A detection method for the cold storage efficiency of a coil heat exchanger

Abstract

The present invention provides a method and system for detecting the cold storage efficiency of a coil heat exchanger, relating to the technical field of heat exchanger detection. The method includes: determining the mass, initial temperature, and lowest temperature of a cooling medium according to preset detection requirements; determining the temperature difference data of the cooling medium; collecting in real time the inlet temperature signal, outlet temperature signal, real-time flow signal, and running time of the cooling medium; performing wavelet denoising and analog-to-digital conversion on each signal to obtain the inlet temperature, outlet temperature, and real-time flow; performing data cleaning on the collected inlet temperature, outlet temperature, real-time flow, and running time to obtain cleaned data; and determining the cold storage efficiency according to the cleaned data, the mass of the cooling medium, and the temperature difference data. Through advanced signal processing techniques and systematic process design, the present invention significantly improves the detection accuracy and reliability of the cold storage efficiency of the coil heat exchanger, and has broad application prospects and remarkable economic benefits.

Description

Technical Field

[0001] The present invention relates to the technical field of heat exchanger detection, and particularly to a method for detecting the cold storage efficiency of a coil heat exchanger. Background Art

[0002] The coil heat exchanger is a common heat exchange device, which is widely used in air conditioners, refrigeration systems, and industrial cooling systems. Its cold storage efficiency is an important indicator to measure its performance, directly affecting the energy consumption and operating cost of the system. However, the existing methods for detecting the cold storage efficiency of coil heat exchangers have the following problems:

[0003] Insufficient detection accuracy: Traditional methods mostly rely on empirical formulas or simple temperature measurements, and do not fully consider the complex thermodynamic processes inside the heat exchanger, resulting in large deviations in the detection results.

[0004] High operation complexity: Existing detection methods usually require complex experimental devices and a large amount of manual intervention, making it difficult to achieve fast and accurate detection.

[0005] Lack of standardized processes: There is no unified standard among different detection methods, resulting in poor comparability of detection results.

[0006] Therefore, there is an urgent need for an efficient, accurate, and easy-to-operate method for detecting the cold storage efficiency of coil heat exchangers to meet the needs of the industrial and scientific research fields. Summary of the Invention

[0007] In order to overcome the deficiencies of the prior art, the purpose of the present invention is to provide a method and system for detecting the cold storage efficiency of a coil heat exchanger. Through advanced signal processing technology and systematic process design, the detection accuracy and reliability of the cold storage efficiency of the coil heat exchanger are significantly improved, with broad application prospects and remarkable economic benefits.

[0008] To achieve the above purpose, the present invention provides the following solutions:

[0009] A method for detecting the cold storage efficiency of a coil heat exchanger, comprising:

[0010] Determining the mass, initial temperature, and minimum temperature of the cooling medium according to the preset detection requirements;

[0011] Determining the temperature difference data of the cooling medium from the initial temperature to the minimum temperature;

[0012] During the operation of the coil heat exchanger, real-time collecting the inlet temperature signal, outlet temperature signal, real-time flow signal, and operation time of the cooling medium;

[0013] Perform wavelet denoising and analog-to-digital conversion on the inlet temperature signal, the outlet temperature signal, and the real-time flow signal to obtain the inlet temperature, the outlet temperature, and the real-time flow;

[0014] Perform data cleaning on the collected inlet temperature, outlet temperature, real-time flow, and running time to obtain cleaned data;

[0015] Determine the cold storage efficiency according to the cleaned data, the mass of the cooling medium, and the temperature difference data.

[0016] Preferably, performing wavelet denoising and analog-to-digital conversion on the inlet temperature signal, the outlet temperature signal, and the real-time flow signal to obtain the inlet temperature, the outlet temperature, and the real-time flow includes:

[0017] Perform multi-scale decomposition on the inlet temperature signal, the outlet temperature signal, and the real-time flow signal based on wavelet basis functions to obtain wavelet coefficients at different decomposition scales;

[0018] Construct a denoising threshold based on the median of the wavelet coefficients at different decomposition scales;

[0019] Construct a denoising function using the denoising threshold;

[0020] Process the wavelet coefficients at different decomposition scales based on the denoising function to obtain denoised wavelet coefficients;

[0021] Perform inverse wavelet transform on the denoised wavelet coefficients to obtain a denoised signal;

[0022] Perform analog-to-digital conversion on the denoised signal to obtain the inlet temperature, the outlet temperature, and the real-time flow.

[0023] Preferably, constructing a denoising function using the denoising threshold includes:

[0024] Calculate the mean square deviation of the wavelet coefficients at the corresponding decomposition scales according to the median of the wavelet coefficients at different decomposition scales;

[0025] Construct a denoising threshold according to the mean square deviation of the wavelet coefficients; where the denoising threshold is:

[0026] ; where represents the denoising threshold, represents the mean square deviation of the wavelet coefficients at the j-th decomposition scale, represents the median of the wavelet coefficients at the j-th decomposition scale, represents the length of the signal at the j-th decomposition scale.

[0027] Preferably, the denoising function is:

[0028] ; where, represents the j th filtered wavelet coefficient at the k th decomposition scale, represents the j th original wavelet coefficient at the k th decomposition scale, represents a preset parameter, represents the sign function.

[0029] Preferably, data cleaning is performed on the collected inlet temperature, outlet temperature, real-time flow rate, and running time to obtain cleaned data, including:

[0030] Group the inlet temperature, outlet temperature, real-time flow rate, and running time respectively according to a preset collection period to obtain multiple data groups;

[0031] Calculate the difference coefficient between the current data group and the previous data group in sequence;

[0032] Judge whether the value of the difference coefficient is within a preset range;

[0033] If the value of the difference coefficient is not within the preset range, remove the corresponding data group;

[0034] If the value of the difference coefficient is within the preset range, retain the corresponding data group until all data groups are traversed to obtain the cleaned data.

[0035] Preferably, the difference coefficient calculation formula is:

[0036]

[0037] where, is the difference coefficient, represents the covariance between the current data group X and the previous data group Y, represents the mean of the current data group X, represents the mean of the previous data group Y.

[0038] Preferably, the calculation formula for the cold storage efficiency is:

[0039]

[0040] where: is the actually stored cold quantity during the operation of the coil heat exchanger, is the theoretical cold storage quantity of the coil heat exchanger under ideal conditions; ; is the real-time flow rate, is the specific heat capacity of the cooling medium, and are respectively the real-time inlet temperature and the outlet temperature of the cooling medium, is the operation time; ; is the mass of the cooling medium in the coil heat exchanger, is the temperature difference data of the cooling medium.

[0041] A detection system for the cold storage efficiency of a coil heat exchanger, comprising:

[0042] An initial data determination unit, configured to determine the mass, initial temperature and lowest temperature of the cooling medium according to preset detection requirements;

[0043] A temperature difference data determination unit, configured to determine the temperature difference data of the cooling medium from the initial temperature to the lowest temperature;

[0044] A real-time data acquisition unit, configured to, during the operation of the coil heat exchanger, acquire in real time the inlet temperature signal, outlet temperature signal, real-time flow signal and operation time of the cooling medium;

[0045] A data preprocessing unit, configured to perform wavelet denoising and analog-to-digital conversion on the inlet temperature signal, the outlet temperature signal and the real-time flow signal to obtain the inlet temperature, the outlet temperature and the real-time flow;

[0046] A data cleaning unit, configured to perform data cleaning on the acquired inlet temperature, outlet temperature, real-time flow and operation time to obtain cleaned data;

[0047] An efficiency calculation unit, configured to determine the cold storage efficiency according to the cleaned data, the mass of the cooling medium and the temperature difference data.

[0048] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0049] The present invention provides a method and system for detecting the cold storage efficiency of a coil heat exchanger. The method includes: determining the mass, initial temperature, and minimum temperature of a cooling medium according to preset detection requirements; determining the temperature difference data of the cooling medium from the initial temperature to the minimum temperature; during the operation of the coil heat exchanger, collecting in real time the inlet temperature signal, outlet temperature signal, real-time flow signal, and operation time of the cooling medium; performing wavelet denoising and analog-to-digital conversion on the inlet temperature signal, the outlet temperature signal, and the real-time flow signal to obtain the inlet temperature, outlet temperature, and real-time flow; performing data cleaning on the collected inlet temperature, outlet temperature, real-time flow, and operation time to obtain cleaned data; and determining the cold storage efficiency according to the cleaned data, the mass of the cooling medium, and the temperature difference data. Through advanced signal processing technology and systematic process design, the present invention significantly improves the detection accuracy and reliability of the cold storage efficiency of the coil heat exchanger, and has broad application prospects and significant economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0051] Figure 1 It is a flowchart of the method provided by an embodiment of the present invention;

[0052] Figure 2 It is a schematic structural diagram of the system provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0053] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0054] The purpose of the present invention is to provide a method and system for detecting the cold storage efficiency of a coil heat exchanger. Through advanced signal processing technology and systematic process design, the present invention significantly improves the detection accuracy and reliability of the cold storage efficiency of the coil heat exchanger, and has broad application prospects and significant economic benefits.

[0055] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below with reference to the drawings and specific embodiments.

[0056] Figure 1 The flowchart of the method provided by the embodiment of the present invention is as follows Figure 1 As shown, the present invention provides a method for detecting the cold storage efficiency of a coil heat exchanger, including:

[0057] Step 100: Determine the mass, initial temperature, and minimum temperature of the cooling medium according to the preset detection requirements;

[0058] Step 200: Determine the temperature difference data of the cooling medium from the initial temperature to the minimum temperature;

[0059] Step 300: During the operation of the coil heat exchanger, real-time collect the inlet temperature signal, outlet temperature signal, real-time flow signal, and operation time of the cooling medium;

[0060] Step 400: Perform wavelet denoising and analog-to-digital conversion on the inlet temperature signal, the outlet temperature signal, and the real-time flow signal to obtain the inlet temperature, outlet temperature, and real-time flow;

[0061] Step 500: Perform data cleaning on the collected inlet temperature, outlet temperature, real-time flow, and operation time to obtain cleaned data;

[0062] Step 600: Determine the cold storage efficiency according to the cleaned data, the mass of the cooling medium, and the temperature difference data.

[0063] Specifically, step 100 of this embodiment includes:

[0064] Step 101: Determine the type and physical property parameters of the cooling medium according to the preset detection requirements

[0065] First, according to the specific application scenario and experimental conditions of the coil heat exchanger, determine the type of the cooling medium (such as water, ethylene glycol solution, brine, etc.). Combining the type of the cooling medium, consult relevant technical manuals or databases to obtain its physical property parameters, including density ρ and specific heat capacity c. These physical property parameters are the key basis for subsequent calculations of the mass of the cooling medium and the cold storage efficiency.

[0066] Step 102: Calculate the mass of the cooling medium in combination with the design parameters of the heat exchanger

[0067] Calculate the total mass M of the cooling medium according to the density ρ of the cooling medium and the internal volume V of the coil heat exchanger. The calculation formula is:

[0068] M = V×ρM = V×ρ

[0069] Among them, the internal volume V of the heat exchanger can be obtained through the design parameters of the heat exchanger (such as coil diameter, length, etc.) or by direct measurement. Through the above calculations, the mass M of the cooling medium is determined, providing the necessary input parameters for subsequent efficiency calculations.

[0070] Step 103: Set the initial temperature and the lowest temperature of the cooling medium

[0071] According to the operating conditions of the heat exchanger and the experimental requirements, set the initial temperature T init and the lowest temperature T min . The initial temperature T init is usually the ambient temperature of the cooling medium or the temperature when the heat exchanger starts to operate; the lowest temperature T min is determined by the design capacity of the heat exchanger and the lowest refrigeration temperature of the refrigerator. The determination of the initial temperature and the lowest temperature directly affects the calculation of the temperature difference data ΔT, and thus affects the evaluation of the theoretical cold storage capacity.

[0072] Optionally, in step 200 of this embodiment, clarify the sources of the initial temperature and the lowest temperature. The initial temperature Tinit and the lowest temperature Tmin of the cooling medium are determined according to the detection requirements and experimental conditions set in step 100. The initial temperature is usually the actual temperature of the cooling medium at the start of the experiment, which may be directly measured by a temperature sensor or set according to the ambient temperature; the lowest temperature is determined by the design capacity of the heat exchanger and the operating limit of the refrigerator, and is usually the lowest temperature that the cooling medium can reach in the heat exchanger. These two temperature values are the basis for the temperature difference data. Then determine the range and significance of the temperature difference data. The temperature difference data is the temperature change range experienced by the cooling medium during the process of dropping from the initial temperature to the lowest temperature, and is used to reflect the potential of the cooling medium to store cold in the heat exchanger. By clarifying the initial temperature and the lowest temperature, the magnitude of the temperature difference data can be directly determined. The temperature difference data is not only an important input for subsequent theoretical cold storage capacity calculations, but also provides a reference for the performance evaluation of the heat exchanger, ensuring that the detection process meets the actual operating conditions.

[0073] Preferably, perform wavelet denoising and analog-to-digital conversion on the inlet temperature signal, the outlet temperature signal, and the real-time flow signal to obtain the inlet temperature, the outlet temperature, and the real-time flow, including:

[0074] Perform multi-scale decomposition on the inlet temperature signal, the outlet temperature signal, and the real-time flow signal respectively based on the wavelet basis function to obtain wavelet coefficients at different decomposition scales;

[0075] Construct a denoising threshold based on the median of the wavelet coefficients at different decomposition scales;

[0076] Construct a denoising function using the denoising threshold;

[0077] Process the wavelet coefficients at different decomposition scales based on the denoising function to obtain the denoised wavelet coefficients;

[0078] Perform inverse wavelet transform on the denoised wavelet coefficients to obtain the denoised signal;

[0079] Perform analog-to-digital conversion on the denoised signal to obtain the inlet temperature, the outlet temperature, and the real-time flow rate.

[0080] Preferably, constructing the denoising function using the denoising threshold includes:

[0081] Calculate the mean square error of the wavelet coefficients at the corresponding decomposition scale according to the median of the wavelet coefficients at different decomposition scales;

[0082] Construct the denoising threshold according to the mean square error of the wavelet coefficients; where the denoising threshold is:

[0083] ; where represents the denoising threshold, represents the mean square error of the wavelet coefficients at the j-th decomposition scale, represents the median of the wavelet coefficients at the j-th decomposition scale, represents the length of the signal at the j-th decomposition scale.

[0084] Preferably, the denoising function is:

[0085] ; where represents the j -th filtered wavelet coefficient at the k -th decomposition scale, represents the j -th original wavelet coefficient at the k -th decomposition scale, represents a preset parameter, represents the sign function.

[0086] Specifically, in this embodiment, multi-scale decomposition and the construction of the denoising threshold are performed. First, based on the wavelet basis function, multi-scale decomposition is performed on the inlet temperature signal, the outlet temperature signal, and the real-time flow rate signal, and the original signal is decomposed into wavelet coefficients at different scales. These wavelet coefficients correspond to different frequency components of the signal and can effectively separate the noise and useful information in the signal. Subsequently, by calculating the median of the wavelet coefficients at each decomposition scale and combining its distribution characteristics, the mean square error is further calculated for constructing the denoising threshold. The design of the denoising threshold can be adaptively adjusted according to the characteristics of the signal, so as to more accurately filter out the noise.

[0087] Optionally, in this embodiment, a denoising function is constructed and wavelet coefficients are processed. A denoising function is constructed using a denoising threshold to process wavelet coefficients at different decomposition scales. The role of the denoising function is to retain the useful components in the signal and suppress the noise components according to the magnitude and distribution characteristics of the wavelet coefficients. By processing each wavelet coefficient at each decomposition scale one by one, the denoising function can effectively filter out high-frequency noise while retaining the main feature information of the signal, ensuring that the denoised signal is smoother and more realistic.

[0088] Next, after completing the denoising process of the wavelet coefficients in this embodiment, an inverse wavelet transform is performed on the denoised wavelet coefficients to restore the signal from the wavelet domain to the time domain, obtaining the denoised inlet temperature, outlet temperature, and real-time flow rate signals. Subsequently, an analog-to-digital conversion is performed on the denoised signal to convert the continuous signal into a digital signal for subsequent data processing and analysis. Through this process, high-precision inlet temperature, outlet temperature, and real-time flow rate data are finally obtained, providing reliable inputs for the calculation of the cold storage efficiency.

[0089] Preferably, data cleaning is performed on the collected inlet temperature, outlet temperature, real-time flow rate, and running time to obtain cleaned data, including:

[0090] Grouping the inlet temperature, outlet temperature, real-time flow rate, and running time according to a preset acquisition period to obtain multiple data groups;

[0091] Calculating the difference coefficient between the current data group and the previous data group in sequence;

[0092] Determining whether the value of the difference coefficient is within a preset range;

[0093] If the value of the difference coefficient is not within the preset range, the corresponding data group is removed;

[0094] If the value of the difference coefficient is within the preset range, the corresponding data group is retained until all data groups are traversed to obtain the cleaned data.

[0095] Preferably, the difference coefficient calculation formula is:

[0096]

[0097] Where, is the difference coefficient, represents the covariance between the current data group X and the previous data group Y, represents the mean value of the current data group X, represents the mean value of the previous data group Y.

[0098] Specifically, in this embodiment, according to a preset acquisition period, the data of the inlet temperature, outlet temperature, real-time flow rate, and running time collected are divided into multiple data groups in chronological order. Each data group contains all data points within one acquisition period. Then, the difference coefficient between the current data group and the previous data group is calculated in sequence. The difference coefficient is used to quantify the degree of change between two data groups and can reflect the smoothness or abnormal fluctuations of the signal trend. After calculating the difference coefficient of each data group, it is compared with a preset normal range. If the difference coefficient exceeds the preset range, it indicates that the change between the current data group and the previous data group is too large, and there may be abnormal data. At this time, the data group is marked as abnormal and removed from the data set. If the difference coefficient is within the preset range, it is considered that the change of the data group is reasonable and it is retained. In this way, the data groups that meet the expectations are gradually screened out. All data groups are traversed and judged according to the above method until all data groups have undergone the calculation of the difference coefficient and the range judgment. Finally, the remaining data groups form the cleaned data set. Cleaning the data can effectively remove abnormal data caused by noise, equipment failures, or other accidental factors during the acquisition process, ensuring the accuracy and reliability of the data used for subsequent calculations and analyses, thereby providing high-quality data support for the calculation of the cold storage efficiency.

[0099] Preferably, the calculation formula for the cold storage efficiency is:

[0100]

[0101] Where: is the actual cold storage capacity stored by the coil heat exchanger during operation, is the theoretical cold storage capacity of the coil heat exchanger under ideal conditions; ; is the real-time flow rate, is the specific heat capacity of the cooling medium, and are respectively the real-time inlet temperature and outlet temperature of the cooling medium, is the running time; ; is the mass of the cooling medium in the coil heat exchanger, is the temperature difference data of the cooling medium.

[0102] Furthermore, during the operation of the coiled - tube heat exchanger in this embodiment, the actual stored cooling capacity of the cooling medium at each moment is calculated point - by - point by using the real - time collected cleaning data, including real - time flow rate, inlet temperature, outlet temperature, and operation time. By combining the specific heat capacity of the cooling medium and the real - time temperature difference between the inlet and outlet, the change in the cooling capacity of the heat exchanger during the entire operation cycle can be dynamically reflected. Finally, by accumulating these real - time cooling capacities, the actual stored cooling capacity of the coiled - tube heat exchanger during the entire operation process is obtained. The theoretical cooling storage capacity is calculated based on the design parameters of the coiled - tube heat exchanger and the physical properties of the cooling medium. By using the known mass of the cooling medium and its temperature difference data (i.e., the temperature difference from the initial temperature to the lowest temperature), and combining the specific heat capacity of the cooling medium, the maximum cooling capacity that the heat exchanger can store under ideal conditions can be determined. The calculation of the theoretical cooling storage capacity does not depend on real - time data, but is determined by preset conditions and design parameters, and is used as a reference value for evaluating the actual operation efficiency. The cooling storage efficiency is the ratio of the actual stored cooling capacity to the theoretical cooling storage capacity, and is used to evaluate the operation performance of the coiled - tube heat exchanger. By comparing the actual stored cooling capacity calculated from the real - time collected and cleaned data with the theoretical cooling storage capacity, the gap between the actual operation state and the ideal state of the heat exchanger can be quantified. The final cooling storage efficiency can provide a scientific basis for the optimization and improvement of the system, and can also reflect the performance of the equipment under different operating conditions.

[0103] Figure 2 The system structure diagram in the embodiment provided by the present invention is as Figure 2 shown. Corresponding to the above - mentioned method, the present invention also provides a detection system for the cooling storage efficiency of a coiled - tube heat exchanger, including:

[0104] An initial data determination unit, configured to determine the mass, initial temperature, and lowest temperature of the cooling medium according to the preset detection requirements;

[0105] A temperature difference data determination unit, configured to determine the temperature difference data of the cooling medium from the initial temperature to the lowest temperature;

[0106] A real - time data acquisition unit, configured to, during the operation of the coiled - tube heat exchanger, acquire in real - time the inlet temperature signal, outlet temperature signal, real - time flow rate signal, and operation time of the cooling medium;

[0107] A data pre - processing unit, configured to perform wavelet denoising and analog - to - digital conversion on the inlet temperature signal, the outlet temperature signal, and the real - time flow rate signal to obtain the inlet temperature, outlet temperature, and real - time flow rate;

[0108] A data cleaning unit, configured to perform data cleaning on the acquired inlet temperature, outlet temperature, real - time flow rate, and operation time to obtain cleaned data;

[0109] An efficiency calculation unit for determining the cold storage efficiency based on the cleaning data, the mass of the cooling medium, and the temperature difference data.

[0110] The beneficial effects of the present invention are as follows:

[0111] (1) By collecting the inlet temperature, outlet temperature, and flow rate signals of the cooling medium in real time and performing wavelet denoising processing, the present invention significantly reduces the influence of signal noise, thereby improving the accuracy and reliability of the data. This highly accurate data provides a solid foundation for the calculation of the cold storage efficiency.

[0112] (2) The present invention introduces analog-to-digital conversion and wavelet denoising technologies, making the signal processing more scientific and effective. This method can effectively filter out high-frequency noise and retain useful signal information, ensuring that the result after data cleaning more truly reflects the actual operating state of the heat exchanger.

[0113] (3) The method of the present invention systematically determines the mass, initial temperature, and minimum temperature of the cooling medium by presetting the detection requirements, forming a set of standardized detection processes. This standardization makes the detection process more convenient, reduces manual intervention, improves the automation level of detection, and is suitable for large-scale applications.

[0114] (4) By collecting and processing data in real time, the present invention enables the detection process to be carried out under the actual conditions of the heat exchanger operation, and can timely reflect the operation state of the system and the change of the cold storage efficiency. This is of great significance for optimizing the operation parameters of the heat exchanger and improving the overall energy efficiency of the system.

[0115] (5) The method of the present invention is not only applicable to different types of coil heat exchangers, but also can be flexibly adjusted according to different cooling media, with strong adaptability and can meet the needs of various industrial applications.

[0116] (6) By cleaning the collected data to remove outliers and noise, the present invention ensures that the finally calculated cold storage efficiency is more credible. This process enhances the scientific nature of data analysis and helps with subsequent performance evaluation and optimization.

[0117] (7) The accurate detection of the cold storage efficiency of the present invention can help users better understand the performance of the heat exchanger, thereby optimizing its operation parameters, reducing energy consumption, improving the overall energy efficiency of the system, and contributing to the goal of energy conservation and emission reduction.

[0118] In this specification, each embodiment is described in a progressive manner. The key point of each embodiment is to illustrate the differences from other embodiments. The same or similar parts among the embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method part.

[0119] In this article, specific examples are used to elaborate on the principles and implementation manners of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manners and application scopes. To sum up, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A method for detecting the cold storage efficiency of a coil heat exchanger, characterized in that, Including: Determine the mass, initial temperature, and minimum temperature of the cooling medium according to preset detection requirements; Determine the temperature difference data of the cooling medium from the initial temperature to the minimum temperature; During the operation of the coil heat exchanger, real-time collect the inlet temperature signal, outlet temperature signal, real-time flow signal, and operation time of the cooling medium; Perform wavelet denoising and analog-to-digital conversion on the inlet temperature signal, outlet temperature signal, and real-time flow signal to obtain the inlet temperature, outlet temperature, and real-time flow; Perform data cleaning on the collected inlet temperature, outlet temperature, real-time flow, and operation time to obtain cleaned data; Determine the cold storage efficiency according to the cleaned data, the mass of the cooling medium, and the temperature difference data; The calculation formula for the cold storage efficiency η is: Among them: Q 实际 is the actual cold storage of the coil heat exchanger during operation, and Q 理论 is the theoretical cold storage capacity of the coil heat exchanger under ideal conditions; is the real-time flow rate, c is the specific heat capacity of the cooling medium, and T in (t) and T out (t) are respectively the real-time inlet temperature and the outlet temperature of the cooling medium, and t is the operation time; Q 理论 = M·c·ΔT max ; M is the mass of the cooling medium in the coil heat exchanger, and ΔT max is the temperature difference data of the cooling medium; Perform data cleaning on the collected inlet temperature, outlet temperature, real-time flow, and operation time to obtain cleaned data, including: Group the inlet temperature, outlet temperature, real-time flow, and operation time according to a preset collection period to obtain multiple data groups; Calculate the difference coefficient between the current data group and the previous data group in sequence; Judge whether the value of the difference coefficient is within a preset range; If the value of the difference coefficient is not within the preset range, remove the corresponding data group; If the value of the difference coefficient is within the preset range, retain the corresponding data group until all data groups are traversed to obtain the cleaned data.

2. The detection method for the cold storage efficiency of the coiled tube heat exchanger according to claim 1, characterized in that, Perform wavelet denoising and analog-to-digital conversion on the inlet temperature signal, outlet temperature signal, and real-time flow signal to obtain the inlet temperature, outlet temperature, and real-time flow, including: Perform multi-scale decomposition on the inlet temperature signal, outlet temperature signal, and real-time flow signal based on wavelet basis functions to obtain wavelet coefficients at different decomposition scales; Construct a denoising threshold based on the median of the wavelet coefficients at different decomposition scales; Construct a denoising function using the denoising threshold; Process the wavelet coefficients at different decomposition scales based on the denoising function to obtain denoised wavelet coefficients; Perform inverse wavelet transform on the denoised wavelet coefficients to obtain a denoised signal; Perform analog-to-digital conversion on the denoised signal to obtain the inlet temperature, outlet temperature, and real-time flow.

3. The detection method for the cold storage efficiency of the coiled tube heat exchanger according to claim 2, wherein, Construct a denoising function using the denoising threshold, including: Calculate the mean square deviation of the wavelet coefficients at the corresponding decomposition scale according to the median of the wavelet coefficients at different decomposition scales; Construct a denoising threshold according to the mean square deviation of the wavelet coefficients; where the denoising threshold is: Among them, λ j represents the denoising threshold, σ j represents the mean square error of the wavelet coefficients at the j-th decomposition scale, median(|ω0|) represents the median of the wavelet coefficients at the j-th decomposition scale, and k j represents the length of the signal at the j-th decomposition scale.

4. The method for detecting the cold storage efficiency of the coiled tube heat exchanger according to claim 3, wherein, The denoising function is: Among them, represents the k-th filtered wavelet coefficient at the j-th decomposition scale, ω j,k represents the k-th original wavelet coefficient at the j-th decomposition scale, a represents a preset parameter, and sign represents the sign function.

5. The detection method for the cold storage efficiency of the coiled tube heat exchanger according to claim 1, wherein, The calculation formula for the difference coefficient is: where p X,Y is the difference coefficient, cov(X, Y) represents the covariance between the current data group X and the previous data group Y, α X represents the mean of the current data group X, and β Y represents the mean of the previous data group Y.

6. A detection system for the cold storage efficiency of a coiled tube heat exchanger, characterized in that, Including: An initial data determination unit for determining the mass, initial temperature, and minimum temperature of the cooling medium according to preset detection requirements; A temperature difference data determination unit for determining the temperature difference data of the cooling medium from the initial temperature to the minimum temperature; A real-time data collection unit for real-time collecting the inlet temperature signal, outlet temperature signal, real-time flow signal, and operation time of the cooling medium during the operation of the coil heat exchanger; A data preprocessing unit, configured to perform wavelet denoising and analog-to-digital conversion on the inlet temperature signal, the outlet temperature signal, and the real-time flow signal to obtain the inlet temperature, the outlet temperature, and the real-time flow; A data cleaning unit, configured to clean the collected inlet temperature, outlet temperature, real-time flow, and running time to obtain cleaned data; An efficiency calculation unit, configured to determine the cold storage efficiency according to the cleaned data, the mass of the cooling medium, and the temperature difference data; The calculation formula of the cold storage efficiency η is: Among them: Q 实际 is the actual cold storage of the coil heat exchanger during operation, and Q 理论 is the theoretical cold storage capacity of the coil heat exchanger under ideal conditions; is the real-time flow rate, c is the specific heat capacity of the cooling medium, T in (t) and T out (t) are the real-time inlet temperature and the outlet temperature of the cooling medium respectively, t is the operating time; Q 理论 = M·c·ΔT max ; M is the mass of the cooling medium in the coil heat exchanger, and ΔT max is the temperature difference data of the cooling medium; Cleaning the collected inlet temperature, outlet temperature, real-time flow, and running time to obtain cleaned data, including: Grouping the inlet temperature, the outlet temperature, the real-time flow, and the running time respectively according to a preset collection period to obtain a plurality of data groups; Calculating the difference coefficient between the current data group and the previous data group in sequence; Judging whether the value of the difference coefficient is within a preset range; If the value of the difference coefficient is not within the preset range, removing the corresponding data group; If the value of the difference coefficient is within the preset range, retaining the corresponding data group until all data groups are traversed to obtain the cleaned data.

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