CN111063528B - Active noise reduction equipment of transformer and transformer noise on-line monitoring system - Google Patents
Active noise reduction equipment of transformer and transformer noise on-line monitoring system Download PDFInfo
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Abstract
The utility model relates to an equipment and transformer noise on-line monitoring system of making an uproar falls in transformer active, this equipment includes error sensor, self-adaptation feedback control system and secondary sound source, error sensor is used for gathering the noise signal of transformer in the place of environment, and with noise signal transmission to self-adaptation feedback control system, self-adaptation feedback control system obtains ambient noise data according to the noise signal analysis of receiving, adopt basic particle swarm optimization to carry out the parameter optimization of secondary sound source according to ambient noise data, it sends to secondary sound source to obtain the active signal of making an uproar and fall, satisfy the active requirement of making an uproar of falling with the power and the vocal precision of the secondary sound source of control secondary sound source, can effectively reduce the transformer noise, the active reliability of making an uproar falls in the transformer has been improved.
Description
Technical Field
The application relates to the technical field of power grids, in particular to active noise reduction equipment of a transformer and an online transformer noise monitoring system.
Background
With the development of economy in China, the power consumption requirements of industry and residents are increased, the load level of an urban power grid is continuously improved, a large-capacity power transformer goes deep into a load center, and part of transformer substations have to be located in an urban center area with dense power loads. The noise generated by the transformer in the working state causes the noise intensity near the transformer substation to increase, and the normal life and work of surrounding residents are seriously influenced, and moreover, the noise of the transformer also reflects the running state of the transformer. The transformer fault is represented in the form of sound no matter what causes the transformer fault is in design, manufacture, installation, operation and maintenance, external interference or damage and the like, and the sound abnormity is the representation of the fault and the precursor of an accident. In practice, electric power enterprises pay attention to the safety of transformers for many years, and noise judgment is an important means for judging whether the transformers are normal or not. The transformer will hum continuously and evenly during normal operation, and if there is other noise, the transformer will fail or will fail. Therefore, how to effectively eliminate and suppress transformer noise has become a popular research topic.
In the traditional active transformer noise silencing method, a plurality of noise generators are arranged in a distance of 1m from a transformer, so that noise emitted by the noise generators and the transformer noise are mutually offset, and further the transformer noise is attenuated or suppressed. However, due to the fact that noise and disturbance exist in a secondary channel (including a secondary sound source, an error sensor, a sound transmission channel and the like) of the transformer active noise reduction system, a controller cannot converge to an optimal solution in a self-adaptive process, actual noise reduction effect of the transformer noise reduction system is difficult to achieve an expected target, and active noise reduction reliability is low.
Disclosure of Invention
In view of the above, it is necessary to provide an active noise reduction device for a transformer and an on-line transformer noise monitoring system, which can improve the reliability of active noise reduction.
A transformer active noise reduction device comprises an error sensor, a self-adaptive feedback control system and a secondary sound source, wherein the self-adaptive feedback control system is connected with the error sensor and the secondary sound source;
the adaptive feedback control system analyzes the received noise signal to obtain environmental noise data, performs parameter optimization on a secondary sound source by adopting a basic particle swarm algorithm according to the environmental noise data to obtain an active noise reduction signal, and transmits the active noise reduction signal to the secondary sound source to control the power and the sounding precision of the secondary sound source.
In one embodiment, the ambient noise data includes time domain noise data and frequency noise data.
In one embodiment, the adaptive feedback control system performs parameter configuration on the secondary sound source through the active noise reduction signal, so that the secondary sound source outputs a noise reduction signal according to configuration parameters.
In one embodiment, the configuration parameters include position, number, magnitude, and initial phase angle.
In one embodiment, the adaptive feedback control system includes a signal processing device coupled to the error sensor and the secondary sound source, and a processor coupled to the signal processing device.
In one embodiment, the transformer active noise reduction device further comprises a data uploading device and an alarm device which are connected with the adaptive feedback control system.
In one embodiment, the data uploading device comprises a 485-type transmitter and a data exporter, and the 485-type transmitter is connected with the adaptive feedback control system and the data exporter.
In one embodiment, the transformer active noise reduction device further comprises a concentrator, the concentrator is connected with the 485 type transmitter and is further used for communicating with a base station.
A transformer noise online monitoring system comprises a remote control terminal and the transformer active noise reduction equipment.
In one embodiment, the transformer noise online monitoring system further comprises a mobile terminal, and the mobile terminal is communicated with the remote control terminal.
According to the active noise reduction equipment of the transformer and the on-line monitoring system of the noise of the transformer, the error sensor is used for collecting the noise signal of the transformer in the environment, the self-adaptive feedback control system analyzes the received noise signal to obtain the environmental noise data, the parameter optimization of the secondary sound source is carried out by adopting the basic particle swarm algorithm according to the environmental noise data, the active noise reduction signal is obtained and sent to the secondary sound source, the power and the sound production precision of the secondary sound source are controlled to meet the active noise reduction requirement, the noise of the transformer can be effectively reduced, and the active noise reduction reliability of the transformer is improved.
Drawings
FIG. 1 is a block diagram of an embodiment of an active noise reduction device of a transformer;
FIG. 2 is a schematic diagram of an embodiment of a transformer active noise reduction apparatus;
FIG. 3 is a discrete domain equivalent diagram of the adaptive feedback control system in one embodiment;
FIG. 4 is a flow diagram of a basic particle swarm algorithm in one embodiment;
FIG. 5 is a block diagram of a software framework of an adaptive feedback control system in accordance with an embodiment;
fig. 6 is a hardware structure diagram of an online transformer noise monitoring system according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The noise of the power transformer includes auxiliary cooling device noise and power transformer body noise, and the noise frequency mainly includes 100Hz, 200Hz, 300Hz, 400Hz, 500Hz and 600Hz, and is low-frequency noise. The low frequency characteristics of transformer noise make traditional passive noise reduction techniques ineffective and expensive. A large amount of researches on transformer noise problems are carried out by some foreign large-scale power transformer manufacturing companies and related research institutions, and the research directions mainly relate to transformers: noise and acoustic characteristics, vibration mechanisms, noise reduction methods and measures, etc. The research on the aspect of transformer noise suppression in China lags behind the research in foreign countries, and the research work mainly focuses on the aspects of transformer noise mechanism and control, qualitative analysis and practical experience summary. With the development of testing technology and computer aided analysis, some scholars in China analyze the vibration frequency spectrum of the noise of the transformer, and also analyze the noise mechanism of the transformer by using a finite element technology.
In an active noise reduction system, the most critical thing is how to effectively replicate the primary noise source and generate secondary sound waves with equal amplitude and opposite direction, which mainly depends on the reasonable design of the system structure and the optimal selection of the parameters of the secondary sound source. Around these problems, a great deal of research work has been done by scholars both at home and abroad. Transformer noise control by active noise reduction techniques has been proposed in 1955. He experimented with a large 15000kVA transformer. In the experiment of noise reduction of a single loudspeaker, although a maximum 15dB noise reduction amount is obtained at the error sensor, the noise reduction range is limited to a very small angle in the radiation axis direction of the loudspeaker, and other directional noise may be increased. In order to obtain a global noise reduction effect, the number of speakers must be increased. The variable gain amplifier and the phase shifter in the system are adjusted manually, and because the noise of the transformer changes continuously, the adjustment is frequently performed manually, so that the time and the labor are wasted, the accuracy is high, the automatic adjustment capability of the system is improved, and the development of an adaptive system is the key for solving the problem.
Currently, the research on the active noise reduction technology of the power transformer has made significant progress in various aspects, such as: combining theories in related subject fields, and deeply analyzing a mechanism of transformer noise generation; secondly, constructing a transformer noise radiation model to predict a sound field around the transformer, and gradually developing from experimental research to theoretical research; the research object relates to transformers with different specifications, and the research scale is continuously enlarged; and fourthly, new technical methods such as a sound intensity noise calibration method and the like are continuously introduced into the research. However, the following key technical problems still exist when the active noise reduction technology is applied to the noise control of the practical power transformer:
1) power transformer noise measurement and analysis. It is known that the body noise of a power transformer is mainly caused by the magnetostrictive vibration of the iron core, and 100Hz is the fundamental frequency. The noise characteristics of the transformer can be known by measuring the noise of the transformer, and then active noise reduction design is carried out aiming at the noise frequency band required to be subjected to noise reduction. The conventional noise measurement method comprises a sound pressure method and a sound intensity method, the advantages and the disadvantages of the two methods are correctly analyzed, and a proper method is selected for sound power level analysis, sound pressure level analysis and low-frequency noise analysis of the transformer, so that data support can be provided for active noise reduction research of the transformer.
2) And (4) reasonably modeling a power transformer noise source. The existing noise source model is generally regular in shape and is excited by a time harmonic function, but in actual transformer noise control, the noise source generally has the properties of randomness in time, irregular distribution in space and the like, so how to correctly analyze the type and the characteristics of the noise source and establish reasonable simplified modeling of the noise source has a crucial role in relation to the design and optimization of the whole active noise reduction system.
3) And self-adaptive design and parameter optimization of the transformer active noise reduction system. The power transformer noise source generally has the characteristics of randomness in time, irregular distribution in space and the like, in order to obtain better global and real-time noise reduction effect, the active noise reduction system must have self-adaptability, parameters of a secondary sound source are key, various methods can be adopted for optimizing the secondary sound source, and meanwhile, the selection of an error sensor should enable an actual control target to approach a theoretical control target as much as possible.
The active noise reduction of the power transformer is active noise control of a three-dimensional free sound field space and is implemented based on a sound field coherent theory and a Huygens principle. Therefore, a hemisphere sound source model is established on a self-adaptive system, the type and the characteristics of a noise source are correctly analyzed, four parameters of the number, the position, the initial phase angle and the amplitude of a secondary sound source are optimized based on a particle swarm algorithm, a set of effective secondary sound source parameter optimization method is obtained, and spatial noise reduction of a cube noise reduction area is realized through initial adjustment and fine adjustment.
In one embodiment, the transformer active noise reduction device is suitable for a distribution transformer low-frequency noise reduction system and effectively reduces low-frequency noise. As shown in fig. 1, the transformer active noise reduction apparatus includes an error sensor 100, an adaptive feedback control system 200, and a secondary sound source 300, the adaptive feedback control system 200 connecting the error sensor 100 and the secondary sound source 300. The error sensor 100 is configured to collect a noise signal of a transformer in an environment, and send the noise signal to the adaptive feedback control system 200, where the adaptive feedback control system 200 obtains environmental noise data according to the received noise signal, performs parameter optimization of a secondary sound source by using a basic particle swarm algorithm according to the environmental noise data, obtains an active noise reduction signal, sends the active noise reduction signal to the secondary sound source 300, and controls the power and the sound production accuracy of the secondary sound source 300.
The number of the error sensors 100 and the secondary sound sources 300 is not unique, and can be adjusted according to actual requirements. The method comprises the steps that noise detection is carried out through each error sensor 100 to generate signals and the signals are sent to the self-adaptive feedback control system 200, the self-adaptive feedback control system 200 establishes a hemispherical sound source model to analyze the type and the characteristics of a noise source, an active noise reduction target function is set to be the square sum of sound pressure at each error sensor, parameter optimization of a secondary sound source is carried out by adopting a basic particle swarm algorithm, an active noise reduction signal is sent to the secondary sound source 300, and the power and the sound production precision of the secondary sound source 300 meet the requirements of active noise reduction.
In one embodiment, the adaptive feedback control system 200 parametrically configures the secondary sound source 300 with the active noise reduction signal such that the secondary sound source 300 outputs the noise reduction signal according to the configured parameters. The configuration parameters specifically include position, number, amplitude and initial phase angle. The adaptive feedback control system 200 optimizes four parameters of the number, the position, the initial phase angle and the amplitude of the secondary sound source based on the particle swarm optimization, and improves the accuracy of active noise reduction of the transformer.
The specific hardware configuration of the adaptive feedback control system 200 is not exclusive, and in one embodiment, as shown in fig. 2, the adaptive feedback control system 200 includes a signal processing device 220 and a processor 240, the signal processing device 220 is connected to the error sensor 100 and the secondary acoustic source 300, and the processor 240 is connected to the signal processing device 220. The received signals are measured, processed and analyzed through the signal processing device 220 to obtain environmental noise data, the processor 240 establishes constraint conditions for an active noise reduction objective function according to the minimum sum of squares of sound pressure at each error sensor by combining the environmental noise data, parameter optimization is performed through a basic particle swarm optimization, and the signal processing device 220 generates active noise reduction signals according to optimization results and sends the active noise reduction signals to the secondary sound source 300. Wherein the signal processing device 220 comprises a measuring part 222, a control part 224 and a generating part 226, the measuring part 222 is controlled by the control part 224 to perform signal measurement analysis, and the generating part 226 is controlled to generate an active noise reduction signal to be sent to the secondary sound source 300.
Correspondingly, in one embodiment, the error sensor 100 includes a microphone 110 and a first amplifier 120, the microphone 110 being connected to the signal processing device 220 through the first amplifier 120. The microphone 110 collects ambient noise, and the collected signal is amplified by the first amplifier 120 and then sent to the signal processing device 220.
Further, the secondary sound source 300 comprises a second amplifier 320 and a loudspeaker 340, the loudspeaker 340 being connected to the signal processing device 220 via the second amplifier 320. The active noise reduction signal output by the signal processing device 220 is amplified by the second amplifier 320 and then transmitted to the speaker 340, and the speaker 340 performs parameter configuration according to the received signal and sends out a secondary sound source signal to perform active noise reduction on the transformer noise.
In particular, in one embodiment, the ambient noise data includes time domain noise data and frequency noise data. The adaptive feedback control system 200 performs time domain analysis and frequency analysis respectively according to the noise signal monitored by the error sensor 100 to obtain time domain noise data and frequency noise data, as shown in fig. 3, which is a discrete domain equivalent diagram of the adaptive feedback control system 200. The adaptive feedback control system 200 establishes constraint conditions by combining with the objective function of active noise reduction, and performs parameter optimization by using the adaptive particle swarm optimization.
As shown in fig. 4, which is a flowchart of a basic particle swarm algorithm, a population initializes initial positions and initial speeds of N particles, calculates a fitness of each particle, updates individual historical optimal particles pbest and population optimal particles gbest in combination with constraint conditions, analyzes whether the particles gbest meet a precision requirement according to an objective function, if so, ends optimization, and if not, determines whether a maximum number of iterations is reached. And ending the optimization when the maximum optimization times are reached, otherwise, updating the speed and the position of each particle, and returning to the step of updating the individual history optimal particle pbest and the population optimal particle gbest. And carrying out initial adjustment and fine adjustment on the parameter optimization by adopting a basic particle swarm algorithm, and realizing spatial noise reduction of a cube noise reduction area by using the obtained optimized parameters.
In addition, the adaptive feedback control system 200 also supports operations of saving, outputting and reading the collected ambient noise data and the generated optimized parameters, for example, the adaptive feedback control system 200 may upload related data to a terminal through a data transmission interface for an operator to view, and the operator may also send a query instruction, and the adaptive feedback control system 200 reads corresponding data according to the query instruction and sends the corresponding data to a display for displaying. Fig. 5 is a diagram of a software framework of the adaptive feedback control system 200, where the adaptive feedback control system 200 includes a data collection module, an output module, a storage module, a noise measurement analysis module, and an active noise reduction module, where the data collection module, the output module, the storage module, and the read module are used for performing data collection, data output, data storage, and data reading functions, the noise measurement analysis module is used for performing time domain analysis and frequency domain analysis, the time domain analysis includes analyzing time-amplitude data and time-sound pressure level data of a noise signal, and the frequency domain analysis includes analyzing frequency-amplitude data and frequency-sound pressure level data of the noise signal. And the active noise reduction module is used for optimizing parameters according to the self-adaptive particle swarm algorithm.
In addition, in one embodiment, the transformer active noise reduction device further comprises a data uploading device and an alarm device connected to the adaptive feedback control system 200. The adaptive feedback control system 200 may upload data to the local terminal through the data upload device, or may send data to the base station through the data upload device and transmit the data to the remote control terminal through the wide area network. In addition, the adaptive feedback control system 200 also controls the alarm device to alarm when the collected noise data exceeds a preset limited threshold value, and reminds an operator to overhaul in time when the noise of the transformer is too high. The alarm device does not have the only alarm mode, and can give an alarm by controlling the alarm lamp to flash, or give an alarm by the alarm loudspeaker, or display alarm information by the control display. In addition, the alarm device can also adopt the combination of the above modes to alarm.
In one embodiment, the data uploading device comprises a 485-type transmitter and a data exporter, wherein the 485-type transmitter is connected with the adaptive feedback control system 200 and the data exporter. The model 485 transmitter exports the data output by the adaptive feedback control system 20 through a data exporter to realize data transfer. In addition, the 485 type transmitter also transmits data to the base station through a line, and uploads the data to the wide area network through the base station.
Further, the transformer active noise reduction device further comprises a concentrator, wherein the concentrator is connected with the 485 type transmitter and is also used for communicating with the base station. The concentrator can specifically adopt a GPRS (General Packet Radio Service) concentrator, the concentrator sends data transmitted by the 485-type transmitter to the base station, and in addition, the concentrator can also generate a data curve according to the transmitted data and export the data curve, so that an operator can check the data and perform statistical analysis.
According to the transformer active noise reduction equipment, the parameter optimization of the secondary sound source is carried out by adopting the basic particle swarm optimization according to the environmental noise data, the active noise reduction signal is obtained and sent to the secondary sound source, so that the power and the sounding precision of the secondary sound source are controlled to meet the active noise reduction requirement, the transformer noise can be effectively reduced, and the active noise reduction reliability of the transformer is improved. In addition, the active noise reduction technology is applied to distribution transformer low frequency noise reduction system with advantages such as the system is little, light in weight, the low frequency is effectual, effectively reduce low frequency noise, can effectively solve residential district distribution transformer noise problem, reduce noise is to resident's influence, and can constantly strengthen the research to residential district distribution transformer for power supply unit staff moreover, formulate more reasonable noise reduction scheme, better guarantee residential district's environment has higher practical value.
In one embodiment, a transformer noise online monitoring system is further provided, and the transformer noise online monitoring system comprises a remote control terminal and the transformer active noise reduction device. In addition, the transformer noise online monitoring system further comprises a mobile terminal, and the mobile terminal is communicated with the remote control terminal. Specifically, as shown in fig. 6, data uploaded by the adaptive feedback control system 200 is sent to the base station through the 485-type transmitter and the concentrator, and is transmitted to the remote control terminal through the wide area network for display, so that the noise of the transformer can be remotely monitored on line. The remote control terminal can also share the data to the mobile terminal for displaying, so that an operator can conveniently check the data at any time. The remote control terminal can be a desktop computer, and the mobile terminal can be a mobile phone, a notebook or wearable equipment. In addition, the mobile terminal can also be directly communicated with the wide area network through a cloud platform to acquire transformer noise data for viewing.
According to the transformer noise online monitoring system, the parameter optimization of the secondary sound source is carried out by adopting the basic particle swarm optimization according to the environmental noise data, the active noise reduction signal is obtained and sent to the secondary sound source, so that the power and the sounding precision of the secondary sound source are controlled to meet the active noise reduction requirement, the transformer noise can be effectively reduced, and the active noise reduction reliability of the transformer is improved. Meanwhile, the noise of the transformer can be remotely monitored on line through a remote control terminal, and the convenience of monitoring the noise of the transformer is improved.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (8)
1. The transformer active noise reduction equipment is characterized by comprising an error sensor, an adaptive feedback control system and a secondary sound source, wherein the adaptive feedback control system is connected with the error sensor and the secondary sound source;
the adaptive feedback control system comprises a signal processing device and a processor, wherein the signal processing device is connected with the error sensor and the secondary sound source, and the processor is connected with the signal processing device; the error sensor comprises a microphone and a first amplifier, and the microphone is connected with the signal processing device through the first amplifier; the secondary sound source comprises a second amplifier and a loudspeaker, and the loudspeaker is connected with the signal processing device through the second amplifier;
the adaptive feedback control system obtains environmental noise data by establishing a hemispherical sound source model to analyze the type and the characteristics of a noise source according to the received noise signal, sets an active noise reduction target function as the square sum of sound pressure at each error sensor to be minimum, optimizes the parameters of the number, the position, the initial phase angle and the amplitude of a secondary sound source by adopting a basic particle swarm algorithm according to the environmental noise data to obtain an active noise reduction signal, sends the active noise reduction signal to the secondary sound source, and controls the power and the sound production precision of the secondary sound source;
the basic particle swarm optimization process comprises the following steps: initializing initial positions and initial speeds of N particles by a population, calculating the fitness of each particle, updating individual history optimal particle pbest and population optimal particle gbest by combining constraint conditions, analyzing whether the particle gbest meets the precision requirement or not according to an objective function, finishing optimization if the particle gbest meets the precision requirement, and judging whether the maximum iteration frequency is reached or not if the particle gbest does not meet the precision requirement; ending the optimization when the maximum optimization times is reached, otherwise, updating the speed and the position of each particle, and returning to the step of updating the individual history optimal particle pbest and the population optimal particle gbest;
the adaptive feedback control system also supports time domain analysis and frequency domain analysis of the collected ambient noise data, the time domain analysis including analyzing time-amplitude data and time-sound pressure level data of the noise signal, and the frequency domain analysis including analyzing frequency-amplitude data and frequency-sound pressure level data of the noise signal.
2. The transformer active noise reduction device of claim 1, wherein the ambient noise data comprises time domain noise data and frequency noise data.
3. The transformer active noise reduction device of claim 1, wherein the adaptive feedback control system parametrically configures the secondary sound source with the active noise reduction signal such that the secondary sound source outputs a noise reduction signal according to the configured parameters.
4. The transformer active noise reduction device of claim 1, further comprising a data uploading device and an alarm device connected to the adaptive feedback control system.
5. The transformer active noise reduction device of claim 4, wherein the data uploading means comprises a 485-type transmitter and a data exporter, the 485-type transmitter is connected with the adaptive feedback control system and the data exporter.
6. The transformer active noise reduction device of claim 5, further comprising a concentrator, connected to the 485-type transmitter, for further communication with a base station.
7. An on-line transformer noise monitoring system, which is characterized by comprising a remote control terminal and the transformer active noise reduction device of any one of claims 1 to 6.
8. The transformer noise online monitoring system according to claim 7, further comprising a mobile terminal, wherein the mobile terminal is in communication with the remote control terminal.
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| CN112151249B (en) * | 2020-08-26 | 2024-04-02 | 国网安徽省电力有限公司检修分公司 | Active noise reduction method and system for transformer and storage medium |
| CN112581931A (en) * | 2020-12-28 | 2021-03-30 | 中国电力工程顾问集团西北电力设计院有限公司 | Indoor noise reduction method and system applied to thermal power plant |
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