; The data processing and analysis module (310) adopts a multi-parameter weighted scoring model, and each of the parameters is provided with a real-time status label, and the real-time status label includes four levels: normal, caution, abnormal, and dangerous; The data processing and analysis module (310) is also integrated with a fault prediction model. The fault prediction model is based on historical operation data and real-time monitoring data, analyzes parameter change trends through a machine learning algorithm, generates a health status report, and predicts potential fault types and occurrence probabilities.

2. The dry-type transformer intelligent monitoring system according to claim 1 is characterized in that: One side of the dry-type transformer body (100) is equipped with a fire extinguishing device (400) for automatically receiving smoke sensor monitoring data and automatically updating fire monitoring perception based on the monitoring data. The fire extinguishing device (400) is started in two or more modes of constant temperature start, hot start, and electric control start. The starting modes specifically include: a combination of constant temperature start and electric control start, a combination of constant temperature start and hot start, and a combination of constant temperature start, hot start, and electric control start. The fire extinguishing device (400) and the smoke collection unit (280) are linked through a control execution module (320). When the smoke concentration exceeds a threshold, the fire extinguishing device (400) is automatically started.

3. The dry-type transformer intelligent monitoring system according to claim 1 is characterized in that: The temperature and humidity controller adopts a pre-buried and attached installation method, and is installed on a core temperature measurement point of the dry-type transformer body (100).

4. The dry-type transformer intelligent monitoring system according to claim 1, characterized in that: The control execution module (320) includes an input / output submodule (321) and an alarm submodule (322), wherein the input / output submodule (321) is used to receive remote control instructions and realize a linkage function with an external switch, and the alarm submodule (322) is used to issue early warning, alarm and trip signals according to set alarm thresholds, wherein the alarm thresholds include power parameter thresholds, temperature thresholds, humidity thresholds, partial discharge and insulation state thresholds, vibration and noise thresholds, and smoke and video monitoring abnormality thresholds.

5. The dry-type transformer intelligent monitoring system according to claim 1, characterized in that: The electronic voltage transformer in the high-voltage side electric quantity collection unit (210) adopts an insulator-type structure, and the electronic current transformer adopts a cable-through-type structure.

6. The dry-type transformer intelligent monitoring system according to claim 1, characterized in that: The data acquisition device (200) further comprises a noise monitoring unit (290), wherein the noise monitoring unit (290) monitors the noise level of the dry-type transformer body (100) during operation via a noise sensor, wherein the noise sensor is installed above the dry-type transformer body (100), and monitoring data of the noise sensor is transmitted to the data processing and analysis module (310) via a network for comprehensive judgment of the equipment status in combination with vibration parameters.

7. The dry-type transformer intelligent monitoring system according to claim 1, characterized in that: The sensors of each unit of the data acquisition device (200) all adopt an anti-electromagnetic interference structure.

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