Direct-current bias magnet data uploading method and device, computer device and storage medium

Abstract

This application relates to a method, apparatus, computer device, storage medium, and computer program product for uploading DC bias data. The method includes: acquiring DC bias data; judging the DC bias data according to the priority of judgment conditions; and when the DC bias data meets any one of the judgment conditions, uploading the DC bias data to a server, wherein the server stores the DC bias data. This method can effectively reduce data transmission resources.

Description

Technical Field

[0001] This application relates to the field of DC bias monitoring of transformers, and in particular to a method, apparatus, computer equipment, storage medium and computer program product for uploading DC bias data. Background Technology

[0002] Most urban rail transit systems use DC-powered vehicles. The DC power supply for rail transit returns through the rails, and since the rails are not completely insulated from the ground, stray currents exist in the ground. These stray currents can enter the power transformer from the neutral point, causing an increase in the transformer's neutral point current. This results in a DC magnetic flux being generated in the transformer core, thus producing a DC bias magnetization phenomenon.

[0003] DC bias can lead to increased noise and vibration in power transformers, and in severe cases, cause localized overheating, loosening of fasteners, and insulation damage, affecting the normal operation of the power transformer and even the entire power system. Therefore, an online monitoring system for transformer DC bias is crucial for studying, analyzing, and suppressing DC bias, and ensuring the stable operation of the power system.

[0004] However, the DC bias monitoring system for urban power grid transformers requires simultaneous monitoring of multiple signals such as neutral point DC, noise intensity, and vibration velocity for dozens or even hundreds of transformers in the power grid. The amount of data collected is enormous, posing a great challenge to the limited data transmission resources and data storage space. Summary of the Invention

[0005] Therefore, it is necessary to provide a DC biased magnetic data uploading method, apparatus, computer equipment, computer-readable storage medium, and computer program product that can effectively reduce data transmission resources in response to the above-mentioned technical problems.

[0006] Firstly, this application provides a method for uploading DC bias data, the method comprising:

[0007] Acquire DC bias data;

[0008] The DC bias data is judged according to the priority of the judgment conditions;

[0009] When the DC bias data meets any one of the judgment conditions, the DC bias data is uploaded to the server, and the server stores the DC bias data.

[0010] In one embodiment, the step of uploading the DC bias data to the server when the DC bias data satisfies any one of the judgment conditions includes:

[0011] When the acquisition time of the DC bias data meets the preset acquisition time range, the DC bias data is uploaded to the server;

[0012] When the acquisition time of the DC bias data does not meet the preset acquisition time range, the proportion of the DC bias data exceeding the preset threshold is calculated to obtain the DC bias ratio, and the DC bias data is uploaded to the server according to the DC bias ratio.

[0013] In one embodiment, the DC bias data includes neutral point DC, noise intensity, and vibration velocity; when the acquisition time of the DC bias data does not meet a preset time range, the proportion of the DC bias data exceeding a preset threshold is calculated to obtain the DC bias ratio, and the DC bias data is uploaded to the server according to the DC bias ratio, including:

[0014] The proportions of the neutral point DC, the noise intensity, and the vibration velocity exceeding the preset threshold are calculated to obtain the DC bias ratios corresponding to the neutral point DC, the noise intensity, and the vibration velocity. When at least one of the neutral point DC, the noise intensity, and the DC bias ratios corresponding to the velocity vibrations meet the corresponding threshold ratios, the DC bias data is uploaded to the server.

[0015] In one embodiment, the step of calculating the proportions of the neutral point DC, the noise intensity, and the vibration velocity exceeding the preset threshold to obtain the DC bias ratios corresponding to the neutral point DC, noise intensity, and vibration velocity, and uploading the DC bias data to the server when at least one of the neutral point DC, noise intensity, and vibration velocity-corresponding DC bias ratios satisfies the corresponding threshold ratio, includes:

[0016] The proportion of the neutral point DC exceeding a preset neutral point DC threshold in the DC bias data is calculated to obtain the neutral point proportion. When the neutral point proportion meets the preset neutral point proportion, the DC bias data is uploaded to the server.

[0017] When the neutral point ratio does not meet the preset neutral point ratio, the proportion of the noise intensity exceeding the preset intensity in the DC bias data is calculated to obtain the intensity ratio. When the intensity ratio meets the preset intensity ratio, the DC bias data is uploaded to the server.

[0018] When the intensity ratio does not meet the preset intensity ratio, the proportion of the vibration velocity exceeding the preset velocity in the DC bias data is calculated to obtain the velocity ratio. When the velocity ratio meets the preset velocity ratio, the DC bias data is uploaded to the server.

[0019] In one embodiment, the judgment condition is determined based on historical DC bias data analysis; the historical DC bias data analysis process includes:

[0020] Acquire the historical DC bias data;

[0021] The judgment criteria are obtained by statistically analyzing the historical DC bias data.

[0022] In one embodiment, acquiring DC bias data includes:

[0023] Read the initial DC bias data;

[0024] DC bias data is obtained by collecting the initial DC bias data according to the preset monitoring time.

[0025] Secondly, this application also provides a DC bias data uploading device, the device comprising:

[0026] The acquisition module is used to acquire DC bias data;

[0027] The judgment module is used to judge the DC bias data according to the priority of the judgment conditions;

[0028] An upload module is used to upload the DC bias data to a server when the DC bias data meets any one of the judgment conditions, and the server stores the DC bias data.

[0029] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described method.

[0030] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0031] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method.

[0032] The aforementioned DC bias magnetic data uploading method, device, computer equipment, storage medium, and computer program product first acquire the DC bias magnetic field, then judge the DC bias magnetic data according to the priority of the judgment conditions. When the DC bias magnetic data meets any one of the judgment conditions, the DC bias magnetic data is uploaded to the server, where it is stored. This can greatly reduce the transmission pressure on the DC bias magnetic data uploading device and effectively reduce data transmission resources; it can also effectively save data storage space on the monitoring server. Attached Figure Description

[0033] Figure 1 This is an application environment diagram of the DC bias data upload method in one embodiment;

[0034] Figure 2 This is a flowchart illustrating a DC bias data upload method in one embodiment;

[0035] Figure 3 This is a flowchart illustrating the DC bias data upload method in another embodiment;

[0036] Figure 4 This is a structural block diagram of a DC biased data upload device in one embodiment;

[0037] Figure 5 This is an internal structural diagram of a DC biased data upload device in one embodiment. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0039] The DC bias data uploading method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, the DC bias data upload device 102 communicates with the server 104 via a network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated onto the server 104 or placed in the cloud or on another network server. The DC bias data upload device 102 acquires DC bias data and then judges the DC bias data according to the priority of judgment conditions. When the DC bias data meets any one of the judgment conditions, it uploads the DC bias data to the server 104, which stores the DC bias data. This greatly reduces the transmission pressure on the DC bias data upload device and effectively saves the data storage space of the monitoring server. The server 104 can be implemented using a standalone server or a server cluster composed of multiple servers.

[0040] In one embodiment, such as Figure 2 As shown, a method for uploading DC bias data is provided, which can be applied to... Figure 1 The following steps are described using the DC bias data upload device 102 as an example:

[0041] S202, acquire DC bias data.

[0042] Among them, DC bias data is the grid data that can cause DC bias, which is obtained by the DC bias data uploading device when detecting grid data. DC bias data can include multiple signals such as neutral point DC, noise intensity, and vibration velocity.

[0043] S204: Judge the DC bias data according to the priority of the judgment conditions.

[0044] The judgment condition refers to the pre-set conditions that determine whether to send the DC bias data. For example, whether the acquisition time of the DC bias data meets the preset acquisition time range, whether the proportion of DC bias data exceeding the preset threshold meets the threshold proportion, etc.

[0045] Optionally, the judgment criteria are determined based on the analysis of historical DC bias data; the historical DC bias data analysis process includes: acquiring historical DC bias data; and statistically analyzing the historical DC bias data to obtain the judgment criteria.

[0046] Historical DC bias data refers to historical data acquired by the DC bias data upload device, which can be obtained based on a preset acquisition time. The preset acquisition time is a pre-defined period for collecting historical data. For example, if the preset acquisition event is set to the past two years, the DC bias data upload device will use historical data from the past two years as historical DC bias data. By setting a preset acquisition time, more meaningful historical DC bias data can be obtained, thereby improving the real-time performance and accuracy of the judgment conditions.

[0047] Specifically, after acquiring historical DC bias data, the DC bias data uploading device performs statistical analysis on the historical DC bias data to obtain judgment conditions.

[0048] Optionally, the judgment criteria can be obtained by filtering historical DC bias data using a trained weak model. The weak model can provide accurate judgment criteria from a large amount of historical DC bias data.

[0049] Optionally, the DC bias data uploading device statistically analyzes each data point in the historical DC bias data that can cause DC bias phenomena, obtains the correlation between each data point in the historical DC bias data and the DC bias phenomenon, sorts the correlations, obtains the data that has a greater impact on DC bias, uses it as a judgment condition, and sets a priority.

[0050] For example, after the DC bias data uploading device performs statistics on the historical DC bias data, the correlation ranking results are 5:00-6:00, central DC, noise intensity, vibration velocity, etc. Then the DC bias data uploading device will use 5:00-6:00 as the judgment condition and set its priority as the first. The priorities of the remaining judgment conditions are central DC, noise intensity, and vibration velocity, respectively.

[0051] Optionally, the DC bias data uploading device acquires and statistically analyzes historical DC bias data according to a preset update time, and then judges the conditions. This allows for timely updates to the judgment conditions based on the DC bias data, thereby accurately judging and uploading the DC bias data.

[0052] S206: When the DC bias data meets any one of the judgment conditions, the DC bias data is uploaded to the server, and the server stores the DC bias data.

[0053] Specifically, when the DC bias data meets any one of the judgment conditions, the DC bias data uploading device uploads it to the server, and the server stores the DC bias data.

[0054] Optionally, the server uses a combined storage method when storing DC bias data, so that it can be analyzed later based on the DC bias data.

[0055] In the above-mentioned DC bias magnetic data uploading method, the DC bias magnetic data uploading device first acquires DC bias magnetic data, and then judges the DC bias magnetic data according to the priority of the judgment conditions. When the DC bias magnetic data meets any one of the judgment conditions, the DC bias magnetic data is uploaded to the server, and the server stores the DC bias magnetic data. This can greatly reduce the transmission pressure of the DC bias magnetic data uploading device and effectively save the data storage space of the monitoring server.

[0056] In one embodiment, when the DC bias data meets any one of the judgment conditions, the DC bias data is uploaded to the server, including: when the acquisition time of the DC bias data meets the preset acquisition time range, the DC bias data is uploaded to the server; when the acquisition time of the DC bias data does not meet the preset acquisition time range, the proportion of the DC bias data exceeding the preset threshold is calculated to obtain the DC bias ratio, and the DC bias data is uploaded to the server according to the DC bias ratio.

[0057] The preset acquisition time refers to the time during which DC bias data is collected, which can be set according to the actual application scenario. For example, the preset acquisition time can be set to 5:00-6:00 AM, because this time period is when subway trains depart in the morning, and the monitoring data during this period is of great significance for the evaluation and analysis of transformer DC bias on that day.

[0058] The preset threshold refers to a pre-set threshold used to determine whether a transformer has experienced DC bias based on DC bias data. For example, taking DC neutral point as an example, the presence of stray current at the neutral point of the transformer does not necessarily lead to DC bias. DC bias will only occur when the stray current at the neutral point exceeds the preset DC neutral point threshold.

[0059] Specifically, the DC bias data uploading device first determines whether the DC bias data acquisition time is within a preset acquisition time range. If the acquisition time meets the preset acquisition time range, the DC bias data is uploaded to the server without further consideration of other conditions. If the acquisition time does not meet the preset acquisition time range, the proportion of DC bias data exceeding a preset threshold is calculated to obtain the DC bias ratio, and the DC bias data is uploaded to the server based on the DC bias ratio. Optionally, the device can determine whether to upload the DC bias data to the server based on the DC bias ratio.

[0060] In the above embodiment, the DC bias data uploading device first uploads DC bias data whose acquisition time meets the preset acquisition time range, and then uploads the DC bias data to the server according to the DC bias ratio, which can avoid repeated judgment.

[0061] In one embodiment, the DC bias data includes neutral point DC, noise intensity, and vibration velocity. When the acquisition time of the DC bias data does not meet the preset time range, the proportion of DC bias data exceeding a preset threshold is calculated to obtain the DC bias ratio, and the DC bias data is uploaded to the server according to the DC bias ratio. This includes: calculating the proportion of neutral point DC, noise intensity, and vibration velocity exceeding the preset threshold to obtain the DC bias ratio corresponding to neutral point DC, noise intensity, and vibration velocity; when at least one of the DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity meets the corresponding threshold ratio, the DC bias data is uploaded to the server.

[0062] Specifically, in this embodiment, the DC bias data includes neutral point DC, noise intensity, and vibration velocity. Therefore, the DC bias data uploading device calculates the proportions of neutral point DC, noise intensity, and vibration velocity that exceed their corresponding pre-thresholds, obtaining the DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity. The device then judges the DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity. When at least one of the DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity meets the corresponding threshold ratio, the DC bias data is uploaded to the server.

[0063] In this embodiment, when at least one of the DC bias ratios corresponding to the neutral point DC, noise intensity, and velocity vibration meets the corresponding threshold ratio, the DC bias data is uploaded to the server. This avoids missing any DC bias data that needs to be uploaded.

[0064] In one embodiment, the proportions of neutral point DC, noise intensity, and vibration velocity exceeding preset thresholds are calculated to obtain the DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity. When at least one of the DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity satisfies its corresponding threshold ratio, the DC bias data is uploaded to the server. This includes: calculating the proportion of neutral point DC exceeding a preset neutral point DC threshold in the DC bias data to obtain a neutral point ratio; when the neutral point ratio satisfies the preset neutral point ratio, the DC bias data is uploaded to the server; when the neutral point ratio does not satisfy the preset neutral point ratio, the proportion of noise intensity exceeding a preset intensity threshold in the DC bias data is calculated to obtain an intensity ratio; when the intensity ratio satisfies the preset intensity ratio, the DC bias data is uploaded to the server; when the intensity ratio does not satisfy the preset intensity ratio, the proportion of vibration velocity exceeding a preset velocity in the DC bias data is calculated to obtain a velocity ratio; when the velocity ratio satisfies the preset velocity ratio, the DC bias data is uploaded to the server.

[0065] The preset neutral point DC threshold is a pre-set standard used to determine whether the transformer has experienced DC bias based on the neutral point DC threshold. It is obtained in advance based on data analysis. For example, the neutral point DC threshold can be set to 10A (amperes).

[0066] The neutral point ratio refers to the proportion of data in the DC bias data where the neutral point exceeds the preset neutral point DC threshold. The preset neutral point ratio is a standard used to determine whether DC bias data needs to be uploaded. For example, the preset neutral point ratio can be set to 0.95.

[0067] Specifically, the DC bias data uploading device first calculates the proportion of neutral point DC exceeding a preset neutral point DC threshold in the DC bias data, obtaining the neutral point proportion. Then, it judges based on the neutral point proportion, and when the neutral point proportion meets the preset neutral point proportion, the DC bias data is uploaded to the server. Because the mechanism of DC bias in a transformer is the intrusion of DC current at the transformer neutral point, which leads to an abnormal increase in transformer vibration and noise, the judgment of neutral point DC can identify the vast majority of data packets that need to be uploaded.

[0068] The preset intensity threshold is a pre-set standard used to determine whether a transformer is experiencing DC bias based on noise intensity. It is obtained in advance based on data analysis. For example, the intensity threshold can be set to 80 dB.

[0069] The intensity ratio refers to the proportion of data in the DC bias data whose noise intensity exceeds a preset intensity threshold; the preset intensity ratio is a standard used to determine whether DC bias data needs to be uploaded, and for example, the intensity ratio can be set to 0.9.

[0070] Specifically, the DC bias data uploading device first calculates the proportion of noise intensity exceeding a preset intensity threshold in the DC bias data to obtain the intensity ratio. Then, it judges based on the intensity ratio, and when the intensity ratio meets the preset intensity ratio, it uploads the DC bias data to the server. This can avoid the situation where DC bias data is missed in a few cases where the DC current at the neutral point is not large but the noise is large.

[0071] The preset speed threshold is a pre-set standard used to determine whether the transformer has experienced DC bias magnetization based on the vibration speed. It is obtained in advance based on data analysis. For example, the preset speed threshold can be set to 1 mm / s.

[0072] The speed ratio refers to the proportion of DC bias data whose speed exceeds a preset speed DC threshold; the preset speed ratio is a standard used to determine whether DC bias data needs to be uploaded, and for example, the preset speed ratio can be set to 0.9.

[0073] Specifically, the DC bias data uploading device first calculates the proportion of vibration velocity exceeding a preset velocity threshold in the DC bias data, obtaining the velocity proportion. Then, based on the velocity proportion, it makes a judgment; when the velocity proportion meets the preset velocity proportion, the DC bias data is uploaded to the server. This avoids the situation where DC bias data is missed in a few cases where the neutral point DC current is small but the vibration is large.

[0074] It should be noted that the priority for noise intensity and vibration velocity can be the same.

[0075] In the above embodiment, the DC bias data uploading device sequentially judges the neutral point DC, noise intensity, and vibration velocity, thus enabling accurate uploading of DC bias data.

[0076] In one embodiment, acquiring DC bias data includes: reading initial DC bias data; and collecting DC bias data from the initial DC bias data according to a preset monitoring time.

[0077] Among them, the initial DC bias data refers to the DC bias data directly acquired by the DC bias data uploading device; the preset detection time refers to the time during which the DC bias data uploading device collects the initial DC bias data.

[0078] Optionally, the preset detection time can be set to 5 minutes, that is, the DC bias data uploading device will package the collected initial DC bias data every 5 minutes starting from the monitoring start time t0 to obtain DC bias data.

[0079] In the above embodiments, the DC bias data uploading device periodically collects DC bias data to facilitate timely judgment and uploading of the DC bias data.

[0080] In one exemplary embodiment, combined with Figure 3 As shown, Figure 3 This is a schematic diagram of the DC bias data upload process in one embodiment.

[0081] Step S1 Data Reading: Real-time reading of neutral point DC, noise intensity, and vibration velocity signals collected by the transformer DC bias monitoring device;

[0082] Step S2 Data Packaging: Starting from the monitoring start time t0, the neutral point DC, noise intensity and vibration velocity signals collected by the device are packaged once at the same preset time interval T to obtain data packet D;

[0083] Step S3 Data upload judgment: Sequentially perform data upload judgment on the consecutive data packets D;

[0084] The specific steps of the data upload judgment in step S3 are as follows:

[0085] S301: For data packets D whose acquisition time t is within the preset time range TR, send them directly;

[0086] S302: Calculate the proportion of data points in the data packet D whose neutral point DC absolute value exceeds the preset current threshold Im in the data packet. If KIn is greater than the preset DC proportion value P1, then the data packet is sent up.

[0087] S303: Calculate the proportion KNn of data points in the data packet D whose noise intensity exceeds the preset noise intensity threshold Nm. If KNn is greater than the preset noise proportion value P2, then the data packet is sent up.

[0088] S304: Calculate the proportion KVn of data points in the data packet D whose vibration velocity exceeds the preset vibration velocity threshold Vm. If KVn is greater than the preset vibration proportion value P3, the data packet is sent up; otherwise, the data packet is not sent up.

[0089] Among them, the preset time T is 5 minutes; the preset time range TR is the early departure period of the subway from 5:00 to 6:00; the preset current threshold Im is 10A; the preset DC ratio P1 is 0.95; the preset noise intensity threshold Nm is 80dB; the preset noise ratio P2 is 0.9; the preset vibration velocity threshold is 1mm / s; and the preset vibration ratio P3 is 0.9.

[0090] In the above embodiments, firstly, the data transmission pressure of the DC bias data upload device can be greatly reduced; secondly, the data storage space of the DC bias data upload device server can be effectively saved.

[0091] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0092] Based on the same inventive concept, this application also provides a DC bias data uploading device for implementing the DC bias data uploading method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more DC bias data uploading device embodiments provided below can be found in the limitations of the DC bias data uploading method described above, and will not be repeated here.

[0093] In one embodiment, such as Figure 4 As shown, a DC bias data uploading device is provided, comprising: an acquisition module 100, a judgment module 200, and an uploading module 300, wherein:

[0094] The acquisition module 100 is used to acquire DC bias data.

[0095] The judgment module 200 is used to judge the DC bias data according to the priority of the judgment conditions.

[0096] The upload module 300 is used to upload the DC bias data to the server when the DC bias data meets any one of the judgment conditions, and the server stores the DC bias data.

[0097] In one embodiment, the upload module 300 includes:

[0098] The time judgment unit is used to upload the DC bias data to the server when the acquisition time of the DC bias data meets the preset acquisition time range.

[0099] The data judgment unit is used to calculate the proportion of DC bias data exceeding a preset threshold when the acquisition time of DC bias data does not meet the preset acquisition time range, obtain the DC bias ratio, and upload the DC bias data to the server according to the DC bias ratio.

[0100] In one embodiment, the above data determination unit includes:

[0101] The condition judgment subunit is used to calculate the proportions of neutral point DC, noise intensity, and vibration velocity that exceed preset thresholds, and obtain the DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity. When at least one of the DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity meets the corresponding threshold ratio, the DC bias data is uploaded to the server.

[0102] In one embodiment, the above condition judgment subunit includes:

[0103] The neutral point subunit is used to calculate the proportion of neutral point DC exceeding a preset neutral point DC threshold in the DC bias data, and obtain the neutral point proportion. When the neutral point proportion meets the preset neutral point proportion, the DC bias data is uploaded to the server.

[0104] The noise subunit is used to calculate the proportion of noise intensity exceeding the preset intensity in the DC bias data when the neutral point ratio does not meet the preset neutral point ratio, and obtain the intensity ratio. When the intensity ratio meets the preset intensity ratio, the DC bias data is uploaded to the server.

[0105] The vibration subunit is used to calculate the proportion of vibration velocity exceeding the preset velocity in the DC bias magnetic data when the intensity ratio does not meet the preset intensity ratio, and to obtain the velocity ratio. When the velocity ratio meets the preset velocity ratio, the DC bias magnetic data is uploaded to the server.

[0106] In one embodiment, the above-mentioned apparatus includes:

[0107] The data acquisition module is used to acquire historical DC bias data.

[0108] The statistics module is used to perform statistical analysis on historical DC bias data to obtain judgment criteria.

[0109] In one embodiment, the acquisition module 100 includes:

[0110] The reading unit is used to read the initial DC bias data.

[0111] The monitoring unit is used to collect initial DC bias data according to a preset monitoring time to obtain DC bias data.

[0112] Each module in the aforementioned DC bias data upload device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0113] In one embodiment, a DC bias data uploading device is provided. This DC bias data uploading device can be a server, and its internal structure diagram can be as follows: Figure 5 As shown, the DC bias data upload device includes a processor, memory, and network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores DC bias data. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements a DC bias data upload method.

[0114] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0115] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps: acquiring DC bias data; judging the DC bias data according to the priority of judgment conditions; when the DC bias data meets any one of the judgment conditions, uploading the DC bias data to a server, and the server storing the DC bias data.

[0116] In one embodiment, when the processor executes a computer program, the function of uploading DC bias data to a server when the DC bias data meets any one of the judgment conditions includes: uploading the DC bias data to the server when the acquisition time of the DC bias data meets a preset acquisition time range; and when the acquisition time of the DC bias data does not meet the preset acquisition time range, calculating the proportion of DC bias data exceeding a preset threshold to obtain the DC bias ratio, and uploading the DC bias data to the server according to the DC bias ratio.

[0117] In one embodiment, the DC bias data implemented by the processor when executing the computer program includes neutral point DC, noise intensity, and vibration velocity; when the acquisition time of the DC bias data does not meet the preset time range, the proportion of DC bias data exceeding the preset threshold is calculated to obtain the DC bias ratio, and the DC bias data is uploaded to the server according to the DC bias ratio, including: calculating the proportion of neutral point DC, noise intensity, and vibration velocity exceeding the preset threshold to obtain the DC bias ratio corresponding to neutral point DC, noise intensity, and vibration velocity; when at least one of the DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity meets the corresponding threshold ratio, the DC bias data is uploaded to the server.

[0118] In one embodiment, when the processor executes a computer program, it calculates the proportions of neutral point DC, noise intensity, and vibration velocity exceeding preset thresholds to obtain DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity. When at least one of the DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity satisfies its corresponding threshold ratio, the DC bias data is uploaded to the server. This includes: calculating the proportion of neutral point DC exceeding a preset neutral point DC threshold in the DC bias data to obtain a neutral point ratio; when the neutral point ratio satisfies the preset neutral point ratio, the DC bias data is uploaded to the server; when the neutral point ratio does not satisfy the preset neutral point ratio, the noise intensity exceeds a preset intensity ratio in the DC bias data to obtain an intensity ratio; when the intensity ratio satisfies the preset intensity ratio, the DC bias data is uploaded to the server; when the intensity ratio does not satisfy the preset intensity ratio, the vibration velocity exceeds a preset velocity ratio in the DC bias data to obtain a velocity ratio; when the velocity ratio satisfies the preset velocity ratio, the DC bias data is uploaded to the server.

[0119] In one embodiment, the judgment condition implemented by the processor when executing the computer program is determined based on the analysis of historical DC bias data; the historical DC bias data analysis process includes: acquiring historical DC bias data; and performing statistics on the historical DC bias data to obtain the judgment condition.

[0120] In one embodiment, the acquisition of DC bias data implemented by the processor when executing a computer program includes: reading initial DC bias data; and acquiring DC bias data by collecting the initial DC bias data according to a preset monitoring time.

[0121] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, it performs the following steps: acquiring DC bias data; judging the DC bias data according to the priority of judgment conditions; when the DC bias data meets any one of the judgment conditions, uploading the DC bias data to a server, and the server storing the DC bias data.

[0122] In one embodiment, when the computer program is executed by the processor, the function of uploading DC bias data to the server when the DC bias data meets any one of the judgment conditions includes: uploading the DC bias data to the server when the acquisition time of the DC bias data meets a preset acquisition time range; and when the acquisition time of the DC bias data does not meet the preset acquisition time range, calculating the proportion of DC bias data exceeding a preset threshold to obtain the DC bias ratio, and uploading the DC bias data to the server according to the DC bias ratio.

[0123] In one embodiment, the DC bias data implemented when the computer program is executed by the processor includes neutral point DC, noise intensity, and vibration velocity. When the acquisition time of the DC bias data does not meet the preset time range, the proportion of DC bias data exceeding a preset threshold is calculated to obtain the DC bias ratio, and the DC bias data is uploaded to the server according to the DC bias ratio. This includes: calculating the proportion of neutral point DC, noise intensity, and vibration velocity exceeding the preset threshold to obtain the DC bias ratio corresponding to neutral point DC, noise intensity, and vibration velocity; and when at least one of the DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity meets the corresponding threshold ratio, the DC bias data is uploaded to the server.

[0124] In one embodiment, when the computer program is executed by the processor, it calculates the proportions of neutral point DC, noise intensity, and vibration velocity exceeding preset thresholds to obtain DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity. When at least one of the DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity satisfies the corresponding threshold ratio, the DC bias data is uploaded to the server. This includes: calculating the proportion of neutral point DC exceeding a preset neutral point DC threshold in the DC bias data to obtain a neutral point ratio; when the neutral point ratio satisfies the preset neutral point ratio, the DC bias data is uploaded to the server; when the neutral point ratio does not satisfy the preset neutral point ratio, calculating the proportion of noise intensity exceeding a preset intensity in the DC bias data to obtain an intensity ratio; when the intensity ratio satisfies the preset intensity ratio, the DC bias data is uploaded to the server; when the intensity ratio does not satisfy the preset intensity ratio, calculating the proportion of vibration velocity exceeding a preset velocity in the DC bias data to obtain a velocity ratio; when the velocity ratio satisfies the preset velocity ratio, the DC bias data is uploaded to the server.

[0125] In one embodiment, the judgment condition implemented by the computer program when executed by the processor is determined based on the analysis of historical DC bias data; the historical DC bias data analysis process includes: acquiring historical DC bias data; and performing statistics on the historical DC bias data to obtain the judgment condition.

[0126] In one embodiment, the acquisition of DC bias data implemented when the computer program is executed by the processor includes: reading initial DC bias data; and collecting DC bias data from the initial DC bias data according to a preset monitoring time.

[0127] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps: acquiring DC bias data; judging the DC bias data according to the priority of judgment conditions; and uploading the DC bias data to a server when the DC bias data meets any one of the judgment conditions, wherein the server stores the DC bias data.

[0128] In one embodiment, when the computer program is executed by the processor, the function of uploading DC bias data to the server when the DC bias data meets any one of the judgment conditions includes: uploading the DC bias data to the server when the acquisition time of the DC bias data meets a preset acquisition time range; and when the acquisition time of the DC bias data does not meet the preset acquisition time range, calculating the proportion of DC bias data exceeding a preset threshold to obtain the DC bias ratio, and uploading the DC bias data to the server according to the DC bias ratio.

[0129] In one embodiment, the DC bias data implemented when the computer program is executed by the processor includes neutral point DC, noise intensity, and vibration velocity. When the acquisition time of the DC bias data does not meet the preset time range, the proportion of DC bias data exceeding a preset threshold is calculated to obtain the DC bias ratio, and the DC bias data is uploaded to the server according to the DC bias ratio. This includes: calculating the proportion of neutral point DC, noise intensity, and vibration velocity exceeding the preset threshold to obtain the DC bias ratio corresponding to neutral point DC, noise intensity, and vibration velocity; and when at least one of the DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity meets the corresponding threshold ratio, the DC bias data is uploaded to the server.

[0130] In one embodiment, when the computer program is executed by the processor, it calculates the proportions of neutral point DC, noise intensity, and vibration velocity exceeding preset thresholds to obtain DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity. When at least one of the DC bias ratios corresponding to neutral point DC, noise intensity, and vibration velocity satisfies the corresponding threshold ratio, the DC bias data is uploaded to the server. This includes: calculating the proportion of neutral point DC exceeding a preset neutral point DC threshold in the DC bias data to obtain a neutral point ratio; when the neutral point ratio satisfies the preset neutral point ratio, the DC bias data is uploaded to the server; when the neutral point ratio does not satisfy the preset neutral point ratio, calculating the proportion of noise intensity exceeding a preset intensity in the DC bias data to obtain an intensity ratio; when the intensity ratio satisfies the preset intensity ratio, the DC bias data is uploaded to the server; when the intensity ratio does not satisfy the preset intensity ratio, calculating the proportion of vibration velocity exceeding a preset velocity in the DC bias data to obtain a velocity ratio; when the velocity ratio satisfies the preset velocity ratio, the DC bias data is uploaded to the server.

[0131] In one embodiment, the judgment condition implemented by the computer program when executed by the processor is determined based on the analysis of historical DC bias data; the historical DC bias data analysis process includes: acquiring historical DC bias data; and performing statistics on the historical DC bias data to obtain the judgment condition.

[0132] In one embodiment, the acquisition of DC bias data implemented when the computer program is executed by the processor includes: reading initial DC bias data; and collecting DC bias data from the initial DC bias data according to a preset monitoring time.

[0133] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0134] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0135] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for uploading DC bias data, characterized in that, The method is applied in a DC biased data upload device; the method includes: Real-time reading of initial DC bias data; wherein, the initial DC bias data refers to the DC bias data directly acquired by the DC bias data uploading device; According to the preset monitoring time, the initial DC bias data is packaged once every same preset time to obtain DC bias data; The DC bias data is judged according to the priority of the judgment conditions; When the acquisition time of the DC bias data meets the preset acquisition time range, the DC bias data is uploaded to the server; the server stores the DC bias data; wherein, the preset acquisition time is the time period during which the subway departs on the same day; the preset acquisition time includes 5:00-6:00 in the morning; When the acquisition time of the DC bias data does not meet the preset acquisition time range, the proportion of the DC bias data exceeding the preset threshold is calculated to obtain the DC bias ratio, and the DC bias data is uploaded to the server according to the DC bias ratio; the server stores the DC bias data.

2. The method according to claim 1, characterized in that, The DC bias data includes neutral point DC, noise intensity, and vibration velocity; when the acquisition time of the DC bias data does not meet the preset time range, the proportion of the DC bias data exceeding the preset threshold is calculated to obtain the DC bias ratio, and the DC bias data is uploaded to the server according to the DC bias ratio, including: The proportions of the neutral point DC, the noise intensity, and the vibration velocity exceeding the preset threshold are calculated to obtain the DC bias ratios corresponding to the neutral point DC, the noise intensity, and the vibration velocity. When at least one of the DC bias ratios corresponding to the neutral point DC, the noise intensity, and the vibration velocity meets the corresponding threshold ratio, the DC bias data is uploaded to the server.

3. The method according to claim 2, characterized in that, The calculation of the proportions of the neutral point DC, the noise intensity, and the vibration velocity exceeding the preset threshold yields the DC bias ratios corresponding to the neutral point DC, noise intensity, and vibration velocity. When at least one of the DC bias ratios corresponding to the neutral point DC, noise intensity, and vibration velocity satisfies the corresponding threshold ratio, the DC bias data is uploaded to the server, including: The proportion of the neutral point DC exceeding a preset neutral point DC threshold in the DC bias data is calculated to obtain the neutral point proportion. When the neutral point proportion meets the preset neutral point proportion, the DC bias data is uploaded to the server. When the neutral point ratio does not meet the preset neutral point ratio, the proportion of the noise intensity exceeding the preset intensity threshold in the DC bias data is calculated to obtain the intensity ratio. When the intensity ratio meets the preset intensity ratio, the DC bias data is uploaded to the server. When the intensity ratio does not meet the preset intensity ratio, the proportion of the vibration velocity exceeding the preset velocity threshold in the DC bias data is calculated to obtain the velocity ratio. When the velocity ratio meets the preset velocity ratio, the DC bias data is uploaded to the server.

4. The method according to claim 1, characterized in that, The judgment criteria are determined based on the analysis of historical DC bias data; the historical DC bias data analysis process includes: Acquire the historical DC bias data; The judgment criteria are obtained by statistically analyzing the historical DC bias data.

5. A DC biased magnetic data uploading device, characterized in that, The device includes: The acquisition module is used to read the initial DC bias data in real time; wherein, the initial DC bias data refers to the DC bias data directly acquired by the DC bias data upload device; according to the preset monitoring time, the initial DC bias data is packaged once at the same preset time interval to obtain DC bias data; The judgment module is used to judge the DC bias data according to the priority of the judgment conditions; The upload module includes a time judgment unit and a data judgment unit. The time judgment unit is used to upload the DC bias magnetic data to the server when the acquisition time of the DC bias magnetic data meets the preset acquisition time range. The server stores the DC bias magnetic data. The preset acquisition time is the time period during which the subway departs on the same day. The preset acquisition time includes 5:00-6:00 in the morning. The data judgment unit is used to calculate the proportion of the DC bias data exceeding a preset threshold when the acquisition time of the DC bias data does not meet the preset acquisition time range, obtain the DC bias ratio, and upload the DC bias data to the server according to the DC bias ratio; the server stores the DC bias data.

6. The apparatus according to claim 5, characterized in that, The DC bias data includes neutral point DC, noise intensity, and vibration velocity; the data judgment unit includes a condition judgment subunit, used to calculate the proportions of the neutral point DC, the noise intensity, and the vibration velocity exceeding the preset threshold, to obtain the DC bias ratios corresponding to the neutral point DC, the noise intensity, and the vibration velocity; when at least one of the DC bias ratios corresponding to the neutral point DC, the noise intensity, and the vibration velocity satisfies the corresponding threshold ratio, the DC bias data is uploaded to the server.

7. The apparatus according to claim 6, characterized in that, The data judgment unit includes a condition judgment subunit, which comprises a neutral point calculation unit, a noise calculation unit, and a vibration calculation unit. The neutral point calculation unit is used to calculate the proportion of the neutral point DC exceeding the preset neutral point DC threshold in the DC bias data to obtain the neutral point ratio. When the neutral point ratio meets the preset neutral point ratio, the DC bias data is uploaded to the server. The noise calculation unit is used to calculate the proportion of the noise intensity in the DC bias data that exceeds a preset intensity threshold when the neutral point ratio does not meet the preset neutral point ratio, and to obtain the intensity ratio. When the intensity ratio meets the preset intensity ratio, the DC bias data is uploaded to the server. The vibration calculation unit is used to calculate the proportion of the vibration velocity in the DC bias magnetic data that exceeds a preset velocity threshold when the intensity ratio does not meet the preset intensity ratio, and to obtain the velocity ratio. When the velocity ratio meets the preset velocity ratio, the DC bias magnetic data is uploaded to the server.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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