CN117092437A - LED display device for monitoring health state of transformer in power grid - Google Patents
LED display device for monitoring health state of transformer in power grid Download PDFInfo
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Abstract
The application relates to an LED display device for monitoring the health state of a transformer in a power grid. The device mainly comprises the following parts: the transformer health monitoring module is used for collecting real-time parameters such as temperature, vibration, load, oil temperature, impurities in oil and the like of a transformer in a power grid; the health evaluation algorithm module calculates the health index of each transformer through a specific algorithm according to the collected real-time parameters; the position-related image generation module is used for generating a position-related image according to the actual position of the transformer in the power grid and the upstream-downstream relationship between the actual position and the upstream-downstream relationship; and the transformer health state display module is used for displaying the image combination generated by the health index and position related image generation module calculated by the health evaluation algorithm module on the LED display screen. The structure allows the power grid operators to know the health condition of the transformer timely and accurately, and clearly know the topological structure of the power grid through visual image representation, so that more effective operation and maintenance management are realized.
Description
Technical Field
The application relates to the technical field of monitoring and displaying of power systems, in particular to an LED display device for monitoring the health state of a transformer in a power grid.
Background
With modern power grids becoming increasingly complex and interconnected, real-time monitoring and analysis of transformers is becoming increasingly important. Particularly, in advanced power grid systems such as smart power grids, the health condition of the transformer has higher requirements. This requires more complex data analysis and visualization tools in order for the grid operators to quickly and accurately understand the health of the transformer and to take necessary maintenance measures in time.
Existing transformer monitoring systems often fail to adequately meet these needs because they may lack comprehensive monitoring of the transformer, may fail to effectively relate health to the topology of the power grid, or may fail to provide a sufficiently intuitive visual representation. In addition, existing monitoring systems often cannot effectively fuse different types of data, such as temperature, vibration, load, etc., which may lead to erroneous determinations of the health of the transformer.
Therefore, there is an urgent need to monitor the transformers in the power grid comprehensively and in real time, and display the health condition and the positional relationship thereof in an intuitive and organized manner.
Disclosure of Invention
The application provides an LED display device for monitoring the health state of a transformer in a power grid, so as to improve the operation and management efficiency of the power grid.
The application provides an LED display device for monitoring the health state of a transformer in a power grid, which comprises:
the transformer health monitoring module is used for collecting real-time parameters such as temperature, vibration, load, oil temperature, impurities in oil and the like of a transformer in a power grid;
the health assessment algorithm module calculates the health index H for each transformer by the following formula:
；
wherein T is temperature, V is vibration, L is load, T 0 Is the oil temperature, P is the pressure, X is the amount of impurities in the oil, X max Is the maximum threshold value of impurities in oil, and alpha, beta, gamma, delta, epsilon and zeta are preset parameters;
the position-related image generation module is used for generating an LED display image corresponding to an actual power grid topological structure according to the actual position of the transformer in the power grid and the upstream-downstream relation between the actual position and the actual position;
and the transformer health state display module is used for displaying the health index calculated by the health evaluation algorithm module and the image generated by the position-related image generation module on an LED display screen in a combined mode.
Still further, the position-related image generation module is further configured to:
determining the position of the transformer on the LED display screen by using a force guiding algorithm, wherein the expression of the force guiding algorithm is as follows:
；
wherein,is the force between transformers i and j, < >>Is the distance of transformers i and j on the LED display screen, < >>Is the ideal distance of transformers i and j on the LED display screen, k is the spring constant.
Further, the ideal distance between the transformers i and j on the LED display screenThe calculation can be performed by the following formula:
；
wherein,is the actual physical distance between transformers i and j; />Is the connection length between transformers i and j; />For the complexity of the connection between transformers i and j; />The importance of power transfer between transformers i and j; w1, w2, w3 and w4 are preset parameters.
Still further, the position-related image generation module further includes a color modulation unit for assigning a different color to each transformer on the LED display screen according to the health index.
Still further, the color modulation unit includes:
the color modulation module calculates the display color of the transformer by adopting the following formula:
；
wherein C is the final color value, S is the health index, G is the real-time parameter of the transformer, R is the preset primary color,is a preset parameter.
Still further, the color modulation unit further includes:
and the color conversion module is used for converting the calculated color C into a specific color of RGB or other color space.
Still further, the health evaluation algorithm module further includes a threshold judgment unit, configured to classify the health index of each transformer into a level of good, bad, medium, bad, etc. according to a preset health status threshold.
Further, the health evaluation algorithm module further comprises a dynamic parameter adjustment unit; the dynamic parameter adjusting unit dynamically adjusts preset parameters used in calculating the health index according to the health index trend in a period of time.
Further, the transformer health monitoring module further comprises an abnormality alarm unit; the abnormal alarm unit is used for triggering an alarm signal when the health index of a certain transformer is lower than a preset abnormal threshold value.
Further, the transformer health status display module further comprises a data storage unit; the data storage unit is used for storing historical health index data so as to carry out long-term trend analysis and backup.
The LED display device for monitoring the health state of the transformer in the power grid provided by the application is used for collecting real-time parameters such as temperature, vibration, load, oil temperature, impurities in oil and the like. The device adopts a complex calculation method and combines a plurality of preset parameters, so that the calculation of the health index is more accurate and representative. The device converts the actual position of the transformer in the power grid and the upstream-downstream relation between the actual position and the downstream relation into the LED display image, so that the visual display of the power grid topological structure is realized.
The beneficial technical effects of the application mainly comprise: the device provided by the application can monitor and evaluate the health state of the transformer in real time, and greatly reduces the requirement of manual inspection and the time cost. By comprehensively analyzing a plurality of real-time parameters and historical data, the device can more accurately diagnose the health condition of the transformer, so that necessary measures can be taken in time. Through real-time monitoring and timely alarming, the device is beneficial to preventing and timely processing potential problems, so that the reliable operation of the whole power grid is ensured.
Drawings
Fig. 1 is a schematic diagram of an LED display device for monitoring the health status of a transformer in a power grid according to a first embodiment of the present application.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. The present application may be embodied in many other forms than those herein described, and those skilled in the art will readily appreciate that the present application may be similarly embodied without departing from the spirit or essential characteristics thereof, and therefore the present application is not limited to the specific embodiments disclosed below.
The first embodiment of the application provides an LED display device for monitoring the health state of a transformer in a power grid. Referring to fig. 1, a schematic diagram of a first embodiment of the present application is shown. A first embodiment of the present application is described in detail below with reference to fig. 1, which provides an LED display device for monitoring the health status of a transformer in a power grid.
The LED display device comprises a transformer health monitoring module 101, a health evaluation algorithm module 102, a position correlation image generation module 103 and a transformer health state display module 104.
The transformer health monitoring module 101 is used for collecting real-time parameters such as temperature, vibration, load, oil temperature, impurities in oil and the like of a transformer in a power grid.
The transformer health monitoring module is a complex and precise system for collecting real-time parameters of transformers in the power grid, such as temperature, vibration, load, oil temperature and impurities in the oil.
In order to measure temperature, this embodiment uses a high-precision thermocouple sensor mounted on a critical hot spot of the transformer. These sensors operate by exploiting the linear relationship between the temperature and resistance of the material and automatically calibrate the readings as the ambient temperature changes through a real-time temperature compensation algorithm.
Vibration monitoring is achieved by means of a high-sensitivity accelerometer mounted on the transformer housing. These devices are capable of detecting the frequency and amplitude of vibration of the transformer housing for evaluating the integrity of the internal mechanical structure. The present embodiment also employs an adaptive filtering technique to eliminate vibration disturbances of the external environment.
The monitoring of the load is done by means of current transformers, which are mounted on the input and output lines of the transformer. These devices can continuously monitor the input and output currents to calculate the real-time load. The embodiment also analyzes the current waveform in real time to detect unbalanced load and harmonic content, thereby providing basis for optimizing the operation of the power grid.
The monitoring of oil temperature and impurities in oil uses a specially designed oil temperature sensor and an impurity analysis device. These devices detect moisture, gases and impurities in the oil by spectroscopic analysis or chemical sensors. The embodiment adopts an online real-time analysis technology, so that the state of oil can be monitored under the condition of no shutdown.
Finally, the data of all these monitoring units are integrated and transmitted to a central control and display system by wired or wireless communication. This embodiment also introduces advanced encryption and authentication techniques to ensure data integrity and security.
Further, the transformer health monitoring module further comprises an abnormality alarm unit; the abnormal alarm unit is used for triggering an alarm signal when the health index of a certain transformer is lower than a preset abnormal threshold value.
Besides the core function, an abnormality alarm unit is added to the transformer health monitoring module in the LED display device. The task of this unit is to monitor the health index of the transformer in real time and trigger an alarm signal when the health index is below a preset abnormal threshold. The following is a detailed description of the abnormality warning unit.
First, the anomaly alarm unit cooperates closely with other system components (e.g., health assessment algorithm modules) to obtain the health index of the transformer. The health index may be calculated based on a number of factors (e.g., temperature, oil quality, vibration, etc.), and may dynamically change over a period of time.
Then, the abnormality alert unit will compare with a preset abnormality threshold. This threshold is a critical parameter that can be set according to the actual need and risk level. When the health index is below the threshold, it indicates that the transformer may have serious problems or risk of failure.
Upon detecting that the health index is below an abnormality threshold, the abnormality alert unit will trigger an alert signal. This may involve a number of steps and components:
(1) Generating an alarm signal: may be visual, audible or other types of signals, and may even be a set of composite signals.
(2) Alarm transmission: the alarm signal may be transmitted through different communication channels, for example, through a short message, an email, application push, etc., to a mobile phone or a computer of the relevant person.
(3) Logging and analysis: the anomaly alarm unit may also include the functionality to record and analyze alarm events. This may help diagnose problems, analyze trends, and possibly facilitate future predictions and precautions.
(4) Emergency response integration: in some application scenarios, the anomaly alarm unit may also be integrated with an emergency response system, such as automatically shutting down power or activating a rescue procedure.
The abnormality alarming unit enhances the reliability and safety of the whole system through real-time monitoring and timely alarming.
In general, the transformer health monitoring module 101 implements real-time monitoring of key parameters of the transformer through a series of advanced technologies and methods, not only providing accurate assessment of health conditions thereof, but also ensuring safe and stable operation of modern smart grids.
The health assessment algorithm module calculates the health index H for each transformer by the following formula:
；
wherein T is temperature, V is vibration, L is load, T 0 Is the oil temperature, P is the pressure, X is the amount of impurities in the oil, X max Is the maximum threshold value of impurities in oil, and alpha, beta, gamma, delta, epsilon and zeta are preset parameters.
The core of the health evaluation algorithm module is a mathematical model specially designed for transformers. The model aims to quantify the health of the transformer by a series of key parameters such as temperature (T), vibration (V), load (L), oil temperature (T0), pressure (P) and the amount of impurities in the oil (X).
Formula (VI)；
For calculating the health index H of each transformer. This formula is based on physical and engineering principles, as well as a number of field tests and simulation analyses.
Part represents the temperature versus health indexInfluence. Temperature is generally related to internal losses and efficiency of the transformer. This index is an exponential decay function reflecting the rate of decrease of the health index as the temperature increases.
Part represents the effect of vibration on the health index. Vibration may mean mechanical failure, the logarithmic relationship of which reflects the increasing negative impact of vibration on the health index.
The delta and L portions reflect the linear effect of load on the health index. Excessive loading can lead to overheating and mechanical stress, reducing the life of the transformer.
The oil health is quantified in part by combining the oil temperature and pressure. This ratio can reflect the viscosity and fluidity of the oil and is a key indicator of the cooling efficiency of the transformer.
Partially shutting off the amount of impurities in the oil, and the maximum threshold X of impurities in the oil max In comparison with the prior art. This ratio indicates the degree of contamination of the oil and is closely related to the insulation and cooling efficiency.
The parameters α, β, γ, δ, ε, ζ are preset and can be adjusted according to the specific transformer type and operating conditions. These parameters are determined through extensive research and extensive field tests, ensuring that the formula accurately reflects the health conditions under various conditions.
Still further, the health evaluation algorithm module further includes a threshold judgment unit, configured to classify the health index of each transformer into a level of good, bad, medium, bad, etc. according to a preset health status threshold.
The threshold value judging unit is a key component for classifying the health index of each transformer into different grades, such as excellent, good, medium and bad, according to a preset health state threshold value. The unit can help operators to quickly know the operation condition of the transformer and take corresponding measures.
First, the threshold judgment unit needs to receive the health index of the transformer as an input. These indices may be calculated from a combination of various parameters, such as temperature, vibration, oil quality, etc. At the same time, the unit needs to know preset health status thresholds, which can be fixed or dynamically adjusted by expert systems or artificial intelligence algorithms.
After receiving these inputs, the threshold judgment unit will perform a series of processes. First, it will compare with a preset threshold to determine to which class the health index belongs. Then, the health index is assigned to the corresponding grade according to the comparison result. In addition, fault tolerant processing may be required, such as special processing of abnormal or missing health indices, such as interpolation, warning, or error reporting.
The output of the threshold judgment unit is the health level of each transformer. These levels may be used for further processing or direct display.
The threshold judgment unit may be realized by hardware or software. The hardware implementation may employ a dedicated processing chip or programmable logic device, while the software implementation may run on a general purpose computer or embedded system.
The health evaluation algorithm module further comprises a dynamic parameter adjustment unit; the dynamic parameter adjusting unit dynamically adjusts preset parameters used in calculating the health index according to the health index trend in a period of time.
The dynamic parameter adjusting unit is a part of the health evaluation algorithm module of the LED display device. The core task of the unit is to dynamically adjust preset parameters used in calculating the health index according to the health index trend in the past period of time.
The dynamic parameter adjustment unit first collects health index data of the transformer over a period of time. Such data may be obtained from various sensors and monitoring systems and may cover various parameters related to the health of the transformer, such as temperature, oil quality, vibration, etc.
Next, the dynamic parameter adjustment unit will analyze the trend of these historical health index data. This may involve identifying the rising or falling, periodic variation, etc., of the health index using statistical methods, machine learning algorithms, or other advanced techniques.
Based on the results of the trend analysis, the dynamic parameter adjustment unit will determine how to adjust the preset parameters used in calculating the health index. For example, if the trend shows a continuous decrease in the health index, it may be necessary to increase the weight of certain parameters in order to more sensitively reflect this decreasing trend.
Finally, the dynamic parameter adjusting unit adjusts the preset parameters. This may involve directly modifying parameter values, adjusting parameter calculation formulas, or other operations.
The health assessment algorithm module 101 utilizes an innovative and comprehensive formula that combines a plurality of key parameters of the transformer to quantitatively assess its health. By the method, the state of the transformer can be monitored in real time, potential faults and maintenance requirements can be predicted, and therefore intelligent and reliable power grid operation is achieved.
The position-related image generating module 103 is configured to generate an LED display image corresponding to an actual power grid topology according to an actual position of the transformer in the power grid and an upstream-downstream relationship between the actual position and the power grid.
In order to accurately represent the spatial structure of the power grid on the LED display screen, a special spatial layout algorithm may be employed. The algorithm may determine the location of each transformer on the display screen by modeling the interaction between electromagnetic and gravitational forces based on a force directed graph algorithm. Specifically, the following formula may be used:
(equation 1);
wherein,is the force between transformers i and j, < >>Is the distance of transformers i and j on the LED display,is the ideal distance of transformers i and j on the LED display screen, k is the spring constant.
The present embodiment provides a method for determining an ideal distance. Let the ideal distance between transformers i and j beThe calculation can be performed by the following formula:
；
wherein,is the actual physical distance between transformers i and j; />Is the length of connection between transformers i and j, which is related to the number or type of cables or wires connected; />For the complexity of the connection between transformers i and j, it can be evaluated based on the type and number of connections between them; />For the importance of power transfer between transformers i and j, it may be adjusted to reflect the relative importance of the different factors, as the case may be. w1, w2, w3 and w4 are preset parameters.
This formula provides a flexible and comprehensive way to reflect the actual situation of the grid by combining a number of factors to calculate the ideal distance. The weighting factors can be adjusted according to specific application requirements, so that the algorithm can be flexibly applied in different situations.
The spatial layout algorithm is illustrated below. Assume a simple grid topology, comprising three transformers T1, T2 and T3, and connected as follows: t1 is connected with T2, and T2 is connected with T3.
To start the algorithm, each transformer needs to be assigned an initial position on the LED display screen. This may be random or selected according to some logic. Assume that the initial coordinates of the LED display screen are as follows:
T1： （x1，y1）= （10，10）；
T2： （x2，y2）= （20，20）；
T3： （x1，y1）= （10，30）；
step S1001, calculation of force:
the distance of the transformers T1 and T2 on the LED display screen is calculated by the Euclidean distance formula:
；
then willWith the equation 1, the force F can be obtained 12 。
Step S1002, position update:
the calculated force is used to update the position of each transformer. For example, the new position of T1 may be calculated by:
；
；
step S1001 and step S1002 are then repeated until the positions of all transformers on the LED display screen are stabilized. And determining the stabilized position as the final position of the transformer on the LED display screen.
In this embodiment, the force steering algorithm is used as a visualization tool, particularly suited for graphical representations of complex network structures. The function of this algorithm is as follows:
the force steering algorithm may bring connected nodes close to each other while keeping unconnected nodes at a distance, thereby generating a natural and easily understood layout.
By simulating physical force, the algorithm can reduce the overlapping and crossing of nodes and connecting wires and improve the readability of the graph.
By adjusting parameters such as ideal distance, spring constant, etc., different visualization effects can be achieved that better meet specific requirements and constraints.
If the topology of the grid changes, the force steering algorithm can be easily updated to reflect these changes.
By properly adjusting the parameters of the force directing algorithm, transformers and connections in the grid can be highlighted, thus making critical components more prominent.
In general, the purpose of the force-directed algorithm is to generate a visual and accurate representation of the topology of the power grid on the LED display screen, which more closely conforms to the visual habits of people, and at the same time, more easily identifies and understands important information in the power grid.
Still further, the position-related image generation module further includes a color modulation unit for assigning a different color to each transformer on the LED display screen according to the health index.
The color modulation unit is used for distributing different colors to each transformer on the LED display screen according to the health state and the like. This step visualizes the health of the transformer, enabling the operator to quickly identify potential problems. The health index is derived by the health assessment algorithm module 102, which may classify the health of the transformer into a number of classes, such as good, bad, medium, bad, etc.
Each transformer on the LED display is assigned a different color according to the health index. For example, a transformer with good health may appear green, while a transformer with poor health may appear red.
Still further, the color modulation unit includes:
the color modulation module calculates the display color of the transformer by adopting the following formula:
；
wherein, C is the final color value of the transformer; s is the health index of the transformer; g is the real-time parameter of the transformer, and can be the real-time parameter of the transformer such as temperature, vibration, load and the like; r is a preset primary color, and can be a common basic color such as red, green, blue and the like;the preset parameters may be obtained through experiments or experience to adjust the accuracy and sensitivity of the color representation.
And the color conversion module is used for converting the calculated color C into a specific color of RGB or other color space. The function of this module is to convert the calculated color value C into a specific color of RGB or other color space. Since the calculated color value may be an abstract value, it needs to be converted into the actual color that can be presented by the display device. This may be achieved by a look-up table, interpolation method or other color space conversion algorithm. For example, standard color model conversion methods may be used, or a display device specific color calibration method may be used.
Finally, the location-related image generation module 102 uses the coordinates calculated by the algorithm described above to generate an LED display image corresponding to the actual grid topology. Including the connection lines between the transformers and possibly other elements, such as flow arrows, etc.
And the transformer health state display module 104 is configured to display the health index calculated by the health evaluation algorithm module and the image generated by the position-related image generation module on an LED display screen in a combined manner.
The transformer health status display module 104 is a core output part of the whole LED display device, and is responsible for displaying the health index calculated by the health evaluation algorithm module and the image combination generated by the position-related image generation module on the LED display screen. The following is a detailed description of the components and operation of the module:
the health index representation may be implemented as follows:
(1) Numerical value represents: the health index is displayed as a numerical value and may be displayed in digital form near an icon for each transformer.
(2) Graphical representation: the health index can also be represented by graphs such as bar graphs, radar graphs and the like, so that the information is visual and easy to understand.
(3) Color representation: by the color modulation unit, the health state is mapped to the color, and the health condition is more intuitively represented.
The combined display technique may be implemented as follows:
(1) Lamination layout: by overlaying the health index and the location-related image together, a combined display is achieved. The visibility and importance of the layers may be adjusted by attributes such as transparency, size, etc.
(2) Adaptive interface: according to the requirements of users and the size of the display screen, the layout and the size of the images and the texts are automatically adjusted, so that the images and the texts are ensured to be clear and readable.
The embodiment can use a high-resolution LED display screen to ensure clear images. Meanwhile, the brightness can be automatically adjusted according to the ambient light, so that the visibility is improved and the energy is saved.
Still further, the transformer health status display module 104 further includes a data storage unit; the data storage unit is used for storing historical health index data so as to carry out long-term trend analysis and backup.
The main purpose of the data storage unit is to store historical health index data of the transformer. These data can be used for long-term trend analysis to detect and predict performance degradation, life and possible failure of the transformer. In addition, the stored data may also be used as a backup for recovery in the event of a system failure or data loss.
The data storage unit may employ different types of storage media, such as hard disks, solid state drives, cloud storage, and the like. The storage medium selected will depend on factors such as capacity required, access speed, reliability and cost. The stored health index data may be in different formats and structures, such as a relational database, a time series database, or a custom file format. The design of the data structure should take into account ease of use, efficiency and compatibility. The data storage unit should include suitable security measures, such as encryption, access control, etc., to protect the data from unauthorized access. Furthermore, integrity checking and error correction mechanisms may also be required to ensure accuracy and reliability of the data.
By storing historical health index data, the data storage unit supports the use of long-term trend analysis. This may include using statistical analysis, machine learning, etc. techniques to detect and predict the behavior and performance of the transformer. Such analysis may be used for maintenance planning, fault prevention, life assessment, etc.
In general, the transformer health status display module 104 is not only responsible for displaying key information on the LED screen in combination, but also can employ various embodiments, so that the presentation of information is beautiful and practical, and can adapt to different usage scenarios and user requirements. The module integrates the health evaluation and the position related information deeply, provides a powerful and visual tool for power grid monitoring personnel, and is beneficial to more effectively managing and maintaining the power grid.
While the application has been described in terms of preferred embodiments, it is not intended to be limiting, but rather, it will be apparent to those skilled in the art that various changes and modifications can be made herein without departing from the spirit and scope of the application as defined by the appended claims.
Claims (10)
1. An LED display device for monitoring the health status of a transformer in a power grid, comprising:
the transformer health monitoring module is used for collecting real-time parameters such as temperature, vibration, load, oil temperature, impurities in oil and the like of a transformer in a power grid;
the health assessment algorithm module calculates the health index H for each transformer by the following formula:
；
wherein T is temperature, V is vibration, L is load, T 0 Is the oil temperature, P is the pressure, X is the amount of impurities in the oil, X max Is the maximum threshold value of impurities in oil, and alpha, beta, gamma, delta, epsilon and zeta are preset parameters;
the position-related image generation module is used for generating an LED display image corresponding to an actual power grid topological structure according to the actual position of the transformer in the power grid and the upstream-downstream relation between the actual position and the actual position;
and the transformer health state display module is used for displaying the health index calculated by the health evaluation algorithm module and the image generated by the position-related image generation module on an LED display screen in a combined mode.
2. The LED display device of claim 1, wherein the position-related image generation module is further configured to:
determining the position of the transformer on the LED display screen by using a force guiding algorithm, wherein the expression of the force guiding algorithm is as follows:
；
wherein,is the force between transformers i and j, < >>Is the distance of transformers i and j on the LED display screen, < >>Is the ideal distance of transformers i and j on the LED display screen, k is the spring constant.
3. The LED display device of claim 2, wherein the transformers i and j are at a desired distance on the LED display screenThe calculation can be performed by the following formula:
；
wherein,is the actual physical distance between transformers i and j; />Is the connection length between transformers i and j; />For the complexity of the connection between transformers i and j; />The importance of power transfer between transformers i and j; w1, w2, w3 and w4 are preset parameters.
4. The LED display device of claim 1, wherein the location-dependent image generation module further comprises a color modulation unit for assigning a different color to each transformer on the LED display screen based on the health index.
5. The LED display device of claim 4, wherein the color modulation unit comprises:
the color modulation module calculates the display color of the transformer by adopting the following formula:
；
wherein C is the final color value, S is the health index, G is the real-time parameter of the transformer, R is the preset primary color,is a preset parameter.
6. The LED display device of claim 5, wherein the color modulation unit further comprises:
and the color conversion module is used for converting the calculated color C into a specific color of RGB or other color space.
7. The LED display device of claim 1, wherein the health assessment algorithm module further comprises a threshold determination unit for classifying the health index of each transformer as excellent, good, medium, bad, etc. according to a preset health status threshold.
8. The LED display device of claim 1, wherein the health assessment algorithm module further comprises a dynamic parameter adjustment unit; the dynamic parameter adjusting unit dynamically adjusts preset parameters used in calculating the health index according to the health index trend in a period of time.
9. The LED display device of claim 1, wherein the transformer health monitoring module further comprises an anomaly alarm unit; the abnormal alarm unit is used for triggering an alarm signal when the health index of the transformer is lower than a preset abnormal threshold value.
10. The LED display device of claim 1, wherein the transformer health status display module further comprises a data storage unit; the data storage unit is used for storing historical health index data so as to carry out long-term trend analysis and backup.
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