Fault detection method, device and system and computer readable storage medium

Abstract

The invention relates to the technical field of electric furnace transformers of submerged arc furnaces, in particular to a fault detection method, device and system and a computer readable storage medium. The fault detection method is combined with the structural form of the secondary outgoing line terminal of the electric furnace transformer of the submerged arc furnace and the open circuit, short circuit and circulating current online detection of the corresponding secondary low-voltage multi-group and multi-branch structure coil. The invention further provides a comprehensive online detection method for transformer standardization difference area analysis and transformer coil frequency response analysis offline measurement matching switching. According to the invention, real-time and accurate detection of the turn-to-turn fault of the secondary coil of the electric furnace transformer of the submerged arc furnace can be realized, and reliable guarantee is provided for safe operation of the transformer.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of electric furnace transformer of the electric arc furnace, and particularly relates to a fault detection method, device and system and a computer readable storage medium. BACKGROUND

[0002] In industry, three-phase three-pole electric arc furnaces arranged in equilateral triangles are commonly used. There are generally four typical arrangements of short network connection, the first of which is star or delta connection at the transformer box cover: generally, small transformers of 500-1000 kVA, or when the impedance of the furnace transformer is very small, this connection mode is used. The star or delta is directly connected at the outlet end of the transformer box cover or the low-voltage lead inside the transformer. The current flowing in the short network is all line current; the second is over-wall delta: the wall-penetrating hard bus section of this connection mode flows the phase current, and the positive and negative currents of each phase are mutually compensated. The soft bus section between B and C is all line current. There is slight compensation between the three phases; the third is three-phase electrode delta: in addition to the line current flowing in the electrode, the rest of the short network flows all phase current, and the positive and negative currents of adjacent phases are well compensated; the fourth is single-phase symmetrical delta: three single-phase transformers are used, placed on the floor above the furnace platform, arranged at 120 degrees on the plane, and the short network can be very short, with balanced compensation of the three phases. This arrangement method is generally used for large-capacity electric furnaces.

[0003] The electric furnace transformer is the core equipment of the electric arc furnace system, and its operating state directly affects the production efficiency and stability. The occurrence rate of the inter-turn short circuit fault of the secondary coil of the transformer is high, and the fault monitoring and operation and maintenance cost are also high, which seriously threatens the safe and stable operation of the electric arc furnace system.

[0004] The weight of the low-voltage lead copper bar and the outlet terminal of the electric furnace transformer accounts for a large proportion of the weight of the coil. The secondary coil of the electric furnace transformer is commonly double-pie type and 8-shaped. The low-voltage lead structure is various, and the outlet is commonly arranged on the box cover or the side wall. The structure type of the secondary outlet terminal commonly adopts single branch, 2 branches, 3 branches, 4 branches, 2x2 branches, 2x3 branches, 2x4 branches, etc.

[0005] For example, "2x4 branch structure" refers to the fact that the secondary coil is divided into two groups ("2") in terms of circuit structure, and each group contains 4 parallel branches ("4"), that is, the whole is composed of 2 groups x 4 branches. The essence of this structure is to increase the current-carrying capacity of the coil by parallel connection of multiple branches, and to make the current distribution in the coil more uniform, to adapt to the large current working requirement of the electric arc furnace. The 4 branches in each group are usually arranged symmetrically during winding to ensure that the impedance of each branch is consistent and to avoid unbalanced current distribution. Through this multi-level parallel connection, the requirement of the electric arc furnace for large current output at the low voltage side of the transformer is met. However, this type makes the coil current distribution complex, and the number of coil cakes and the wire diameter are large, which are easily affected by electromagnetic force and thermal stress during operation, and the insulation is prone to aging, thereby increasing the possibility of faults between groups and organizations. Moreover, there is electromagnetic coupling between the multiple branch coils, and a turn-to-turn fault in a branch of a group may affect other branches, expanding the fault range between groups. A turn-to-turn short circuit in the transformer coil will cause a sudden change in the short-circuit current of the fault phase, an increase in electric power and vibration, and if the operation continues, the coil will be deformed or even burned out, not only causing the electric arc furnace to stop production, but also possibly causing a safety accident and causing significant economic losses.

[0006] Traditional fault detection methods such as DC resistance test and no-load current detection are difficult to effectively judge for less serious turn-to-turn short circuits. Frequency response analysis based on coil anomaly detection technology is sensitive, but is greatly affected by external noise and measurement conditions, and is only suitable for offline state. The online detection method based on turn-to-turn fault magnetizing current is only suitable for no-load and light-load conditions. From the product type, the transformer detection instrument industry can be divided into several sub-fields, such as insulation test instruments, oil dissolved gas analysis instruments, temperature rise test instruments, and ultrasonic detection instruments. Each sub-field has its specific application scenario and technical requirements. For example, insulation test instruments are mainly used to evaluate the insulation performance of transformers to ensure their safe and stable operation in high-voltage environments; oil dissolved gas analysis instruments are used to monitor the content of dissolved gases in transformer oil to determine the internal fault condition of the transformer.

[0007] With the increasing demand for production continuity and reliability of the electric arc furnace, it is necessary to detect turn-to-turn faults in the secondary coil of the transformer during operation. Therefore, there is an urgent need for an effective detection method for the multi-branch structure of the secondary coil of the electric arc furnace transformer, which is arranged in an equilateral triangular arrangement, except for the short net connection of the low-voltage lead inside the transformer, which is the first to the fourth typical arrangement, in order to detect faults early and take measures to ensure the safe and stable operation of the transformer. SUMMARY

[0008] In view of the above-mentioned defects or deficiencies in the prior art, the present application aims to provide a fault detection method, device and system, and a computer readable storage medium.

[0009] In a first aspect, according to embodiments of the present application, a fault detection method is provided, comprising the steps of:

[0010] obtaining turn-to-turn short circuit fault influence source data of each phase multi-outlet terminal of an electric furnace transformer of an electric arc furnace in real time;

[0011] determining a turn-to-turn short circuit fault influence factor of each phase group of secondary windings of the electric furnace transformer based on the turn-to-turn short circuit fault influence source data, the turn-to-turn short circuit fault influence factor comprising: current anomaly, normalized difference area, and frequency response;

[0012] comparing the turn-to-turn short circuit fault influence factor of the secondary windings of the electric furnace transformer with a corresponding threshold value;

[0013] if the turn-to-turn short circuit fault influence factor of a certain group of branch secondary windings of the electric furnace transformer is greater than the corresponding threshold value, the phase windings of the electric furnace transformer have a turn-to-turn short circuit fault, otherwise, the phase secondary windings of the electric furnace transformer do not have a turn-to-turn short circuit fault.

[0014] In combination with the first aspect, in some embodiments of the present application, the turn-to-turn short circuit fault influence source data comprises: current data, output voltage waveform, and frequency response curve.

[0015] In combination with the first aspect, in some embodiments of the present application, the determination of the turn-to-turn short circuit fault influence factor of a certain phase group of secondary windings of the electric furnace transformer based on the turn-to-turn short circuit fault influence source data comprises:

[0016] taking the current data of each phase secondary winding to determine the measured current of each phase group of the electric furnace transformer.

[0017] In combination with the first aspect, in some embodiments of the present application, the determination of the turn-to-turn short circuit fault influence factor of each phase secondary winding of the electric furnace transformer based on the turn-to-turn short circuit fault influence source data comprises:

[0018] first comparing the current output voltage waveform with the reference output voltage waveform to calculate the difference area, and then taking the difference area ratio to the reference area as the normalized difference area of each phase secondary winding of the electric furnace transformer.

[0019] In combination with the first aspect, in some embodiments of the present application, the determination of the turn-to-turn short circuit fault influence factor of each phase group of secondary windings of the electric furnace transformer based on the turn-to-turn short circuit fault influence source data comprises:

[0020] The current frequency response curve is compared with a reference curve, and a root mean square error is calculated as a frequency response of each phase and each group of secondary coils of the electric furnace transformer.

[0021] In a second aspect, according to embodiments of the present application, there is provided a fault detection device adapted to the fault detection method of any one of the first aspect, the fault detection device comprising:

[0022] a sensor module for determining turn-to-turn short circuit fault impact source data;

[0023] a data acquisition module in communication with the sensor module for acquiring the turn-to-turn short circuit fault impact source data;

[0024] a calculation and analysis module in communication with the data acquisition module for calculating circulating current, standardized difference area and frequency response;

[0025] an alarm module in communication with the calculation and analysis module for issuing an alarm information and recording fault information when a turn-to-turn short circuit fault is detected; and

[0026] a display module in communication with the calculation and analysis module for displaying detection result information and alarm information obtained by calculating circulating current, standardized difference area and frequency response.

[0027] In a third aspect, according to embodiments of the present application, there is provided a fault detection system adapted to the fault detection method of any one of the first aspect, the fault detection system comprising:

[0028] a detection unit for detecting open circuit, short circuit and circulating current;

[0029] a transformer standardized difference area analysis unit for measuring short circuit impedance and calculating difference area;

[0030] a transformer each phase and each group of secondary coil frequency response analysis unit for comparing a current frequency response curve with a reference curve, and calculating a root mean square error as a frequency response of each phase and each group of secondary coils of the electric furnace transformer;

[0031] a data processing unit for integrating analysis data of the detection unit, the transformer standardized difference area analysis unit and the transformer coil frequency response analysis unit and generating a detection report;

[0032] an alarm unit for issuing an alarm information when a fault occurs.

[0033] In a fourth aspect, according to an embodiment of the present application, a computer readable storage medium is provided, including a computer program, when the computer program is run on an electronic device, causing the electronic device to execute the fault detection method as described in the first aspect.

[0034] Compared with the prior art, the present application has the following beneficial effects:

[0035] The present application can realize real-time and accurate detection of the secondary coil turn-to-turn fault of the electric furnace transformer of the submerged arc furnace, provide reliable guarantee for the safe operation of the transformer, reduce the fault downtime and maintenance cost, realize the automation of the detection process, reduce manual intervention, and solve the problems of low detection precision, difficult fault positioning, insufficient data integration and low automation degree of the existing submerged arc furnace electric furnace transformer turn-to-turn short circuit fault detection. BRIEF DESCRIPTION OF DRAWINGS

[0036] In order to more clearly illustrate the schemes in the embodiments of the present application, the drawings needed to be used in the description of the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0037] Figure 1 is a flowchart of the fault detection method according to an embodiment of the present application;

[0038] Figure 2 is a schematic diagram of the 2x2 secondary outlet terminal structure of the electric furnace transformer of the submerged arc furnace according to an embodiment of the present application;

[0039] Figure 3 is a configuration diagram of the turn-to-turn fault detection device of the 2x2 secondary outlet terminal structure of the electric furnace transformer of the submerged arc furnace according to an embodiment of the present application;

[0040] Figure 4 is a flowchart of the coil open circuit, short circuit and circulating current detection and judgment of the 2x2 secondary outlet terminal structure of the electric furnace transformer of the submerged arc furnace according to an embodiment of the present application;

[0041] Figure 5 is a flowchart of the 2x2 secondary outlet terminal structure of the transformer connected to the standardized difference area SDA system through the Rogowski coil according to an embodiment of the present application;

[0042] Figure 6 is a flowchart of the coil frequency response analysis FRA system of the 2x2 secondary outlet terminal structure of the electric furnace transformer of the submerged arc furnace according to an embodiment of the present application. DETAILED DESCRIPTION

[0043] The application will be described in further detail below with reference to the drawings and embodiments. It is to be understood that the specific embodiments described herein are intended to be illustrative only and not limiting of the application. It is also to be understood that the drawings are not necessarily to scale and that, unless otherwise indicated, they are merely intended to aid in the description of the application.

[0044] At present, in the on-line detection of turn-to-turn short circuit fault of electric furnace transformer of the ore smelting furnace, the detection difficulty is increased due to the adoption of 2x2 secondary winding terminal structure type coil (for convenience of description, hereinafter referred to as secondary coil). The turn-to-turn short circuit fault refers to the short circuit phenomenon caused by the damage of insulation between adjacent turns in the secondary coil of the transformer, which can cause local overheating and abnormal current of the transformer, and can even cause the transformer to burn out in severe cases.

[0045] In order to solve the above-mentioned problems in the on-line detection of turn-to-turn short circuit fault, the application provides a fault detection method. The fault detection method combines the on-line detection of open circuit, short circuit and circulating current of the secondary coil, and the off-line measurement of SDA (standardized difference area analysis of transformer) and FRA (frequency response analysis of transformer coil) to realize the comprehensive on-line detection method with switching.

[0046] For the sake of simplicity, the 2x2 secondary winding terminal structure type of the electric furnace transformer of the ore smelting furnace will be analyzed below. The characteristics, logic and application scenarios of other multi-group multi-branch structure types are based on the same principle.

[0047] As shown in Figures 1 to 6 In an embodiment, a fault detection method is provided, which is suitable for the electric furnace transformer of the ore smelting furnace, and can also be widely used in high-power transformer equipment in the metallurgical, chemical and other industries. For the sake of simplicity, the structure type of the secondary winding terminal of the electric furnace transformer involved in the application adopts the 2x2 branch structure type (each secondary coil is divided into two groups in the circuit structure, and each group contains two parallel branches). The fault detection method comprises the following steps:

[0048] Step S1, acquiring the turn-to-turn short circuit fault influence source data of the multi-way secondary winding terminal of the electric furnace transformer of the ore smelting furnace in real time;

[0049] In some embodiments, the turn-to-turn short circuit fault influence source data includes current data, output voltage waveform and frequency response curve;

[0050] In some embodiments, based on the current measuring device, the current data of the secondary coil of the electric furnace transformer of the electric arc furnace is collected in real time by the data acquisition system, wherein the sampling frequency is not less than 1HZ but not more than 10HZ; the current measuring device is configured at each phase multi-way outlet end of the electric furnace transformer of the electric arc furnace, and the range of the current measuring device covers the rated current range of the electric furnace transformer of the electric arc furnace, so as to achieve the purpose of multi-way current monitoring and monitor the circulating current between the parallel coils and find the imbalance phenomenon. In some embodiments, the current measuring device comprises a Rogowski coil, also known as a current measuring coil or a differential current sensor, and the Rogowski coil is installed in the multi-way parallel coil on the secondary coil side, which is used to monitor the current value of the secondary coil of the electric furnace transformer of the electric arc furnace in real time. In some embodiments, the fault detection method further comprises current balance analysis, that is, by analyzing the balance state of the multi-way current through the characteristics of the secondary coil, if the current of a certain way is abnormal, there may be a turn-to-turn short circuit fault. In some embodiments, the fault detection method further comprises high-frequency signal injection, that is, injecting a high-frequency signal into the secondary coil, and by analyzing the signal response characteristics, it is detected whether there is a turn-to-turn short circuit.

[0051] Step S2, based on the turn-to-turn short circuit fault influence source data, determining the turn-to-turn short circuit fault influence factor of the secondary coil of the electric furnace transformer of the electric arc furnace, the turn-to-turn short circuit fault influence factor comprising: measured current, standardized difference area and frequency response;

[0052] In some embodiments, based on the turn-to-turn short circuit fault influence source data, determining the turn-to-turn short circuit fault influence factor of the secondary coil of the electric furnace transformer of the electric arc furnace comprises:

[0053] Taking the current data of the secondary coil, the measured current of the secondary coil of the electric furnace transformer of the electric arc furnace is determined.

[0054] In some embodiments, FRA (transformer secondary coil frequency response analysis): the FRA signal generator first excites the transformer secondary coil by injecting a sweep signal (usually 1 Hz to 10 MHz) through a voltage transformer isolated from the transformer secondary coil, and then measures the response signal of the secondary coil through a signal acquisition device to detect changes in the coil structure and identify faults. Due to the high voltage and strong current of the electric furnace transformer during operation, the FRA test requires excitation and signal measurement of the transformer secondary coil, which may introduce additional safety risks, and the test equipment may be damaged or even cause accidents due to high voltage, large current and other abnormal conditions. The electromagnetic environment during transformer operation is extremely complex, in addition to the interference caused by the secondary coil, there are other interference sources such as harmonics in the system, electromagnetic radiation from other electrical equipment nearby, bus current, etc. These interferences are difficult to completely eliminate by simply adding a voltage transformer, and will seriously affect the accuracy of the FRA test results. The excitation signal applied during the FRA test process may affect the normal operation of the transformer, such as causing changes in the electromagnetic force inside the transformer, affecting its insulation performance, etc. Especially for important electric furnace transformers in operation, this potential impact may threaten the stable power supply of the electric furnace transformer. According to the requirements of standards and specifications: relevant power standards and specifications such as GB / T1094.18-2016 "Electric Power Transformer Part 18: Frequency Response Measurement", etc., usually require FRA testing under certain conditions such as transformer power off to ensure the reliability and comparability of the test results. Considering the above reasons, the present disclosure proposes to set a switching switch on the secondary side of the voltage transformer, and when the electric furnace transformer is effectively confirmed to be powered off, the FRA offline measurement system can be put into detection.

[0055] In some embodiments, determining the inter-turn short circuit fault influence factor of the secondary coil of the electric furnace transformer based on the inter-turn short circuit fault influence source data includes:

[0056] First, compare the current output voltage waveform with the reference output voltage waveform, calculate the difference area, and then take the difference area to reference area ratio as the normalized difference area of the secondary coil of the electric furnace transformer.

[0057] In some embodiments, determining the inter-turn short circuit fault influence factor of the secondary coil of the electric furnace transformer based on the inter-turn short circuit fault influence source data includes:

[0058] Compare the current frequency response curve with the reference curve, calculate the root mean square error, and take it as the frequency response of each phase secondary coil of the electric furnace transformer.

[0059] Step S3, compare the inter-turn short circuit fault influence factor of the secondary coil of the electric furnace transformer with the corresponding threshold value;

[0060] Step S4: If the influence factor of the inter-turn short circuit fault in a certain phase secondary coil of the electric arc furnace transformer is greater than the corresponding threshold, then there is an inter-turn short circuit fault in that phase secondary coil of the electric arc furnace transformer; otherwise, there is no inter-turn short circuit fault in the secondary coil of the electric arc furnace transformer.

[0061] In some embodiments, an open circuit occurs when the secondary coil is disconnected, preventing normal current flow and resulting in an abnormal current. The phenomenon is that when open-circuited, the secondary coil current I drops to zero or near zero. The determination method involves real-time monitoring of the secondary coil current I using a Rogowski coil. If I is lower than a set threshold value... min If the current is not met, it is considered an open circuit. Threshold setting: based on the transformer's rated current I. rated Set the open-circuit threshold Imin =

[0062] k·I rated , where k is a coefficient less than 1 (e.g., k = 0.1).

[0063] In some embodiments, a short circuit occurs when a short circuit occurs inside or outside the secondary coil, causing an abnormal increase in current. The phenomenon is that during a short circuit, the current I in the secondary coil increases significantly. The determination method involves real-time monitoring of the secondary coil current I using a Rogowski coil. If I exceeds a set threshold value... max If the current is too high, it is considered a short circuit; threshold setting: based on the transformer's rated current I. rated Set short-circuit threshold I max =m·I rated , where m is a coefficient greater than 1 (e.g., m = 1.5).

[0064] In some embodiments, the circulating current is the current generated due to the imbalance between the secondary coils or the asymmetry of the external load. Assuming the currents in the secondary coils are I1 and I2, the circulating current I... cir It can be represented as:

[0065]

[0066] Where I1 and I2 are the effective values ​​of the coil current.

[0067] Calculation of circulating current: By measuring the secondary coil currents I1 and I2 using a Rogowski coil, the circulating current I can be obtained according to the formula above. cir .

[0068] Determination of circulating current: If the circulating current I cir Exceeding the set threshold I cirmax If it does not, it is considered abnormal; threshold setting: based on the transformer's rated current I. rated Set the circulating current threshold I cirmax =n·I ratedwhere n is a coefficient less than 1 (e.g. n = 0.2).

[0069] In some embodiments, the circulating current detection method comprises the following steps:

[0070] Step 1. Install Rogowski coils at the secondary coil outlet terminals of the electric furnace transformer (e.g. a1, a2 for phase A, b1, b2 for phase B, c1, c2 for phase C), as shown in Figure 3 Ensure that the Rogowski coil has a range covering the rated current range of the transformer and has good anti-interference ability.

[0071] Step 2. Collect current data (e.g. I a1 , I a2 , I b1 , I b2 , I c1 , I c2 , etc.) at the secondary coil outlet terminals in real time through the data acquisition system. The sampling frequency should be high enough (recommended ≥ 1 Hz but ≤ 10 MHz) to capture the instantaneous changes in current.

[0072] Step 3. Calculate the circulating current for the secondary coil.

[0073] For example:

[0074] Circulating current of phase A:

[0075] Circulating current of phase B:

[0076] Circulating current of phase C:

[0077] To ensure that the circulating current intensity is non-negative, take the absolute value of the circulating current.

[0078] If the secondary coil is normal, the circulating current should be close to zero.

[0079] Step 4. Set the threshold I threshold (10% of the rated current, for example) for the circulating current based on the rated current and design parameters of the transformer. If I ringA , I ringB or I ringC exceeds I threshold , it is determined that there is a turn-to-turn short circuit fault in the secondary coil of that phase.

[0080] In some embodiments, SDA (Standardized Difference Area Analysis of Transformer): Compare the signals (e.g. current, voltage, etc.) under normal and fault conditions, calculate the difference area and standardize it, analyze the changes, and determine the turn-to-turn short circuit fault.

[0081] Standardized Difference Area (SDA) is a metric used to quantify the difference in secondary coil current. It reflects the operating state of the secondary coil by calculating the difference area of the secondary coil current waveform and normalizing it.

[0082] Difference Area Calculation:

[0083] Assuming the currents of the secondary coils are I1(t) and I2(t) respectively, the difference area A is defined as:

[0084]

[0085] Where:

[0086] t1 and t2 are the time intervals for calculation. |I1(t)-I2(t)| is the absolute difference between the two currents.

[0087] Normalization:

[0088] To eliminate the influence of current amplitude, the difference area A is normalized as:

[0089]

[0090] Where: The denominator of the formula is the integral of the average of the two currents, used to normalize the difference area.

[0091] The threshold value of SDA needs to be determined according to the normal operating state of the transformer and historical data. The following is the calculation method of the threshold value:

[0092] Historical data statistics: Record the SDA values over a period of time under the normal operating state of the transformer;

[0093] Calculate the mean and standard deviation: Assuming the mean of historical SDA values is μ and the standard deviation is σ;

[0094] Set threshold: According to statistical principles, set the threshold value as:

[0095] Threshold (Threshold) = μ + k·δ

[0096] Where: k is a constant, usually 2 or 3, indicating the sensitivity to abnormal state.

[0097] Decision rule: If the current SDA value exceeds the threshold, it is determined to be an abnormal state. If the SDA value is within the threshold range, it is determined to be a normal state.

[0098] Detailed derivation:

[0099] (1) Derivation of difference area

[0100] Assuming the currents of the secondary coils are:

[0101]

[0102] wherein:

[0103] • I1 and I2 are the current amplitudes. m1 and I m2 is the current amplitude.

[0104] • Φ1 and Φ2 are the phase angles.

[0105] The formula for calculating the difference area A is:

[0106]

[0107] (2) Derivation of the standardization

[0108] The formula for calculating the standardization difference area SDA is:

[0109]

[0110] Derivation of the threshold: assuming that the distribution of historical SDA values follows a normal distribution N(μ,σ 2 ), the threshold calculation formula is:

[0111] Threshold = μ + k·σ

[0112] wherein: μ is the mean of the historical SDA values; σ is the standard deviation of the historical SDA values; k is a constant, usually taking 2 or 3.

[0113] Implementation of online detection: using a Rogowski coil to collect the current signals I1(t) and I2(t) of the secondary coil in real time; inputting the collected current signals into a data acquisition system;

[0114] Calculating SDA: integrating the collected current signals to obtain the difference area A, and integrating the average values of the two current signals to obtain the denominator of the standardization formula, and calculating the SDA value.

[0115] Judgment and alarm: comparing the calculated SDA value with the threshold value, if the SDA value exceeds the threshold value, triggering an alarm.

[0116] In some embodiments, the transformer standardization difference area analysis (SDA) method comprises the following steps:

[0117] Step 1: Install a high-precision voltage transformer at each outgoing line end for measuring the output voltage waveform. Ensure that the voltage transformer has a range covering the rated voltage range of the transformer and has good anti-interference ability.

[0118] Step 2: Under normal transformer operation, collect the voltage waveform at each outgoing line terminal as a reference waveform. The reference waveform should be recorded in the system for subsequent comparison.

[0119] Step 3: During transformer operation, collect the voltage waveform of each outgoing line in real time. The sampling frequency should be high enough (recommended ≥1Hz but ≤10MHz) to capture instantaneous voltage changes.

[0120] Step 4: Compare the current waveform with the reference waveform and calculate the area of ​​difference.

[0121] The formula for calculating the standardized area of ​​difference (SDA) is:

[0122]

[0123] The difference area can be obtained by integrating the difference region between the current waveform and the reference waveform.

[0124] Step 5, set the SDA threshold. threshold (e.g., 5%). If the SDA value exceeds SDA... threshold It was determined that there was an inter-turn short circuit fault in the secondary coil of that phase.

[0125] In some embodiments, frequency response analysis (FRA) involves applying excitation signals of different frequencies to a transformer coil and measuring its response signal (such as voltage or current) to obtain the coil's frequency response characteristics. FRA can be used to detect coil deformation, short circuits, open circuits, and other faults.

[0126] For electric arc furnace transformers in submerged arc furnaces, the transmission of FRA signals can be achieved through the voltage transformer interface. The following is a detailed derivation and calculation method.

[0127] (1) Offline detection of FRA signal transmission and acquisition

[0128] Signal transmission path: The voltage signal from the secondary coil is transmitted to the FRA detection device via the voltage transformer interface and the transformer power outage permission detection switch. The voltage transformer converts the high-voltage side voltage signal into a low-voltage signal for use by the FRA detection device.

[0129] Signal acquisition: A data acquisition system is installed at the output of the voltage transformer to acquire the voltage signal of the secondary coil in real time. The acquired signal is then subjected to a Fourier transform to obtain the frequency response characteristics of the secondary coil.

[0130] (2) Calculation of FRA signal and generation of frequency response curve

[0131] Apply excitation signal: Apply a sweep signal (e.g. sine wave) to the transformer secondary winding, with a frequency range typically from 1 Hz to 10 MHz. Record the input voltage Vin(f) and output voltage Vout(f) at each frequency point.

[0132] Calculate frequency response function: The frequency response function H(f) is defined as the ratio of output voltage to input voltage:

[0133]

[0134] Take the logarithm of H(f) to get the amplitude frequency response (in dB):

[0135] |H(f)| dB = 20log 10 |H(f)|

[0136] Generate frequency response curve: Plot |H(f)| dB as a function of frequency f, which is the frequency response curve of the secondary winding.

[0137] (3) FRA difference analysis and threshold calculation

[0138] Difference analysis: Compare the current measured frequency response curve with the historical baseline curve, and calculate the difference index.

[0139] Common difference indexes include:

[0140] Root mean square error (English abbreviation RMSE), specifically as follows:

[0141]

[0142] Where: N is the number of discrete frequency points calculated, i is the index in the summation loop (the i-th frequency point), ∑ is the cumulative result of the calculation for all frequency points (i = 1 to N), |H current (f i )| dB is the amplitude (in decibels) of the real-time measured secondary winding at frequency (f i ), |H baseline (f i )| dB is the amplitude (in decibels) of the secondary winding in healthy state at frequency (f i )

[0143] Correlation coefficient (English abbreviation CC), specifically as follows:

[0144]

[0145] Where: CC is a measure of the similarity between the current measured frequency response curve and the historical baseline curve, N is the number of discrete frequency points calculated, i is the index in the summation loop (i-th frequency point), ∑ is the accumulation of the results of the calculation over all frequency points (i = 1 to N), |H current (f i )| dB is the amplitude (in decibel form) of the secondary winding at frequency (f i ) for the real-time measurement, |H baseline (f i )| dB is the amplitude (in decibel form) of the secondary winding at frequency (f i ) for the healthy state, μ current and μ baseline are the mean values of the current curve and the baseline curve, respectively.

[0146] Threshold calculation:

[0147] According to historical data and design parameters of the transformer, set the threshold of the difference index. For example, set the threshold of RMSE as RMSE threshold , and the threshold of correlation coefficient as CC threshold . If the difference index of the current measurement exceeds the threshold, it is determined that the secondary winding has a fault.

[0148] (4) Fault determination and alarm

[0149] Determination rule: if RMSE > RMSE threshold or CC < CC threshold , it is determined that the secondary winding has a fault. According to the shape of the difference curve, further determine the fault type (such as secondary winding deformation, short circuit, open circuit, etc.).

[0150] Alarm mechanism: when a fault is detected, trigger the alarm system and record the fault information. The alarm information includes fault type, difference index value, fault occurrence time, etc.

[0151] (5) Advantages of offline FRA monitoring

[0152] No need to purchase transformer secondary winding deformation tester or frequency characteristic tester: an integrated device for implementing this test method can be used to effectively and conveniently check the transformer in the state of power failure, and the FRA offline monitoring unit has high sensitivity to small deformation or displacement.

[0153] Non-invasive: inject signals through the coupling device without direct contact with the high-voltage part. When any detection method triggers an alarm, the system will record the current data and notify the maintenance personnel for processing.

[0154] In some embodiments, the frequency response analysis (FRA) method comprises the following steps:

[0155] Step 1, install a switchable frequency response analyzer input circuit on each group of outgoing terminals for measuring the frequency response curve of the coil. The frequency range of the frequency response analyzer should cover the typical operating frequency of the transformer (e.g. 50Hz-1MHz). Set a switch on the secondary side of the voltage transformer, and when the electric furnace transformer is effectively confirmed to be powered off, the frequency response analyzer in the device can be put into detection.

[0156] Step 2, in the normal state of the transformer, collect the frequency response curve of each group of outgoing terminals as the baseline curve. The baseline curve should be recorded in the system for subsequent comparison.

[0157] Step 3, periodically collect the frequency response curve of each outgoing terminal of the transformer. The sampling frequency should be set according to the actual needs.

[0158] Step 4, compare the current frequency response curve with the baseline curve and calculate the difference index (such as root mean square error RMSE). The difference index calculation formula is:

[0159]

[0160] Current curve: real-time collected frequency response data |H current (f i )| dB .

[0161] Baseline curve: frequency response data |H baselin ( e f i )| dB

[0162] N is the total number of data points.

[0163] Step 5, set the threshold value of the difference index FRA threshold (e.g. 10% of RMSE). If the difference index exceeds FRA threshold , it is determined that there is a turn-to-turn short circuit fault in the secondary coil of the phase.

[0164] The fault detection method has the following advantages:

[0165] (1) Comprehensive detection: combine multiple methods to perform online secondary coil detection and SDA (transformer standardized difference area analysis) as the main method, and cooperate with FRA (transformer secondary coil frequency response analysis) offline detection to improve detection accuracy and ensure the reliability and comparability of test results.

[0166] (2) Early warning: timely detection of early faults to prevent accidents;

[0167] (3) Automation: automated detection and alarm, reducing manual intervention.

[0168] The present application can realize real-time and accurate detection of the secondary coil turn-to-turn short circuit fault of the electric furnace transformer of the electric arc furnace, provide reliable guarantee for the safe operation of the transformer, reduce the fault downtime and maintenance cost, realize the automation of the detection process, reduce manual intervention, and solve the problems of low detection accuracy, difficult fault positioning, insufficient data integration and low automation degree of the existing electric furnace transformer turn-to-turn short circuit fault detection.

[0169] The fault detection method solves the following technical problems:

[0170] (1) Difficulty in turn-to-turn short circuit detection: due to the multi-coil multi-path parallel structure of the low-voltage secondary coil side and the internal current balance connection line, the traditional detection method is difficult to accurately identify the turn-to-turn short circuit fault.

[0171] (2) Uneven current distribution: in the multi-path parallel structure, turn-to-turn short circuit will cause uneven current distribution, which may cause local overheating or equipment damage.

[0172] (3) Lack of real-time performance: traditional detection methods are mostly offline detection, which cannot monitor the running state of the transformer in real time, and are difficult to meet the needs of continuous production of the electric arc furnace.

[0173] (4) Low sensitivity: early or slight turn-to-turn short circuit faults are difficult to detect by traditional methods, leading to fault accumulation and causing more serious problems.

[0174] In some embodiments, a fault detection device is provided, which is suitable for the above-mentioned fault detection method, and the fault detection device comprises a sensor module, a data acquisition module, a calculation and analysis module, an alarm module and a display module.

[0175] The sensor module is used to measure the turn-to-turn short circuit fault influence source data; in some embodiments, the sensor module comprises a Rogowski coil, a voltage sensor and a frequency response analyzer; the Rogowski coil has a range of 5000A-100KA and an accuracy of ±0.5%, and the circulating current threshold is 10%-20% of the rated current; the voltage sensor has a range of 0-1000V and an accuracy of ±0.2%, and the SDA threshold is 5%-10%; the frequency response analyzer has a frequency range of 1Hz to 10MHz and an accuracy of ±0.1%, and the difference index threshold is 10% of RMSE;

[0176] The data acquisition module is in communication connection with the sensor module and is used to acquire the turn-to-turn short circuit fault influence source data; in some embodiments, the data acquisition module comprises a multi-channel data acquisition card (such as a PLC input module);

[0177] The computing analysis module is communicatively connected with the data acquisition module, and is configured to calculate the circulating current, the normalized difference area, and the frequency response. In some embodiments, the computing analysis module comprises an industrial-grade embedded computer (e.g., Advantech ARK-3500).

[0178] The alarm module is communicatively connected with the computing analysis module, and is configured to send an alarm information and record the fault information when detecting the turn-to-turn short circuit fault. In some embodiments, the alarm module comprises an audible and visual alarm (e.g., PATLITE PHL-200).

[0179] The display module is communicatively connected with the computing analysis module, and is configured to display the detection result information and the alarm information obtained by calculating the circulating current, the normalized difference area, and the frequency response. In some embodiments, the display module comprises a touch screen industrial display (e.g., Siemens SIMATIC HMI KTP700).

[0180] In some embodiments, a fault detection system is provided, which is suitable for the above-mentioned fault detection method. The fault detection system comprises a detection unit, a transformer normalized difference area analysis unit, a transformer secondary coil frequency response analysis unit, a data processing unit, and an alarm unit.

[0181] The detection unit is configured to detect the open circuit, the short circuit, and the circulating current. The detection unit comprises a voltage sensor and a Rogowski coil, which are configured to measure the open circuit voltage, the short circuit current, and the circulating current.

[0182] Open circuit detection: By measuring the voltage or impedance of the secondary coil in the open circuit state, it is determined whether the secondary coil is normal, which is used to detect the open circuit or poor contact of the secondary coil.

[0183] Short circuit detection: By measuring the current or impedance of the 2x2 branch structure coil in the short circuit state, it is determined whether the secondary coil has a short circuit fault, which is used to detect the turn-to-turn short circuit or the inter-coil short circuit of the secondary coil.

[0184] Circulating current detection: The circulating current between each group of secondary coils of each phase is monitored to determine whether there is current imbalance, which is used to detect the fault or connection problem of each group of coils.

[0185] The transformer normalized difference area analysis unit compares the difference area between the impedance frequency response curves (or voltage frequency response curves) before and after the fault by monitoring the real-time data, and normalizes it into a percentage form. It is used to assess the health status and fault degree of the secondary coil online, analyze whether the coil has a fault, sensitive to the turn-to-turn short circuit fault, and can locate the fault position. The transformer normalized difference area analysis unit comprises a normalized difference area analysis module.

[0186] The transformer coil frequency response analysis unit is used to compare the current frequency response curve with the reference curve, and calculate the root mean square error as the frequency response of the secondary coil of the electric furnace transformer of the electric arc furnace; the FRA signal generator first excites the transformer secondary coil by injecting a sweep signal (usually 1Hz to 10MHz) through a voltage transformer isolated from the transformer secondary coil group, and then measures the response signal of the secondary coil through a signal acquisition device, detects the structural change of the secondary coil, and identifies the fault. The transformer secondary coil frequency response analysis unit compares the frequency response curve (impedance or voltage changes with frequency) of the transformer secondary coil measured in real time with the reference curve, analyzes the health status of the secondary coil, and thus detects the deformation, displacement, short circuit, open circuit and other faults of the coil online. The transformer secondary coil frequency response analysis unit includes a frequency signal generator and a response analysis module.

[0187] The data processing unit is used to integrate the analysis data of the detection unit, the transformer standardized difference area analysis unit and the transformer secondary coil frequency response analysis unit and generate a detection report;

[0188] Specifically, the data processing unit is a module for collecting, processing and analyzing detection data, integrating open circuit, short circuit, circulating current, SDA and FRA data, and generating a detection report.

[0189] The alarm unit is used to issue alarm information when a fault occurs, provide audible and visual alarms or remote notifications, and facilitate timely handling of faults.

[0190] The fault detection system has the following advantages:

[0191] (1) Improve detection accuracy: by combining open circuit, short circuit and circulating current detection of the secondary coil, as well as SDA and FRA analysis, sensitive detection of early inter-turn short circuit faults is achieved, and the misjudgment rate of single detection method is reduced by using multi-technology fusion and multi-parameter comprehensive analysis, improving the accuracy and reliability of fault detection;

[0192] (2) Realize accurate fault positioning: for 2x2 secondary terminal structure type, a special detection algorithm is designed to accurately locate the fault position, and through data integration and comparative analysis, the misjudgment and omission are reduced; for example, the present application can not only detect faults, but also accurately locate the outlet terminal of the secondary coil fault coil (such as a1 or a2 of phase A), and provide maintenance suggestions to guide the operation and maintenance personnel to quickly handle faults, reduce downtime, and improve the operation efficiency of the transformer.

[0193] (3) Enhance data integration capability: design an efficient data processing unit to integrate open circuit detection, short circuit detection, circulating current detection, SDA and FRA data, and generate a comprehensive fault diagnosis report to reduce the burden of manual analysis;

[0194] (4) Improve the degree of automation: realize the automation of the detection process, reduce manual intervention, and improve the detection efficiency and response speed through the alarm unit to inform the fault information in real time.

[0195] (5) The operation environment of the electric furnace transformer of the electric furnace is poor, and the current fluctuates greatly. The traditional detection method is difficult to adapt. The online detection method has strong anti-interference ability, can adapt to complex operation environment, and ensures the stability of the detection result.

[0196] In a fourth aspect, according to an embodiment of the present application, a computer readable storage medium comprising a computer program which, when executed on an electronic device, causes the electronic device to perform the fault detection method of the first aspect is provided.

[0197] According to another embodiment of the present application, a computer readable storage medium comprising a computer program which, when executed on an electronic device, causes the electronic device to perform the fault detection method is provided.

[0198] In the description of the present application, the description of the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In addition, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in an appropriate manner. In addition, the person skilled in the art can combine and combine the various embodiments or examples described in the specification, and the features of the various embodiments or examples, without contradiction.

[0199] In addition, the terms "first", "second", etc. are used only for description, and should not be interpreted as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined as "first" and "second" can be explicitly or implicitly included at least one feature. In the description of the present application, unless otherwise explicitly and specifically defined, the meaning of "multiple" is two or more.

[0200] Any process or method descriptions in the flowchart or other descriptions herein can be understood as representing modules, segments, or code portions comprising one or more steps for implementing the specified logical functions or processes. And the scope of the preferred embodiments of the present application includes additional implementations, in which these functions can be performed in a substantially simultaneous manner or in reverse order relative to the order shown or discussed, which should be understood by those skilled in the art involved in the embodiments of the present application.

[0201] The logic and / or steps represented in the flowcharts and / or other aspects described herein. For example, an ordered listing of executable instructions for implementing logic functions can be considered an example of such logic, which can be contained in any computer-readable medium, for use by or in connection with an instruction execution system, apparatus, or apparatus (a computer-based system, a system that includes a computing analysis module, or other system that can fetch instructions from an instruction execution system and execute the instructions), or a combination of the above, which operate with or upon the instructions. For purposes of this specification, a "computer-readable medium" can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or apparatus. More specific examples (a non-exhaustive list) of the computer-readable medium include: an electrical connection (electrical) having one or more wires, a portable computer diskette (magnetic), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber (optical), and a portable compact disc read-only memory (CD ROM). In addition, the computer-readable medium can even be paper or another suitable medium upon which the program can be printed, as the program can be electronically captured, for example, by optically scanning the paper or other suitable medium, then electronically converted into a form that can be further processed by the computer. The computer-readable medium can be a computer- readable storage medium, a computer-readable signal medium or a combination of the two, depending on the particular usage or context. A "computer-readable storage medium" refers to any medium, a computer can access for reading instructions, data structures, program modules or other data, from the medium. A "computer-readable signal medium" refers to a medium that can communicate, propagate or transport program for use by or in connection with an instruction execution system, apparatus or apparatus. The computer-readable medium can be any available medium or a combination of media that can be accessed by a computer. By way of example, and not limitation, the computer-readable medium can comprise a computer-readable storage medium. The computer-readable storage medium can be a tangible device that can retain, store or maintain the program for use by or in connection with the instruction execution system, apparatus or apparatus. The program can be stored on the computer-readable storage medium by way of baseband signaling or carrier wave. The computer-readable storage medium can be any available medium or a combination of media that can be accessed by a computer. By way of example, and not limitation, the computer-readable storage medium can comprise a read-only memory (ROM), a random access memory (RAM), a cache, a flash memory, a

[0202] It should be understood that portions of the present application can be implemented in hardware, software, firmware, or combinations thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following can be used: discrete logic circuitry having logic gates for implementing logic functions upon data signals, application specific integrated circuits having appropriate combinational logic gates, programmable gate arrays (PGA), field programmable gate arrays (FPGA), etc., as is well known in the art.

[0203] Those skilled in the art can understand that all or part of the steps carried out by the method of the above embodiment can be completed by program instruction related hardware, and the program can be stored in a computer-readable storage medium. When executed, it includes one or a combination of the steps of the method embodiment.

[0204] In addition, the functional units in the embodiments of the present application can be integrated in a processing module, or each unit can exist independently physically, or two or more units can be integrated in a module. The integrated module can be implemented in the form of hardware, or in the form of software function module. If the integrated module is implemented in the form of software function module and sold or used as an independent product, it can be stored in a computer readable storage medium. The storage medium can be a read-only memory, a magnetic disk or an optical disk, etc.

[0205] The above is only a specific implementation of the present application, and does not limit the protection scope of the present application. Any person skilled in the art can easily think of the invention within the technical scope of the present application. All these should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be the protection scope of the claims.

Claims

1. A fault detection method, characterized in that, The method comprises the following steps: real-time acquisition of turn-to-turn short-circuit fault influence source data of a secondary coil of an electric furnace transformer of an electric arc furnace; determination of a turn-to-turn short-circuit fault influence factor of each phase secondary coil of the electric furnace transformer based on the turn-to-turn short-circuit fault influence source data, the turn-to-turn short-circuit fault influence factor comprising a measured current, a normalized difference area and a frequency response; comparison of the turn-to-turn short-circuit fault influence factor of each phase secondary coil of the electric furnace transformer with a corresponding threshold value; if the turn-to-turn short-circuit fault influence factor of a phase secondary coil of the electric furnace transformer is greater than the corresponding threshold value, the phase secondary coil of the electric furnace transformer has a turn-to-turn short-circuit fault, otherwise, the phase secondary coil of the electric furnace transformer does not have a turn-to-turn short-circuit fault.

2. The fault detection method of claim 1, wherein: The turn-to-turn short-circuit fault influence source data comprises current data, an output voltage waveform and a frequency response curve.

3. The fault detection method of claim 1, wherein: The determination of the turn-to-turn short-circuit fault influence factor of each phase secondary coil of the electric furnace transformer based on the turn-to-turn short-circuit fault influence source data comprises: determination of a measured current of each phase secondary coil of the electric furnace transformer from the current data of the secondary coil.

4. The fault detection method of claim 1, wherein: The determination of the turn-to-turn short-circuit fault influence factor of each phase secondary coil of the electric furnace transformer based on the turn-to-turn short-circuit fault influence source data comprises: comparison of a current output voltage waveform with a reference output voltage waveform to calculate a difference area, and then taking a difference area ratio as a normalized difference area of each phase secondary coil of the electric furnace transformer.

5. The fault detection method of claim 1, wherein: The determination of the turn-to-turn short-circuit fault influence factor of each phase secondary coil of the electric furnace transformer based on the turn-to-turn short-circuit fault influence source data comprises: comparison of a current frequency response curve with a reference curve to calculate a root mean square error as a frequency response of each phase secondary coil of the electric furnace transformer.

6. Fault detection device, characterized in that The fault detection device suitable for the fault detection method of any one of claims 1-5 comprises: a sensor module for measuring turn-to-turn short-circuit fault influence source data; a data acquisition module in communication connection with the sensor module for acquiring the turn-to-turn short-circuit fault influence source data; a calculation and analysis module in communication connection with the data acquisition module for calculating a circulating current, a normalized difference area and a frequency response; an alarm module in communication connection with the calculation and analysis module for issuing an alarm information and recording fault information when a turn-to-turn short-circuit fault is detected; and a display module in communication connection with the calculation and analysis module for displaying detection result information and alarm information obtained by calculating the circulating current, the normalized difference area and the frequency response.

7. A fault detection system characterized in that, The fault detection system suitable for the fault detection method of any one of claims 1-5 comprises: a detection unit for detecting an open circuit, a short circuit and a circulating current; a transformer normalized difference area analysis unit for measuring a short-circuit impedance and calculating a difference area; a transformer secondary coil frequency response analysis unit for comparing a current frequency response curve with a reference curve to calculate a root mean square error as a frequency response of each phase secondary coil of the electric furnace transformer; A data processing unit is configured to integrate analysis data of the detection unit, the transformer standardization difference area analysis unit and the transformer secondary coil frequency response analysis unit and generate a detection report. An alarm unit is configured to send an alarm information when a fault occurs.

8. A computer readable storage medium comprising a computer program, characterized in that, When the computer program runs on the electronic device, the electronic device is caused to perform the fault detection method according to any one of claims 1-5.

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