Maintenance-free intelligent moisture absorber and method and system for online prediction of remaining service life of moisture absorber

Abstract

This invention discloses an online prediction method and system for the remaining lifespan of desiccant in a maintenance-free intelligent desiccant, belonging to the field of power equipment condition monitoring and predictive maintenance technology. This method fully utilizes the built-in temperature and humidity sensors of the maintenance-free desiccant to obtain the average regeneration temperature and average humidity load for each desiccant-regeneration cycle. By calculating the damage fraction caused by a single cycle and accumulating these values, the cumulative damage degree is obtained, ultimately achieving a quantitative and online prediction of the remaining lifespan of the desiccant. This method solves the problem of inaccurate maintenance caused by traditional desiccant replacement relying on fixed cycles or experience-based judgment, realizing a shift from preventative maintenance to predictive maintenance, improving equipment reliability and reducing maintenance costs.

Description

Technical Field

[0001] This invention relates to the field of online monitoring and intelligent operation and maintenance technology for power equipment, specifically to an online prediction method for the remaining lifespan of the desiccant in a maintenance-free intelligent desiccant. Background Technology

[0002] Intelligent desiccant (also known as maintenance-free desiccant) is installed at the end of the connecting pipe extending from the oil tank. When the oil inside the transformer tank deforms due to thermal expansion and contraction, this device removes moisture from the drawn-in air, making it a key accessory for ensuring the dryness of the insulating oil inside oil-immersed power equipment. Compared to traditional color-changing silica gel desiccant desiccant desorbs moisture through periodic or triggered heating cycles, achieving automatic regeneration and significantly extending maintenance intervals.

[0003] However, the lifespan of desiccant itself is not infinite. In repeated cycles of "moisture absorption-heat regeneration," the desiccant gradually ages due to factors such as thermal stress, repeated phase transitions, and microstructural fatigue, eventually causing its adsorption capacity to irreversibly decrease to failure levels. Currently, there are two major challenges in managing the lifespan of smart desiccant: first, the lack of effective online monitoring methods means users cannot know the actual health status of the desiccant; second, the blind maintenance strategy, typically employing a fixed time period (e.g., 3-5 years) for complete replacement. This one-size-fits-all approach may lead to two consequences: the desiccant is replaced before it expires, resulting in resource waste; or the desiccant has expired but has not been replaced in time, endangering the insulation of the main equipment.

[0004] In existing technologies, a few high-end desiccant units have a simple cycle count function, but they only accumulate the number of mechanical cycles and do not consider the different aging damage caused by differences in ambient temperature, humidity, and regeneration heating intensity between different cycles. A single high-intensity regeneration cycle in a hot and humid season has a different impact on the desiccant's lifespan than a single cycle in a dry and mild season. Therefore, simple cycle counting cannot reflect the true lifespan loss, and the prediction results are extremely inaccurate.

[0005] Therefore, there is an urgent need for an intelligent prediction method that can accurately quantify the actual damage in each regeneration cycle and calculate the remaining lifespan online. Summary of the Invention

[0006] The technical problem this invention aims to solve is to overcome the issues of blind and inaccurate lifespan management in existing intelligent desiccant systems, and to provide a method and device for accurately predicting the remaining lifespan of the desiccant based on cumulative damage theory and implemented online. This method fully utilizes the desiccant's built-in sensors and, through an innovative mathematical model, transforms operating data into quantitative indicators of lifespan loss.

[0007] In a first aspect, the present invention provides an online method for predicting the remaining lifespan of the desiccant in a maintenance-free intelligent desiccant, comprising:

[0008] S1: Collect and record key parameters for each complete moisture absorption and regeneration cycle of the dehumidifier, including the average regeneration temperature of that cycle. and the average relative humidity inside the drying drum during the moisture absorption cycle ;

[0009] S2: Based on the collected parameters and according to the preset lifespan prediction model, update the cumulative damage of the desiccant. ;

[0010] S3: Calculate the remaining lifespan ratio of the desiccant based on the calculated cumulative damage. ;

[0011] S4: The remaining lifespan ratio Compared with the preset alarm threshold If a comparison is made, Less than the lifespan threshold If this occurs, a desiccant replacement warning will be generated.

[0012] Optionally, in step S2, the cumulative damage degree of the desiccant is calculated as follows:

[0013] ;

[0014] in, The first one representing the desiccant Secondary regeneration cycle ( =1, 2, 3...); This represents the number of effective regeneration cycles that have been completed.

[0015] Damage caused by a single cycle The calculation formula is as follows:

[0016] ;

[0017] in, To ensure the safety of the desiccant, the maximum permissible regeneration temperature is designed. This represents the saturated moisture absorption capacity of the desiccant. This represents the theoretical regeneration cycle life of the desiccant under reference conditions, where the reference conditions are the rated temperature. saturated humidity , For the first The actual average regeneration temperature K of each cycle For the first The average relative humidity inside the secondary cycle drying drum , These are material property indices that characterize the sensitivity of the desiccant's lifespan to regeneration temperature and humidity load.

[0018] Optionally, in step S3, the remaining lifespan of the desiccant is compared to... The calculation method is as follows:

[0019] .

[0020] Optionally, the parameters , , , , These are fixed parameters that are pre-calibrated and stored in the desiccant control unit for accelerated aging experiments using desiccants.

[0021] Optionally, in step S4, the data obtained from the calculation is processed as follows:

[0022] The remaining lifespan ratio of the desiccant is calculated based on data collected by the temperature and humidity sensors in the maintenance-free smart desiccant. This remaining lifespan ratio is then compared with a preset alarm threshold. Compare them.

[0023] Secondly, the present invention provides an online prediction system for the remaining life of intelligent desiccant based on the theory of cumulative damage, comprising:

[0024] The data acquisition module is used to collect and record key parameters of each complete moisture absorption and regeneration cycle of the dehumidifier, including the average regeneration temperature of that cycle. and the average relative humidity inside the drying drum during the moisture absorption cycle ;

[0025] The calculation and processing module updates the cumulative damage of the desiccant based on the collected parameters and according to the preset lifespan prediction model. Based on the calculated cumulative damage, the remaining lifespan ratio of the desiccant is calculated. ;

[0026] The diagnostic output module is used to output the remaining life ratio. Compared with the preset alarm threshold If a comparison is made, Less than the lifespan threshold If this occurs, a desiccant replacement warning will be generated.

[0027] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the method as described in any one of the first aspects. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the accompanying drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below:

[0029] Figure 1 This is a flowchart illustrating an online method for predicting the remaining lifespan of the desiccant in a maintenance-free smart desiccant, as described in one embodiment.

[0030] Figure 2 This is a schematic diagram of the internal structure of a computer device provided in an exemplary embodiment. The computer device may be a server.

[0031] Figure 3 A schematic diagram showing the installation location of a maintenance-free smart dehumidifier and its internal temperature and humidity sensors. Detailed Implementation

[0032] The present invention will be further described in detail below with reference to specific embodiments and accompanying drawings. It should be emphasized that the specific embodiments described herein are intended to explain the present invention and should not be construed as limiting the present invention.

[0033] Example 1

[0034] Embodiment 1 of this invention discloses an online prediction method for the remaining lifespan of the desiccant in a maintenance-free intelligent desiccant, such as... Figures 1 to 3 As shown, this method can be applied in actual field situations. The method in Embodiment 1 of this invention includes the following steps:

[0035] Step S1: Collect and record key parameters for each complete moisture absorption and regeneration cycle of the dehumidifier, including the average regeneration temperature of that cycle. and the average relative humidity inside the drying drum during the moisture absorption cycle .

[0036] Specifically, this step includes the following process:

[0037] 1. The average temperature inside the drying drum during the regeneration stage is collected by a built-in temperature sensor. .

[0038] 2. The average relative humidity inside the drying drum during the moisture absorption stage is collected using a humidity sensor. .

[0039] 3. The data is recorded and stored in real time by the microprocessor built into the dehumidifier.

[0040] Step S2: Based on the collected parameters, update the cumulative damage of the desiccant according to the preset lifetime prediction model. .

[0041] In this embodiment of the invention, the method for calculating the cumulative damage of the desiccant in step S2 is as follows:

[0042] ;

[0043] in, The first one representing the desiccant Secondary regeneration cycle ( =1, 2, 3...); This represents the number of effective regeneration cycles that have been completed.

[0044] Damage caused by a single cycle The calculation formula is as follows:

[0045] ;

[0046] in, To ensure the safety of the desiccant, the maximum permissible regeneration temperature is designed. This represents the saturated moisture absorption capacity of the desiccant. This represents the theoretical regeneration cycle life of the desiccant under reference conditions, where the reference conditions are the rated temperature. saturated humidity , For the first The actual average regeneration temperature K of each cycle For the first The average relative humidity inside the secondary cycle drying drum , These are material property indices characterizing the sensitivity of the desiccant's lifespan to regeneration temperature and humidity load (when the desiccant is silica gel). Take 1.3, Take 1.0; for other types of desiccants, the value can be determined through accelerated aging tests.

[0047] In this embodiment of the invention, parameters , , , , These are fixed parameters that are pre-calibrated and stored in the desiccant control unit for accelerated aging experiments using desiccants.

[0048] Step S3: Calculate the remaining lifespan ratio of the desiccant based on the calculated cumulative damage. ;

[0049] The remaining lifespan of the desiccant is higher than The calculation method is as follows:

[0050] .

[0051] Specifically, this step includes the following process:

[0052] 1. Calculate the damage to the desiccant caused by a single cycle. .

[0053] 2. Update the cumulative damage level of the desiccant. .

[0054] 3. Calculate the remaining lifetime ratio .

[0055] Step S4: Calculate the remaining lifetime ratio Compared with the preset alarm threshold If a comparison is made, Less than the lifespan threshold Then, a desiccant replacement warning is generated and uploaded to the operation and maintenance platform via the communication module.

[0056] In this embodiment of the invention, the method for processing the calculated data is as follows:

[0057] The remaining lifespan ratio of the desiccant is calculated based on data collected by the temperature and humidity sensors in the maintenance-free smart desiccant. This remaining lifespan ratio is then compared with a preset alarm threshold. Compare them.

[0058] This invention provides an online prediction system for the remaining lifespan of the desiccant in a maintenance-free intelligent desiccant, the system comprising:

[0059] The data acquisition module is used to collect and record key parameters of each complete moisture absorption and regeneration cycle of the dehumidifier, including the average regeneration temperature of that cycle. and the average relative humidity inside the drying drum during the moisture absorption cycle The calculation and processing module updates the cumulative damage of the desiccant based on the collected parameters and according to the preset lifespan prediction model. Based on the calculated cumulative damage, the remaining lifespan ratio of the desiccant is calculated. The diagnostic output module is used to output the remaining life ratio. Compared with the preset alarm threshold If a comparison is made, Less than the lifespan threshold If this occurs, a desiccant replacement warning will be generated. Figure 2 A schematic diagram of an electronic device provided in an embodiment of the present invention, such as... Figure 2As shown, the electronic device 21 includes a processor 211, a memory 212, and a computer program 213 stored in the memory 212 and executable on the processor 211. When the computer program 213 is executed by the processor 211, it implements the online prediction method for the remaining lifespan of the desiccant in the maintenance-free smart desiccant in the embodiment. To avoid repetition, it will not be described in detail here.

[0060] Electronic device 21 includes, but is not limited to, processor 211 and memory 212. Those skilled in the art will understand that... Figure 2 This is merely an example of electronic device 21 and does not constitute a limitation on electronic device 21. It may include more or fewer components than shown, or combine certain components, or different components. For example, electronic device may also include input / output devices, network access devices, buses, etc.

[0061] The processor 211 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0062] The memory 212 can be an internal storage unit of the electronic device 21, such as a hard disk or RAM of the electronic device 21. The memory 212 can also be an external storage device of the electronic device 21, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or FlashCard equipped on the electronic device 21. Furthermore, the memory 212 can include both internal and external storage units of the electronic device 21. The memory 212 is used to store computer programs and other programs and data required by network devices. The memory 212 can also be used to temporarily store data that has been output or will be output.

[0063] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0064] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for online prediction of the remaining lifespan of the desiccant in a maintenance-free intelligent desiccant, characterized in that, The maintenance-free intelligent dehumidifier has a built-in temperature sensor and a humidity sensor. The method includes the following steps: S1: Collect and record key parameters for each complete moisture absorption and regeneration cycle of the dehumidifier, including the average regeneration temperature of that cycle. and the average relative humidity inside the drying drum during the moisture absorption cycle ; S2: Based on the collected parameters and according to the preset lifespan prediction model, update the cumulative damage of the desiccant. ; S3: Calculate the remaining lifespan ratio of the desiccant based on the calculated cumulative damage. ; S4: The remaining lifespan ratio Compared with the preset alarm threshold If a comparison is made, Less than the lifespan threshold If this occurs, a desiccant replacement warning will be generated.

2. The method as described in claim 1, characterized in that, In step S2, the cumulative damage degree of the desiccant is calculated as follows: ； in, The first one representing the desiccant Secondary regeneration cycle ( =1, 2, 3...); This represents the number of effective regeneration cycles that have been completed. Damage caused by a single cycle The calculation formula is as follows: ； in, To ensure the safety of the desiccant, the maximum permissible regeneration temperature is designed. This represents the saturated moisture absorption capacity of the desiccant. This represents the theoretical regeneration cycle life of the desiccant under reference conditions, where the reference conditions are the rated temperature. saturated humidity , For the first The actual average regeneration temperature K of each cycle For the first The average relative humidity inside the secondary cycle drying drum , These are material property indices that characterize the sensitivity of the desiccant's lifespan to regeneration temperature and humidity load.

3. The method as described in claim 1, characterized in that, In step S3, the remaining lifespan of the desiccant is compared to The calculation method is as follows: 。 4. The method as described in claim 2, characterized in that, The parameters , , , , These are fixed parameters that are pre-calibrated and stored in the desiccant control unit for accelerated aging experiments using desiccants.

5. The method as described in claim 1, characterized in that, In step S4, the data processing method is as follows: The remaining lifespan ratio of the desiccant is calculated based on data collected by the temperature and humidity sensors in the maintenance-free smart desiccant. This remaining lifespan ratio is then compared with a preset alarm threshold. Compare them.

6. A maintenance-free intelligent desiccant remaining life online prediction system, characterized in that, The system includes: The data acquisition module is used to collect and record key parameters of each complete moisture absorption and regeneration cycle of the dehumidifier, including the average regeneration temperature of that cycle. and the average relative humidity inside the drying drum during the moisture absorption cycle ; The calculation and processing module updates the cumulative damage of the desiccant based on the collected parameters and according to the preset lifespan prediction model. Based on the calculated cumulative damage, the remaining lifespan ratio of the desiccant is calculated. ; The diagnostic output module is used to output the remaining life ratio. Compared with the preset alarm threshold If a comparison is made, Less than the lifespan threshold If this occurs, a desiccant replacement warning will be generated.

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