CN108776804A - A kind of transformer specialization repair method based on portable terminal - Google Patents

Abstract

The invention relates to a transformer professional maintenance method based on a portable terminal. 1. Build a transformer professional maintenance data platform; 2. Use a portable terminal to collect data on the transformer to be repaired; 3. Transfer the collected data group to the remote end Server; 4. Evaluate through the transformer state discrimination and early warning model based on fuzzy comprehensive evaluation and Bayesian discrimination, and give early warning suggestions; 5. Send the evaluation results and early warning suggestions to portable terminals; 6. Maintenance personnel evaluation results, early warning It is recommended to overhaul the transformer. The present invention proposes a comprehensive evaluation method of fuzzy theory + Bayesian discriminant method, and comprehensively evaluates the subordination status of the evaluated transformer from multiple factors, so that the evaluation method of the specialized maintenance of the transformer is more scientific and comprehensive, and the result of the professional maintenance of the transformer is ensured. Accuracy: collect data required for maintenance on site during transformer maintenance, and obtain transformer maintenance results in real time.

Description

A Transformer Professional Maintenance Method Based on Portable Terminal

technical field

The invention belongs to the technical field of power system transformer maintenance, and in particular relates to a portable terminal-based professional transformer maintenance method.

Background technique

The state information collection technology level of traditional power grid equipment is not high, and the key state information of some equipment cannot be obtained in real time, and the self-inspection and self-diagnosis capabilities of the equipment need to be further improved. In terms of the application of operation and maintenance information, traditional status assessment and diagnosis mainly focus on the analysis of single indicators, fail to effectively use multi-source data to achieve comprehensive research and judgment, and provide insufficient support for equipment status control and factory maintenance.

The state evaluation process is a quantitative process that maps the equipment state quantity from the information space to the state space. At present, the reliability analysis methods commonly used at home and abroad mainly include failure mode and effect analysis (FMEA) and failure severity analysis (FCA). , Fault Tree Analysis (FTA) three. The main models used for reliability analysis include reliability block diagram, fault tree model, fuzzy diagnosis model, Markov model, Bayesian network model, neural network model, etc. The more common methods in the application of state evaluation include Bayesian network, neural network, gray system theory, evidence theory, expert system, etc. The fuzzy mathematics method + analytic hierarchy process (AHP) in the commonly used comprehensive state evaluation method is an effective method to solve multi-criteria and multi-objective problems, but when there are many comparison factors, the judgment matrix is not easy to achieve consistency, and Difficult to adjust; the gray relational degree analysis method provides a quantitative measure for the development and change of a system, which is very suitable for dynamic process analysis, but when performing fault diagnosis, adopting different processing methods for the sequence will cause the size of the relational degree to change. change, but the association order usually does not change.

Contents of the invention

In order to solve the above-mentioned technical problems of unclear quantitative boundary and strong subjectivity, based on the requirement of being able to comprehensively evaluate the subordinate level status of the evaluated object from multiple factors, the present invention proposes a comprehensive method of fuzzy theory + Bayesian discriminant method According to the evaluation method, a portable terminal for transformer professional maintenance is developed to realize on-site collection and management of maintenance data, and corresponding data collection methods are adopted for the maintenance data obtained for different maintenance items. Technical thought of the present invention is as follows:

(1) Study the acquisition method of transformer status information and collect data;

Collect a variety of status information data during the operation of large transformers, including factory data, pre-test data, operating data, and recorded temporary maintenance data, periodic maintenance data, accident data, etc. Collect and investigate historical data, and make a summary to judge the current state of the transformer.

(2) Classify and analyze the operation data of the transformer, and study the storage scheme of the database;

Classify and analyze the collected data, investigate different databases, analyze their respective advantages and disadvantages, determine the appropriate database storage scheme, specify a consistent data structure and storage method, and save a large amount of historical data in the database for subsequent analysis application.

(3) Formulate the transformer operation status evaluation index system;

Carry out modeling analysis on the current operating data of the transformer, determine the appropriate fault analysis model, and judge the development trend of the operating state of the transformer. On the basis of summarizing and sorting out various data of historical and current transformer operation status, according to the current status of monitoring and maintenance of transformers in the power sector, starting from the needs of transformer condition maintenance and actual operability, classify and process various information, research And establish a scientific and objective evaluation index system for transformer operation status.

(4) According to the classification of transformer status information and classification of transformer faults, determine the functions required by the portable terminal of the transformer professional comprehensive management system; determine the function modules of the portable terminal terminal of the transformer professional maintenance comprehensive management system and the connection between modules .

The technical scheme adopted in the present invention is as follows:

A transformer professional maintenance method based on a portable terminal, comprising the following steps:

Step 1. Carry out data classification for transformer professional maintenance status information, and build a transformer professional maintenance data platform;

Step 2. Use the portable terminal to collect on-site data of the transformer being overhauled;

Step 3, the portable terminal transmits the collected data group to the remote server through a wireless network or a wired network;

Step 4. The remote server evaluates the safety state of the transformer through the power transformer state discrimination and early warning model based on fuzzy comprehensive evaluation and Bayesian discrimination based on the collected data received and combined with the historical data in the data platform, and gives Corresponding early warning recommendations;

Step 5. The remote server sends the evaluation results and early warning suggestions to the portable terminal through a wireless network or a wired network;

Step 6. The on-site maintenance personnel overhaul the transformer according to the evaluation results and early warning suggestions of the portable terminal, and make follow-up corresponding operations on the transformer to ensure the safe operation of the transformer.

Preferably, when performing data classification on transformer specialized maintenance status information in step 1, the data is divided into the following six categories:

(1) Historical data: technical performance parameters of the transformer, factory inspection data, handover and acceptance data, maintenance records, fault records, these data information form the basic state of the transformer before it is put into operation;

(2) Operation data: transformer load, oil temperature data, sealing and leakage, abnormal noise of transformer during operation, short circuit data of transformer near area, transformer relay protection data, operation data is the record of transformer operation status, and the operation status is directly related to Transformer life and aging state;

(3) Preventive test data: Transformer insulation resistance, power frequency AC withstand voltage data, preventive test data can reflect various characteristics of transformers, and are used to discover hidden dangers of transformers in operation and prevent accidents or equipment damage;

(4) On-line monitoring data: on-line monitoring data of gas in oil, on-line monitoring data of partial discharge, on-line monitoring data is the supplement of preventive test data, and is the specific performance of the current state of the transformer;

(5) The evaluation of transformer state quantity should not only reflect the overall hierarchy of the system, but also reflect the independence of each component of the transformer. Therefore, the data of each component of the transformer is divided into six parts: body, bushing, tap changer, Cooling system, non-electrical protection, online monitoring.

(6) The data of other factors, including: the operation of accessories, the appearance inspection, the service life, and the environment of operation.

Preferably, in step 2, the portable terminal is used to collect on-site data of the transformer being overhauled, and the collected data includes:

(1) Visual inspection data of transformer and its components;

When a transformer fails, whether it is an internal fault or an external fault of the transformer, the abnormal phenomenon will often be manifested in the form of sound, smell, heating degree of the transformer oil tank shell (tactile) and external protection devices of the transformer. Therefore, the appearance of the transformer body and its components should be checked according to the relevant operating procedures to understand its working state (such as the size of the temperature indication value, whether the oil level of the oil conservator is normal, whether there is gas in the gas relay, whether the oil tank Whether there is leakage in the body and whether the lead wire connection is loose or discolored, etc.), and combined with the obtained data or historical records for judgment and analysis, and complete the collection of transformer and its component appearance inspection data.

(2) Ground current test data of transformer core and clamp;

When a large power transformer is in normal operation, one point of the iron core should be well grounded. Once a multi-point ground fault occurs, the normal operation and service life of the transformer will be directly threatened. When the iron core of a power transformer is grounded at two or more points, a circulating current (sometimes up to tens of amperes) will be induced inside the iron core, resulting in partial overheating of the transformer. , a partial discharge fault occurs, seriously affecting the reliable operation of the transformer. When a multi-point ground fault occurs in the transformer core, the grounding position is different, and the size of the core ground fault current generated is also different. Therefore, it is necessary to monitor the change of the ground current of the transformer core and clamps in real time during the operation of the transformer. At the substation site, the grounding current of the iron core and clamp can be measured manually by using an AC forward ammeter.

(3) Infrared precise temperature measurement data of transformers and their components;

The faults of electrical equipment are mainly composed of two parts: internal faults and external faults. Among them, the characteristics of internal faults are mainly characterized by long heating time and continuous and stable heating process. At the same time, other characteristics will be shown according to different external environments; internal thermal faults of transformers are usually caused by factors such as poor contact. Such problems can be well solved by using infrared temperature measurement to detect the fault point and analyzing the fault in combination with oil chromatography.

External faults are mainly manifested in the form of local overheating that radiates infrared rays to the surroundings. This feature determines that the solution to its faults must require the help of infrared temperature measurement.

Faults of transformer oil pipelines occur from time to time, and the main manifestation of the fault is pipeline blockage. When the pipeline blockage occurs, the heat dissipation of the blocked part will be seriously affected, which is very unfavorable to the good operation of the transformer. It needs to be used Infrared temperature measurement combined with thermogram to solve it.

The failure of transformer oil conservator or high-voltage bushing lacking oil is a very common type of transformer failure. It is the same as the solution to oil pipeline blockage. This problem should mainly be solved by combining infrared temperature measurement and thermogram analysis. Fix it.

In addition, infrared temperature measurement can find problems such as terminal connections, cooler defects, magnetic shielding and grounding. At the substation site, the far-infrared thermometer can be used to achieve accurate temperature measurement of the transformer and its components.

(4) Ultrasonic (high frequency) partial discharge monitoring and positioning data;

When there are insulation defects inside the high-voltage power equipment, it will lead to the generation of partial discharge. The ultrasonic signal excited by the partial discharge is conducted by the partial discharge source along the insulating medium and metal parts to the casing of the power equipment, and propagates to the surrounding air through the medium and the gap. Install an ultrasonic sensor on the casing of the power equipment or near the equipment, and couple the ultrasonic signal to judge the partial discharge of the power equipment, and then indirectly reflect the insulation status of the equipment.

The partial discharge ultrasonic detection method has a wide detection frequency band, usually in the range of 20-200kHz. The ultrasonic method is a non-invasive detection method. There is no electrical connection between the detection system and the high-voltage circuit. Therefore, the ultrasonic method can avoid the influence of electromagnetic signals in principle, and has good anti-interference ability and high sensitivity. In addition, partial discharge ultrasonic detection can be performed without affecting the operation of equipment and enables the localization of partial discharge sources.

When the transformer has manufacturing defects, such as poor contact, partial discharge will occur inside the transformer. At the same time, if there are air bubbles in the oil or paper, partial discharge will also occur. Partial discharge is divided into low-energy spark discharge and high-energy arc discharge. By detecting the ultrasonic/ultra-high frequency signal at key parts of the transformer, it can accurately reflect the partial discharge inside the transformer.

At the substation site, the partial discharge ultrasonic locator can be used to monitor and locate the partial discharge in the transformer, and collect relevant data.

(5) Conventional and chromatographic analysis data of transformer oil;

It is the first choice for professional maintenance of transformers to fully evaluate the operation status of main equipment and devices in substations without power failure. Therefore, the most basic method for judging the operation status of transformers is through comprehensive evaluation of transformer oil, which is essential for evaluating all relevant parameters are important. The current parameters and historical trends of transformer oil are closely related to the operation changes of substations and the changes of external conditions (load, temperature). Dissolved gas analysis technology in oil is one of the main technologies for on-site power transformer fault diagnosis in China at present. This technology can be carried out when the system is running, and it is not affected by external electric and magnetic field factors, and can detect early faults in the transformer in time , is considered to be one of the most widely used methods for transformer fault diagnosis.

Gas chromatography analyzes the dissolved gas in the insulating oil, and regularly diagnoses the internal conditions of the transformer through oil chromatography detection without power outages, and discovers internal defects in time, which is an important means to ensure the safe and stable operation of the transformer. Early latent or partial faults of some equipment, such as multi-point grounding of the transformer core, slight inter-turn short circuit of the transformer internal coil, and relatively slight discharge, are often difficult to detect in practice. However, through the detection and analysis of dissolved gases in insulating oil, in It can be sensitively reflected in the change of the volume fraction of the fault characteristic gas in the oil. However, the oil chromatographic detection data cannot contain enough information to accurately determine the type and location of the fault. In practical applications, it is necessary to comprehensively analyze and judge according to the actual situation combined with various effective detection methods such as infrared temperature measurement and ultrasonic detection, in order to achieve better results. fault diagnosis.

At the substation site, the conventional and chromatographic analysis data of transformer oil can be collected through insulating oil dielectric strength tester, oil dielectric loss tester and automatic gas chromatograph.

(6) Verification data of transformer short-circuit resistance capability;

Short circuit accidents are serious safety accidents in substations, and substations should avoid such problems. Therefore, calculating the short-circuit resistance capacity of the medium and low-voltage windings of the transformer, finding the design and material hazards of the same batch of products, and checking whether the transformer meets the short-circuit current of the system environment are important basis for evaluating whether the substation can operate safely. After the necessary parameters are provided, high-level design and verification personnel and comprehensive verification software are used to calculate and verify the short-circuit resistance capacity of the transformer, so as to judge whether the short-circuit resistance capacity of the inspected transformer meets the operation requirements.

(7) Implementation data of the 18 countermeasures of the State Grid;

The 18 countermeasures of the State Grid are an important means to improve the safe and stable operation of the substation. The relevant inspection content can be formulated according to the relevant documents of the State Grid Corporation, and the data can be quantified to help the substation find the deficiencies in the relevant work.

Preferably, the discrimination process of the power transformer state discrimination and early warning model based on fuzzy comprehensive evaluation and Bayesian discrimination described in step 4 includes the following steps:

Step a. Carry out online monitoring for the sample to be tested, and obtain the measured values of various indicators of the power transformer;

Step b. Initialize the measurement results and quantify them according to the state evaluation system;

Step c. Obtain the evaluation result of the sample data according to the power transformer state discrimination and early warning model;

Step d. Based on the evaluation results of the power transformer state discrimination and early warning model, the Bayesian discriminant model is used to calculate the correct rate of sample discrimination. If the correct rate is higher than 90%, the output result is based on the model; if the correct rate is lower than 90%, Then update the index weight, improve the evaluation model, and return to step b;

Step e. According to the diagnosis result, determine the operation status of the power transformer and put forward corresponding early warning suggestions.

Preferably, obtaining the evaluation result of the sample data according to the power transformer state discrimination and early warning model described in step c includes the following steps:

(1) Analyze the current state of the transformer: According to the basic information of the equipment, through the production management system or other intelligent monitoring systems, all kinds of equipment basic data, test data and other data reflecting the equipment health status indicators are summarized and processed to judge the current equipment status;

(2) Data processing: extract the necessary data from the obtained data resources for analysis and processing, and convert them into state quantity indicators that can reflect the health status of the equipment for use in monitoring, early warning and state evaluation;

(3) Monitoring and early warning: According to the changes in monitoring status indicators, carry out status warnings for deterioration indicators that exceed the range specified in the status evaluation guidelines and regulations, and issue early warning information to management personnel in a timely manner according to different categories and levels;

(4) State evaluation: According to relevant evaluation standards such as the state characteristic quantity of the transformer and state evaluation guidelines, analyze and evaluate the data of each state quantity index item reflecting the health state of the equipment, and finally obtain the health state level of the equipment;

(5) Decision-making suggestions: Based on the previous data, comprehensively consider the risk assessment and hierarchical maintenance standards, and determine the specific items and time for maintenance. Through the decision-making and suggestion module, the classified maintenance standards for electric equipment are established, and the specific maintenance items and time are determined, so that maintenance personnel can arrange maintenance.

Preferably, when carrying out specialized transformer maintenance based on the portable terminal, the operation of the portable terminal includes the following steps:

(1) User registration or login: If you are a new user, you need to register first, and the new user needs to submit relevant information, including user name, contact information, etc., and the administrator will enter it into the database through operations. At the same time of new user registration, the administrator will assign operation rights according to the user level.

Registered users need to enter the user name and password on the login page, click login, and submit the relevant information to the remote background server. The background server authenticates the user's identity and feedbacks the user's operation authority. After the user logs in successfully, he will enter the default main page of the system. User registration The user registration and logout functions are operational functions available to users with administrator access rights. This operation is performed by the user directly logging in to the background server.

(2) By scanning the QR code on the transformer with a portable terminal, the basic information of the transformer can be obtained, which is convenient and quick.

(3) To create a new maintenance project, you need to fill in the substation name, project name, project start and end date, select the project execution working group, and add maintenance tasks. It can be realized by clicking New Maintenance Item, and then operating on the pop-up New Maintenance Item page. After creating a maintenance project, maintenance tasks can be added to the project content. To add a maintenance task, you can specify the maintenance transformer through the page of adding maintenance tasks, and the maintenance transformer is specified by the actual number.

(4) Input and modify transformer maintenance data. Maintenance data includes transformer basic information, maintenance safety operation information, maintenance tool/material information, transformer body inspection data, transformer bushing inspection data, transformer tap changer inspection data, cooling system inspection data, non-electrical protection and secondary circuit inspection data , On-line monitoring device inspection data, core/clamp grounding current test data, infrared temperature measurement data, ultrasonic/high frequency positioning inspection data and transformer oil chromatography detection and analysis data, etc.

(5) Query evaluation results and early warning suggestions, including: query of all maintenance items, query of maintenance items in a certain period of time, query of maintenance items in a certain area. After querying, enter the web page, and the results are displayed in the form of cards, which include the project name, the total number of tasks contained in the project, the number of completed tasks contained in the project, the start and end time of the project, the working group and other information.

Beneficial effects of the present invention:

1) The present invention proposes a comprehensive evaluation method of fuzzy theory + Bayesian discriminant method, which can comprehensively evaluate the subordination status of the evaluated transformer from multiple factors, making the evaluation method of transformer professional maintenance more scientific and comprehensive;

2) The present invention builds a data platform that can reflect the comprehensive status of the transformer, and scientifically classifies and stores the data, ensuring the accuracy of the results of specialized maintenance of the transformer;

3) The present invention improves the existing portable terminal to make it more intelligent, and can collect the data required for the maintenance and obtain the maintenance results of the transformer in real time during the professional maintenance of the transformer.

Description of drawings

Fig. 1 is a functional module frame diagram of a portable terminal;

Fig. 2 is a logic flow diagram of the present invention;

Figure 3 is a logic flow chart of the state discrimination and early warning model for transformer maintenance.

Detailed ways

Embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

As shown in Figure 1, it is a frame diagram of the functional modules of the portable terminal. In this embodiment, on the basis of the PWS-472 professional overhaul mobile portable terminal, the following functional modules are added: user login and user registration modules for user management, two-dimensional codes for data management, new tasks, data Input and query module. During the specific operation, after the maintenance personnel log in, scan the QR code on the transformer through the portable terminal to obtain the basic information of the transformer; create a new maintenance project, fill in the substation name, project name, project start and end date, select the project execution working group, add Maintenance tasks; enter and modify transformer maintenance data; query evaluation results and early warning suggestions, including: query of all maintenance items, query of maintenance items in a certain period of time, and query of maintenance items in a certain area.

As shown in Fig. 2, it is a logic flow diagram of the present invention. A transformer professional maintenance method based on a portable terminal, comprising the following steps:

Step 1. Carry out data classification for transformer professional maintenance status information, and build a transformer professional maintenance data platform;

Step 2. Use the portable terminal to collect on-site data of the transformer being overhauled;

Step 3, the portable terminal transmits the collected data group to the remote server through a wireless network or a wired network;

Step 4. The remote server evaluates the safety state of the transformer through the power transformer state discrimination and early warning model based on fuzzy comprehensive evaluation and Bayesian discrimination based on the collected data received and combined with the historical data in the data platform, and gives Corresponding early warning recommendations;

Step 5. The remote server sends the evaluation results and early warning suggestions to the portable terminal through a wireless network or a wired network;

Step 6. The on-site maintenance personnel overhaul the transformer according to the evaluation results and early warning suggestions of the portable terminal, and perform follow-up corresponding operations on the transformer.

In step 4, the power transformer state discrimination and early warning model based on fuzzy comprehensive evaluation and Bayesian discrimination evaluates the safety state of the transformer, as shown in Figure 3, which is the logic flow chart of the state discrimination and early warning model of transformer maintenance, including the following step:

Step a. Carry out online monitoring for the sample to be tested, and obtain the measured values of various indicators of the power transformer;

Step b. Initialize the measurement results and quantify them according to the state evaluation system;

Step c. Obtain the evaluation result of the sample data according to the power transformer state discrimination and early warning model;

Step d. Based on the evaluation results of the power transformer state discrimination and early warning model, the Bayesian discriminant model is used to calculate the correct rate of sample discrimination. If the correct rate is higher than 90%, the output result is based on the model; if the correct rate is lower than 90%, Then update the index weight, improve the evaluation model, and return to step b;

Step e. According to the diagnosis result, determine the operation status of the power transformer and put forward corresponding early warning suggestions. Maintenance personnel take follow-up maintenance measures based on the evaluation results and early warning recommendations.

Claims (7)

1. a kind of transformer specialization repair method based on portable terminal, which is characterized in that include the following steps：

Step 1 carries out transformer specialization inspecting state information data classification, and structure transformer specialization overhaul data is flat Platform；

Step 2 carries out data acquisition on the spot using portable terminal to the transformer overhauled；

The data aggregate of acquisition is transferred to far-end server by step 3, portable terminal by wireless network or cable network；

Step 4, far-end server are according to the gathered data received, in conjunction with the historical data in data platform, by being based on mould The Power Transformer Condition of paste overall merit and Bayesian Decision differentiates and Early-warning Model comments the safe condition of transformer Estimate, and provides corresponding early warning suggestion；

Assessment result, early warning suggestion are sent to portable terminal by step 5, far-end server by wireless network or cable network End；

Step 6, field service personnel overhaul transformer according to the assessment result of portable terminal, early warning suggestion, and right Transformer makes subsequent corresponding operating.

2. a kind of transformer specialization repair method based on portable terminal according to claim 1, which is characterized in that When carrying out data classification to transformer specialization inspecting state information in step 1, following six class is splitted data into：

(1) historical data；(2) operation data；(3) preventive trial data；(4) online monitoring data；(5) each component of transformer Data, including：Ontology, casing, tap switch, cooling system, non-ionizing energy loss, on-line monitoring；(6) number of other factors According to, including：Attachment operating condition, visual examination situation, the operation time limit, running environment amount.

3. a kind of transformer specialization repair method based on portable terminal according to claim 2, which is characterized in that Data on the spot are carried out in step 2 to the transformer overhauled using portable terminal to acquire, the data acquired include：

(1) transformer and its component facade check data；(2) transformer core, clamp earthing current test data；(3) transformation Device and its infrared accurate temperature measurement data of component；(4) ultrasonic wave (high frequency) partial discharge monitoring and location data；(5) transformer oil Routine and chromatogram analysis data；(6) transformer anti-short circuit capability verify data；(7) counter arrange of 18, state's net executes data.

4. a kind of transformer specialization repair method based on portable terminal according to claim 3, which is characterized in that Being differentiated based on the Power Transformer Condition of fuzzy overall evaluation and Bayesian Decision described in step 4 and the differentiation of Early-warning Model Journey includes the following steps：

Step a. monitors sample to be tested on-line, obtains the measured value of power transformer indices；

Step b. carries out initialization process to measurement result and quantifies according to state evaluation system；

Step c. differentiates the evaluation result that sample data is acquired with Early-warning Model according to Power Transformer Condition；

Step d. differentiates according to Power Transformer Condition and the assessment result of Early-warning Model, and sample is calculated using Bayesian Decision model The accuracy of this differentiation exports result if accuracy is higher than 90% according to model；If accuracy is less than 90%, more New Set weight improves evaluation model, return to step b；

Step e. determines Operation Condition of Power Transformers and proposes corresponding early warning suggestion according to diagnostic result.

5. a kind of transformer specialization repair method based on portable terminal according to claim 4, which is characterized in that Foundation Power Transformer Condition described in step c differentiates that it includes following step to acquire the evaluation result of sample data with Early-warning Model Suddenly：

(1) transformer current state is analyzed；

(2) extraction necessary data carries out analysis working process, is converted into the quantity of state that can reflect equipment transformer health status Index；

(3) status early warning is carried out to the deterioration index beyond state evaluation directive/guide and regulation prescribed limit, according to different classifications With grade warning information is issued to administrative staff in time；

(4) state evaluation：To reflecting that each quantity of state index item data of transformer health status is analyzed and evaluated, and final Go out equipment health status grade；

(5) decision recommendation determines project and the time for specifically needing to overhaul.

6. according to a kind of transformer specialization repair method based on portable terminal of claim 1-5 any one of them, It is characterized in that, when being overhauled into line transformer specialization based on portable terminal, the operation of portable terminal includes the following steps：

(1) user's registration or login；

(2) by the Quick Response Code on portable tty terminal transformer, the essential information of this transformer is obtained；

(3) overhauling project is created, power transformation station name, project name, project commencement date and deadline, selection project implementation working group are filled in, Add maintenance task；

(4) typing and modification of Repair of Transformer data are carried out；

(5) query assessment result, early warning suggestion, including：Complete overhaul project query, the inquiry of certain period overhauling project, somewhere Area's overhauling project inquiry.

7. a kind of transformer specialization repair method based on portable terminal according to claim 6, which is characterized in that When step (4) carries out the typing and modification of Repair of Transformer data, overhaul data includes：Transformer essential information, maintenance safety Operation information, service kit/material information, transformer body check that data, bushing shell for transformer check that data, transformer tap are opened It closes and checks that data, cooling system check that data, non-ionizing energy loss and secondary circuit check that data, on-Line Monitor Device check number According to, iron core/clamp earthing current test data, infrared measurement of temperature data, ultrasonic wave/high frequency localization examination data and transformer oil colours Spectrum detection and analysis data.