Power transformation equipment monitoring and early warning method based on voiceprint data

Abstract

The invention discloses a power transformation equipment monitoring and early warning method based on voiceprint data, and relates to the technical field of data analysis. The working condition of target power transformation equipment monitored by a voiceprint sensor is compared with the actual working condition, so that the position of the voiceprint sensor is optimized; according to the method, the target power transformation equipment is optimized through the voiceprint sensors, so that the influence of the equipment environment noise of the target power transformation on the voiceprint sensors is avoided, the optimized voiceprint sensors monitor the component groups of the target power transformation equipment, any component in each component group is associated with at least two component groups, and when the target power transformation equipment breaks down, the target power transformation equipment is protected from being damaged. According to the technical scheme, the fault part group can be accurately obtained through the voiceprint sensor in each part group, then fault analysis is carried out on the part group associated with the fault part group, and then each fault part is accurately obtained, so that the fault monitoring accuracy is greatly improved, and convenience is also provided for subsequent maintenance work of related workers.

Description

Technical Field

[0001] The present application relates to the technical field of data analysis, and in particular to a method for monitoring and early warning of substation equipment based on voiceprint data. Background Art

[0002] Substation equipment is one of the most important equipment in the power system. Maintaining stable and reliable operation of substation equipment is crucial to the development of social industry and economy. Therefore, this application proposes a substation equipment monitoring and early warning method based on voiceprint data.

[0003] Prior art, such as the invention application patent with announcement number: CN113380258A, discloses a voiceprint recognition method for determining substation faults. The problem of the prior art that the number of substations and the increasing number of equipment in the substations makes it difficult to determine equipment faults is overcome. The method includes first establishing a system model to store the common noise types in the substation, storing the waveforms and voiceprint information of various noises in the system model, constructing multiple filters based on known noises, and collecting noise information in the substation in real time. The noise information collected in real time is passed through the filter of the system model. If the filtered noise can be associated with a certain noise waveform stored in advance, the substation fault is determined. The present invention adopts a voiceprint recognition method to obtain a conclusion by filtering the sound and then comparing the waveforms graphically.

[0004] With respect to the above scheme, there are at least the following technical problems: 1. The current technology mainly stores the waveform and voiceprint information of common noise in the system model, and associates the noise information collected in real time in the substation with the stored noise after processing to determine the substation fault. The current technology lacks a method for determining substation faults when new types of noise appear, and as the service life of equipment in the substation continues to increase, the aging of each device may cause the waveform of the noise to change, and thus it is impossible to accurately determine the substation fault.

[0005] 2. The current technology mainly determines the faults of multiple substation equipment in the substation, but lacks the fault determination of specific components in the specific substation equipment. It is impossible to accurately locate the fault location, which makes the subsequent inspection and maintenance work of relevant personnel not simple enough, and also makes the fault determination method lack accuracy and perfection. Summary of the invention

[0006] The purpose of this application is to provide a substation equipment monitoring and early warning method based on voiceprint data, which solves the problems existing in the background technology.

[0007] To solve the above technical problems, the present application adopts the following technical solutions: The present application provides a substation equipment monitoring and early warning method based on voiceprint data. Step one: obtain the voiceprint data of the target substation equipment, analyze and obtain the working evaluation coefficient of the target substation equipment, and determine whether it is necessary to optimize the installation position of the voiceprint sensor.

[0008] Step 2: Use the optimized voiceprint sensor to monitor the operation of the target substation equipment, analyze whether the target substation equipment has a fault, and then obtain the faulty parts.

[0009] Step 3: Display the acquired faulty parts and fault information on the terminal device and issue an early warning prompt.

[0010] Preferably, the voiceprint data of the target substation includes amplitude, fundamental frequency and zero-crossing rate; the amplitude represents the maximum deviation of the acoustic signal of the target substation from the equilibrium position; the fundamental frequency represents the speed at which the acoustic signal waveform repeats within one cycle; the zero-crossing rate represents the number of times the acoustic signal crosses the zero point within one cycle.

[0011] Preferably, the position of the voiceprint sensor is optimized, and the specific optimization process is as follows: A1. The sound frequency of each component of the target substation equipment is obtained when it is working, and the designated component is recorded as the reference component, and a component adjacent to the designated component is recorded as the matching component. When the difference in sound frequency between the reference component and the matching component is greater than or equal to the threshold of the difference in sound frequency between the reference component and the matching component in the database, the reference component and the matching component are recorded as the first target component group; when the difference in sound frequency between the reference component and the matching component is less than the threshold of the difference in sound frequency between the reference component and the matching component in the database, the matching component is re-marked until the first target component group is obtained.

[0012] A2. Update the matching components in the first target component group to the reference components, and repeat the above steps until the second target component group is obtained.

[0013] A3. Update the matching components in the second component group to the reference components, and repeat the above steps until the third target component group is obtained.

[0014] A4. Repeat the above steps until all components of the target substation equipment are grouped.

[0015] A5. Install a voiceprint sensor at the middle point of each target component group to monitor the voiceprint data of each target component group.

[0016] Preferably, the sound frequency of each component of the target substation equipment when it is working is obtained, and the specific acquisition process is as follows: the target substation equipment is placed in a test chamber, and the test chamber environment is set to be the same as the working environment of the target substation equipment. When all devices are normally connected, each component of the target substation equipment is started separately, and the sound of each component of the target substation equipment when it is working is repeatedly collected. After pre-processing the collected sound, the sound spectrum of each component is obtained through spectrum analysis, and the sound spectrum is stored in a database. After the storage is completed, the test is terminated.

[0017] Preferably, the specific acquisition process of obtaining the faulty parts is as follows: The specific acquisition process of obtaining the faulty parts is as follows: S1. Obtain a group of parts that match the reference parts and matching parts in the target fault group, and record them as the first test part group and the second test part group, respectively.

[0018] S2. Compare the waveform of the voiceprint signal of the first component test group with the energy distribution waveform of the voiceprint signal of the group corresponding to the database. If the energy distribution waveforms of the two Figure 1 If the energy distribution waveforms of the two are inconsistent, then the first component test group is not faulty and the faulty device is judged to be a matching component in the target fault group; if the energy distribution waveforms of the two are inconsistent, then it is judged that the first component test group is faulty.

[0019] S3, compare the energy distribution waveform of the voiceprint signal of the second component test group with the energy distribution waveform of the voiceprint signal of the corresponding group in the database. If the energy distribution waveforms of the two Figure 1 If the energy distribution waveforms of the two are inconsistent, it is determined that the second component test group has not failed, and the fault is determined to be the reference component in the target fault group; if the energy distribution waveforms of the two are inconsistent, it is determined that the second component test group has failed.

[0020] S4. If it is determined that the target fault group, the first component test group and the second component test group are all faulty, each component in the target fault group, the first component test group and the second component test group is tested respectively to obtain the faulty component.

[0021] Preferably, the warning prompt content includes the faulty device and the target parts group where the faulty device is located; the warning prompt form includes voice prompt and information prompt.

[0022] The beneficial effects of the present application are as follows: 1. The substation equipment monitoring and early warning method based on voiceprint data provided by the present application compares the working condition of the target substation equipment monitored by the voiceprint sensor with the actual working condition, and then optimizes the position of the voiceprint sensor, thereby avoiding the influence of the equipment environment noise of the target substation on the voiceprint sensor. The optimized voiceprint sensors respectively monitor the component groups of the target substation equipment, and any component in each component group is associated with at least two component groups. When the target substation equipment fails, the faulty component group can be accurately obtained through the voiceprint sensors in each component group, and then the fault analysis is performed on the component groups associated with the faulty component group, and then each faulty component is accurately obtained, which greatly improves the accuracy of fault monitoring and provides convenience for the subsequent maintenance work of relevant staff.

[0023] 2. This application obtains the voiceprint data of the target substation equipment, and compares the working condition of the target substation equipment analyzed from the voiceprint data with the actual working condition of the target substation equipment, thereby optimizing the installation position of the voiceprint sensor, thereby greatly improving the accuracy and completeness of the working condition of the target substation equipment monitored by the voiceprint sensor, and also greatly reducing the impact of environmental noise on the collected voiceprint data.

[0024] 3. This application monitors the operation of the target substation through an optimized voiceprint sensor, and divides the components of the target substation into component groups. Any component group has components that overlap with other component groups. By comparing adjacent faulty component groups, the faulty components can be directly analyzed, thereby avoiding errors caused by cumbersome calculation processes and greatly improving the accuracy of fault monitoring and fault location. This method also makes the work of voiceprint sensors in the field of target substation equipment detection more reasonable and complete. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 The present invention is a flowchart of the steps for implementing the present application method. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0028] Reference Figure 1 As shown, the present application provides a substation equipment monitoring and early warning method based on voiceprint data, comprising the following steps: Step 1, obtaining the voiceprint data of the target substation equipment, analyzing to obtain the working evaluation coefficient of the target substation equipment, and determining whether it is necessary to optimize the installation position of the voiceprint sensor.

[0029] In a specific example, the voiceprint data of the target substation includes amplitude, fundamental frequency and zero-crossing rate; the amplitude represents the maximum deviation of the acoustic signal of the target substation from the equilibrium position; the fundamental frequency represents the speed at which the acoustic signal waveform is repeated within one cycle; the zero-crossing rate represents the number of times the acoustic signal crosses the zero point within one cycle.

[0030] It should be noted that the voiceprint data of the target substation is any parameter related to the target substation collected by the voiceprint sensor when the target substation is working stably, which can be amplitude, base frequency, bandwidth, or maximum cutoff frequency. Therefore, it cannot be understood as a limitation on the present application.

[0031] In a specific example, the analysis obtains the working evaluation coefficient of the target substation equipment. The specific analysis process is as follows: the amplitude, fundamental frequency and zero-crossing rate of the voiceprint of the target substation equipment collected by the voiceprint sensor in any cycle are recorded as F, K and L respectively, and according to the calculation formula: Get the working evaluation coefficient α of the target substation equipment, where F′, K ′ and L′ respectively represent the standard value of amplitude, standard value of base frequency and standard value of zero-crossing rate of the target substation in the database, ζ1, ζ2 and ζ3 respectively represent the weight factor corresponding to the amplitude, weight factor corresponding to the base frequency and weight factor corresponding to the zero-crossing rate of the target substation in the database.

[0032] It should be noted that the standard amplitude value, the standard fundamental frequency value and the standard zero-crossing rate value of the target substation in the database represent the actual amplitude, the fundamental frequency and the zero-crossing rate of the target substation when it is working stably.

[0033] It should be noted that 0<ζ1<1, 0<ζ2<1, 0<ζ2<1, ζ1+ζ2+ζ3=1.

[0034] It should be noted that the weight factors corresponding to the amplitude, the fundamental frequency and the zero-crossing rate in the voiceprint data of the target substation are obtained by factor analysis. First, the information of the spatial path attenuation of the amplitude value, fundamental frequency and zero-crossing rate in the voiceprint data of the target substation is concentrated, and then the variance explanation rate after rotation is obtained, and the weight is obtained by dividing the cumulative variance explanation rate.

[0035] It should be noted that factor analysis is a well-known technology. It is a multivariate statistical analysis method that starts from studying the internal dependencies of variables and reduces some variables with intricate relationships to a few comprehensive factors; information concentration is expressed as calculating the median; the variance explanation rate is the amount of information extracted by the factor, and the variance explanation rate = characteristic root / total number of analysis items; the variance explanation rate after rotation is expressed as the variance explanation rate of the factor after maximum variance rotation.

[0036] In a specific example, the judgment of whether it is necessary to optimize the installation position of the voiceprint sensor is as follows: the working evaluation coefficient of the target substation is compared with the standard value of the working evaluation coefficient of the target substation in the database. When the ratio of the working evaluation coefficient of the target substation to the standard value of the working evaluation coefficient of the target working equipment in the database is within the interval [0.8, 1.0], it is judged that the monitoring result of the voiceprint sensor is accurate and there is no need to optimize the position of the voiceprint sensor; otherwise, it is judged that the monitoring result of the voiceprint sensor is inaccurate and the position of the voiceprint sensor needs to be optimized.

[0037] It should be noted that the standard value of the working evaluation coefficient of the target substation equipment in the database is expressed as the actual working evaluation coefficient of the target substation equipment when it is working stably.

[0038] In a specific example, the position of the voiceprint sensor is optimized, and the specific optimization process is as follows:

[0039] A1. Obtain the sound frequency of each component of the target substation equipment when it is working, and record the designated component as the reference component, and record a component adjacent to the designated component as the matching component. When the difference in sound frequency between the reference component and the matching component is greater than or equal to the threshold of the difference in sound frequency between the reference component and the matching component in the database, the reference component and the matching component are recorded as the first target component group; when the difference in sound frequency between the reference component and the matching component is less than the threshold of the difference in sound frequency between the reference component and the matching component in the database, the matching component is re-marked until the first target component group is obtained.

[0040] A2. Update the matching components in the first target component group to the reference components, and repeat the above steps until the second target component group is obtained.

[0041] A3. Update the matching components in the second component group to the reference components, and repeat the above steps until the third target component group is obtained.

[0042] A4. Repeat the above steps until all components of the target substation equipment are grouped.

[0043] A5. Install a voiceprint sensor at the middle point of each target component group to monitor the voiceprint data of each target component group.

[0044] It should be noted that the greater the difference in sound frequency between components, the smaller the frequency influence between them.

[0045] It should be noted that the threshold of the difference between the sound frequencies of the reference component and the matching component in the database is the minimum value of the difference between the sound frequencies of any two adjacent components when they are not affected by each other's sound frequencies.

[0046] It should be noted that the number of components in each target component group is set by the relevant staff and can be two, three, or four, and therefore cannot be understood as a limitation on the present application.

[0047] In a specific example, the sound frequency of each component of the target substation equipment when it is working is obtained, and the specific acquisition process is as follows: the target substation equipment is placed in a test chamber, and the test chamber environment is set to be the same as the working environment of the target substation equipment. When all devices are normally connected, each component of the target substation equipment is started separately, and the sound of each component of the target substation equipment when it is working is repeatedly collected. After pre-processing the collected sound, the sound spectrum of each component is obtained through spectrum analysis, and it is stored in a database. After the storage is completed, the test is ended.

[0048] It should be noted that during the test, a spectrum analyzer was used to collect the sound spectrum of each component of the target substation equipment when it was working.

[0049] It should be noted that the preprocessing includes pre-emphasis, framing and windowing operations on the sound of each component to obtain a clearer sound spectrum image.

[0050] The same environment includes temperature, humidity, atmospheric pressure and ambient noise.

[0051] Step 2: Use the optimized voiceprint sensor to monitor the operation of the target substation equipment, analyze whether the target substation equipment has a fault, and then obtain the faulty parts.

[0052] In a specific example, the optimized voiceprint sensor is used to monitor the operation of the target substation equipment. The specific monitoring process is as follows: the voiceprint signal of the corresponding target parts group collected by each voiceprint sensor in the target substation equipment is recorded as X j (n), where n represents the sample index in the original signal sequence, n = 0, 1, 2 ... N-1, j represents the number of each voiceprint sensor, j = 1, 2, 3 ... g, according to the function transformation formula: The energy distribution of the voiceprint signals of the corresponding target parts group collected by each voiceprint sensor at different frequencies is obtained, thereby realizing the separation of high-frequency signals and low-frequency signals in the voiceprint signals, where π is the number of circles, k represents the index in the transformed frequency domain sequence, k=0,1,2...N-1, and N represents the signal length within one cycle.

[0053] In a specific example, the analysis of whether the target substation equipment fails is performed as follows: the energy distribution waveforms of each soundprint signal monitored by the soundprint sensor in each target part group at different frequencies are compared with the standard energy distribution waveforms of each target part group in the database. When the energy distribution waveforms of the soundprint signal monitored by the soundprint sensor in a target part group at different frequencies are inconsistent with the standard energy distribution waveforms of the target part group in the database, it is determined that the components in the target part group are faulty and recorded as a target fault group. Otherwise, it is determined that the components in the target part group are not faulty and are recorded as a target normal group.

[0054] It should be noted that the standard energy distribution waveform diagram of each target part group in the database is represented by an energy distribution waveform diagram of the voiceprint signal monitored by the voiceprint sensor in each target part group when the target substation equipment is working stably.

[0055] It should be noted that the inconsistency of the energy distribution waveform diagram is indicated by the inconsistency of the shape, period or amplitude of the waveform.

[0056] In a specific example, the specific acquisition process of acquiring the faulty components is as follows: S1. Acquire a component group that matches the reference component and the matching component in the target fault group, and record them as a first test component group and a second test component group, respectively.

[0057] S2. Compare the waveform of the voiceprint signal of the first component test group with the energy distribution waveform of the voiceprint signal of the group corresponding to the database. If the energy distribution waveforms of the two Figure 1 If the energy distribution waveforms of the two are inconsistent, then the first component test group is not faulty and the faulty device is judged to be a matching component in the target fault group; if the energy distribution waveforms of the two are inconsistent, then it is judged that the first component test group is faulty.

[0058] S3, compare the energy distribution waveform of the voiceprint signal of the second component test group with the energy distribution waveform of the voiceprint signal of the corresponding group in the database. If the energy distribution waveforms of the two Figure 1 If the energy distribution waveforms of the two are inconsistent, it is determined that the second component test group has not failed, and the fault is determined to be the reference component in the target fault group; if the energy distribution waveforms of the two are inconsistent, it is determined that the second component test group has failed.

[0059] S4. If it is determined that the target fault group, the first component test group and the second component test group are all faulty, each component in the target fault group, the first component test group and the second component test group is tested respectively to obtain the faulty component.

[0060] It should be noted that the database includes standard values ​​of amplitude, base frequency and zero-crossing rate of target substation equipment; it also includes weight factors corresponding to the amplitude, base frequency and zero-crossing rate of target substation equipment; it also includes standard values ​​of working evaluation coefficients of target substation equipment; it also includes threshold values ​​of the difference in sound frequency between reference components and matching components; it also includes energy distribution waveforms of each voiceprint signal monitored by the voiceprint sensor in each target parts group at different frequencies.

[0061] Step 3: Display the acquired faulty parts and fault information on the terminal device and issue an early warning prompt.

[0062] In a specific example, the early warning prompt content includes the faulty device and the target parts group where the faulty device is located; the early warning prompt form includes voice prompt and information prompt.

[0063] The substation equipment monitoring and early warning method based on voiceprint data provided by the present application compares the working condition of the target substation equipment monitored by the voiceprint sensor with the actual working condition, and then optimizes the position of the voiceprint sensor, thereby avoiding the influence of the equipment environment noise of the target substation on the voiceprint sensor. The optimized voiceprint sensors respectively monitor the component groups of the target substation equipment, and any component in each component group is associated with at least two component groups. When the target substation equipment fails, the faulty component group can be accurately obtained through the voiceprint sensors in each component group, and then the fault analysis is performed on the component groups associated with the faulty component group, and then each faulty component is accurately obtained, which greatly improves the accuracy of fault monitoring and provides convenience for the subsequent maintenance work of relevant staff.

[0064] The above contents are merely examples and explanations of the concept of the present application. The technical personnel in this technical field may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in the present application, they should all fall within the scope of protection of the present application.

Claims

1. A substation equipment monitoring and early warning method based on voiceprint data, characterized in that: include: Step 1: Acquire the voiceprint data of the target substation equipment, analyze and obtain the working evaluation coefficient of the target substation equipment, and determine whether the installation position of the voiceprint sensor needs to be optimized; Step 2: Use the optimized voiceprint sensor to monitor the operation of the target substation equipment, analyze whether the target substation equipment has a fault, and then obtain the faulty parts; Step 3: Display the acquired faulty parts and fault information on the terminal device and issue an early warning prompt.

2. The method for monitoring and early warning of substation equipment based on voiceprint data according to claim 1 is characterized in that: The voiceprint data of the target substation includes amplitude, fundamental frequency and zero-crossing rate; the amplitude represents the maximum deviation of the acoustic signal from the equilibrium position; the fundamental frequency represents the speed at which the acoustic signal waveform repeats within one cycle; and the zero-crossing rate represents the number of times the acoustic signal crosses the zero point within one cycle.

3. The method for monitoring and early warning of substation equipment based on voiceprint data according to claim 2 is characterized in that: The analysis obtains the working evaluation coefficient of the target substation equipment. The specific analysis process is as follows: The amplitude, fundamental frequency and zero-crossing rate of the target substation equipment collected by the voiceprint sensor in any cycle are recorded as F, K and L respectively. According to the calculation formula: Get the working evaluation coefficient α of the target substation equipment, where F′, K ′ and L′ respectively represent the standard value of amplitude, standard value of base frequency and standard value of zero-crossing rate of the target substation in the database, ζ1, ζ2 and ζ3 respectively represent the weight factor corresponding to the amplitude, weight factor corresponding to the base frequency and weight factor corresponding to the zero-crossing rate of the target substation in the database.

4. The method for monitoring and early warning of substation equipment based on voiceprint data according to claim 3 is characterized in that: The specific process of determining whether the installation position of the voiceprint sensor needs to be optimized is as follows: The working evaluation coefficient of the target substation equipment is compared with the standard value of the working evaluation coefficient of the target substation equipment in the database. When the ratio of the working evaluation coefficient of the target substation equipment to the standard value of the working evaluation coefficient of the target working equipment in the database is within the interval [0.8, 1.0], the voiceprint sensor monitoring result is judged to be accurate and there is no need to optimize the voiceprint sensor position; otherwise, the voiceprint sensor monitoring result is judged to be inaccurate and the voiceprint sensor position needs to be optimized.

5. The method for monitoring and early warning of substation equipment based on voiceprint data according to claim 4 is characterized in that: The optimization of the position of the voiceprint sensor is specifically carried out as follows: A1. Acquire the sound frequency of each component of the target substation when it is working, and record the designated component as the reference component, and record a component adjacent to the designated component as the matching component. When the difference between the sound frequencies of the reference component and the matching component is greater than or equal to the threshold of the difference between the sound frequencies of the reference component and the matching component in the database, record the reference component and the matching component as the first target component group; When the difference between the sound frequencies of the reference component and the matching component is less than a threshold of the difference between the sound frequencies of the reference component and the matching component in the database, the matching component is re-marked until a first target component group is obtained; A2, updating the matching parts in the first target parts group to the reference parts, and repeating the above steps until the second target parts group is obtained; A3, updating the matching parts in the second part group to the reference parts, and repeating the above steps until a third target part group is obtained; A4. Repeat the above steps until all components of the target substation equipment are grouped; A5. Install a voiceprint sensor at the middle point of each target component group to monitor the voiceprint data of each target component group.

6. The method for monitoring and early warning of substation equipment based on voiceprint data according to claim 5 is characterized in that: The specific acquisition process of obtaining the sound frequency of each component of the target substation equipment when it is working is as follows: The target substation equipment is placed in a test chamber, and the test chamber environment is set to be the same as the working environment of the target substation equipment. When all equipment is connected normally, each component of the target substation equipment is started separately, and the sound of each component when the target substation equipment is working is repeatedly collected. After pre-processing the collected sound, the sound spectrum of each component is obtained through spectrum analysis, and the sound spectrum is stored in the database. After the storage is completed, the test ends.

7. The method for monitoring and early warning of substation equipment based on voiceprint data according to claim 6 is characterized in that: The optimized voiceprint sensor is used to monitor the operation of the target substation equipment. The specific monitoring process is as follows: The voiceprint signal of the corresponding target parts group collected by each voiceprint sensor in the target substation equipment is recorded as X j (n), where n represents the sample index in the original signal sequence, n = 0, 1, 2 ... N-1, j represents the number of each voiceprint sensor, j = 1, 2, 3 ... g, according to the function transformation formula: The energy distribution of the voiceprint signals of the corresponding target parts group collected by each voiceprint sensor at different frequencies is obtained, thereby realizing the separation of high-frequency signals and low-frequency signals in the voiceprint signals, where k represents the index in the transformed frequency domain sequence, k=0,1,2......N-1, and N represents the signal length within one cycle.

8. The method for monitoring and early warning of substation equipment based on voiceprint data according to claim 7 is characterized in that: The specific analysis process of analyzing whether the target substation equipment fails is as follows: The energy distribution waveforms of each soundprint signal monitored by the soundprint sensor in each target part group at different frequencies are compared with the standard energy distribution waveforms of each target part group in the database. When the energy distribution waveforms of the soundprint signal monitored by the soundprint sensor in a target part group at different frequencies are inconsistent with the standard energy distribution waveforms of the target part group in the database, it is judged that the parts in the target part group are faulty and recorded as a target faulty group. Otherwise, it is judged that the parts in the target part group are not faulty and are recorded as a target normal group.

9. The method for monitoring and early warning of substation equipment based on voiceprint data according to claim 8 is characterized in that: The specific process of obtaining the faulty parts is as follows: S1, obtaining a component group that matches the reference component and the matching component in the target fault group, and recording them as a first test component group and a second test component group respectively; S2. Compare the waveform of the voiceprint signal of the first component test group with the energy distribution waveform of the voiceprint signal corresponding to the group in the database. If the energy distribution waveforms of the two are consistent, the first component test group is not faulty, and the faulty device is judged to be a matching component in the target fault group; if the energy distribution waveforms of the two are inconsistent, it is judged that the first component test group is faulty; S3, comparing the energy distribution waveform of the voiceprint signal of the second component test group with the energy distribution waveform of the voiceprint signal corresponding to the group in the database, if the energy distribution waveforms of the two are consistent, it is determined that the second component test group has no fault, and the fault is determined to be a reference component in the target fault group; If the energy distribution waveforms of the two are inconsistent, it is determined that the second component test group has a fault; S4. If it is determined that the target fault group, the first component test group and the second component test group are all faulty, each component in the target fault group, the first component test group and the second component test group is tested respectively to obtain the faulty component.

10. The method for monitoring and early warning of substation equipment based on voiceprint data according to claim 9 is characterized in that: The warning prompt content includes the faulty equipment and the target parts group where the faulty equipment is located; the warning prompt form includes voice prompt and information prompt.

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