CN114002533A - Integrated online monitoring and grey evaluation system for high-voltage bushing - Google Patents
Integrated online monitoring and grey evaluation system for high-voltage bushing Download PDFInfo
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Abstract
The invention discloses a multi-parameter-based high-voltage bushing integrated online monitoring and grey evaluation system, which comprises an integrated bushing end screen intelligent adapter, a data processing unit and a data analysis software platform. The intelligent adapter is used for collecting bushing end screen leakage current, relative dielectric loss, relative capacitance and partial discharge signal monitoring, a micro-power consumption remote real-time communication technology is used for transmitting data, a grey theory analysis algorithm is used, and bushing high-voltage bushing multi-parameter real-time data are combined to achieve bushing uninterrupted detection and intelligent evaluation. The invention integrates on-line monitoring and grey evaluation for the high-voltage bushing, and research results can provide a basis for the research and development of key technologies of monitoring the running state of the high-voltage bushing and early warning faults. And the user comprehensively judges the running condition of the high-voltage bushing according to the evaluation information so as to take corresponding operation and maintenance measures.
Description
Technical Field
The invention belongs to the field of on-line monitoring of power equipment, and particularly relates to a multi-parameter-based high-voltage bushing integrated on-line monitoring and grey evaluation system.
Background
Modern substation management pays great attention to the problem of equipment insulation aging, once the insulation performance of power equipment is reduced due to aging and overhauling, accidents such as fire disasters are likely to happen, and the potential safety hazard and economic loss caused by the accidents are inestimable. Therefore, the good operation of the power transformer is helpful to ensure the safety and stability of the whole power system. The transformer bushing can lead the high-voltage wire out of the oil tank, is a very important wire outlet device in the transformer, and is also a key power transmission and transformation device. However, the phenomenon that the normal power supply is affected due to the poor insulation performance of the transformer bushing sometimes occurs, which not only brings great economic loss, but also poses great threat to the personal safety of related workers. Therefore, the key for ensuring the normal work of the transformer and the stable operation of the power system is to strengthen the monitoring of the transformer bushing and eliminate all fault hidden dangers as much as possible.
The traditional detection method needs to arrange wiring on site, and is long in detection time and complicated in test steps. With the continuous development of detection means, the existing operation detection method for the power equipment mostly adopts a non-contact portable device, is convenient to operate and high in efficiency, and comprises an ultraviolet imaging technology, an infrared imaging technology, a high-frequency detection technology, an ultrahigh-frequency detection technology, an ultrasonic detection technology and the like. The ultraviolet imaging technology can be used for finding corona discharge abnormity around the sleeve in time, the infrared imaging technology can identify heating faults by observing temperature distribution of different positions of the sleeve, and the high-frequency detection technology, the ultrahigh-frequency detection technology and the ultrasonic detection technology can identify partial discharge types of the sleeve to a certain extent so as to reflect corresponding internal fault defects.
Although the existing live detection method can identify the potential fault hazard of the transformer bushing to a certain extent, the special instruments adopted by the advanced portable detection method are high in value, and long-term continuous online monitoring is difficult to realize. The international large power grid Conference (CIGRE) working group 33-04 provides that external insulation equipment is a weak link of each power transmission line and an outdoor transformer substation, and is vital to properly monitoring and maintaining the operation of the external insulation equipment. Therefore, if the on-line monitoring and evaluation of the running state of the transformer bushing can be realized, the method has great engineering value.
Disclosure of Invention
The invention aims to solve the technical problem of overcoming the defects in the prior art and provides a multi-parameter-based high-voltage bushing integrated online monitoring and grey evaluation system and method, which can accurately monitor the running state characteristic parameters of a high-voltage bushing in real time on one hand, carry out quantitative evaluation on the running state of the high-voltage bushing through a background grey algorithm on the other hand, and remind operation and inspection personnel to carry out operation and maintenance in time when identifying an obvious abnormal state or sending bushing information with low evaluation score to a client terminal. Potential fault defects can be found in time, and safe and stable operation of the power distribution network in the district is guaranteed.
Specifically, the invention provides a multi-parameter-based high-voltage bushing integrated online monitoring and gray evaluation system, which comprises: the integrated bushing end screen intelligent adapter, the data processing unit and the data analysis platform are arranged on the bushing end screen intelligent adapter; the intelligent adapter monitors and collects bushing end screen parameter data, a real-time communication technology is adopted to transmit the data, the data processing unit processes the collected data, and the data analysis platform utilizes a grey theory analysis and evaluation method and combines multi-parameter real-time data of the high-voltage bushing to realize uninterrupted power detection and intelligent evaluation of the bushing.
Preferably, the sleeve tap intelligent adapter adopts a miniaturized design, the sleeve tap is reliably grounded, a high-frequency and low-current sensor is arranged in the intelligent adapter, and high-frequency partial discharge and grounding current signals are extracted under the condition that the electrical characteristics of the original sleeve tap are not changed.
Preferably, the anti-drop structure is designed in a matched manner with the sleeve end screen intelligent adapter, the measuring unit is completely isolated from the sleeve, and a near-zero magnetic space is constructed by utilizing a high-permeability magnetic material and is used for resisting strong magnetic field interference at the end screen position of the strong sleeve.
Preferably, the data processing unit includes: the intelligent adapter comprises a power module, a power management chip, a comprehensive multi-channel signal conditioning circuit, a multi-channel parallel AD sampling chip, an AD sampling and signal processing FPGA module, a synchronization module, a CPU system, an electro-optical conversion and optical fiber interfaces, and is used for processing data collected by the sleeve tap intelligent adapter, outputting the processed data to a data analysis platform and carrying out intelligent evaluation.
Preferably, the power module and the power management chip are used for conversion and adaptation of power voltage and power management; the comprehensive multi-channel signal conditioning circuit and the multi-channel parallel AD sampling chip finish the conditioning function of leakage current signals and 4-20mA analog quantity signals, input signals are amplified, denoised and converted into voltage signals suitable for AD sampling, and multi-channel parallel acquisition of the signals is finished.
Preferably, the AD sampling and signal processing FPGA module completes sampling and real-time signal processing of high-frequency partial discharge signals, and the synchronization module is used for completing high-precision synchronous sampling control among devices working in different places.
Preferably, the CPU system: the photoelectric conversion and optical fiber interface is responsible for data storage and management work of the whole acquisition module, and the photoelectric conversion and optical fiber interface is responsible for data transmission after processing by the CPU system and direct communication with system background software.
Preferably, the data analysis platform performs quantitative evaluation on the detected high voltage bushing by a grey correlation method, and the method comprises the following steps:
s1: normalizing the high-voltage bushing parameter data output by the data processing unit;
s2: determining a reference series for evaluating the state characteristics of the high-voltage bushing and a comparison series for influencing the system behavior;
s3: calculating four parameter characteristic correlation coefficients of the high-voltage bushing to be evaluated and the standard high-voltage bushing;
s4: calculating an evaluation index of the monitored high-voltage bushing;
s5: and the background system sends an evaluation result and prompt information to the client terminal.
Preferably, the step S1 includes: acquiring four parameter data of leakage current, relative dielectric loss, relative capacitance and partial discharge signals, and normalizing original data:
in the formula, Wi[t]For monitoring data, Wi[]minThe minimum value in the array of the monitoring data bureau; wi[]maxTo monitor the maximum in the data array, i represents A, B, C and D four parameter data.
Preferably, the step S2 includes: taking leakage current, relative dielectric loss, relative capacitance and partial discharge signal parameter data of a standard high-voltage bushing as a reference sequence Y, wherein Y is { Y (k) | k is 1,2, …, n }; the four parameter data of the monitored high-voltage bushing to be evaluated are used as a comparison sequence XiComparing the series Xi＝{Xi(k) 1,2, …, n, i is 1,2, …, m; wherein n is 4, representing 4 parametric data; and m is the number of the high-voltage bushings to be evaluated.
Preferably, in the step S3,
reference sequence Y (k) and comparison sequence Xi(k) The correlation coefficient calculation formula is as follows:
remember Deltai(k)＝|y(k)-xi(k) I, then
Wherein rho belongs to (0, infinity), is called a resolution coefficient, and has a value interval of (0,1) and xii(k) Is a comparison of the series XiAnd the k-th element of the reference number series Y.
Preferably, the correlation coefficient at each time or condition is concentrated to one value, that is, averaged, as a number representative of the degree of correlation between the comparison number series and the reference number series, and the degree of correlation r is expressed as a numberiThe calculation formula is as follows:
and respectively calculating the grey correlation values of the four parameter data of the high-voltage bushing, and taking the mean value as the evaluation index of the monitored high-voltage bushing.
Preferably, the step S5 includes:
comparing the direct monitoring results of the leakage current, the relative dielectric loss, the relative capacitance and the partial discharge signal, and if the monitoring value of a certain parameter is excessively deviated from the parameter value of the standard high-voltage bushing, the background system sends prompt information to the client terminal.
Preferably, in step S5:
the abnormal recognition result sent to the client terminal by the background system comprises four parameter historical data besides the prompt message.
Preferably, the step S5 further includes:
the user comprehensively judges the running condition of the high-voltage bushing according to the information so as to take corresponding operation and maintenance measures; if the four parameter monitoring data do not obviously deviate from the parameter values of the standard high-voltage bushing, quantitative evaluation is carried out through a grey theory, and important attention or maintenance treatment is carried out on the high-voltage bushing with low score.
The invention discloses a multi-parameter-based high-voltage bushing integrated online monitoring and grey evaluation system, which comprises an integrated bushing end screen intelligent adapter, a data processing unit and a data analysis software platform. The intelligent adapter is used for collecting bushing end screen leakage current, relative dielectric loss, relative capacitance and partial discharge signal monitoring, a micro-power consumption remote real-time communication technology is used for transmitting data, a grey theory analysis algorithm is used, and bushing high-voltage bushing multi-parameter real-time data are combined to achieve bushing uninterrupted detection and intelligent evaluation.
The invention achieves the following beneficial effects:
according to the invention, the leakage current, the relative dielectric loss, the relative capacitance and the partial discharge signal of the bushing end screen are monitored in real time through the intelligent adapter, so that whether the high-voltage bushing has obvious abnormal faults or not is accurately judged, and meanwhile, the state of the high-voltage bushing is quantitatively evaluated through a grey evaluation method, so that the purposes of timely acquiring the running state of the high-voltage bushing and timely troubleshooting the degradation fault are achieved; the invention provides a multi-parameter-based high-voltage bushing integrated online monitoring and grey evaluation system and method, which can make up for the defects of the existing detection means, effectively monitor the running state of a high-voltage bushing in real time and carry out quantitative evaluation, discover potential fault defects in time and further ensure the safe and stable running of a power distribution network in a district.
Drawings
Fig. 1 is a schematic view of an integrated on-line monitoring and gray evaluation system for a high voltage bushing according to the present invention.
Fig. 2 is a block diagram of the overall design of the data processing unit of the present invention.
FIG. 3 is a schematic flow chart of the gray evaluation method of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the drawings of the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the described embodiments of the invention, are within the scope of the invention.
The integrated online monitoring and grey evaluation system based on the multi-parameter high-voltage bushing is shown in figure 1, and comprises:
the system comprises an integrated bushing end screen intelligent adapter, a data processing unit and a data analysis software platform. The working principle is as follows: the intelligent adapter is used for collecting bushing end screen leakage current, relative dielectric loss, relative capacitance and partial discharge signal monitoring, a micro-power consumption remote real-time communication technology is used for transmitting data, a grey theory analysis and evaluation method is used, and bushing high-voltage bushing multi-parameter real-time data are combined to achieve uninterrupted detection and intelligent evaluation of the bushing.
The integrated bushing tap intelligent adapter ensures reliable grounding of the bushing tap, and can extract high-precision leakage current and high-frequency partial discharge signals. The structure of the integrated bushing tap intelligent adapter is as follows:
the sleeve tap intelligent adapter is designed in a miniaturized mode, a high-frequency and small-current sensor is arranged in the sleeve tap intelligent adapter, the structure of the sleeve tap intelligent adapter and an existing tap protective cover can be completely replaced, and high-frequency partial discharge and grounding current signals can be extracted in a high-quality mode under the condition that the electrical characteristics (particularly the grounding characteristics) of the original sleeve tap are not changed.
The anti-drop structure is designed in a matched mode for the sleeve end screen intelligent adapter, the measuring unit and the sleeve are designed in a completely isolated mode, the sleeve end screen intelligent adapter does not affect the sleeve end screen grounding, and the monitoring unit does not affect the operation of primary equipment. .
The near-zero magnetic space is constructed by utilizing high magnetic conductive materials, and the special magnetic shielding design is adopted, so that the strong magnetic field interference at the end screen position of the strong sleeve is effectively resisted.
The adapter has excellent antirust, moistureproof and anticorrosive performances and is convenient to install. The waterproof performance reaches IP68 level.
As shown in fig. 2, the overall design block diagram of the data processing unit includes the following modules:
power module and power management chip: and the power supply is responsible for the functions of conversion and adaptation of power supply voltage, power supply management and the like.
Synthesize multichannel signal conditioning circuit and multichannel parallel AD sampling chip: the method has the advantages that the conditioning function of leakage current signals and 4-20mA analog quantity signals is completed, input signals are converted into voltage signals suitable for AD sampling after being amplified and denoised, and multi-path parallel acquisition of the signals is completed. The sampling time of the multi-path parallel AD sampling chip is controlled by the synchronization module to realize high-precision synchronous sampling.
High-speed AD sampling and signal processing FPGA module: the high-frequency partial discharge signal sampling and real-time signal processing are completed, and various filter functions such as low-pass, high-pass and band-pass are supported.
A synchronization module: and high-precision synchronous sampling control between equipment working in different places is completed according to an IEEE1588 protocol or a Beidou positioning system signal, and the synchronous precision is less than 1 us.
A CPU system: and the data acquisition module is responsible for data processing, storage and management of the whole acquisition module.
Electro-optical conversion and fiber interface: the system is responsible for the transmission of data processed by the CPU system only and for the direct communication with the background software of the system.
As shown in FIG. 3, the data analysis software platform quantitatively evaluates the detected high voltage bushing through a grey correlation algorithm. The specific method comprises the following steps:
1) normalization process
The method collects four parameter data of leakage current, relative dielectric loss, relative capacitance and partial discharge signal, and has different initial values due to different units. Therefore, in order to make four groups of monitoring data comparable, the influence of data magnitude and dimension needs to be eliminated, that is, the raw data is normalized:
in the formula, Wi[t]For monitoring data, Wi[]minFor monitoring data in arrayMinimum value of (d); wi[]maxTo monitor the maximum in the data array, i represents A, B, C and D four parameter data.
2) Determining an analysis series
A reference series for evaluating the high voltage bushing condition characteristics and a comparison series for influencing the system behavior are determined. The data sequence reflecting the behavior characteristics of the system is called a reference sequence.
In the method, four parameter data (leakage current, relative dielectric loss, relative capacitance and partial discharge signal) of a standard high-voltage bushing are used as a reference number sequence (also called a mother sequence) Y,
Y＝{Y(k)|k＝1，2，…，n}；
four parameter data of the monitored high-voltage bushing to be evaluated are used as a comparison sequence XiComparison of series of numbers (also known as subsequence)
Xi＝{Xi(k)|k＝1,2,…,n}，i＝1，2，…，m。
Wherein n is 4, representing 4 parametric data; and m is the number of the high-voltage bushings to be evaluated.
3) Calculating four-parameter characteristic correlation coefficient of high-voltage bushing to be evaluated and standard high-voltage bushing
The correlation coefficient calculation formula for the reference sequence y (k) and the comparison sequence xi (k) is shown below.
Remember Deltai(k)＝|y(k)-xi(k) I, then
Where ρ ∈ (0, ∞), is called the resolution factor. The smaller ρ is, the larger the resolution is, and the value interval of ρ is generally (0,1), and the specific value may be determined according to the circumstances. When ρ ≦ 0.5463, the resolution is best, and ρ is usually 0.5.
ξi(k) Is a comparison of the series XiAnd the kth element of the reference sequence YThe correlation coefficient between them.
4) Calculating a relevance value
Since the correlation coefficient is the correlation degree value of the comparison array and the reference array at each time or condition, the number of the correlation coefficient is more than one, and the information is too scattered to be convenient for overall comparison. Therefore, it is necessary to collect the correlation coefficients at each time or condition as one value, that is, to obtain the average value thereof, and it is also possible to give weights to the correlation coefficients at each condition to obtain the degree of correlation thereof, which is expressed as the number of degrees of correlation between the comparison sequence and the reference sequence, and the degree of correlation r is obtained by taking the average value as an exampleiThe calculation formula is as follows:
according to the meaning of the grey correlation theory, the obtained correlation degree is in positive correlation with the standard bushing parameter index, the grey correlation values of the four parameter data of the high-voltage bushing are respectively calculated by the method, and the average value is taken as the evaluation index of the monitored high-voltage bushing.
Comparing the direct monitoring results of the leakage current, the relative dielectric loss, the relative capacitance and the partial discharge signal, and if the monitoring value of a certain parameter is excessively deviated from the parameter value of the standard high-voltage bushing, the background system sends prompt information to the client terminal. The abnormal recognition result sent to the client terminal by the background system comprises four parameter historical data besides the prompt message.
And the user comprehensively judges the running condition of the high-voltage bushing according to the information so as to take corresponding operation and maintenance measures.
If the four parameter monitoring data do not obviously deviate from the parameter values of the standard high-voltage bushing, quantitative evaluation is carried out through a grey theory, and important attention is paid or even measures are taken for the high-voltage bushing with lower score.
According to the invention, the leakage current, the relative dielectric loss, the relative capacitance and the partial discharge signal of the bushing end screen are monitored in real time through the intelligent adapter, so that whether the high-voltage bushing has obvious abnormal faults or not is accurately judged, and meanwhile, the state of the high-voltage bushing is quantitatively evaluated through a grey evaluation method, so that the purposes of timely acquiring the running state of the high-voltage bushing and timely troubleshooting the degradation fault are achieved; the invention provides a multi-parameter-based high-voltage bushing integrated online monitoring and grey evaluation system and method, which can make up for the defects of the existing detection means, effectively monitor the running state of a high-voltage bushing in real time and carry out quantitative evaluation, discover potential fault defects in time and further ensure the safe and stable running of a power distribution network in a district.
While the best mode for carrying out the invention has been described in detail and illustrated in the accompanying drawings, it is to be understood that the same is by way of illustration and example only and is not to be taken by way of limitation, the scope of the invention should be determined by the appended claims and any changes or modifications which fall within the true spirit and scope of the invention should be construed as broadly described herein.
Claims (15)
1. A multi-parameter-based high-voltage bushing integrated online monitoring and gray evaluation system is characterized by comprising: the integrated bushing end screen intelligent adapter, the data processing unit and the data analysis platform are arranged on the bushing end screen intelligent adapter; the intelligent adapter monitors and collects bushing end screen parameter data, a real-time communication technology is adopted to transmit the data, the data processing unit processes the collected data, and the data analysis platform utilizes a grey theory analysis and evaluation method and combines multi-parameter real-time data of the high-voltage bushing to realize uninterrupted power detection and intelligent evaluation of the bushing.
2. The system of claim 1, wherein the sleeve tap intelligent adapter is designed in a miniaturized manner, the sleeve tap is reliably grounded, a high-frequency and low-current sensor is arranged in the sleeve tap intelligent adapter, and a high-frequency partial discharge and grounding current signal is extracted without changing the electrical characteristics of the original sleeve tap.
3. The system of claim 2, wherein the sleeve end screen intelligent adapter is designed with an anti-drop structure, the measuring unit is completely isolated from the sleeve, and a near-zero magnetic space is constructed by using a high magnetic permeability material for resisting the strong magnetic field interference at the position of the strong sleeve end screen.
4. The system of claim 3, wherein the data processing unit comprises: the intelligent adapter comprises a power module, a power management chip, a comprehensive multi-channel signal conditioning circuit, a multi-channel parallel AD sampling chip, an AD sampling and signal processing FPGA module, a synchronization module, a CPU system, an electro-optical conversion and optical fiber interfaces, and is used for processing data collected by the sleeve tap intelligent adapter, outputting the processed data to a data analysis platform and carrying out intelligent evaluation.
5. The system of claim 4, wherein the power module and the power management chip are used for power voltage conversion and adaptation, power management; the comprehensive multi-channel signal conditioning circuit and the multi-channel parallel AD sampling chip finish the conditioning function of leakage current signals and 4-20mA analog quantity signals, input signals are amplified, denoised and converted into voltage signals suitable for AD sampling, and multi-channel parallel acquisition of the signals is finished.
6. The system according to claim 4, wherein the AD sampling and signal processing FPGA module performs sampling and real-time signal processing of the high-frequency partial discharge signal, and the synchronization module is used for performing high-precision synchronous sampling control between devices operating at different places.
7. The system of claim 6, wherein the CPU system: the photoelectric conversion and optical fiber interface is responsible for data storage and management work of the whole acquisition module, and the photoelectric conversion and optical fiber interface is responsible for data transmission after processing by the CPU system and direct communication with system background software.
8. The system according to claim 6, wherein the data analysis platform performs quantitative evaluation of the detected high voltage bushings by a grey correlation method, the method comprising the steps of:
s1: normalizing the high-voltage bushing parameter data output by the data processing unit;
s2: determining a reference series for evaluating the state characteristics of the high-voltage bushing and a comparison series for influencing the system behavior;
s3: calculating four parameter characteristic correlation coefficients of the high-voltage bushing to be evaluated and the standard high-voltage bushing;
s4: calculating an evaluation index of the monitored high-voltage bushing;
s5: and the background system sends an evaluation result and prompt information to the client terminal.
9. The system of claim 8,
the step S1 includes: acquiring four parameter data of leakage current, relative dielectric loss, relative capacitance and partial discharge signals, and normalizing original data:
in the formula, Wi[t]For monitoring data, Wi[]minThe minimum value in the array of the monitoring data bureau; wi[]maxTo monitor the maximum in the data array, i represents A, B, C and D four parameter data.
10. The system according to claim 9, wherein the step S2 includes:
taking leakage current, relative dielectric loss, relative capacitance and partial discharge signal parameter data of a standard high-voltage bushing as a reference sequence Y, wherein Y is { Y (k) | k is 1,2, …, n }; the four parameter data of the monitored high-voltage bushing to be evaluated are used as a comparison sequence XiComparing the series Xi＝{Xi(k) 1,2, …, n, i is 1,2, …, m; wherein n is 4, representing 4 parametric data; and m is the number of the high-voltage bushings to be evaluated.
11. The system according to claim 10, wherein in the step S3,
reference sequence Y (k) and comparison sequence Xi(k) The correlation coefficient calculation formula is as follows:
remember Deltai(k)＝|y(k)-xi(k) I, then
Wherein rho belongs to (0, infinity), is called a resolution coefficient, and has a value interval of (0,1) and xii(k) Is a comparison of the series XiAnd the k-th element of the reference number series Y.
12. The system of claim 11,
the correlation coefficient at each time or condition is concentrated into one value, that is, the average value is obtained as the number of the degree of correlation between the comparison number series and the reference number series, and the degree of correlation riThe calculation formula is as follows:
and respectively calculating the grey correlation values of the four parameter data of the high-voltage bushing, and taking the mean value as the evaluation index of the monitored high-voltage bushing.
13. The system according to claim 12, wherein the step S5 includes:
comparing the direct monitoring results of the leakage current, the relative dielectric loss, the relative capacitance and the partial discharge signal, and if the monitoring value of a certain parameter is excessively deviated from the parameter value of the standard high-voltage bushing, the background system sends prompt information to the client terminal.
14. The system according to claim 13, wherein in the step S5:
the abnormal recognition result sent to the client terminal by the background system comprises four parameter historical data besides the prompt message.
15. The system according to claim 12, wherein the step S5 further comprises:
the user comprehensively judges the running condition of the high-voltage bushing according to the information so as to take corresponding operation and maintenance measures; if the four parameter monitoring data do not obviously deviate from the parameter values of the standard high-voltage bushing, quantitative evaluation is carried out through a grey theory, and important attention or maintenance treatment is carried out on the high-voltage bushing with low score.
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| CN202111294750.0A CN114002533A (en) | 2021-11-03 | 2021-11-03 | Integrated online monitoring and grey evaluation system for high-voltage bushing |
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| CN117572295A (en) * | 2024-01-12 | 2024-02-20 | 山东和兑智能科技有限公司 | Multi-mode on-line monitoring and early warning method for high-voltage sleeve |
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| CN115063049A (en) * | 2022-08-16 | 2022-09-16 | 山东和兑智能科技有限公司 | High-voltage bushing multidimensional state monitoring system and method based on micro intelligent sensor |
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| CN117572295A (en) * | 2024-01-12 | 2024-02-20 | 山东和兑智能科技有限公司 | Multi-mode on-line monitoring and early warning method for high-voltage sleeve |
| CN117572295B (en) * | 2024-01-12 | 2024-04-12 | 山东和兑智能科技有限公司 | Multi-mode on-line monitoring and early warning method for high-voltage sleeve |
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