Power distribution transformer equipment detection and evaluation method based on big data analysis

Abstract

The application discloses a power distribution transformer equipment detection evaluation method based on big data analysis. The application sets a detection time interval based on the running years of the power distribution transformer, and collects the operation parameters and use parameters of the power distribution transformer after reaching the set detection time interval, so as to obtain the operation evaluation index and use evaluation index of the power distribution transformer in the current detection process, thereby reflecting the operation state and use state of the power distribution transformer in the current detection process, and comprehensively evaluating the equipment condition of the power distribution transformer. The application solves the problem that in the prior art, the condition of the power distribution transformer is mostly evaluated from a single angle, and the operation and use state of the power distribution transformer cannot be comprehensively evaluated from multiple angles.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power equipment detection, and particularly relates to a power distribution transformer equipment detection and evaluation method based on big data analysis. BACKGROUND

[0002] With the acceleration of urbanization, especially in the city network construction and reconstruction, box-type substations are widely used due to their small land occupation, beautiful appearance and other advantages.

[0003] In actual application process, it is necessary to regularly detect the state of the power distribution transformer in the substation, and the existing detection method still has the following shortcomings:

[0004] It depends on manual inspection, and has problems of low detection efficiency, low accuracy, poor real-time performance and safety hazards;

[0005] If a simple automatic instrument is used for detection, such as a sensor, most of the existing technologies only evaluate the condition of the power distribution transformer from a single angle, and cannot comprehensively evaluate the operation and use state of the power distribution transformer from multiple angles, such as temperature, power, running sound, etc., resulting in low accuracy and intelligence of the power distribution transformer detection and evaluation, and safety hazards still exist.

[0006] Therefore, a power distribution transformer equipment detection and evaluation method based on big data analysis is proposed. SUMMARY

[0007] Therefore, the present application provides a power distribution transformer equipment detection and evaluation method based on big data analysis to solve the problems in the background art.

[0008] The purpose of the present application can be achieved by the following technical scheme: a power distribution transformer equipment detection and evaluation method based on big data analysis, comprising:

[0009] Data acquisition: extracting the running years of the power distribution transformer from the record log, setting the detection time interval based on the running years of the power distribution transformer, and collecting the operation parameters and use parameters of the power distribution transformer after reaching the set detection time interval; the operation parameters include temperature, power factor and load loss; the use parameters include running sound and insulation resistance;

[0010] Communication technology: transmitting the collected operation parameters and use parameters to the central processing platform through wireless communication technology;

[0011] Central processing: analyzing the operation parameters and use parameters of the power distribution transformer respectively, thereby obtaining the operation evaluation index Yx and the use evaluation index Yf of the power distribution transformer in the current detection process;

[0012] Intelligent diagnosis: set the early warning threshold index of the running evaluation index Yx and the use evaluation index Yf, if the running evaluation index Yx is greater than the corresponding set early warning threshold index, the running early warning signal is triggered, if the use evaluation index Yf is greater than the corresponding set early warning threshold index, the use early warning signal is triggered;

[0013] Remote maintenance: when the running early warning signal is triggered, select the technical personnel in working state at the current time point, and send the running early warning signal to the mobile terminal of the personnel, and allow the personnel to be authorized to remotely establish a communication connection with the power distribution transformer and perform remote troubleshooting;

[0014] On-site operation: when the use early warning signal is triggered, the corresponding step of selecting the processing personnel with the maximum field value Ne at the current time point is executed, and the location of the power distribution transformer is sent to the mobile terminal of the personnel;

[0015] Diagnosis optimization: if the power distribution transformer appears failure and abnormality in the subsequent actual use process, the early warning optimization signaling is triggered and sent to the mobile terminal of the technical personnel, and the technical personnel receives the early warning optimization signaling to dynamically adjust the set early warning threshold index.

[0016] In some embodiments, the running parameters of the power distribution transformer are analyzed, specifically:

[0017] The active power and apparent power of the power distribution transformer at each time point in the set time period in the current detection process are obtained, and the active power and apparent power at each time point are further converted into power factor, i.e. the power factor of the power distribution transformer at each time point is obtained by calculating the active power / apparent power;

[0018] The power factor of the power distribution transformer at each time point is calculated by using the standard deviation formula, and the calculated result is taken as the power fluctuation of the power distribution transformer in the set time period in the current detection process;

[0019] The highest value and the lowest value are extracted from the power factor at each time point, and the difference value between the highest value and the lowest value is calculated, so as to obtain the power difference value of the power distribution transformer in the set time period in the current detection process;

[0020] The mean value of the power factor of the power distribution transformer at each time point is calculated, and the calculated mean value is taken as the power mean value of the power distribution transformer in the set time period in the current detection process;

[0021] The maximum allowed power fluctuation, the maximum allowed power difference and the minimum allowed power mean value corresponding to the power fluctuation, the power difference and the power mean value of the power distribution transformer are respectively preset;

[0022] The power fluctuation, power difference and power average of the distribution transformer in the current detection process within the set time period are respectively calculated by the ratio of the corresponding preset maximum allowed power fluctuation, maximum allowed power difference and minimum allowed power average, that is, by the calculation of power fluctuation / maximum allowed power fluctuation, power difference / maximum allowed power difference and minimum allowed power average / power average, thereby obtaining the fluctuation ratio, difference ratio and average ratio;

[0023] The weight coefficients corresponding to the fluctuation ratio, difference ratio and average ratio are set, the fluctuation ratio, difference ratio and average ratio of the distribution transformer in the current detection process within the set time period are respectively multiplied by the corresponding weight coefficients, and then summed to obtain the power evaluation value Dw of the distribution transformer in the current detection process.

[0024] In some embodiments, the operation parameters of the distribution transformer are analyzed, which further comprises:

[0025] The temperature change of each divided region of the distribution transformer in the current detection process within the set time period is obtained, and the highest allowed value of the temperature of each divided region of the distribution transformer is preset.

[0026] The temperature values of each divided region of the distribution transformer at each time point within the set time period are extracted, and the average of the temperature values of each divided region at each time point is taken as the temperature average of each divided region within the set time period in the current detection process, and is recorded as Kai; wherein i represents the number of the corresponding divided region, wherein i=1, 2..., t;

[0027] Meanwhile, the highest allowed value of the preset temperature corresponding to each divided region is marked as , according to the formula The temperature average of each divided region of the distribution transformer is weighted calculated, thereby obtaining the temperature evaluation value Dq of the distribution transformer in the current detection process; wherein Zi represents the preset influence weight factor corresponding to the temperature average Kai of each divided region;

[0028] Based on the active power of the distribution transformer at each time point within the set time period in the current detection process, the load loss at each time point is calculated, and the average of the load loss at each time point is calculated, thereby obtaining the average load loss De of the distribution transformer.

[0029] In some embodiments, the operation evaluation index Yx of the distribution transformer in the current detection process is obtained, which is specifically:

[0030] According to the formula , the temperature evaluation value Dq, the power evaluation value Dw and the average load loss De of the distribution transformer in the current detection process within the set time period are weighted calculated, thereby obtaining the operation evaluation index Yx of the distribution transformer in the current detection process; wherein , and respectively represent preset reference thresholds corresponding to the power distribution transformer temperature evaluation value Dq, the power evaluation value Dw and the average load loss De, and c1, c2 and c3 are respectively preset influence weight factors corresponding to the temperature evaluation value Dq, the power evaluation value Dw and the average load loss De.

[0031] In some embodiments, the use parameters of the power distribution transformer are analyzed, specifically:

[0032] The sound signal generated by the power distribution transformer when running in a set time period in the current detection process is captured; the captured sound signal is compared and analyzed with the sound waveform in the normal state;

[0033] Two sets of allowable difference distances in the waveform comparison and analysis process are preset, if the distance of a certain segment of the sound signal from the sound waveform in the normal state is greater than the preset allowable difference distance, the segment is marked as an abnormal sound segment, and the start and end time points of the abnormal sound segment are determined to obtain the duration of the abnormal sound segment; the durations of the abnormal sound segments are accumulated to obtain the abnormal duration of the power distribution transformer in the current detection process, denoted as Ma;

[0034] The vibration frequency of the power distribution transformer in the current detection process is obtained, the vibration amplitude in each vibration frequency is identified, and a threshold value of the vibration amplitude is set; the vibration amplitude of each vibration frequency is compared with the set threshold value, if the vibration amplitude of a certain vibration frequency is greater than the set threshold value, the vibration is marked as an abnormal vibration, and the number of abnormal vibrations of the power distribution transformer in the current detection process is counted, denoted as Mb.

[0035] In some embodiments, the use parameters of the power distribution transformer are analyzed, and further comprising:

[0036] The insulation resistance of the power distribution transformer in the current detection process is measured; the temperature value of the surrounding environment of the current power distribution transformer is read and compared with the set basic temperature value, if it is higher than the set basic temperature value, the difference between the two is calculated and denoted as a high difference value, if it is lower than the set basic temperature value, the difference between the two is calculated and the absolute value is denoted as a low difference value, each set of difference value ranges of the high difference value and the low difference value are preset, and each set of difference value ranges corresponding to the high difference value and the low difference value corresponds to a compensation value; the calculated high difference value or low difference value is matched with the corresponding preset each set of difference value range, so as to obtain the compensation value of the power distribution transformer in the current detection process;

[0037] The measured insulation resistance is added to the obtained compensation value to obtain a compensation resistance value of the distribution transformer; a reference standard value of the insulation resistance of the distribution transformer is set; the compensation resistance value is subtracted from the set reference standard value, and the absolute value of the calculation result is taken to obtain an abnormal resistance value Mc of the distribution transformer in the current detection process.

[0038] In some embodiments, a use evaluation index Yf of the distribution transformer in the current detection process is obtained, specifically:

[0039] According to the formula , the abnormal duration Ma, the abnormal vibration number Mb, and the abnormal resistance value Mc of the distribution transformer in the current detection process are weighted calculated, thereby obtaining the use evaluation index Yf of the distribution transformer in the current detection process; wherein , and respectively represent the preset reference threshold values corresponding to the abnormal duration Ma, the abnormal vibration number Mb, and the abnormal resistance value Mc; n1, n2, and n3 are respectively the preset influence weight factors corresponding to the abnormal duration Ma, the abnormal vibration number Mb, and the abnormal resistance value Mc.

[0040] In some embodiments, the specific steps for obtaining the on-site efficiency value Ne of the processing personnel are:

[0041] Taking the location of the current distribution transformer as the center and setting the distance as the radius to draw a circle; all use warning signal processing personnel within the range of the circle are screened and marked as candidate personnel; position feedback signaling is sent to the mobile terminal of each candidate personnel, and each candidate personnel obtains the current location of each candidate personnel after confirming the position feedback signaling;

[0042] Based on the location of the distribution transformer and the locations of the candidate personnel, the required distance of each candidate personnel to reach the distribution transformer is obtained, denoted as g; the working years of each candidate personnel are extracted from the working log of each candidate personnel, denoted as u; the number of times each candidate personnel is selected this month is counted, denoted as e;

[0043] According to the formula , the required distance g, the working years u, and the number of times e of each candidate personnel are weighted calculated, thereby obtaining the on-site efficiency value Ne of each candidate personnel; wherein r1, r2, and r3 are respectively the preset influence weight factors corresponding to the required distance g, the working years u, and the number of times e; is a preset correction factor.

[0044] In some embodiments, based on the running years of the power distribution transformer, the time interval of detection is set, specifically: preset each group of year value ranges of the running years, set each group of year value ranges respectively corresponding to a detection time interval; match the running years of the power distribution transformer with the preset each group of year value ranges, thereby obtaining the time interval of detection of the power distribution transformer.

[0045] Compared with the prior art, the beneficial effects of the present application are:

[0046] The present application sets the time interval of detection based on the running years of the power distribution transformer, and collects the running parameters and use parameters of the power distribution transformer after reaching the set detection time interval, thereby obtaining the running evaluation index and use evaluation index of the power distribution transformer in the current detection process, reflecting the running state and use state of the power distribution transformer in the current detection process, and comprehensively evaluating the equipment condition of the power distribution transformer, solving the problem that in the prior art, the condition of the power distribution transformer is mostly evaluated from a single angle, and the running and use state of the power distribution transformer cannot be comprehensively evaluated from multiple angles.

[0047] The present application sets the early warning threshold index of the running evaluation index and the use evaluation index respectively, triggers the running early warning signal if the running evaluation index is greater than the corresponding set early warning threshold index, triggers the use early warning signal if the use evaluation index is greater than the corresponding set early warning threshold index, and performs targeted operation according to the specific type of the triggered early warning signal, thereby improving the processing efficiency of the detection result.

[0048] The present application selects the processing personnel with the maximum field value at the current time point by performing corresponding steps when the use early warning signal is triggered, realizes the intelligentization of personnel selection, and improves the processing speed and processing efficiency when the early warning is triggered. BRIEF DESCRIPTION OF DRAWINGS

[0049] In the following description of exemplary embodiments in conjunction with the accompanying drawings, more details, features and advantages of the present application are disclosed, in which:

[0050] Figure 1 The flowchart of the present application. DETAILED DESCRIPTION

[0051] Several embodiments of the present application will be described in more detail below with reference to the accompanying drawings so as to enable those skilled in the art to implement the present application. The present application can be embodied in many different forms and purposes and should not be limited to the embodiments described herein. These embodiments are provided to make the present application comprehensive and complete, and to fully convey the scope of the present application to those skilled in the art. The embodiments do not limit the present application.

[0052] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and the present disclosure and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

[0053] Referring to Figure 1 The power distribution transformer equipment detection and evaluation method based on big data analysis is shown to include:

[0054] Data collection: extract the running years of the power distribution transformer from the record log, set the detection time interval based on the running years of the power distribution transformer, and collect the operating parameters and usage parameters of the power distribution transformer after reaching the set detection time interval; the operating parameters include temperature, power factor and load loss; the usage parameters include operating sound and insulation resistance;

[0055] Specifically:

[0056] Each group of running year value ranges is preset, and each group of running year value ranges is set to correspond to a detection time interval; the running years of the power distribution transformer are matched with the preset each group of running year value ranges, so as to obtain the detection time interval of the power distribution transformer;

[0057] The higher the running years, the shorter the detection time interval obtained by matching; the setting is performed by a technician, and subsequent dynamic adjustment can be made according to actual conditions;

[0058] Communication technology: the collected operating parameters and usage parameters are transmitted to the central processing platform through wireless communication technology;

[0059] Wireless communication technologies such as 4G / 5G, Wi-Fi, RF, etc. are used, and encryption algorithms are used to encrypt the collected data, to ensure the safety and reliability of the data transmission process;

[0060] Central processing: the operating parameters and usage parameters of the power distribution transformer are analyzed respectively, and the operating evaluation index Yx and the usage evaluation index Yf of the power distribution transformer in the current detection process are obtained;

[0061] Specifically:

[0062] The temperature sensor previously arranged on the transformer is used to obtain the temperature change of each divided region of the power distribution transformer in the set time period in the current detection process, wherein the divided regions are set by a technician, such as winding temperature, oil surface temperature, core temperature and clamp temperature;

[0063] preset the maximum allowable value of the temperature of each divided area of the power distribution transformer by the technician;

[0064] extract the temperature values of each time point in the set time period of each divided area of the power distribution transformer, take the mean value of the temperature values of each time point corresponding to each divided area as the temperature mean value of each divided area in the set time period in the current detection process, and mark it as Kai; wherein i represents the number of the corresponding divided area, wherein i = 1, 2, …, t;

[0065] At the same time, mark the maximum allowable value of the preset temperature corresponding to each divided area as , and perform weighted calculation on the temperature mean value of each divided area of the power distribution transformer according to the formula , thereby obtaining the temperature evaluation value Dq of the power distribution transformer in the current detection process; wherein Zi represents the preset influence weight factor corresponding to the temperature mean value Kai of each divided area;

[0066] It should be noted that by arranging temperature sensors in the key areas of the transformer, comprehensive monitoring of the temperatures of the winding, oil surface, core and clamp is realized, which helps to comprehensively understand the thermal state of the transformer.

[0067] Use the power analyzer to obtain the active power and apparent power of the power distribution transformer at each time point in the set time period in the current detection process, and further convert the active power and apparent power at each time point into the power factor, i.e. calculate the power factor of the power distribution transformer at each time point by active power / apparent power;

[0068] Use the standard deviation formula to calculate the power factor of the power distribution transformer at each time point, and take the calculated result as the power fluctuation of the power distribution transformer in the set time period in the current detection process;

[0069] Extract the maximum value and the minimum value from the power factor of each time point, and calculate the difference value between the maximum value and the minimum value, thereby obtaining the power difference value of the power distribution transformer in the set time period in the current detection process;

[0070] Calculate the mean value of the power factor of the power distribution transformer at each time point, and take the calculated mean value as the power mean value of the power distribution transformer in the set time period in the current detection process;

[0071] Respectively preset the maximum allowable power fluctuation, the maximum allowable power difference value and the minimum allowable power mean value corresponding to the power fluctuation, the power difference value and the power mean value of the power distribution transformer;

[0072] The power fluctuation, power difference and power average of the distribution transformer in the current detection process within the set time period are respectively compared with the corresponding preset maximum allowable power fluctuation, maximum allowable power difference and minimum allowable power average, that is, the calculation is performed through power fluctuation / maximum allowable power fluctuation, power difference / maximum allowable power difference and minimum allowable power average / power average, thereby obtaining the fluctuation ratio, difference ratio and average ratio;

[0073] The weight coefficients corresponding to the fluctuation ratio, difference ratio and average ratio are set, the fluctuation ratio, difference ratio and average ratio of the distribution transformer in the current detection process within the set time period are respectively multiplied by the corresponding weight coefficients, and then summed to obtain the power evaluation value Dw of the distribution transformer in the current detection process;

[0074] It should be noted that the above-mentioned not only considers the instantaneous value of the power factor, but also analyzes the fluctuation, difference and average of the power factor, thereby providing a comprehensive understanding of the running state of the transformer.

[0075] Based on the active power of the distribution transformer at each time point within the set time period in the current detection process, the load loss at each time point is calculated; that is, the calculation is performed through , wherein is the load loss, is the input active power, is the output active power; the average of the load loss at each time point is calculated, thereby obtaining the average load loss De of the distribution transformer;

[0076] According to the formula , the temperature evaluation value Dq, the power evaluation value Dw and the average load loss De of the distribution transformer in the current detection process within the set time period are weighted and calculated, thereby obtaining the running evaluation index Yx of the distribution transformer in the current detection process; wherein , and respectively represent the preset reference threshold value corresponding to the temperature evaluation value Dq, the power evaluation value Dw and the average load loss De, and c1, c2 and c3 are respectively the preset influence weight factor corresponding to the temperature evaluation value Dq, the power evaluation value Dw and the average load loss De;

[0077] It should be noted that the above-mentioned comprehensively analyzes the evaluation results of the temperature, power and load loss of the distribution transformer in the detection process, thereby comprehensively reflecting the running state of the distribution transformer.

[0078] The sound signals generated by the distribution transformer during the set time period in the current detection process are captured by the sound acquisition device;

[0079] The sound signal is pre-processed, including but not limited to filtering, denoising and other steps, to improve the accuracy of subsequent analysis;

[0080] The captured sound signal is compared and analyzed with the sound waveform in the normal state, and the sound waveform in the normal state is stored in the constructed sound waveform data model library;

[0081] Two groups of waveform comparison analysis processes are preset, and if the distance of a certain segment of the sound signal from the sound waveform in the normal state is greater than the preset allowable difference distance, the segment is marked as an abnormal sound segment, and the start and end time points of the abnormal sound segment are determined to obtain the duration of the abnormal sound segment;

[0082] The duration of each group of abnormal sound segments is accumulated to obtain the abnormal duration of the distribution transformer in the current detection process, denoted as Ma;

[0083] The vibration sensor is used to obtain the vibration frequency of the distribution transformer in the current detection process, identify the vibration amplitude of each vibration frequency, and set a threshold value for the vibration amplitude; The threshold value is set according to industry standards;

[0084] The vibration amplitude of each vibration frequency is compared with the set threshold value, and if the vibration amplitude of a certain vibration frequency is greater than the set threshold value, the vibration is marked as an abnormal vibration, and the number of abnormal vibrations of the distribution transformer in the current detection process is counted, denoted as Mb;

[0085] The megohmmeter meeting the voltage level requirement is used to measure the insulation resistance of the distribution transformer in the current detection process;

[0086] The temperature value of the current distribution transformer is read and compared with the set basic temperature value, if it is higher than the set basic temperature value, the difference between the two is calculated and denoted as high difference value, if it is lower than the set basic temperature value, the difference between the two is calculated and the absolute value is denoted as low difference value, each group of difference value ranges of high difference value and low difference value are preset, and the difference value range corresponding to each group of high difference value and low difference value is set to correspond to a compensation value; The calculated high difference value or low difference value is matched with the corresponding preset difference value range, so as to obtain the compensation value of the distribution transformer in the current detection process;

[0087] The compensation values corresponding to various difference value ranges are set by technicians, wherein the compensation value matched by the high difference value is a positive number, and the compensation value matched by the low difference value is a negative number;

[0088] For example, the insulation resistance value may be reduced to 2 / 3 of the original value for every 10℃ increase in temperature, and the insulation resistance value may be increased to 1.5 times the original value for every 10℃ decrease in temperature; the base temperature value can be set to 20 degrees, and the current environmental temperature is calculated by subtracting the base temperature value, and the measured insulation resistance is compensated based on the preset matching rule, thereby improving the accuracy of data analysis;

[0089] The measured insulation resistance is added to the obtained compensation value to obtain the compensation resistance value of the distribution transformer;

[0090] A reference standard value of the insulation resistance of the distribution transformer is set; the reference standard value is set by a technician in combination with historical data and operating conditions of the transformer;

[0091] The compensation resistance value is calculated by subtracting the set reference standard value, and the absolute value of the calculation result is obtained to obtain the abnormal resistance value Mc of the distribution transformer in the current detection process;

[0092] According to the formula , the abnormal duration Ma, the abnormal vibration number Mb and the abnormal resistance value Mc of the distribution transformer in the current detection process are weighted calculated, and the use evaluation index Yf of the distribution transformer in the current detection process is obtained; wherein 、 and respectively represent the preset reference threshold value corresponding to the abnormal duration Ma, the abnormal vibration number Mb and the abnormal resistance value Mc; n1, n2 and n3 are respectively the preset influence weight factor corresponding to the abnormal duration Ma, the abnormal vibration number Mb and the abnormal resistance value Mc.

[0093] It should be noted that, as described above, the use condition of the transformer is comprehensively checked from different angles through sound signal analysis, vibration monitoring and insulation resistance measurement, which helps to more comprehensively understand the health condition of the transformer.

[0094] Intelligent diagnosis: based on the operation evaluation index Yx and the use evaluation index Yf of the distribution transformer in the current detection process, the warning threshold index of the operation evaluation index Yx and the use evaluation index Yf is set respectively, if the operation evaluation index Yx is greater than the corresponding set warning threshold index, the operation warning signal is triggered, if the use evaluation index Yf is greater than the corresponding set warning threshold index, the use warning signal is triggered;

[0095] Remote maintenance: when the operation warning signal is triggered, a technician in a working state at the current time point is selected, and the operation warning signal is sent to the mobile terminal of the technician, and the technician is authorized to remotely establish a communication connection with the distribution transformer and remotely troubleshoot;

[0096] On-site operation: when the early warning signal is triggered, the corresponding step is executed to select the processing personnel with the maximum on-site efficiency value Ne at the current time point, and the location of the distribution transformer is sent to the mobile terminal of the personnel;

[0097] Specifically,

[0098] A circle is drawn with the current location of the distribution transformer as the center and a distance as the radius. The initial distance is set to 3 km, and if no processing personnel are selected, the range is expanded by 1 km, and so on.

[0099] All early warning signal processing personnel within the circle range are selected and marked as candidate personnel. Position feedback signaling is sent to the mobile terminal of each candidate personnel, and each candidate personnel obtains the current location of each candidate personnel after confirming the position feedback signaling. The default automatic confirmation is 10 seconds.

[0100] Based on the location of the distribution transformer and the location of each candidate personnel, the required distance of each candidate personnel to reach the distribution transformer is obtained, denoted as g.

[0101] The working years of each candidate personnel are extracted from the working log of each candidate personnel, denoted as u. The number of times each candidate personnel is selected in the month is counted, denoted as e.

[0102] The shorter the required distance represents the faster the candidate personnel reaches the scene, the higher the working years represents the richer the processing experience of the candidate personnel, and the more the number of times selected in the month represents the excessive workload of the candidate personnel in the month.

[0103] According to the formula , the required distance g, working years u, and the number of times e of each candidate personnel are weighted and calculated to obtain the on-site efficiency value Ne of each candidate personnel. Where r1, r2, and r3 are the corresponding preset influence weight factors of the required distance g, working years u, and the number of times e. is a preset correction factor, with a value of 0.982, which can be dynamically adjusted according to actual conditions.

[0104] Diagnosis optimization: if the distribution transformer fails abnormally during subsequent actual use, an early warning optimization signal is triggered and sent to the mobile terminal of the technician, and the technician adjusts the preset early warning threshold index dynamically after receiving the early warning optimization signal.

[0105] The preferred embodiments of the application disclosed above are only to facilitate the elucidation of the application. The preferred embodiments do not describe all the details of the application and limit the application to the specific embodiments. Obviously, many modifications and variations can be made in light of the teachings above. The description is chosen and described in order to provide the best illustration of the application and its practical application to those skilled in the art and to enable those skilled in the art to best utilize the application. The application is limited only by the claims and their full scope and equivalents.

Claims

1. A method for testing and evaluating distribution transformer equipment based on big data analysis, characterized in that, include: Data acquisition: Extract the years of operation of the distribution transformer from the log. Based on the years of operation of the distribution transformer, set the detection time interval, and collect the operating parameters of the distribution transformer after the set detection time interval is reached. The operating parameters include operating sound and insulation resistance. Communication technology: The collected usage parameters are transmitted to the central processing platform via wireless communication technology; Central processing: Analyze the operating parameters of the distribution transformer to obtain the performance evaluation index Yf of the distribution transformer in the current testing process; The operating parameters of the distribution transformer are analyzed, specifically as follows: The allowable difference distance in the comparison and analysis of two sets of waveforms is preset. If a certain segment of the sound signal is higher than the normal sound waveform by a distance greater than the preset allowable difference distance, the segment is marked as an abnormal sound segment, and the start and end time points of the abnormal sound segment are determined to obtain the duration of the abnormal sound segment. The duration of each abnormal sound segment is summed to obtain the abnormal duration of the distribution transformer during the current detection process, denoted as Ma; The vibration count of the distribution transformer during the current testing process is obtained, the vibration amplitude of each vibration count is identified, and a threshold value for the vibration amplitude is set. The vibration amplitude of each vibration count is compared with the set threshold value. If the vibration amplitude of a certain vibration count is greater than the set threshold value, the vibration is marked as abnormal vibration. The number of abnormal vibrations of the distribution transformer during the current testing process is counted and recorded as Mb. Measure the insulation resistance of the distribution transformer during the current testing process; read the temperature value of the surrounding environment of the distribution transformer and compare it with the set base temperature value. If it is higher than the set base temperature value, calculate the difference between the two and record it as the high difference value. If it is lower than the set base temperature value, calculate the difference between the two and take the absolute value as the low difference value. Preset the value range of each group of high difference value and low difference value. Set a compensation value for each group of high difference value and low difference value. The calculated high or low difference value is matched with the corresponding preset range of difference values ​​to obtain the compensation value of the distribution transformer in the current detection process. The measured insulation resistance is added to the obtained compensation value to obtain the compensation resistance value of the distribution transformer; a reference standard value for the insulation resistance of the distribution transformer is set. The difference between the compensation resistance value and the set reference standard value is calculated, and the absolute value of the calculation result is taken to obtain the abnormal resistance value Mc of the distribution transformer in the current detection process. According to the formula The abnormal duration Ma, abnormal vibration frequency Mb, and abnormal resistance value Mc of the distribution transformer during the current testing process are weighted and calculated to obtain the service evaluation index Yf of the distribution transformer during the current testing process; whereby... , as well as These represent the preset reference thresholds corresponding to the abnormal duration Ma, the number of abnormal vibrations Mb, and the abnormal resistance value Mc, respectively; n1, n2, and n3 are the preset influence weighting factors corresponding to the abnormal duration Ma, the number of abnormal vibrations Mb, and the abnormal resistance value Mc, respectively. Intelligent diagnosis: If the evaluation index Yf is greater than the corresponding set warning threshold index, a warning signal will be triggered. On-site operation: When the warning signal is triggered, the corresponding steps are executed to select the person with the highest on-site effective value Ne at the current time point, and the location of the distribution transformer is sent to the person's mobile terminal; The specific steps to obtain the on-site effectiveness value Ne for the processing personnel are as follows: Draw a circle with the current location of the distribution transformer as the center and the distance as the radius; filter all personnel using early warning signal processing within the circle and mark them as candidates; send a location feedback signal to the mobile terminal of each candidate, and obtain the current location of each candidate after confirming the location feedback signal; Based on the location of the distribution transformer and the location of each candidate, the distance required for each candidate to reach the distribution transformer is obtained, denoted as g; the years of service of each candidate are extracted from their work logs, denoted as u; and the number of times each candidate is selected in the current month is counted, denoted as e. According to the formula The required distance g, years of service u, and number of selections e of each candidate are weighted and calculated to obtain the on-site effectiveness Ne of each candidate; where r1, r2, and r3 are the preset influence weight factors corresponding to the required distance g, years of service u, and number of selections e, respectively. This is the preset correction factor.

2. The method for testing and evaluating distribution transformer equipment based on big data analysis according to claim 1, characterized in that, Also includes: Data acquisition: Collect operating parameters of the distribution transformer; operating parameters include temperature, power factor, and load loss; Central processing: Analyze the operating parameters of the distribution transformer to obtain the operating evaluation index Yx of the distribution transformer in the current testing process; Intelligent diagnosis: If the operation evaluation index Yx is greater than the corresponding set warning threshold index, an operation warning signal will be triggered; Remote maintenance: When an operation warning signal is triggered, select the technician who is currently working and send the operation warning signal to the technician's mobile terminal. At the same time, authorize the technician to remotely establish a communication connection with the distribution transformer and conduct remote troubleshooting. Diagnostic optimization: If the distribution transformer experiences a fault or abnormality during subsequent actual use, an early warning optimization signal will be triggered and sent to the technician's mobile terminal. The technician will receive the early warning optimization signal and dynamically adjust the set early warning threshold index.

3. The method for testing and evaluating distribution transformer equipment based on big data analysis according to claim 2, characterized in that, The operating parameters of the distribution transformer are analyzed, specifically as follows: The active power and apparent power of the distribution transformer at each time point within a set time period during the current detection process are obtained, and the active power and apparent power at each time point are further converted into power factor. That is, the power factor of the distribution transformer at each time point is obtained by calculating the active power / apparent power. The power factor of the distribution transformer at each time point is calculated using the standard deviation formula, and the calculation result is used as the power fluctuation of the distribution transformer within a set time period during the current testing process. The highest and lowest power factor values ​​are extracted from the power factor at each time point, and the difference between the highest and lowest values ​​is calculated to obtain the power difference of the distribution transformer within the set time period during the current testing process. The power factor of the distribution transformer at each time point is calculated as the average value, and the calculated average value is used as the power average value of the distribution transformer within the set time period during the current detection process. The maximum allowable power fluctuation, maximum allowable power difference, and minimum allowable power average corresponding to the power fluctuation, power difference, and power average of the distribution transformer are preset respectively; The power fluctuation, power difference, and power average of the distribution transformer within a set time period during the current testing process are calculated by comparing them with the corresponding preset maximum allowable power fluctuation, maximum allowable power difference, and minimum allowable power average. That is, the fluctuation ratio, difference ratio, and average ratio are obtained by calculating the power fluctuation / maximum allowable power fluctuation, power difference / maximum allowable power difference, and minimum allowable power average / power average. Set the weighting coefficients corresponding to the fluctuation ratio, difference ratio, and mean ratio. Multiply the fluctuation ratio, difference ratio, and mean ratio of the distribution transformer in the current testing process within the set time period by the corresponding weighting coefficients, and then sum them to obtain the power evaluation value Dw of the distribution transformer in the current testing process.

4. The method for testing and evaluating distribution transformer equipment based on big data analysis according to claim 3, characterized in that, The analysis of the operating parameters of distribution transformers also includes: The temperature changes of the distribution transformer in each zone within a set time period during the current testing process are obtained, and the maximum allowable temperature values ​​of each zone of the distribution transformer are preset. Extract the temperature values ​​of each zone of the distribution transformer at each time point within a set time period. Take the average temperature value of each zone at each time point as the average temperature value of each zone within the set time period during the current detection process, and denote it as Kai; where i represents the zone number, i = 1, 2, ..., t; At the same time, the maximum allowable value of the preset temperature corresponding to each divided region is marked as follows: According to the formula The average temperature of each zone of the distribution transformer is weighted and calculated to obtain the temperature assessment value Dq of the distribution transformer in the current testing process; where Zi represents the preset influence weight factor corresponding to the average temperature Kai of each zone; Based on the active power of the distribution transformer at each time point within a set time period during the current testing process, the load loss at each time point is calculated; the average load loss at each time point is calculated to obtain the average load loss De of the distribution transformer.

5. The method for testing and evaluating distribution transformer equipment based on big data analysis according to claim 4, characterized in that, The operational evaluation index Yx of the distribution transformer during the current testing process is obtained as follows: According to the formula The operating evaluation index Yx of the distribution transformer during the current testing process is obtained by weighting the temperature evaluation value Dq, power evaluation value Dw, and average load loss De within a set time period. , as well as c1, c2, and c3 represent the preset reference thresholds corresponding to the temperature assessment value Dq, power assessment value Dw, and average load loss De of the distribution transformer, respectively.

6. The method for testing and evaluating distribution transformer equipment based on big data analysis according to claim 1, characterized in that, Based on the operating years of the distribution transformer, the detection time interval is set. Specifically, the operating years are preset to a range of values ​​for each group of years, and each range of values ​​corresponds to a detection time interval. The operating years of the distribution transformer are matched with the preset ranges of values ​​for each group of years to obtain the detection time interval of the distribution transformer.

Images