A noise reduction method for a medium voltage uninterruptible power supply device

Abstract

The present invention relates to a noise reduction method for a medium voltage uninterruptible power supply device, belonging to the technical field of noise reduction. The specific steps of the noise reduction method are as follows: (1) installing monitoring equipment and detecting synchronization rate; (2) collecting information of each group of uninterruptible power supply devices and classifying them; (3) collecting noise data of each group of devices for analysis; (4) providing noise reduction feedback for each group of devices. The present invention can provide supplementary feedback for missing data by constructing a classification storage repository to ensure the integrity of data collection, and at the same time construct a retrieval data set to improve the data retrieval efficiency of staff, and can perform redundant screening of noise data generated by each group of uninterruptible power supply devices, thereby improving the accuracy of collected noise data, ensuring the accuracy of the noise decibel data of each group of uninterruptible power supply devices fed back, and facilitating staff to view and analyze.

Description

Technical Field

[0001] The present invention belongs to the technical field of noise reduction, and in particular, relates to a noise reduction method for a medium voltage uninterruptible power supply device. Background Art

[0002] The standard usage of noise is noise. From a physiological point of view, any sound that interferes with people's rest, study and work, and interferes with the sounds people want to hear, that is, unnecessary sounds, are collectively referred to as noise. When noise has adverse effects on people and the surrounding environment, noise pollution is formed. In physics, noise refers to all irregular signals, such as electromagnetic noise, thermal noise, noise during radio transmission, laser noise, fiber optic communication noise, noise on the screen when the camera takes pictures, etc. Among them, as computer application systems have higher and higher requirements for power supply, uninterruptible power devices have gradually received people's attention and are widely used in mining, aerospace, industry, communications, national defense, hospitals, computer business terminals and other industries. At the same time, people's noise reduction processing of the noise generated by uninterruptible power devices has also become an important direction for the optimization of uninterruptible power devices.

[0003] The existing noise reduction method for medium-voltage uninterruptible power supply is prone to data missing when collecting uninterruptible power supply information, which reduces the data retrieval efficiency of staff. In addition, the existing noise reduction method for medium-voltage uninterruptible power supply collects each group of uninterruptible power supply noise data with data redundancy, which reduces the accuracy of the collected noise data. Therefore, we propose a noise reduction method for medium-voltage uninterruptible power supply. Summary of the invention

[0004] The object of the present invention is to provide a method for reducing noise of a medium voltage uninterruptible power supply device, which solves the problems of low data retrieval efficiency and low accuracy of noise data existing in the prior art.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A noise reduction method for a medium voltage uninterruptible power supply device, the specific steps of the noise reduction method are as follows:

[0007] (1) Install monitoring equipment and detect synchronization rate: The staff installed the noise monitoring equipment on the uninterruptible power supply device, powered it through UPS, and adjusted the transmission synchronization of each group of noise monitoring equipment;

[0008] (2) Collecting and classifying information about each group of UPS devices: Collecting relevant data about UPS devices in each area, building a classification repository based on the MySQL database, and importing each group of data into the classification repository for classification and filtering;

[0009] (3) Collecting noise data of each group of devices for analysis: The server collects noise data of the running uninterruptible power supply devices in real time through noise monitoring equipment, and analyzes and adjusts the collected noise data of each group;

[0010] (4) Provide noise reduction feedback for each group of devices: The server receives the noise data of each group of uninterruptible power devices, compares and reduces the noise, and feeds back the processed results to the staff.

[0011] As a further solution of the present invention: the UPS described in step (1) is specifically an uninterruptible power supply containing an energy storage device, which is mainly used to provide uninterruptible power supply to some equipment that has high requirements on power supply stability.

[0012] As a further solution of the present invention: the specific steps of the classification filtering in step (2) are as follows:

[0013] Step 1: The classification repository receives each set of UPS information, removes duplicate information, and detects whether there are missing values;

[0014] Step 2: If there are missing values, the missing UPS is marked and the marking information is fed back to the server. After receiving the marking information, the server collects the relevant UPS information again.

[0015] Step 3: If the relevant UPS information cannot be collected, it will be fed back to the relevant staff for repair. After the repair is completed, the information of the UPS will be collected again until there are no missing values;

[0016] Step 4: The classification repository classifies the collected UPS information according to different areas, numbers the classified UPS, extracts feature words from each group of information, and integrates the extracted feature data into a retrieval data set for staff to perform data retrieval.

[0017] As a further solution of the present invention: the specific steps of analysis and adjustment in step (3) are as follows:

[0018] Step 1: The server builds an optimization learning model and imports each set of noise data collected by the noise monitoring equipment into the optimization learning model;

[0019] Step 2: Optimize the learning model to sort each group of noise data, and segment the entire data value of each group of noise data according to user-defined rules, and integrate the segmented data to generate the noise set S n ={A1, A2, A3, ..., A x}, where n is the total number of noise sets segmented, and x is the total number of noise data segmentations in each group;

[0020] Step 3: Group the data set into several clusters. The values ​​outside the clusters are isolated points, and the isolated points are marked as redundant data. Similar or adjacent data are aggregated together to form various cluster sets, and the data outside these cluster sets are marked as redundant data.

[0021] Step 4: Delete the detected redundant data and restore the noise data of each group to obtain accurate noise data of the uninterruptible power supply device.

[0022] As a further solution of the present invention: the specific steps of comparison and noise reduction in step (4) are as follows:

[0023] S1: The server is connected to the Internet for communication, and simultaneously captures each group of noise standard decibels to build a comparison database. At the same time, it extracts the detection decibel value in each group of noise data and compares it with the relevant standard decibel value in the comparison database. If the detection decibel value is greater than the standard decibel value, the noise data is marked as abnormal.

[0024] S2: Construct a regression function so that the function can better satisfy the relationship between each group of abnormal noise data, and use this function to smooth the data;

[0025] S3: Simultaneously start the relevant noise filters of the uninterruptible power supply with abnormal noise data, reduce the noise through the noise filter, adjust the operating voltage of the uninterruptible power supply, reduce its operating frequency, and feed back the noise of each group of uninterruptible power supply to the staff in real time for review.

[0026] As a further solution of the present invention: the specific steps of data retrieval in step 4 are as follows:

[0027] Q1: The staff inputs the characteristic word X, time Y and the UPS number M into the computer;

[0028] Q2: The server searches the retrieval data set based on the keywords transmitted by the staff. If the corresponding feature data is found, the data related to the feature data is fed back to the staff through the LCD display screen for viewing.

[0029] Beneficial effects of the present invention:

[0030] 1. Compared with the previous noise reduction methods, the noise reduction method of the medium voltage uninterruptible power supply device of the present invention constructs a classification repository through the MySql database, and transmits each group of uninterruptible power supply device information to the classification repository, and screens out its duplicate information, and re-collects the uninterruptible power supply device information with missing values. If the relevant uninterruptible power supply device information cannot be collected, it will be fed back to the relevant staff for repair. After the repair is completed, the information of the uninterruptible power supply device is collected again until there are no missing values. After the collection is completed, the classification repository classifies the collected groups of uninterruptible power supply device information according to different areas, and numbers the classified uninterruptible power supply devices, and extracts feature words from each group of information, and integrates the extracted feature data of each group into a retrieval data set for data retrieval by the staff. By constructing a classification repository, the missing data can be supplemented and fed back to ensure the integrity of data collection, and the retrieval data set is constructed to improve the data retrieval efficiency of the staff.

[0031] 2. The present invention sorts each group of noise data by optimizing the learning model, and at the same time, segments the entire data value of each group of noise data according to user-defined rules, and integrates the segmented data to generate a noise set S n ={A1, A2, A3, ..., A x}, where n is the total amount of segmented noise sets, x is the total number of segmentations of each group of noise data, and the data sets are grouped into several clusters. The values ​​outside the clusters are isolated points, and the isolated points are marked as redundant data. Similar or adjacent data are aggregated together to form various cluster sets. At the same time, the data outside these cluster sets are marked as redundant data, and the detected redundant data is deleted. The noise data of each group of segmentation is restored to obtain accurate uninterruptible power supply device noise data, which can screen out the redundant noise data generated by each group of uninterruptible power supply devices, improve the accuracy of the collected noise data, ensure the accuracy of the feedback data of the noise decibels of each group of uninterruptible power supply devices, and facilitate staff to view and analyze. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0033] Figure 1 The present invention is a flowchart of a noise reduction method for a medium voltage uninterruptible power supply device. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] Example 1

[0036] See also Figure 1 As shown, the present invention is a noise reduction method for a medium voltage uninterruptible power supply device. This embodiment specifically discloses a classification filtering method:

[0037] Install monitoring equipment and test synchronization rate: The staff installed the noise monitoring equipment on the uninterruptible power supply device, powered it through UPS, and adjusted the transmission synchronization of each group of noise monitoring equipment.

[0038] It should be further explained that UPS is specifically an uninterruptible power supply with an energy storage device, which is mainly used to provide uninterruptible power supply to some equipment that has high requirements for power supply stability.

[0039] Collect and classify information about each group of UPS devices: Collect relevant data about UPS devices in each area, build a classification repository based on the MySql database, and import each group of data into the classification repository for classification filtering.

[0040] Specifically, first, the classification repository receives each group of uninterruptible power supply device information, and filters out the repeated information therein, and at the same time detects whether there are missing values. If there are missing values, the missing uninterruptible power supply device is marked, and the marked information is fed back to the server. After receiving the marked information, the server collects the relevant uninterruptible power supply device information again. If the relevant uninterruptible power supply device information cannot be collected, it is fed back to the relevant staff for repair. After the repair is completed, the information of the uninterruptible power supply device is collected again until there are no missing values. After the collection is completed, the classification repository classifies the collected groups of uninterruptible power supply device information according to different areas, and numbers the classified uninterruptible power supply devices, and extracts feature words from each group of information, and integrates the extracted feature data of each group into a retrieval data set for the staff to perform data retrieval. By constructing a classification repository, it is possible to supplement the missing data and ensure the integrity of data collection. At the same time, a retrieval data set is constructed to improve the data retrieval efficiency of the staff.

[0041] It should be further explained that the staff inputs the feature word X, time Y and uninterruptible power supply device number M into the computer, and the server searches the retrieval data set according to the keywords transmitted by the staff. If the corresponding feature data is found, the data related to the feature data is fed back to the staff through the LCD display screen for viewing.

[0042] Example 2

[0043] See also Figure 1 As shown, the present invention is a noise reduction method for a medium voltage uninterruptible power supply device. In addition to the same structure as the above embodiment, this embodiment specifically discloses an analysis and adjustment method:

[0044] Collect noise data from each group of devices for analysis: The server collects noise data from the running uninterruptible power supply devices in real time through noise monitoring equipment, and analyzes and adjusts the collected noise data from each group.

[0045] Specifically, the server first builds an optimization learning model and imports each group of noise data collected by the noise monitoring device into the optimization learning model. After the data is imported, the optimization learning model sorts each group of noise data and divides the entire data value of each group of noise data according to user-defined rules, and integrates the divided data to generate a noise set S n ={A1, A2, A3, ..., A x}, where n is the total amount of segmented noise sets, x is the total number of segmentations of each group of noise data, and the data sets are grouped into several clusters. The values ​​outside the clusters are isolated points, and the isolated points are marked as redundant data. Similar or adjacent data are aggregated together to form various cluster sets. At the same time, the data outside these cluster sets are marked as redundant data, and the detected redundant data is deleted. The noise data of each group of segmentation is restored to obtain accurate uninterruptible power supply device noise data, which can screen out the redundant noise data generated by each group of uninterruptible power supply devices, improve the accuracy of the collected noise data, ensure the accuracy of the feedback data of the noise decibels of each group of uninterruptible power supply devices, and facilitate staff to view and analyze.

[0046] Provide noise reduction feedback for each group of devices: The server receives the noise data of each group of uninterruptible power devices, compares and reduces the noise, and feeds back the processed results to the staff.

[0047] Specifically, the server is connected to the Internet for communication, and each group of noise standard decibels is captured to build a comparison database. The detection decibel value in each group of noise data is extracted, and compared with the relevant standard decibel value in the comparison database. If the detection decibel value is greater than the standard decibel value, the noise data is marked as abnormal, and a regression function is constructed so that the function can better meet the relationship between each group of abnormal noise data, and this function is used to smooth the data. At the same time, the relevant noise filters of the uninterruptible power supply with abnormal noise data are started, and the noise is reduced by the noise filter. At the same time, the operating voltage of the uninterruptible power supply is adjusted to reduce its operating frequency, and the noise of each group of uninterruptible power supply is fed back to the staff in real time for review.

[0048] In the description of the specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0049] The above contents are merely examples and explanations of the concept of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described 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 by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A method for reducing noise of a medium voltage uninterruptible power supply device, characterized in that: The specific steps of the noise reduction method are as follows: (1) Install monitoring equipment and detect synchronization rate: The staff installed the noise monitoring equipment on the uninterruptible power supply device, powered it through UPS, and adjusted the transmission synchronization of each group of noise monitoring equipment; (2) Collect and classify information about each group of UPS devices: Collect relevant data about UPS devices in each area, build a classification repository based on the MySQL database, and import each group of data into the classification repository for classification and filtering; (3) Collecting noise data from each group of devices for analysis: The server collects noise data from the running uninterruptible power supply devices in real time through noise monitoring equipment, and analyzes and adjusts the collected noise data from each group; (4) Provide noise reduction feedback for each group of devices: The server receives the noise data of each group of uninterruptible power devices, compares and reduces the noise, and feeds back the processed results to the staff; The specific steps of analysis and adjustment described in step (3) are as follows: Step 1: The server builds an optimization learning model and imports each set of noise data collected by the noise monitoring equipment into the optimization learning model; Step 2: Optimize the learning model to sort each group of noise data, and segment the entire data value of each group of noise data according to user-defined rules, and integrate the segmented data to generate a noise set, where n is the total amount of segmented noise sets, and x is the total number of segmentations of each group of noise data; Step 3: Group the data set into several clusters. The values ​​outside the clusters are isolated points, and the isolated points are marked as redundant data. Similar or adjacent data are aggregated together to form various cluster sets, and the data outside these cluster sets are marked as redundant data. Step 4: Delete the detected redundant data and restore the noise data of each group to obtain accurate noise data of the UPS; The specific steps of comparison and noise reduction in step (4) are as follows: S1: The server is connected to the Internet for communication, and simultaneously captures each group of noise standard decibels to build a comparison database. At the same time, it extracts the detection decibel value in each group of noise data and compares it with the relevant standard decibel value in the comparison database. If the detection decibel value is greater than the standard decibel value, the noise data is marked as abnormal. S2: Construct a regression function so that the function can better satisfy the relationship between each group of abnormal noise data, and use this function to smooth the data; S3: Simultaneously start the relevant noise filters of the uninterruptible power supply with abnormal noise data, reduce the noise through the noise filter, adjust the operating voltage of the uninterruptible power supply, reduce its operating frequency, and feed back the noise of each group of uninterruptible power supply to the staff in real time for review.

2. The noise reduction method for a medium voltage uninterruptible power supply device according to claim 1, characterized in that: The UPS described in step (1) is specifically an uninterruptible power supply containing an energy storage device, which is mainly used to provide uninterruptible power supply to some equipment that has high requirements on power supply stability.

3. The noise reduction method for a medium voltage uninterruptible power supply device according to claim 1, characterized in that: The specific steps of classification filtering described in step (2) are as follows: Step 1: The classification repository receives each set of UPS information, removes duplicate information, and detects whether there are missing values; Step 2: If there are missing values, the missing UPS is marked and the marking information is fed back to the server. After receiving the marking information, the server collects the relevant UPS information again. Step 3: If the relevant UPS information cannot be collected, it will be fed back to the relevant staff for repair. After the repair is completed, the information of the UPS will be collected again until there are no missing values; Step 4: The classification repository classifies the collected UPS information according to different regions, numbers the classified UPS, extracts feature words from each group of information, and integrates the extracted feature data into a search data set for data retrieval by staff; The specific steps of data retrieval in step 4 are as follows: Q1: The staff inputs the characteristic word X, time Y and the UPS number M into the computer; Q2: The server searches the retrieval data set based on the keywords transmitted by the staff. If the corresponding feature data is found, the data related to the feature data is fed back to the staff through the LCD display screen for viewing.

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