Online evaluation method and system for mechanical state of transformer

Abstract

The invention relates to the technical field of transformers, and discloses a transformer mechanical state on-line evaluation method and system, and the method comprises the steps: installing M signal generators and N signal receivers on the wall of an oil tank of a to-be-detected transformer, and comparing the correlation characteristic quantities of scattering signals of a current period and a next period, according to the method, whether the mechanical state of the transformer to be tested is changed or not is assessed, whether the mechanical state of the transformer is changed or not can be assessed visually and accurately, dependence on indirect parameters is not needed, the assessment intuition and accuracy are remarkably improved, meanwhile, the assessment capacity of the mode for the mechanical state of the iron core is enhanced, other special methods do not need to be combined, and the cost is reduced. The problems that in the prior art, the evaluation result is not visual, the accuracy is limited, and the iron core mechanical state evaluation capacity is weak are effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of transformers, and in particular, to an online evaluation method and system for the mechanical state of a transformer. Background Art

[0002] As an indispensable device in the power system, the core function of a transformer is the transmission and distribution of electric energy. However, during operation, a transformer may encounter various faults, especially winding mechanical faults and core mechanical faults, which pose a serious threat to the stable operation of the power system.

[0003] Currently, the industry has developed a variety of methods for evaluating the mechanical state of transformers, such as the short-circuit impedance method, the vibration frequency response method, and the vibration detection method. However, these methods all rely on indirect parameters such as the electrical and mechanical properties of the transformer for indirect evaluation from the side, resulting in problems such as non-intuitive evaluation results and limited accuracy, and they are weak in evaluating the mechanical state of the core and often require the combination of other specialized methods. Summary of the Invention

[0004] Based on this, in view of the above problems, it is necessary to propose an online evaluation method and system for the mechanical state of a transformer, which can intuitively and accurately evaluate whether the mechanical state of the transformer has changed, without relying on indirect parameters, significantly improving the intuitiveness and accuracy of the evaluation. At the same time, the evaluation ability of this method for the mechanical state of the core has also been enhanced, without the need to combine other specialized methods, effectively solving the problems of non-intuitive evaluation results, limited accuracy, and weak evaluation ability for the mechanical state of the core in the prior art.

[0005] To achieve the above object, in a first aspect, the present invention provides an online evaluation method for the mechanical state of a transformer, the method comprising: In the current cycle of operation of the transformer to be tested, control M signal generators to emit M scattered signals with different frequencies, obtain the scattered signal matrix received by N signal receivers, and use the scattered signal matrix as the current scattered signal matrix, where M signal generators and N signal receivers are installed on the oil tank wall of the transformer to be tested; According to the current scattered signal matrix and the reference scattered signal matrix, determine the correlation of the scattered signal deviation matrix, and use the correlation of the scattered signal deviation matrix as the correlation feature quantity of the current cycle; In the next cycle of operation of the transformer to be tested, return to execute the step of controlling M signal generators to emit M scattered signals with different frequencies and obtaining the scattered signal matrix received by N signal receivers until the correlation of the scattered signal deviation matrix is obtained, and use the correlation of the scattered signal phase deviation matrix as the correlation feature quantity of the next cycle; Evaluate whether the mechanical state of the transformer under test has changed according to the correlation characteristic quantity of the current period and the correlation characteristic quantity of the next period.

[0006] Optionally, the determining the correlation of the scattering signal deviation matrix according to the current scattering signal matrix and the reference scattering signal matrix includes: Determine the current average value of all elements in the current scattering signal matrix, and determine the reference average value of all elements in the reference scattering signal matrix; Determine the correlation of the scattering signal deviation matrix according to the current average value and all elements in the current scattering signal matrix, and the reference average value and all elements in the reference scattering signal matrix.

[0007] Optionally, the determining the correlation of the scattering signal deviation matrix according to the current average value and all elements in the current scattering signal matrix, and the reference average value and all elements in the reference scattering signal matrix includes: Using the formula Determine the correlation of the scattering signal deviation matrix; Where Is the correlation of the scattering signal deviation matrix, Is the element in the nth row and mth column of the current scattering signal matrix, Is the current average value, Is the element in the nth row and mth column of the reference scattering signal matrix, Is the reference average value.

[0008] Optionally, the evaluating whether the mechanical state of the transformer under test has changed according to the correlation characteristic quantity of the current period and the correlation characteristic quantity of the next period includes: Determine the change amount of the correlation characteristic according to the correlation characteristic quantity of the current period and the correlation characteristic quantity of the next period; Evaluate whether the mechanical state of the transformer under test has changed according to the change amount of the correlation characteristic and the change amount threshold.

[0009] Optionally, the evaluating whether the mechanical state of the transformer under test has changed according to the change amount of the correlation characteristic and the change amount threshold includes: When the change amount of the correlation characteristic is greater than the change amount threshold, evaluate that the mechanical state of the transformer under test has changed; When the change amount of the correlation characteristic is less than or equal to the change amount threshold, evaluate that the mechanical state of the transformer under test has not changed.

[0010] Optionally, the method further includes: In any cycle when the transformer to be measured is not operating, control M signal generators to emit M scattered signals with different frequencies, obtain the scattered signal matrix received by N signal receivers, and use the scattered signal matrix as the reference scattered signal matrix.

[0011] Optionally, the controlling M signal generators to emit M scattered signals with different frequencies and obtaining the scattered signal matrix received by N signal receivers includes: Control M signal generators to emit M scattered signals with different frequencies, and obtain N×M scattered signals received by N signal receivers; Extract the phase of each of the N×M scattered signals to obtain N×M scattered signal phases; Determine an N×M scattered signal phase matrix based on the N×M scattered signal phases; Use the N×M scattered signal phase matrix as the scattered signal matrix.

[0012] Optionally, the controlling M signal generators to emit M scattered signals with different frequencies and obtaining the N×M scattered signals received by N signal receivers includes: Control M signal generators to emit M scattered signals with different frequencies, and obtain N×M intermediate scattered signals received by N signal receivers at the i-th time, where the initial value of i is 1; Let i = i + 1, and return to execute the step of controlling M signal generators to emit M scattered signals with different frequencies and obtaining N×M intermediate scattered signals received by N signal receivers at the i-th time until the attenuation value of the intermediate scattered signals corresponding one-to-one between the N×M intermediate scattered signals received at the i-th time and the N×M intermediate scattered signals received at the 1st time is less than the attenuation threshold, to obtain the N×M intermediate scattered signals received multiple times; Among the N×M intermediate scattered signals received multiple times, use any one of the N×M intermediate scattered signals received as the N×M scattered signals.

[0013] Optionally, when M is greater than or equal to 2, N is greater than or equal to 1; When M is greater than or equal to 1, N is greater than or equal to 2.

[0014] To achieve the above object, the present invention provides a transformer mechanical state on-line evaluation system in a second aspect. The system includes M signal generators, N signal receivers, and a processor; The M signal generators and the N signal receivers are installed on the oil tank wall of the transformer to be measured; The processor is configured to execute the method described in any item of the first aspect.

[0015] To achieve the above object, in a third aspect, the present invention provides an on-line evaluation device for the mechanical state of a transformer, the device comprising: A current control acquisition module, configured to control M signal generators to emit M scattered signals with different frequencies in the current cycle of the transformer under test, acquire a scattered signal matrix received by N signal receivers, and use the scattered signal matrix as the current scattered signal matrix, wherein the M signal generators and the N signal receivers are installed on the tank wall of the transformer under test; A determination module, configured to determine the correlation of the scattered signal deviation matrix according to the current scattered signal matrix and the reference scattered signal matrix, and use the correlation of the scattered signal deviation matrix as the correlation feature quantity of the current cycle; A next control acquisition module, configured to, in the next cycle of the operation of the transformer under test, return to execute the step of controlling the M signal generators to emit M scattered signals with different frequencies and acquire the scattered signal matrix received by the N signal receivers, until the correlation of the scattered signal deviation matrix is obtained, and use the correlation of the scattered signal phase deviation matrix as the correlation feature quantity of the next cycle; An evaluation module, configured to evaluate whether the mechanical state of the transformer under test has changed according to the correlation feature quantity of the current cycle and the correlation feature quantity of the next cycle.

[0016] To achieve the above object, in a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to execute the method according to any one of the first aspects.

[0017] To achieve the above object, in a fifth aspect, the present invention provides a computer device comprising a memory and a processor, the memory storing a computer program, which, when executed by the processor, causes the processor to execute the method according to any one of the first aspects.

[0018] Adopting the embodiment of the present invention has the following beneficial effects: In the current cycle of the transformer under test, the above method controls M signal generators to emit M scattered signals with different frequencies, obtains the scattered signal matrix received by N signal receivers, and takes the scattered signal matrix as the current scattered signal matrix, where M signal generators and N signal receivers are installed on the oil tank wall of the transformer under test. Then, according to the current scattered signal matrix and the reference scattered signal matrix, the correlation of the scattered signal deviation matrix is determined, and the correlation of the scattered signal deviation matrix is used as the correlation feature quantity of the current cycle. In the next cycle of the transformer under test, return to execute the step of controlling M signal generators to emit M scattered signals with different frequencies and obtaining the scattered signal matrix received by N signal receivers until the correlation of the scattered signal deviation matrix is obtained, and take the correlation of the scattered signal phase deviation matrix as the correlation feature quantity of the next cycle. Finally, according to the correlation feature quantity of the current cycle and the correlation feature quantity of the next cycle, it is evaluated whether the mechanical state of the transformer under test has changed; that is, by installing M signal generators and N signal receivers on the oil tank wall of the transformer under test, and by comparing the correlation feature quantities of the scattered signals in the current cycle and the next cycle, it is evaluated whether the mechanical state of the transformer under test has changed, which can intuitively and accurately evaluate whether the mechanical state of the transformer has changed, without relying on indirect parameters, significantly improving the intuitiveness and accuracy of the evaluation. At the same time, the evaluation ability of the mechanical state of the iron core is also enhanced, and there is no need to combine other special methods, effectively solving the problems of unintuitive evaluation results, limited accuracy, and weak evaluation ability of the mechanical state of the iron core in the prior art. Description of the Drawings

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0020] Wherein: Figure 1 It is a schematic diagram of a method for online evaluation of the mechanical state of a transformer in an embodiment of the present application.

[0021] Figure 2 It is a schematic diagram of the installation relationship between the transformer under test, signal generators, and signal receivers shown in an embodiment of the present application; Figure 3 It is a schematic diagram of a device for online evaluation of the mechanical state of a transformer in an embodiment of the present application; Figure 4 It is an internal structure diagram of a computer device in some embodiments. Specific Embodiments

[0022] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0023] As an indispensable device in the power system, the core function of a transformer is the transmission and distribution of electrical energy. However, during operation, a transformer may encounter various faults, especially winding mechanical faults and core mechanical faults, which pose a serious threat to the stable operation of the power system.

[0024] Currently, the industry has developed various methods for evaluating the mechanical state of transformers, such as the short-circuit impedance method, vibration frequency response method, and vibration detection method. However, these methods all rely on indirect parameters such as the electrical and mechanical parameters of the transformer for indirect evaluation from the side, resulting in problems such as non-intuitive evaluation results and limited accuracy, and are weak in evaluating the mechanical state of the core, often requiring the combination of other specialized methods.

[0025] In response to the above problems, the present application proposes an online evaluation method and system for the mechanical state of transformers, which can intuitively and accurately evaluate whether the mechanical state of the transformer has changed, without relying on indirect parameters, significantly improving the intuitiveness and accuracy of the evaluation. At the same time, the evaluation ability of the mechanical state of the core is also enhanced, without the need to combine other specialized methods, effectively solving the problems of non-intuitive evaluation results, limited accuracy, and weak evaluation ability of the mechanical state of the core in the prior art. The specific implementation principle will be described in detail in the following embodiments.

[0026] The present application provides an online evaluation method for the mechanical state of transformers in the first aspect.

[0027] Please refer to Figure 1 , which is a schematic diagram of an online evaluation method for the mechanical state of a transformer in an embodiment of the present application. The method includes: Step 110: In the current cycle of the transformer under test, control M signal generators to emit M scattered signals with different frequencies, obtain the scattered signal matrix received by N signal receivers, and use the scattered signal matrix as the current scattered signal matrix, where M signal generators and N signal receivers are installed on the tank wall of the transformer under test.

[0028] Among them, the transformer under test refers to the transformer that needs to be evaluated for its mechanical state online; the current cycle refers to the operating cycle of the transformer under test.

[0029] It should be noted that after controlling M signal generators to emit M scattered signals with different frequencies, the M scattered signals with different frequencies will be reflected in the oil tank of the transformer under test until they are received by N signal receivers to obtain a scattered signal matrix.

[0030] Furthermore, it should be noted that the frequencies of the M signal generators need to be different so as to emit M scattered signals with different frequencies, and the frequency bands of each signal receiver need to cover the frequencies of the M signal generators so as to receive scattered signals of all frequencies.

[0031] Regarding the acquisition method of the scattered signal matrix, in some embodiments, by controlling M signal generators to emit M scattered signals with different frequencies, N×M scattered signals received by N signal receivers can be obtained. Then, an N×M scattered signal matrix is determined based on the N×M scattered signals, and finally the N×M scattered signal matrix is used as the scattered signal matrix.

[0032] Regarding the installation method of the M signal generators and N signal receivers, in some embodiments, a preset number of windows can be cut on the oil tank wall of the transformer under test, and these windows are filled with insulating materials to form insulating detection windows. Finally, the M signal generators and N signal receivers are installed on the oil tank wall of the transformer under test. Among them, the specific number of the preset windows can be obtained and preset in advance by the operator based on a large amount of experience, experiments or statistics. Of course, it can also be set by the operator according to actual needs.

[0033] In some embodiments, the specific number of the preset windows can be N+M, or can be N, or can be M, depending on the situation. For example, when N is less than or equal to M, the specific number of the preset windows can be N+M or can be M; when N is greater than or equal to M, the specific number of the preset windows can be N+M or can be N.

[0034] In some embodiments, the M signal generators and the N signal receivers can be paired or not paired, that is, M and N can be equal or not equal.

[0035] In this application, preferably paired signal generators and signal receivers are adopted. More preferably, the number of pairs of signal generators and signal receivers is generally twice the number of windings of the transformer under test.

[0036] For example, assuming that the transformer under test is a three-winding transformer with the number of windings being 3, then the number of pairs of signal generators and signal receivers is 6. For reference, Figure 2, which is a schematic diagram of the installation relationship between the transformer under test, the signal generator, and the signal receiver shown in the embodiments of the present application. In this schematic diagram, 210 is the oil tank of the transformer under test, 220 is the signal generator, 230 is the signal receiver, and 240 is the insulation detection window.

[0037] Step 120: Determine the correlation of the scattering signal deviation matrix based on the current scattering signal matrix and the reference scattering signal matrix, and use the correlation of the scattering signal deviation matrix as the correlation feature quantity of the current cycle.

[0038] Among them, the reference scattering signal matrix refers to the scattering signal matrix when there is no fault or abnormality, which can be obtained and pre-set by the operator based on a large amount of experience, experiments, or statistics. Of course, it can also be set by the operator according to actual needs.

[0039] For the acquisition method of the reference scattering signal matrix, in some embodiments, when the transformer is operating normally, control M signal generators to emit M scattering signals with different frequencies, acquire the scattering signal matrix received by N signal receivers, and use the scattering signal matrix as the reference scattering signal matrix; in other embodiments, when the transformer is not operating, control M signal generators to emit M scattering signals with different frequencies, acquire the scattering signal matrix received by N signal receivers, and use the scattering signal matrix as the reference scattering signal matrix.

[0040] In some embodiments, when the current scattering signal matrix is the current scattering signal phase matrix and the reference scattering signal matrix is the reference scattering signal phase matrix, the correlation of the scattering signal deviation matrix is the correlation of the scattering signal deviation phase matrix; in other embodiments, the phase can also be replaced with amplitude, integral value, or data point average value, etc. For example, when the current scattering signal matrix is the current scattering signal amplitude matrix and the reference scattering signal matrix is the reference scattering signal amplitude matrix, the correlation of the scattering signal deviation matrix is the correlation of the scattering signal deviation amplitude matrix; when the current scattering signal matrix is the current scattering signal integral value matrix and the reference scattering signal matrix is the reference scattering signal integral value matrix, the correlation of the scattering signal deviation matrix is the correlation of the scattering signal deviation integral value matrix; when the current scattering signal matrix is the current scattering signal data point average value matrix and the reference scattering signal matrix is the reference scattering signal data point average value matrix, the correlation of the scattering signal deviation matrix is the correlation of the scattering signal deviation data point average value matrix.

[0041] Step 130: In the next cycle of operation of the transformer under test, return to the step of controlling M signal generators to emit M scattered signals with different frequencies, and obtain the scattered signal matrix received by N signal receivers until the correlation of the scattered signal deviation matrix is obtained, and use the correlation of the scattered signal phase deviation matrix as the correlation feature quantity for the next cycle.

[0042] Herein, the next cycle refers to the next cycle after the current cycle.

[0043] Step 140: Evaluate whether the mechanical state of the transformer under test has changed according to the correlation feature quantity of the current cycle and the correlation feature quantity of the next cycle.

[0044] It should be noted that since the scattered signal matrix is obtained by the reflection of M scattered signals with different frequencies in the oil tank of the transformer under test, the scattered signal matrix can reflect the mechanical conditions in the oil tank of the transformer under test, and the correlation feature quantity is also obtained based on the scattered signal matrix. Therefore, it is possible to evaluate whether the mechanical state of the transformer under test has changed by comparing the correlation feature quantities of the scattered signals in the current cycle and the next cycle.

[0045] In some embodiments, if the correlation feature quantities of the scattered signals in the current cycle and the next cycle differ significantly, it indicates that the mechanical state of the transformer under test has changed; if the correlation feature quantities of the scattered signals in the current cycle and the next cycle differ slightly, it indicates that the mechanical state of the transformer under test has not changed.

[0046] It should also be noted that in this method of the present application, in addition to being able to evaluate whether the mechanical state of the winding and the mechanical state or position of the iron core have changed, it can also evaluate whether the mechanical state or position of other mechanical components in the transformer under test has changed; for example, the spacers, clamping parts, fasteners, etc. of the transformer under test.

[0047] In the embodiments of the present application, by installing M signal generators and N signal receivers on the oil tank wall of the transformer under test, and evaluating whether the mechanical state of the transformer under test has changed by comparing the correlation feature quantities of the scattered signals in the current cycle and the next cycle, it is possible to intuitively and accurately evaluate whether the mechanical state of the transformer has changed, without relying on indirect parameters, significantly improving the intuitiveness and accuracy of the evaluation. At the same time, the evaluation ability of the mechanical state of the iron core is also enhanced, and there is no need to combine other special methods, effectively solving the problems of non-intuitive evaluation results, limited accuracy, and weak evaluation ability of the mechanical state of the iron core in the prior art.

[0048] In addition, the online mechanical state evaluation method for transformers proposed in this application, in addition to being able to intuitively and accurately evaluate the mechanical state of transformers and enhance the evaluation ability of the mechanical state of the iron core as mentioned above, also has the following advantages: Real-time monitoring and early warning: This method can achieve real-time monitoring of the mechanical state of transformers. By continuously comparing the correlation characteristic quantities of scattering signals in different periods, it can timely detect small changes in the mechanical state, providing strong support for the early warning of transformer faults. Real-time monitoring helps to intervene at the initial stage of a fault, avoid the deterioration of the fault, and reduce maintenance costs and power outage time; Improving the stability of the power system: As a key device in the power system, the stable mechanical state of the transformer directly affects the overall stability of the power system. By using this method to conduct online evaluation of the mechanical state of the transformer, potential faults can be detected and processed in a timely manner, thereby improving the reliability and stability of the power system; Non-invasive detection: This method does not require disassembling or invasive detection of the transformer. Only a signal generator and a receiver need to be installed on the oil tank wall, greatly simplifying the detection process. Non-invasive detection avoids potential damage to the transformer caused by detection and also reduces human errors during the detection process; Strong adaptability: This method is applicable to various types of transformers, whether it is a single-phase transformer or a three-phase transformer, whether it is a dry-type transformer or an oil-immersed transformer. This method can be used to evaluate the mechanical state. By adjusting parameters such as the number of signal generators and receivers, it can adapt to the specific requirements of different transformers; Data-driven and intelligent: This method is based on data analysis of the scattering signal matrix and is a data-driven evaluation method. With the development of big data and artificial intelligence technologies, this method can be further combined with intelligent algorithms to achieve more accurate fault prediction and diagnosis; Easy to implement and maintain: The installation of the signal generator and receiver is relatively simple and has little impact on the normal operation of the transformer. The implementation cost of this method is low and it is convenient to maintain, making it suitable for wide application in the power system.

[0049] It can be seen that the online mechanical state evaluation method for transformers proposed in this application not only improves the intuitiveness and accuracy of the evaluation, but also enhances the stability of the power system, realizes non-invasive detection, and has the advantages of strong adaptability, data-driven and intelligent, and easy to implement and maintain.

[0050] In a feasible implementation manner, step 120 in the above embodiment, determining the correlation of the scattering signal deviation matrix according to the current scattering signal matrix and the reference scattering signal matrix, includes: determining the current average value of all elements in the current scattering signal matrix, and determining the reference average value of all elements in the reference scattering signal matrix; determining the correlation of the scattering signal deviation matrix according to the current average value and all elements in the current scattering signal matrix, and the reference average value and all elements in the reference scattering signal matrix.

[0051] In the embodiments of the present application, by calculating the average values of the current scattering signal matrix and the reference scattering signal matrix, and determining the correlation of the scattering signal deviation matrix based on these average values and all elements, not only can the calculation process be simplified, the accuracy and robustness of the evaluation be improved, but also it is convenient for implementation and deployment. This method has important application value in the on-line evaluation of the mechanical state of transformers and can further improve the performance and reliability of the evaluation system.

[0052] It can be understood that the calculation process is simplified: by calculating the average values of the current scattering signal matrix and the reference scattering signal matrix, the complex matrix comparison problem can be simplified to the comparison of the average values, thus greatly simplifying the calculation process. As an overall feature of the matrix, the average value can reflect the overall level of all elements in the matrix, making the subsequent correlation calculation more intuitive and concise; improving the evaluation accuracy: using the average value for comparison can reduce the influence of individual abnormal elements on the evaluation result and improve the evaluation accuracy. The average value can smooth out the noise and fluctuations in the matrix, making the evaluation result more stable and reliable; enhancing the robustness of the evaluation: by calculating the average value, the evaluation method is insensitive to small changes in the matrix, enhancing the robustness of the evaluation. This means that even if some elements in the matrix change slightly, it will not have a significant impact on the final evaluation result, thus improving the stability and reliability of the evaluation method; being convenient for implementation and deployment: calculating the average value is a relatively simple operation and is easy to implement in existing computing devices and algorithms. This method does not require complex computing resources or special hardware support, making the deployment and maintenance of the evaluation system more convenient.

[0053] In a feasible implementation manner, determining the correlation of the scattering signal deviation matrix according to all elements in the current average value and the current scattering signal matrix, as well as all elements in the reference average value and the reference scattering signal matrix in the above embodiments includes: Using the formula To determine the correlation of the scattering signal deviation matrix; Where Is the correlation of the scattering signal deviation matrix, Is the element in the nth row and mth column of the current scattering signal matrix, Is the current average value, Is the element in the nth row and mth column of the reference scattering signal matrix, Is the reference average value.

[0054] In some embodiments, Can also be expressed as the n×mth scattering signal in the current scattering signal matrix, Can also be expressed as the n×mth scattering signal in the reference scattering signal matrix.

[0055] In the embodiments of the present application, by using a formula to determine the correlation of the scattering signal deviation matrix, it not only provides a clear and quantitative standard for evaluating the mechanical state of the transformer, but also improves the efficiency and accuracy of the evaluation, facilitates algorithm implementation and automation, and has strong adaptability. This method has important application value in the on-line evaluation of the mechanical state of the transformer, can further improve the performance and reliability of the evaluation system, and provides a strong guarantee for the stable operation of the power system.

[0056] It can be understood that the clear and quantitative evaluation standard: calculating the correlation of the scattering signal deviation matrix through a specific formula provides a clear and quantitative standard for evaluating the mechanical state of the transformer. This quantitative evaluation method makes the evaluation results more objective and accurate, and reduces the subjectivity of human judgment; improving the evaluation efficiency: the formula-based calculation method can quickly obtain the correlation of the scattering signal deviation matrix, improving the evaluation efficiency. In practical applications, this evaluation method can quickly judge the mechanical state of the transformer, providing the possibility for taking timely measures; enhancing the accuracy of the evaluation: the formula takes into account the relationship between each element in the current scattering signal matrix and the reference scattering signal matrix and the corresponding average value, making the evaluation results more accurate. By comparing the deviation of each element from the average value, it can more finely reflect the changes in the mechanical state of the transformer; facilitating algorithm implementation and automation: the formula-based evaluation method can be easily programmed and implemented, facilitating integration into an automated monitoring system. This automated evaluation method can continuously and real-time monitor the mechanical state of the transformer, providing a strong guarantee for the stable operation of the power system; strong adaptability: this formula is applicable to different types of transformers and different evaluation scenarios, and only parameters such as the number of signal generators and receivers need to be adjusted. This adaptability makes this method have a wide application prospect in the power system.

[0057] In a feasible implementation manner, step 140 in the above embodiment, evaluating whether the mechanical state of the transformer to be tested has changed according to the correlation feature quantity of the current cycle and the correlation feature quantity of the next cycle, includes: determining the correlation feature change quantity according to the correlation feature quantity of the current cycle and the correlation feature quantity of the next cycle; evaluating whether the mechanical state of the transformer to be tested has changed according to the correlation feature change quantity and the change quantity threshold.

[0058] Among them, the change quantity threshold can be obtained and pre-set by the operator based on a large amount of experience, experiments or statistics. Of course, it can also be set by the operator according to actual needs.

[0059] For the determination method of the change amount of the correlation feature, in some embodiments, the difference between the correlation feature amount in the current period and the correlation feature amount in the next period can be used as the change amount of the correlation feature; in other embodiments, the absolute value of the difference between the correlation feature amount in the current period and the correlation feature amount in the next period can also be used as the change amount of the correlation feature.

[0060] In some embodiments, if the difference is used as the change amount of the correlation feature, the change amount threshold can include two thresholds, one positive and one negative. When the change amount of the correlation feature is positive, the positive threshold is used for evaluation; when the change amount of the correlation feature is negative, the negative threshold is used for evaluation. If the absolute value of the difference is used as the change amount of the correlation feature, the change amount threshold can include one threshold, and this threshold is a positive threshold, and the positive threshold can be directly used for evaluation.

[0061] In the embodiments of the present application, by determining the change amount of the correlation feature and comparing it with the change amount threshold, it is used to evaluate whether the mechanical state of the transformer to be tested has changed. This method improves the accuracy, early warning ability and adaptability of the evaluation, simplifies the decision-making process, and provides a strong guarantee for the stable operation of the power system.

[0062] It can be understood that the quantitative evaluation standard: by calculating the change amount of the correlation feature and comparing it with the change amount threshold, it provides a quantitative and objective standard for evaluating the change of the mechanical state of the transformer. This quantitative method reduces the subjectivity and uncertainty of human judgment, making the evaluation result more accurate and reliable; improving the evaluation accuracy: by setting a reasonable change amount threshold, the small changes and normal fluctuations of the mechanical state of the transformer can be accurately distinguished, thereby improving the evaluation accuracy, which helps to detect and take measures in time at the initial stage of the fault to avoid the deterioration of the fault; enhancing the early warning ability: when the change amount of the correlation feature exceeds the change amount threshold, the early warning mechanism can be triggered to notify the operation and maintenance personnel to conduct inspections and maintenance in time. This early warning ability helps to detect potential faults in advance and reduce the power outage time and maintenance cost caused by the faults; strong adaptability: this method is applicable to different types of transformers and different operating environments, and only needs to adjust the change amount threshold according to the specific situation. This adaptability makes this method have a wide application prospect in the power system; simplifying the decision-making process: through the clear change amount threshold, the operation and maintenance personnel can quickly make a decision to judge whether it is necessary to further inspect or repair the transformer, which simplifies the decision-making process and improves the work efficiency.

[0063] In a feasible implementation manner, evaluating whether the mechanical state of the transformer under test has changed according to the change amount of the correlation feature and the change amount threshold in the above embodiments includes: when the change amount of the correlation feature is greater than the change amount threshold, evaluating that the mechanical state of the transformer under test has changed; when the change amount of the correlation feature is less than or equal to the change amount threshold, evaluating that the mechanical state of the transformer under test has not changed.

[0064] In some other embodiments, the change amount threshold may include multiple thresholds. By comparing the change amount of the correlation feature with the multiple thresholds in the change amount threshold, various mechanical states of the transformer under test can be evaluated.

[0065] In the embodiments of the present application, by setting a clear comparison rule for the change amount of the correlation feature and the change amount threshold, this method provides a simple, reliable, warning and adaptable solution for evaluating whether the mechanical state of the transformer under test has changed, which helps to ensure the stable operation of the power system and improve the reliability and safety of the power system.

[0066] It can be understood that: clarity: by setting specific numerical comparisons, the evaluation results have clear judgment bases. Operation and maintenance personnel can quickly make decisions based on the numerical comparison results without relying on subjective judgments or complex analyses, which greatly improves the efficiency and accuracy of the evaluation; simplicity: the judgment process is simple and clear. Only by comparing the size relationship between the change amount of the correlation feature and the change amount threshold can the evaluation result be obtained. This simplicity makes this method easy to promote and use in practical applications and reduces the requirements for the professional skills of operation and maintenance personnel; reliability: through quantitative comparison, the evaluation errors caused by human factors are reduced. The change amount threshold can be set and adjusted according to the actual situation to ensure the reliability and accuracy of the evaluation results; warning: when the change amount of the correlation feature exceeds the change amount threshold, the warning mechanism can be triggered immediately to remind operation and maintenance personnel to check and maintain in time. This warning helps to detect problems at the initial stage of the fault, avoid the further deterioration of the fault, and reduce the maintenance cost and power outage time; adaptability: this method is applicable to different types of transformers and different operating environments. Only by adjusting the change amount threshold according to the specific situation can it be used. This adaptability makes this method have a wide application prospect in the power system and can meet the evaluation needs in different scenarios.

[0067] In a feasible implementation manner, the method in the above embodiments further includes: in any cycle when the transformer under test is not operating, controlling M signal generators to emit M scattered signals with different frequencies, obtaining the scattered signal matrix received by N signal receivers, and using the scattered signal matrix as the reference scattered signal matrix.

[0068] In an embodiment of the present application, preferably, by obtaining a reference scattering signal matrix in any period when the transformer under test is not operating, not only the accuracy and reliability of the evaluation are improved, but also the evaluation process is simplified, and the sensitivity and adaptability of the evaluation are enhanced. This step is of great significance for ensuring the safe and stable operation of the transformer.

[0069] It can be understood that ensuring the accuracy of the reference data: Obtaining the reference scattering signal matrix when the transformer is not operating can exclude various interference factors that may be generated during the operation of the transformer, such as electromagnetic interference, temperature fluctuations, mechanical vibrations, etc., thus ensuring the purity and accuracy of the reference data, which provides a reliable benchmark for subsequent mechanical condition evaluation; Simplifying the evaluation process: By obtaining reference data when the transformer is not operating, complex data collection and processing work during the normal operation of the transformer can be avoided, thus simplifying the evaluation process and improving the evaluation efficiency; Improving the sensitivity of the evaluation: Using the scattering signal matrix when not operating as a reference can more easily detect small changes in the mechanical state of the transformer, because any deviation from the reference data may indicate a change in the mechanical state. This high sensitivity helps to detect and take measures in a timely manner at the initial stage of the fault; Enhancing the reliability of the evaluation: The reference data when not operating provides a stable benchmark for comparison with the data when the transformer is operating. This stability enhances the reliability of the evaluation, making the evaluation results more accurate and credible; Adapting to different operating conditions: By obtaining reference data when not operating, it is easier to adapt to the evaluation requirements of the transformer under different operating conditions, because the reference data is obtained when the transformer is in a stationary state, so it is not affected by the operating conditions and can be used as an evaluation benchmark under various operating conditions.

[0070] In a feasible implementation manner, step 110 in the above embodiment, controlling M signal generators to emit M scattering signals with different frequencies and obtaining the scattering signal matrix received by N signal receivers includes: controlling M signal generators to emit M scattering signals with different frequencies and obtaining N×M scattering signals received by N signal receivers; extracting the phase of each of the N×M scattering signals to obtain N×M scattering signal phases; determining an N×M scattering signal phase matrix according to the N×M scattering signal phases; and using the N×M scattering signal phase matrix as the scattering signal matrix.

[0071] In the present application, preferably, the phase of the scattering signal is used for evaluation.

[0072] In the embodiments of the present application, by controlling a signal generator to emit scattering signals of different frequencies, receiving these signals to extract phase information, and then constructing a scattering signal phase matrix as an evaluation basis, this method not only improves the accuracy and stability of the evaluation, but also enhances the sensitivity of the evaluation and the ability to identify fault types, providing an effective means for the online evaluation of the mechanical state of transformers.

[0073] It can be understood that improving the evaluation accuracy: Phase information, as an important feature of the signal, can accurately reflect the changes in the signal during transmission. By comparing the scattering signal phase matrices in different cycles, the changes in the mechanical state of the transformer can be accurately judged. This phase-based evaluation method improves the evaluation accuracy and helps to detect potential faults in a timely manner; enhancing the evaluation stability: Phase information is insensitive to the amplitude changes of the signal and mainly reflects the time delay and waveform changes of the signal. Therefore, in the case of signal amplitude fluctuations, the phase information can still remain relatively stable, and this stability makes the evaluation results more reliable; improving the evaluation sensitivity: Phase changes often occur prior to amplitude changes. Therefore, by monitoring the phase information, small changes in the mechanical state of the transformer can be detected earlier. This high sensitivity helps to take intervention measures at the initial stage of the fault to avoid the deterioration of the fault; enhancing the ability to identify fault types: Different types of mechanical faults may lead to different phase change patterns. By analyzing the change characteristics of the phase matrix, the fault types can be identified, which provides strong support for fault location and cause analysis; simplifying the data processing process: The extraction of phase information is relatively simple and does not require complex signal processing algorithms, which simplifies the data processing process, improves the evaluation efficiency, and makes this method easier to be popularized in practical applications.

[0074] In a feasible implementation manner, controlling the M signal generators in the above embodiments to emit M scattering signals of different frequencies and obtaining the N×M scattering signals received by the N signal receivers includes: controlling the M signal generators to emit M scattering signals of different frequencies, obtaining the N×M intermediate scattering signals received by the N signal receivers at the i-th time, where the initial value of i is 1; letting i = i + 1, and returning to execute the step of controlling the M signal generators to emit M scattering signals of different frequencies and obtaining the N×M intermediate scattering signals received by the N signal receivers at the i-th time until the attenuation value of the intermediate scattering signals corresponding one-to-one between the N×M intermediate scattering signals received at the i-th time and the N×M intermediate scattering signals received at the first time is less than the attenuation threshold, obtaining the N×M intermediate scattering signals received multiple times; among the N×M intermediate scattering signals received multiple times, taking any one of the N×M intermediate scattering signals as the N×M scattering signals.

[0075] Among them, the attenuation threshold can be set in advance by the operator based on a large amount of experience, experiments or statistics. Of course, it can also be set by the operator according to actual needs.

[0076] In some embodiments, the attenuation threshold can be set to half of the scattered signal emitted by the signal generator.

[0077] It should be noted that since the M scattered signals emitted by the M signal generators are of different frequencies, each signal receiver can identify the number of times of reception when receiving the M scattered signals reflected in the oil tank of the transformer under test.

[0078] Furthermore, it should be noted that when the scattered signal emitted by the signal generator is reflected in the oil tank of the transformer under test, it will gradually attenuate; in this application, the scattered signal emitted by the signal generator is default to attenuate to 0 within one operating cycle.

[0079] In the embodiments of this application, by introducing attenuation threshold control and selecting the N×M intermediate scattered signals received at the same time as the N×M scattered signals during the process of acquiring the scattered signals, not only the data quality and the accuracy of the evaluation are improved, but also the consistency of the evaluation is ensured, the data acquisition process is optimized, the robustness and adaptability of the evaluation are enhanced, the evaluation process is simplified, and a more efficient and reliable method for online evaluation of the mechanical state of the transformer is provided.

[0080] It can be understood that improving data quality: by introducing an attenuation threshold control to ensure that the acquired scattering signals have sufficient intensity and quality, and only when the signal attenuates below a certain threshold, the reception of new scattering signals is stopped. This can avoid receiving signals that are too weak and have large noise interference, thereby improving the accuracy and reliability of subsequent data analysis; ensuring evaluation consistency: among the N×M intermediate scattering signals received multiple times, selecting the signals received at the same time as the evaluation basis can ensure the consistency and comparability of the evaluation, because the signals received each time have undergone reflection attenuation. Selecting the signals received at the same time can avoid evaluation errors caused by differences between signals received at different times; optimizing the data acquisition process: by receiving scattering signals multiple times and stopping the reception when the signal attenuates to a certain extent, the data acquisition process can be optimized. This method can reduce unnecessary data acquisition volume while ensuring data quality, improving data acquisition efficiency; enhancing the robustness of the evaluation: since the scattering signals received each time may be affected by external factors such as electromagnetic interference and temperature fluctuations, by receiving multiple times and selecting appropriate signals as the evaluation basis, the robustness of the evaluation method can be enhanced. Even if the signal received at a certain time is interfered, it can be compensated or corrected by signals received at other times; adapting to different operating conditions: under different transformers and different operating conditions, the attenuation speed and degree of scattering signals may be different. By introducing an attenuation threshold control, different situations can be adapted to ensure high-quality scattering signals can be acquired under different conditions; improving the sensitivity and accuracy of the evaluation: by selecting the intermediate scattering signals when the signal attenuates to a certain extent but has not completely disappeared as the evaluation basis, the sensitivity and accuracy of the evaluation can be improved, because at this time the signal still contains sufficient mechanical state information but relatively less noise and interference; simplifying the evaluation process: after introducing the attenuation threshold control, there is no need to perform complete signal reception and processing for each operating cycle. Just stop the reception when the signal attenuates to a certain extent, thereby simplifying the evaluation process and improving the evaluation efficiency.

[0081] In a feasible implementation manner, when M is greater than or equal to 2, N is greater than or equal to 1; when M is greater than or equal to 1, N is greater than or equal to 2.

[0082] In the embodiments of the present application, the configuration conditions of the number of signal generators and signal receivers (when M is greater than or equal to 2, N is greater than or equal to 1; when M is greater than or equal to 1, N is greater than or equal to 2) provide flexibility and scalability for the on-line evaluation system of the transformer mechanical state, improve the accuracy, robustness and adaptability of the evaluation, and at the same time optimize the system cost. Such configuration conditions enable this method to provide effective solutions under different evaluation scenarios and requirements.

[0083] The present application provides an on-line evaluation system for the mechanical state of a transformer in a second aspect. The system includes M signal generators, N signal receivers, and a processor (not shown in the figure, reference can be made to Figure 2 the schematic diagram shown).

[0084] In a feasible implementation manner, the M signal generators and the N signal receivers are installed on the oil tank wall of the transformer to be measured, and the processor is configured to execute the method according to any one of the first aspect.

[0085] In the embodiments of the present application, the on-line evaluation system for the mechanical state of the transformer proposed by the present application provides a strong guarantee for the stable operation of the power system through beneficial effects such as integrated design, real-time on-line monitoring, flexible scalability, high-efficiency data processing ability, easy deployment and maintenance, and improved evaluation accuracy and reliability. The system not only solves the problems of non-intuitive evaluation results, limited accuracy, and weak evaluation ability for the mechanical state of the iron core in the prior art, but also reduces the operation and maintenance costs and improves the overall efficiency of the power system.

[0086] It is understandable that system integration and automation: By integrating M signal generators, N signal receivers, and a processor into a system, the automation of on-line evaluation of the mechanical state of transformers is achieved. This integrated design makes the evaluation process more efficient and convenient, reduces the need for manual intervention, and improves the accuracy and reliability of the evaluation; Real-time and on-line monitoring: The system can collect and process scattered signal data in real time. Through the real-time analysis of the data by the processor, on-line monitoring of the mechanical state of the transformer is realized. This real-time nature enables maintenance personnel to promptly understand the operating state of the transformer, discover and handle potential faults in a timely manner, and avoid greater losses caused by the deterioration of faults; Flexibility and scalability: The number of signal generators and signal receivers in the system can be flexibly configured according to actual needs. This flexibility enables the system to adapt to different types of transformers and different evaluation requirements. At the same time, with the continuous development of technology, the system can also be easily expanded and upgraded to adapt to new evaluation methods and technologies that may emerge in the future; High-efficiency data processing ability: As the core component of the system, the processor has powerful data processing capabilities. It can quickly process a large amount of scattered signal data and extract useful information for evaluating the mechanical state of the transformer. This high-efficiency data processing ability improves the efficiency and accuracy of the evaluation, enabling the system to obtain reliable evaluation results in a short time; Easy deployment and maintenance: The deployment of the system is relatively simple. It only needs to install signal generators and signal receivers on the oil tank wall of the transformer to be tested and connect the processor. At the same time, the maintenance of the system is very convenient. Due to the high degree of integration and automation of the system, maintenance personnel only need to conduct regular inspections and maintenance to ensure the normal operation of the system; Improve the accuracy and reliability of the evaluation: Through the precise analysis and processing of scattered signal data by the processor, the system can more accurately evaluate the mechanical state of the transformer. Compared with traditional evaluation methods, this system does not need to rely on indirect parameters and can directly reflect the actual operating state of the transformer, thus improving the accuracy and reliability of the evaluation.

[0087] The present application provides an on-line evaluation device for the mechanical state of a transformer in a third aspect.

[0088] Please refer to Figure 3 , which is a schematic diagram of an on-line evaluation device for the mechanical state of a transformer in an embodiment of the present application. The device 310 includes: A current control acquisition module 311, configured to control M signal generators to emit M scattered signals with different frequencies in the current cycle of the transformer to be tested, acquire a scattered signal matrix received by N signal receivers, and use the scattered signal matrix as the current scattered signal matrix, where the M signal generators and the N signal receivers are installed on the oil tank wall of the transformer to be tested; A determination module 312, configured to determine the correlation of the scattering signal deviation matrix according to the current scattering signal matrix and the reference scattering signal matrix, and use the correlation of the scattering signal deviation matrix as the correlation feature quantity of the current period; A next control acquisition module 313, configured to return to execute the step of controlling M signal generators to emit M scattering signals with different frequencies in the next period of operation of the transformer under test, and acquire the scattering signal matrix received by N signal receivers until the correlation of the scattering signal deviation matrix is obtained, and use the correlation of the scattering signal phase deviation matrix as the correlation feature quantity of the next period; An evaluation module 314, configured to evaluate whether the mechanical state of the transformer under test has changed according to the correlation feature quantity of the current period and the correlation feature quantity of the next period.

[0089] In the embodiment of the present application, the relevant content of the above-mentioned current control acquisition module 311, determination module 312, next control acquisition module 313 and evaluation module 314 can refer to Figure 1 the content in the shown embodiment, which will not be elaborated here.

[0090] It should be noted that the device 310 of the present application further includes some other modules. It can be understood that there is a one-to-one correspondence between the method of the present application and the device 310. Therefore, some other modules of the device 310 of the present application are the corresponding content of the method of the present application in the above embodiment.

[0091] In the embodiment of the present application, by installing M signal generators and N signal receivers on the oil tank wall of the transformer under test, and comparing the correlation feature quantities of the scattering signals in the current period and the next period, it is possible to evaluate whether the mechanical state of the transformer under test has changed, which can intuitively and accurately evaluate whether the mechanical state of the transformer has changed, without relying on indirect parameters, significantly improving the intuitiveness and accuracy of the evaluation. At the same time, the evaluation ability of the mechanical state of the iron core is also enhanced, without the need to combine other special devices, effectively solving the problems of non-intuitive evaluation results, limited accuracy and weak evaluation ability of the mechanical state of the iron core in the prior art.

[0092] In addition, the on-line evaluation device for the mechanical state of the transformer proposed in this application, in addition to being able to intuitively and accurately evaluate the mechanical state of the transformer and enhance the evaluation ability of the mechanical state of the iron core as mentioned above, also has the following advantages: Real-time monitoring and early warning: This device can realize the real-time mechanical state monitoring of the transformer. By continuously comparing the correlation characteristic quantities of the scattering signals in different cycles, it can timely detect the small changes in the mechanical state, providing strong support for the fault early warning of the transformer. Real-time monitoring helps to intervene at the initial stage of the fault, avoid the deterioration of the fault, and reduce the maintenance cost and power outage time; Improve the stability of the power system: As a key device in the power system, the mechanical state stability of the transformer directly affects the overall stability of the power system. By using this device to conduct on-line evaluation of the mechanical state of the transformer, potential faults can be detected and processed in a timely manner, thereby improving the reliability and stability of the power system; Non-intrusive detection: This device does not require the disassembly or intrusive detection of the transformer. Only a signal generator and a receiver need to be installed on the oil tank wall, which greatly simplifies the detection process. Non-intrusive detection avoids potential damage to the transformer caused by detection, and also reduces the human error in the detection process; Strong adaptability: This device is applicable to various types of transformers, whether it is a single-phase transformer or a three-phase transformer, whether it is a dry-type transformer or an oil-immersed transformer, this device can be used for the mechanical state evaluation. By adjusting parameters such as the number of signal generators and receivers, it can adapt to the specific needs of different transformers; Data-driven and intelligent: This device conducts data analysis based on the scattering signal matrix and is a data-driven evaluation device. With the development of big data and artificial intelligence technologies, this device can be further combined with intelligent algorithms to achieve more accurate fault prediction and diagnosis; Easy to implement and maintain: The installation of the signal generator and the receiver is relatively simple and has little impact on the normal operation of the transformer. The implementation cost of this device is low and the maintenance is convenient, making it suitable for wide application in the power system.

[0093] In the fourth aspect of this application, a computer-readable storage medium is further provided, storing a computer program, which when executed by a processor, causes the processor to execute a method for on-line evaluation of the mechanical state of a transformer in the above method embodiment.

[0094] In the fifth aspect of this application, a computer device is further provided, including a memory and a processor, the memory storing a computer program, which when executed by the processor, causes the processor to execute a method for on-line evaluation of the mechanical state of a transformer in the above method embodiment.

[0095] Figure 4 The internal structure diagram of the computer device in some embodiments is shown. This computer device can specifically be a terminal, a server, or a gateway. As Figure 4 shown, this computer device includes a processor, a memory, and a network interface connected through a system bus.

[0096] Among them, the memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and may also store a computer program. When the computer program is executed by the processor, the processor can implement each step in the above method embodiments. The internal memory may also store a computer program. When the computer program is executed by the processor, the processor can execute each step in the above method embodiments. Those skilled in the art can understand that Figure 4 The structure shown in is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0097] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the above method embodiments.

[0098] Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or an external cache. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0099] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0100] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the appended claims.

Claims

1. An on-line evaluation method for the mechanical state of a transformer, characterized in that The method includes: In the current cycle when the transformer under test is operating, control M signal generators to emit M scattered signals with different frequencies, obtain the scattered signal matrix received by N signal receivers, and use the scattered signal matrix as the current scattered signal matrix, where M signal generators and N signal receivers are installed on the tank wall of the transformer under test; According to the current scattered signal matrix and the reference scattered signal matrix, determine the correlation of the scattered signal deviation matrix, and use the correlation of the scattered signal deviation matrix as the correlation characteristic quantity of the current cycle; In the next cycle when the transformer under test is operating, return to execute the step of controlling M signal generators to emit M scattered signals with different frequencies and obtain the scattered signal matrix received by N signal receivers until the correlation of the scattered signal deviation matrix is obtained, and use the correlation of the scattered signal phase deviation matrix as the correlation characteristic quantity of the next cycle; According to the correlation characteristic quantity of the current cycle and the correlation characteristic quantity of the next cycle, evaluate whether the mechanical state of the transformer under test has changed.

2. The on-line evaluation method for the mechanical state of a transformer according to claim 1, wherein The determining the correlation of the scattered signal deviation matrix according to the current scattered signal matrix and the reference scattered signal matrix includes: Determine the current average value of all elements in the current scattered signal matrix, and determine the reference average value of all elements in the reference scattered signal matrix; According to the current average value and all elements in the current scattered signal matrix, and the reference average value and all elements in the reference scattered signal matrix, determine the correlation of the scattered signal deviation matrix.

3. The on-line evaluation method for the mechanical state of a transformer according to claim 2, characterized in that The determining the correlation of the scattered signal deviation matrix according to the current average value and all elements in the current scattered signal matrix, and the reference average value and all elements in the reference scattered signal matrix includes: Using the formula to determine the correlation of the scattering signal deviation matrix; wherein, is the correlation of the scattering signal deviation matrix, is the element at the n-th row and m-th column in the current scattering signal matrix, is the current average value, is the element at the n-th row and m-th column in the reference scattering signal matrix, is the reference average value.

4. The on-line evaluation method for the mechanical state of a transformer according to claim 1, characterized in that, The evaluating whether the mechanical state of the transformer under test has changed according to the correlation characteristic quantity of the current cycle and the correlation characteristic quantity of the next cycle includes: Determine the change amount of the correlation characteristic according to the correlation characteristic quantity of the current cycle and the correlation characteristic quantity of the next cycle; According to the change amount of the correlation characteristic and the change amount threshold, evaluate whether the mechanical state of the transformer under test has changed.

5. The on-line evaluation method for the mechanical state of a transformer according to claim 4, characterized in that The evaluating whether the mechanical state of the transformer under test has changed according to the change amount of the correlation characteristic and the change amount threshold includes: In the case where the change amount of the correlation characteristic is greater than the change amount threshold, evaluate that the mechanical state of the transformer under test has changed; In the case where the change amount of the correlation characteristic is less than or equal to the change amount threshold, evaluate that the mechanical state of the transformer under test has not changed.

6. The on-line evaluation method for the mechanical state of a transformer according to claim 1, wherein The method further includes: In any cycle when the transformer under test is not operating, control M signal generators to emit M scattered signals with different frequencies, obtain the scattered signal matrix received by N signal receivers, and use the scattered signal matrix as the reference scattered signal matrix.

7. The on-line evaluation method for the mechanical state of a transformer according to claim 1, wherein, The controlling M signal generators to emit M scattered signals with different frequencies and obtaining the scattered signal matrix received by N signal receivers includes: Control M signal generators to emit M scattered signals with different frequencies, and obtain N×M scattered signals received by N signal receivers; Extract the phase of each of the N×M scattered signals to obtain the phases of the N×M scattered signals; Determine an N×M scattered signal phase matrix according to the phases of the N×M scattered signals; Use the N×M scattered signal phase matrix as the scattered signal matrix.

8. The on-line evaluation method for the mechanical state of a transformer according to claim 7, characterized in that, The controlling M signal generators to emit M scattered signals with different frequencies and obtaining N×M scattered signals received by N signal receivers includes: Control M signal generators to emit M scattered signals with different frequencies, and obtain N×M intermediate scattered signals received by N signal receivers at the i-th time, where the initial value of i is 1; Let i = i + 1, and return to execute the step of controlling M signal generators to emit M scattered signals with different frequencies and obtaining N×M intermediate scattered signals received by N signal receivers at the i-th time, until the attenuation value of the intermediate scattered signals corresponding one by one between the N×M intermediate scattered signals received at the i-th time and the N×M intermediate scattered signals received at the 1st time is less than the attenuation threshold, and obtain the N×M intermediate scattered signals received multiple times; Among the N×M intermediate scattered signals received multiple times, use any one of the N×M intermediate scattered signals received as the N×M scattered signals.

9. The on-line evaluation method for the mechanical state of a transformer according to claim 1, characterized in that When M is greater than or equal to 2, N is greater than or equal to 1; When M is greater than or equal to 1, N is greater than or equal to 2.

10. An on-line evaluation system for the mechanical state of a transformer, characterized in that, The system includes M signal generators, N signal receivers and a processor; The M signal generators and N signal receivers are installed on the oil tank wall of the transformer to be measured; The processor is used to execute the on-line evaluation method for the mechanical state of the transformer according to any one of claims 1 to 9.

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