Multifunctional power equipment monitor with monitoring and alarm functions

Abstract

This application relates to the field of data processing technology, specifically to a multifunctional power equipment monitor with monitoring and alarm functions. The monitor includes a noise monitoring unit, a data acquisition unit, a data processing unit, and an alarm unit. The noise monitoring unit filters and suppresses noise in the raw power signal from the power equipment to obtain a filtered power signal. The data processing unit determines abnormal fluctuation values ​​and their impact coefficients based on real-time operating data. It also determines a real-time warning value based on the abnormal fluctuation value and its impact coefficient. The alarm unit issues an alarm when the real-time warning value is greater than or equal to a preset safety threshold. This monitor can improve alarm accuracy and reduce the probability of false alarms.

Description

Technical Field

[0001] This application relates to the field of data processing technology, specifically to a multifunctional power equipment monitor with monitoring and alarm functions. Background Technology

[0002] Power equipment monitors collect and analyze power data from power equipment to detect whether there are any faults in the equipment.

[0003] In related technologies, in order to ensure the accuracy of data acquisition, power equipment monitors generally use physical shielding (such as adding a metal casing) to combat noise interference in the electromagnetic environment.

[0004] However, this physical shielding method is less effective at suppressing noise generated by the power equipment monitor itself and complex interference transmitted through the lines, resulting in poor quality of the collected power signals, which affects the accuracy of subsequent data analysis and leads to a high false alarm rate for fault alarms. Summary of the Invention

[0005] To address the technical problem of high false alarm rates caused by the weak interference suppression effect of physical shielding in power equipment monitors, this application aims to provide a multifunctional power equipment monitor with both monitoring and alarm functions. The specific technical solution adopted is as follows:

[0006] This application provides a multifunctional power equipment monitor with monitoring and alarm functions. The monitor includes a noise monitoring unit, a data processing unit, and an alarm unit. The noise monitoring unit filters and suppresses noise in the original power signal of the power equipment to obtain a filtered power signal. The data processing unit determines anomaly values ​​and anomaly impact coefficients based on real-time operating data. The anomaly values ​​characterize the degree of disorder in the real-time operating data, and the anomaly impact coefficients characterize the adaptive recovery capability of the power equipment to data fluctuations. The real-time operating data is the filtered power signal within a historical time period. The data processing unit also determines a real-time warning value based on the anomaly values ​​and the anomaly impact coefficients. The alarm unit issues an alarm when the real-time warning value is greater than or equal to a preset safety threshold.

[0007] Optionally, when the data processing unit is used to determine the fluctuation anomaly, it is specifically used to: determine the variance and periodicity parameter of the real-time running data, wherein the variance is used to characterize the fluctuation range of the real-time running data within the historical time period, and the periodicity parameter is used to characterize the regularity of the fluctuation of the real-time running data; and determine the fluctuation anomaly based on the variance and the periodicity parameter.

[0008] Optionally, when the data processing unit is used to determine the fluctuation anomaly impact coefficient, it is specifically used to: identify multiple complete cycles included in the real-time operating data; determine the data set corresponding to each complete cycle, wherein the data set corresponding to a complete cycle is a data set constructed from a preset number of power data after the fluctuation of the complete cycle; and determine the fluctuation anomaly impact coefficient based on the absolute value of the difference between adjacent data in the data set corresponding to each complete cycle and the probability of occurrence of each data in each data set.

[0009] Optionally, the noise monitoring unit includes multiple terminals, which are arranged in a distributed manner, with a preset distance between adjacent terminals.

[0010] Optionally, the noise monitoring unit includes multiple integrated filters and a grounding port; the multiple integrated filters are used to filter out high-frequency electromagnetic interference in the original power signal; the grounding port is used to ground the terminal block to eliminate low-frequency noise in the circuit.

[0011] Optionally, the noise monitoring unit also includes a backup battery for supplying operating current to the plurality of integrated filters.

[0012] Optionally, the alarm unit includes a threshold comparison subunit, a communication transmission subunit, and a signal generation subunit; the threshold comparison subunit is used to compare the real-time warning value with the preset safety threshold; the communication transmission subunit is used to send the real-time operation data to the remote monitoring center when the real-time warning value is greater than or equal to the preset safety threshold; the signal generation subunit is used to generate an alarm command, which is used to drive the alarm indicator light to flash.

[0013] Optionally, the multi-functional power equipment monitor also includes a human-machine interaction unit; the human-machine interaction unit includes a display subunit and a parameter adjustment subunit; the display subunit is used to display the operating parameters and alarm information of the power equipment; the parameter adjustment subunit is used to adjust the preset safety threshold based on user operation.

[0014] Optionally, the display subunit and the parameter adjustment subunit are located on the interface panel, and the human-machine interaction unit also includes the interface panel and the housing of the interface panel; the housing of the interface panel is a non-metallic transparent shell.

[0015] Optionally, the human-machine interface unit also includes a liquid-cooled radiator for heat dissipation of the system interior.

[0016] This application has the following beneficial effects:

[0017] In this embodiment, the original power signal of the power equipment is filtered and noise suppressed to obtain a filtered power signal, ensuring the purity of the data acquisition from the signal source. Then, based on the filtered power signal over a historical period, fluctuation anomalies and fluctuation anomaly influence coefficients are analyzed. Based on these fluctuation anomalies and fluctuation anomaly influence coefficients, a real-time warning value is obtained, which can comprehensively evaluate the operating status and adaptive capability of the power equipment. Based on this real-time warning value, it can effectively distinguish between normal operating condition fluctuations and actual faults, thereby issuing an alarm when the real-time warning value is large, improving the accuracy of the alarm and reducing the probability of false alarms. The multifunctional power equipment monitor with monitoring and alarm functions claimed in this embodiment achieves a more accurate fault identification capability than traditional solutions. Attached Figure Description

[0018] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A schematic diagram of a multifunctional power equipment monitor with monitoring and alarm functions provided in one embodiment of this application;

[0020] Figure 2 is a structural schematic diagram of a noise monitoring unit provided in an embodiment of this application;

[0021] Figure 3 is a flowchart of a method for a data processing unit to perform a multifunctional power equipment monitoring method with monitoring and alarm functions, according to an embodiment of this application.

[0022] Figure 4 is a flowchart of a method for a data processing unit to perform another multifunctional power equipment monitoring method with monitoring and alarm functions, provided in an embodiment of this application.

[0023] Figure 5 is a structural schematic diagram of an alarm unit provided in an embodiment of this application;

[0024] Figure 6 is a schematic diagram of another multifunctional power equipment monitor with monitoring and alarm functions provided in an embodiment of this application;

[0025] Figure 7 is a schematic diagram of the structure of a human-computer interaction unit provided in an embodiment of this application. Detailed Implementation

[0026] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a multifunctional power equipment monitor with monitoring and alarm functions proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0027] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0028] The following description, in conjunction with the accompanying drawings, details a specific scheme for a multifunctional power equipment monitor with monitoring and alarm functions provided in this application.

[0029] Please see Figure 1 The diagram shows a structural schematic of a multifunctional power equipment monitor with monitoring and alarm functions provided in one embodiment of this application.

[0030] like Figure 1 As shown, the multifunctional power equipment monitor 10 with monitoring and alarm functions includes a noise monitoring unit 101, a data processing unit 102, and an alarm unit 103.

[0031] It should be noted that, for ease of description, the multi-functional power equipment monitor 10 with monitoring and alarm functions will be referred to as monitor 10.

[0032] The noise monitoring unit 101 is used to filter and suppress noise in the original power signal of the power equipment to obtain the filtered power signal.

[0033] It should be understood that in practical applications, the noise monitoring unit 101 can be a terminal block. Traditional terminal blocks have an overly compact layout, which makes wiring difficult, and the excessive intertwining of cables can easily cause serious electromagnetic interference, including high-frequency electromagnetic interference (such as pulse noise generated by switching operations) and low-frequency noise (such as continuous interference caused by system voltage fluctuations), affecting the quality of data collected from power equipment by the multi-functional power equipment monitor 10.

[0034] In this embodiment, electromagnetic coupling between lines can be reduced by optimizing the physical layout of the terminals, thereby reducing the possibility of interference at the source. In addition, an independent power supply component can be configured to ensure the stable operation of the filtering function and ensure the continuity and consistency of the noise suppression effect.

[0035] In one alternative implementation, the terminal block can employ differential transmission lines to suppress high-frequency electromagnetic interference by utilizing the anti-interference characteristics of differential signals.

[0036] Alternatively, low-frequency noise can be isolated and eliminated by adding a shielding isolation strip between the terminal block and the power equipment.

[0037] In one implementation of this application, the noise monitoring unit 101 includes multiple terminals, which are arranged in a distributed manner, with a preset distance between adjacent terminals.

[0038] It should be understood that this layout reduces electromagnetic coupling between adjacent lines from a physical structure perspective, thereby reducing secondary electromagnetic interference caused by line interleaving.

[0039] In one implementation of this application, the noise monitoring unit 101 further includes multiple integrated filters and a grounding port. The multiple integrated filters are used to filter out high-frequency electromagnetic interference in the original power signal; the grounding port is used to ground the terminal block to eliminate low-frequency noise in the circuit.

[0040] It should be understood that an integrated filter is installed at a terminal connection point to filter the raw power signal during the operation of the power equipment, thereby reducing the impact of electromagnetic interference (EMI) on the monitor 10.

[0041] Optionally, the integrated filter can also be equipped with a weak current testing circuit. Based on this, the operating logic of power equipment can be extracted using a small amount of monitoring data, without relying on complex integrated sensors or machine learning models.

[0042] Understandably, integrated filters can effectively suppress high-frequency noise, but their suppression effect on low-frequency or transient electromagnetic pulses is limited. Therefore, by connecting the grounding port and the ground wire to form a stable current loop, low-frequency noise in the circuit can be effectively eliminated, thereby enhancing the circuit stability of the terminal block.

[0043] Optionally, the wiring port can be located on the left or right side of the terminal block.

[0044] Understandably, integrated filters can specifically filter out high-frequency electromagnetic interference, and grounding ports can eliminate low-frequency noise through grounding. The combined effect of the two can effectively cover common types of interference in the original power signal. Combined with the distributed layout of multiple terminals, it can control the noise at the source and avoid interference superposition caused by dense wiring.

[0045] In one implementation of this application, the noise monitoring unit 101 further includes a backup battery for providing operating current to the plurality of integrated filters.

[0046] It should be understood that each terminal can be configured with an independent backup battery to provide a stable, weak operating current to the integrated filter connected to the terminal when the external power supply is abnormal (the low-frequency noise caused to the circuit at this time can be eliminated through the grounding port) to ensure the continuity of the filtering function. Then, the original power signal at each terminal connection is filtered by the integrated filter, and the filtered power signal of the multiple terminals is determined as the filtered power signal.

[0047] Optionally, one terminal block corresponds to one spare battery.

[0048] It should be understood that when the external power supply line fluctuates or is briefly interrupted, the backup battery can ensure that the integrated filter continues to work stably, maintain its noise filtering performance, and prevent the acquisition of unprocessed noise signals due to power failure of the integrated filter, thereby ensuring the continuity and accuracy of data acquisition under any operating conditions.

[0049] For example, Figure 2 A schematic diagram of a noise monitoring unit 101.

[0050] As shown in Figure 2, the noise monitoring unit 101 includes a terminal block housing 201, terminals 202, 203, 204, 205, 206, 207, and 208. Taking terminal 202 as an example, an integrated filter 209 and a backup battery 210 are installed at the connection of terminal 202. The right side of the noise monitoring unit 101 includes a grounding port 211.

[0051] The data processing unit 102 is used to determine the fluctuation anomaly value and the fluctuation anomaly impact coefficient based on real-time operating data.

[0052] The fluctuation anomaly value characterizes the degree of disorder in the real-time operating data, which is a filtered power signal from a historical time period. The fluctuation anomaly impact coefficient characterizes the adaptive recovery capability of the power equipment to data fluctuations. Therefore, the data processing unit 102 can determine the real-time warning value for the power equipment based on the fluctuation anomaly value and the fluctuation anomaly impact coefficient.

[0053] In one alternative implementation, multiple fluctuations and their magnitudes in real-time running data can be analyzed. The fluctuation anomaly value can be determined based on the magnitude of each fluctuation, and the fluctuation anomaly impact coefficient can be determined based on the changes in data after each fluctuation.

[0054] It should be understood that the larger the fluctuation anomaly value, the more disordered the real-time operating data is, and the more likely the power equipment is to experience anomalies within a historical period; the larger the fluctuation anomaly impact coefficient, the weaker the adaptive recovery capability of the power equipment is, the greater the impact of the abnormal fluctuation on the power equipment, and the more likely the power equipment is to experience anomalies.

[0055] The data processing unit 102 is also used to determine the real-time warning value based on the fluctuation anomaly value and the influence coefficient of the fluctuation anomaly.

[0056] In one alternative implementation, the product of the fluctuation anomaly value and the fluctuation anomaly influence coefficient can be used to determine the real-time warning value.

[0057] It should be understood that the higher the real-time warning value, the greater the likelihood of a malfunction in the power equipment.

[0058] Alarm unit 103 is used to issue an alarm when the real-time warning value is greater than or equal to a preset safety threshold.

[0059] It should be understood that if the real-time warning value is greater than or equal to the preset safety threshold, it indicates that the power equipment is likely to malfunction, and an alarm can be issued at this time.

[0060] For example, the real-time warning value can be normalized, and in this case, the preset safety threshold can be 0.5.

[0061] In this embodiment, the original power signal of the power equipment is filtered and noise suppressed to obtain a filtered power signal, ensuring the purity of the data acquisition from the signal source. Then, based on the filtered power signal over a historical period, fluctuation anomalies and fluctuation anomaly influence coefficients are analyzed. Based on these fluctuation anomalies and fluctuation anomaly influence coefficients, a real-time warning value is obtained, which can comprehensively evaluate the operating status and adaptive capability of the power equipment. Based on this real-time warning value, it can effectively distinguish between normal operating condition fluctuations and actual faults, thereby issuing an alarm when the real-time warning value is large, improving the accuracy of the alarm and reducing the probability of false alarms. The multifunctional power equipment monitor with monitoring and alarm functions claimed in this embodiment achieves a more accurate fault identification capability than traditional solutions.

[0062] It is understandable that when abnormal values ​​appear in the operating data of power equipment, there may be two situations: one is that the power equipment adaptively adjusts its working state according to the work requirements, and the other is that the working state of the power equipment is abnormal, causing abnormal fluctuations in the power data.

[0063] It should be understood that, in the first scenario, when electrical equipment changes due to load variations or adjustments to different operating modes, the electrical data (such as current and voltage) of various parts of the equipment will change periodically. For example, when starting or stopping a load, the current will increase instantaneously, or the output power of the electrical equipment will change accordingly when the load increases.

[0064] In the second scenario, when a part of the electrical equipment malfunctions (such as a damaged motor or abnormal control circuit), the power data may exhibit severe, aperiodic, and erratic fluctuations. For example, a sudden drop in voltage, a sudden surge in current, or excessive power fluctuations are common signals of electrical equipment failure.

[0065] Combining these two situations, it can be understood that the fluctuations in the normal operating data of power equipment usually have a certain regularity, while the abnormal operating data of power equipment caused by faults usually have suddenness and are not uniform and regularity.

[0066] Based on this, we can analyze the regularity of fluctuations in real-time operating data and more accurately identify whether fluctuations in power equipment are caused by faults.

[0067] Combination Figure 1 ,like Figure 3 As shown, in one implementation of this application embodiment, the data processing unit 102 is specifically used to execute the following S301-S302 when determining abnormal fluctuation values.

[0068] S301. Determine the variance and periodicity parameters of the real-time running data.

[0069] The variance is used to characterize the fluctuation range of the real-time running data within the historical time period, and the periodicity parameter is used to characterize the regularity of the fluctuation of the real-time running data.

[0070] It should be understood that the larger the variance, the more drastic the data fluctuations and the worse the operational stability of the power equipment, meaning the power equipment is operating abnormally. The periodic parameter is used to quantify the regularity of data fluctuations; the smaller the periodic parameter, the weaker the regularity of the data fluctuations and the more abnormal the operation of the power equipment.

[0071] The autocorrelation function (ACF) measures the correlation between a time series signal and itself at different time delays. If a signal is periodic, the ACF will show a peak when the delay equals its period. The magnitude of the peak reflects the significance of the periodic pattern; the higher the amplitude (closer to 1), the stronger the periodicity; the lower the amplitude (closer to 0), the closer the signal is to random noise. In one alternative implementation, the amplitude of the first significant peak in the autocorrelation function (excluding zero delay, i.e., lag=0) can be determined based on the autocorrelation function of the real-time running data, and this amplitude can be used as the periodicity parameter.

[0072] It should be noted that a zero-delay peak represents a signal that is completely similar to itself at that instant; its amplitude is 1, serving as a reference point and carrying no periodic information. The first significant peak indicates that the current data shows a high degree of similarity to the data from previous moments, suggesting the existence of a period in the current data compared to previous data.

[0073] Optionally, the significant peak can be a local maximum with an amplitude greater than a preset threshold (e.g., 0.5).

[0074] S302. Based on variance and periodicity parameters, determine the fluctuation outliers.

[0075] It should be understood that this fluctuation outlier is a dimensionless assessment parameter. It can be normalized to the variance and periodicity parameter to eliminate the influence of dimensions. Then, the difference between the value 1 and the periodicity parameter is taken, and the difference is multiplied by the variance. The resulting product is the fluctuation outlier. It should be understood that the variance and periodicity parameter involved in this calculation process are both standardized or normalized results.

[0076] In this embodiment, variance can characterize the overall intensity of fluctuations in real-time running data, while periodicity parameters characterize whether the fluctuations are regular. Therefore, combining the two yields fluctuation outliers that not only reflect the intensity of the fluctuations but also effectively identify fluctuation patterns, distinguishing between severe but regular fluctuations and severe but irregular fluctuations, thus avoiding the limitations of single-dimensional judgment.

[0077] Combination Figure 1 ,like Figure 4 As shown, in one implementation of this application embodiment, the data processing unit 102 is specifically used to execute the following S401-S403 when determining the fluctuation anomaly influence coefficient.

[0078] S401. Identify multiple complete cycles included in real-time running data.

[0079] It should be understood that a complete cycle refers to the complete process of running data returning to its initial state or reaching a stable state after fluctuations from its initial state. A complete cycle represents one fluctuation.

[0080] Optionally, extreme points in the running data and their corresponding timestamps can be detected, and data segments between adjacent extreme points of the same type can be defined as a complete cycle.

[0081] Optionally, extreme points include maximum and minimum values. Depending on the actual situation, you can choose to determine the complete cycle based on the maximum or minimum value.

[0082] S402. Determine the data set corresponding to each complete cycle.

[0083] Among them, the data set corresponding to a complete cycle is a data set constructed from a preset number of power data after the fluctuation of that complete cycle.

[0084] Specifically, for each identified complete cycle, a specific number of continuous running data are extracted after the end of that complete cycle to form a data set.

[0085] It should be understood that the data set corresponding to a complete cycle is used to characterize the dynamic process by which power equipment attempts to return to a stable state in the short term after the fluctuation.

[0086] S403. Determine the fluctuation anomaly impact coefficient based on the absolute value of the difference between adjacent data in the data sets corresponding to all complete cycles and the probability of occurrence of each data in each data set.

[0087] It should be understood that the absolute value of this difference can reflect the severity of the data change after each fluctuation. The larger the absolute value of this difference, the greater the magnitude of the state adjustment. The probability of each data point is used to measure from a statistical distribution perspective whether the data is concentrated around a certain stable value, thereby judging whether the system has effectively returned to stability.

[0088] Optionally, the absolute value of the difference can be subjected to max-min normalization to eliminate the influence of dimensions, and then the fluctuation anomaly influence coefficient can be determined based on the value after normalization.

[0089] Optionally, the abnormal fluctuation impact coefficient of power equipment within a historical time period satisfies the following formula:

[0090]

[0091] in, Indicates the coefficient of influence of abnormal fluctuations. This indicates the number of complete cycles in the real-time running data. Indicates a complete period The number of data points in the corresponding dataset. Represents the complete period after normalization The corresponding data set The data and the first The absolute value of the difference between the data points. Indicates the first The value of each data point in the complete period Corresponding data set The probability of occurrence in.

[0092] Based on the above formula, it should be understood that, The larger the value, the more drastic and unstable the data will continue to fluctuate during the recovery process after this fluctuation, and the greater the impact coefficient of the fluctuation anomaly. The smaller the value, the better. These data points belong to "rare values" or "outliers"; when there is a large change (i.e., The larger one happens to point to a rare state (i.e., The smaller the value, the more abnormal the fluctuation; the power equipment may not have returned to its normal, common operating range, but rather remains in an abnormal state. Therefore, The denominator can amplify the impact of this fluctuation on the final value. The impact.

[0093] Continue to understand the above formula, This indicates the persistence of anomalies over a complete cycle. When an anomalous change occurs within a dataset, multiplication amplifies the overall impact of this anomaly. When most complete cycles exhibit high persistence of anomalies, it indicates that the adaptive recovery capability of power equipment is generally poor.

[0094] In this embodiment of the application, by identifying the complete cycle and extracting the features of the data set after each complete cycle (i.e., the absolute value of the difference between adjacent data and the probability of occurrence of each data) to determine whether the fluctuation will cause a continuous deviation in the subsequent state, the ability of the power equipment to recover to a stable state after an abnormal fluctuation can be accurately assessed.

[0095] Combination Figure 1 As shown in Figure 5, in one implementation of this application embodiment, the alarm unit 103 includes a threshold comparison subunit 501, a communication transmission subunit 502, and a signal generation subunit 503.

[0096] The threshold comparison subunit 501 is used to compare the real-time warning value with the preset safety threshold.

[0097] The communication transmission subunit 502 is used to send real-time operation data to the remote monitoring center when the real-time warning value is greater than or equal to the preset safety threshold.

[0098] It should be understood that when the real-time warning value is greater than or equal to the preset safety threshold, the communication transmission subunit 502 determines that the current operating status of the power equipment is abnormal and meets the alarm conditions. At this time, the alarm process can be triggered: the communication transmission subunit 502 packages the real-time operating data and equipment identification of the power equipment into a standard data frame through its integrated communication interface and sends it to the remote monitoring center so that the monitoring personnel at the remote monitoring center can handle the abnormality of the power equipment in a timely manner.

[0099] The signal generation subunit 503 is used to generate alarm commands.

[0100] The alarm command is used to drive the alarm indicator light to flash.

[0101] It should be understood that when the real-time warning value is greater than or equal to the preset safety threshold, the signal generation subunit 503 can generate a digital or analog alarm command.

[0102] Optionally, the monitor 10 includes the alarm indicator light.

[0103] In this embodiment, the alarm function is modularized into three collaborative sub-units: threshold comparison, communication transmission, and signal generation, thus achieving a clearer, more professional, and more efficient alarm process. When alarm conditions are met, information is not only reported remotely but also provided with on-site early warning, improving the effectiveness of the alarm.

[0104] Combination Figure 1 As shown in Figure 6, in one implementation of this application embodiment, the multi-functional power equipment monitor further includes a human-machine interaction unit 104. The human-machine interaction unit 104 includes a display subunit and a parameter adjustment subunit. The display subunit is used to display the operating parameters and alarm information of the power equipment; the parameter adjustment subunit is used to adjust the preset safety threshold based on user operation.

[0105] Optionally, the display subunit can be a display screen, and the operating parameters can include real-time voltage, real-time current, real-time power, real-time warning value, etc.

[0106] Alternatively, the display screen can be a liquid crystal display (LCD).

[0107] Optionally, the parameter adjustment subunit can be a physical knob, button, or touchscreen interface.

[0108] In one alternative implementation, the display subunit may also have a data acquisition function, acquiring the filtered power signal and sending the filtered power signal to the data processing unit 102.

[0109] Specifically, the display subunit collects filtered power signals from the noise monitoring unit 101 based on a preset frequency, converts them into digital signals that can be processed and analyzed by the data processing unit 102, and then sends the digital signals to the data processing unit 102 in real time.

[0110] For example, the preset frequency can be once per second.

[0111] Optionally, the display subunit may include an analog-to-digital converter, which samples and quantizes the filtered power signal at a preset frequency.

[0112] In this embodiment, a human-machine interface unit is constructed by integrating display and parameter adjustment functions, which significantly improves the ease of use and adaptability of the monitor. The display subunit can provide users with real-time and intuitive equipment operating parameters and alarm information; the parameter adjustment subunit allows users to flexibly set preset safety thresholds according to actual site conditions and experience, enabling the monitor to adapt to the specific needs of different equipment or different operating stages, thereby improving the flexibility and personalized configuration capabilities of the equipment.

[0113] In one implementation of this embodiment, the display subunit and the parameter adjustment subunit are located on the interface panel. The human-computer interaction unit also includes the interface panel and the housing of the interface panel; the housing of the interface panel is a non-metallic transparent shell.

[0114] It should be understood that the display subunit and parameter adjustment subunit of the human-computer interaction unit are integrated and mounted on an interface panel. The housing of this interface panel is made of non-metallic materials (such as high-strength engineering plastics) and has transparent or translucent properties.

[0115] In this embodiment, the device not only achieves basic protection functions, but also cleverly solves the drawbacks of traditional metal shielding shells. Furthermore, its transparency allows users to directly observe the status of indicator lights installed inside or behind the panel, thus improving the maintainability and intuitiveness of the device.

[0116] In one implementation of this application, the human-computer interaction unit 104 further includes a liquid cooling radiator, which is used to dissipate heat from the inside of the system.

[0117] Understandably, this liquid-cooled heat sink is filled with coolant. It absorbs the heat generated by the data processing unit and other heat-generating components, and utilizes the circulating flow of the coolant to dissipate the heat over a larger heat dissipation surface, thus effectively maintaining the system's internal operating temperature within the permissible range. This active cooling method ensures the reliable operation of the monitor 10 in high-temperature or enclosed environments. This liquid-cooled heat sink can improve the stability and lifespan of the monitor 10's internal electronic components (especially the data processing unit 102) during long-term operation.

[0118] Optionally, the human-machine interface module also includes an RS485 interface, a universal serial bus (USB) interface, and an expansion interface. Based on the RS485 interface, the monitor 10 can transmit data to a remote monitoring center; based on the USB interface, field personnel can export data from the monitor; the physical form and communication protocol of the expansion interface can be customized or open, allowing users to add additional functions according to specific needs.

[0119] Figure 7 is a schematic diagram of the human-computer interaction unit 104.

[0120] As shown in Figure 7, the human-machine interaction unit 104 includes a display screen 701, an on / off button 702, an alarm indicator light 703, an adjustment knob 704, an interface panel 705, a transparent shell 706, a liquid cooling radiator 707, an RS485 interface 708, a USB interface 709, and an expansion interface 710.

[0121] Alternatively, the transparent housing 706 can be covered on the interface panel via a 180-degree hinge.

[0122] In summary, the multifunctional power equipment monitor with monitoring and alarm functions provided in this application eliminates the traditional noise-proof enclosure design in its structural design, replacing it with a filtering and conductive layer isolation method. This design makes the wire connections at the terminal blocks inside the monitor neater and more uniform, avoiding mutual interference problems caused by cross connections, thereby improving the accuracy of power data acquisition. At the same time, this design abandons the practice of multi-layered redundant protection on the enclosure, simplifying the overall structure and reducing unnecessary complexity. Furthermore, an integrated filter is installed on the terminal blocks inside the monitor, along with a weak current testing circuit. Using a small amount of monitoring data, the operating logic of the power equipment can be extracted without relying on complex integrated sensors or machine learning models. Due to the precision of the circuit operation, the data acquired by the testing circuit contains rich characteristics of the equipment's operation. By monitoring this data in real time, the operating status of the power equipment can be accurately assessed, thereby calculating the current operational risk detection value.

[0123] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0124] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A multi-functional power equipment monitor with monitoring and alarming functions, characterized by, The monitor comprises a noise-proof monitoring unit, a data processing unit and an alarm unit. The noise-proof monitoring unit is configured to perform filtering and noise suppression processing on the original power signal of the power equipment to obtain a filtered power signal. The data processing unit is configured to determine a variance and a periodicity parameter of the real-time operation data, the variance being used to represent a fluctuation range of the real-time operation data in a historical time period, the periodicity parameter being used to represent regularity of fluctuation of the real-time operation data, and the fluctuation abnormal value being used to represent a degree of disorder of the real-time operation data, the real-time operation data being the filtered power signal in the historical time period, and the periodicity parameter being an amplitude of a first significant peak in an autocorrelation function of the real-time operation data except for zero delay. The fluctuation abnormal value is determined based on the variance and the periodicity parameter. A plurality of complete periods included in the real-time operation data are identified. A data set corresponding to each complete period is determined, and the data set corresponding to one complete period is a data set constructed by a preset number of power data after fluctuation of the complete period. The fluctuation abnormal influence coefficient is determined based on absolute values of differences between adjacent data in each data set corresponding to each complete period and occurrence probabilities of each data in each data set, and the fluctuation abnormal influence coefficient is used to represent an adaptive recovery capability of the power equipment to data fluctuation. The data processing unit is further configured to determine a real-time early warning value based on the fluctuation abnormal value and the fluctuation abnormal influence coefficient. The alarm unit is configured to issue an alarm in a case where the real-time early warning value is greater than or equal to a preset safety threshold.

2. The multi-functional electric power equipment monitor with monitoring and alarming functions according to claim 1, characterized in that, The noise-proof monitoring unit comprises a plurality of wiring terminals, and the plurality of wiring terminals are arranged in a scattered manner with a preset interval between adjacent wiring terminals.

3. The multi-functional electric power equipment monitor with monitoring and alarming functions according to claim 2, characterized in that, The noise-proof monitoring unit comprises a plurality of integrated filters and a grounding port. The plurality of integrated filters are configured to filter high-frequency electromagnetic interference in the original power signal. The grounding port is configured to ground the wiring terminals to eliminate low-frequency noise in a circuit.

4. The multi-functional electric power equipment monitor with monitoring and alarming functions according to claim 3, characterized in that, The noise-proof monitoring unit further comprises a backup battery. The backup battery is configured to provide working current for the plurality of integrated filters.

5. The multi-functional electric power equipment monitor with monitoring and alarming functions according to claim 1, characterized in that, The alarm unit comprises a threshold comparison subunit, a communication transmission subunit and a signal generation subunit. The threshold comparison subunit is configured to compare a size relationship between the real-time early warning value and the preset safety threshold. The communication transmission subunit is configured to send the real-time operation data to a remote monitoring center when the real-time early warning value is greater than or equal to the preset safety threshold. The signal generation subunit is configured to generate an alarm instruction, and the alarm instruction is used to drive an alarm indicator light to flicker.

6. The multi-functional electric power equipment monitor with monitoring and alarming functions according to claim 1, characterized in that, The multifunctional power equipment monitor further comprises a human-computer interaction unit. The human-computer interaction unit comprises a display subunit and a parameter adjustment subunit. The display subunit is configured to display operation parameters and alarm information of the power equipment. The parameter adjustment subunit is configured to adjust the preset safety threshold based on user operation.

7. The multi-functional electric power equipment monitor with monitoring and alarming functions according to claim 6, characterized in that, The display subunit and the parameter adjustment subunit are located on the interface panel, and the human-computer interaction unit further comprises the interface panel and a shell of the interface panel. The shell of the interface panel is a non-metal transparent shell.

8. The multi-functional electric power equipment monitor with monitoring and alarming functions according to claim 6, characterized in that, The human-computer interaction unit further comprises a liquid cooling radiator for heat dissipation treatment of the inside of the system.

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