Method for detecting cold accumulation efficiency of coiled tube type heat exchanger

Abstract

The invention provides a method and a system for detecting the cold storage efficiency of a coil heat exchanger, and relates to the technical field of heat exchanger detection, and the method comprises the following steps: determining the mass, the initial temperature and the lowest temperature of a cooling medium according to preset detection requirements; determining temperature difference data of the cooling medium; collecting an inlet temperature signal, an outlet temperature signal, a real-time flow signal and operation time of the cooling medium in real time; performing wavelet denoising and analog-to-digital conversion on each signal to obtain an inlet temperature, an outlet temperature and real-time flow; performing data cleaning on the collected inlet temperature, outlet temperature, real-time flow and operation time to obtain cleaning data; and determining the cold storage efficiency according to the cleaning data, the quality of the cooling medium and the temperature difference data. Through the advanced signal processing technology and the systematized process design, the detection precision and reliability of the cold storage efficiency of the coiled tube heat exchanger are remarkably improved, and the method has wide application prospects and remarkable economic benefits.

Description

Technical Field

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

[0002] Coil heat exchanger is a common heat exchange equipment, widely used in air conditioning, refrigeration and industrial cooling systems. Its cold storage efficiency is an important indicator to measure its performance, which directly affects the energy consumption and operating cost of the system. However, the current detection method for the cold storage efficiency of coil heat exchanger has the following problems: Insufficient detection accuracy: Traditional methods mostly rely on empirical formulas or simple temperature measurements, failing to fully consider the complex thermodynamic processes inside the heat exchanger, resulting in large deviations in detection results.

[0003] High operational complexity: Existing detection methods usually require complex experimental setups and a lot of manual intervention, making it difficult to achieve rapid and accurate detection.

[0004] Lack of standardized processes: There is a lack of uniform standards between different testing methods, resulting in poor comparability of test results.

[0005] Therefore, there is an urgent need for an efficient, accurate and easy-to-operate method for detecting the cold storage efficiency of a coil heat exchanger to meet the needs of industry and scientific research. Summary of the invention

[0006] In order to overcome the shortcomings 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-type heat exchanger. Through advanced signal processing technology and systematic process design, the detection accuracy and reliability of the cold storage efficiency of the coil-type heat exchanger are significantly improved, and it has broad application prospects and significant economic benefits.

[0007] To achieve the above object, the present invention provides the following solutions: A method for detecting the cold storage efficiency of a coil heat exchanger, comprising: The quality, initial temperature and minimum temperature of the cooling medium need to be determined by the preset test; 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, the inlet temperature signal, outlet temperature signal, real-time flow signal and operation time of the cooling medium are collected in real time; Performing 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, the outlet temperature, and the real-time flow rate; Cleaning the collected inlet temperature, outlet temperature, real-time flow rate and running time to obtain cleaned data; The cold storage efficiency is determined according to the cleaning data, the quality of the cooling medium, and the temperature difference data.

[0008] Preferably, wavelet denoising and analog-to-digital conversion are performed on the inlet temperature signal, the outlet temperature signal, and the real-time flow rate signal to obtain the inlet temperature, the outlet temperature, and the real-time flow rate, including: Based on the wavelet basis function, the inlet temperature signal, the outlet temperature signal and the real-time flow rate signal are respectively decomposed at multiple scales to obtain wavelet coefficients at different decomposition scales; The denoising threshold is constructed based on the median of the wavelet coefficients at different decomposition scales; Constructing a denoising function using the denoising threshold; Processing the wavelet coefficients at different decomposition scales based on the denoising function to obtain denoised wavelet coefficients; Performing 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, the outlet temperature and the real-time flow rate.

[0009] Preferably, constructing a denoising function using the denoising threshold comprises: The mean square error of the wavelet coefficients at the corresponding decomposition scale is calculated according to the median of the wavelet coefficients at different decomposition scales; The denoising threshold is constructed according to the mean square error of the wavelet coefficients; the denoising threshold is: ;in, represents the denoising threshold, represents the mean square error of the wavelet coefficients at the jth decomposition scale, represents the median value of the wavelet coefficients at the jth decomposition scale, Represents the length of the signal at the jth decomposition scale.

[0010] Preferably, the denoising function is: ;in, Indicates j The decomposition scale k The wavelet coefficients after filtering are Indicates j The decomposition scale k The original wavelet coefficients, Indicates the preset parameters. Represents a symbolic function.

[0011] Preferably, data cleaning is performed on the collected inlet temperature, the outlet temperature, the real-time flow rate and the running time to obtain cleaned data, including: The inlet temperature, the outlet temperature, the real-time flow rate and the running time are grouped according to a preset collection period to obtain a plurality of data groups; Calculate the difference coefficient between the current data group and the previous data group in sequence; Determine whether the value of the coefficient of difference is within a preset range; If the value of the difference coefficient is not within the preset range, the corresponding data group is removed; If the value of the difference coefficient is within a preset range, the corresponding data group is retained until all data groups are traversed to obtain the cleaned data.

[0012] Preferably, the difference coefficient calculation formula is: in, is the coefficient of variation, represents the covariance between the current data set X and the previous data set Y, represents the mean of the current data set X, Represents the mean of the previous data set Y.

[0013] Preferably, the calculation formula of the cold storage efficiency is: in: It is the actual cold storage capacity of the coil heat exchanger during operation. The theoretical cold storage capacity of the coil heat exchanger under ideal conditions; ; For real-time traffic, is the specific heat capacity of the cooling medium, and are the real-time inlet temperature and outlet temperature of the cooling medium, respectively, 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.

[0014] A detection system for cold storage efficiency of a coil heat exchanger, comprising: An initial data determination unit, used to determine the quality, initial temperature and minimum temperature of the cooling medium according to preset detection requirements; A temperature difference data determining unit, used to determine the temperature difference data of the cooling medium dropping from the initial temperature to the minimum temperature; A real-time data acquisition unit is used to collect the inlet temperature signal, outlet temperature signal, real-time flow signal and operation time of the cooling medium in real time during the operation of the coil heat exchanger; A data preprocessing unit, used for performing 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, the outlet temperature, and the real-time flow rate; A data cleaning unit, used for cleaning the collected inlet temperature, outlet temperature, real-time flow rate and running time to obtain cleaned data; The efficiency calculation unit is used to determine the cold storage efficiency according to the cleaning data, the quality of the cooling medium, and the temperature difference data.

[0015] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects: The present invention provides a method and system for detecting the cold storage efficiency of a coil heat exchanger, the method comprising: determining the quality, initial temperature and minimum temperature of the cooling medium according to preset detection needs; 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, real-time acquisition of 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 cleaning data; determining the cold storage efficiency according to the cleaning data, the quality of the cooling medium and the temperature difference data. The present invention significantly improves the detection accuracy and reliability of the cold storage efficiency of the coil heat exchanger through advanced signal processing technology and systematic process design, and has broad application prospects and significant economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0017] Figure 1 A flow chart of a method provided by an embodiment of the present invention; Figure 2 A schematic diagram of the system structure provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] The purpose of the present invention is to provide a method and system for detecting the cold storage efficiency of a coil-type heat exchanger. Through advanced signal processing technology and systematic process design, the detection accuracy and reliability of the cold storage efficiency of the coil-type heat exchanger are significantly improved, and the method and system have broad application prospects and significant economic benefits.

[0020] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0021] Figure 1 A flow chart of a method provided by an embodiment of the present invention, such as Figure 1 As shown, the present invention provides a method for detecting the cold storage efficiency of a coil heat exchanger, comprising: Step 100: Determine the quality, initial temperature and minimum temperature of the cooling medium according to the preset detection requirements; Step 200: determining temperature difference data of the cooling medium from the initial temperature to the minimum temperature; Step 300: During the operation of the coil heat exchanger, the inlet temperature signal, outlet temperature signal, real-time flow rate signal and operation time of the cooling medium are collected in real time; Step 400: performing 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, the outlet temperature, and the real-time flow rate; Step 500: performing data cleaning on the collected inlet temperature, the outlet temperature, the real-time flow rate and the running time to obtain cleaned data; Step 600: Determine the cold storage efficiency according to the cleaning data, the quality of the cooling medium, and the temperature difference data.

[0022] Specifically, step 100 of this embodiment includes: Step 101: Determine the type and physical parameters of the cooling medium according to the preset testing requirements First, according to the specific application scenario and experimental conditions of the coil heat exchanger, determine the type of cooling medium (such as water, ethylene glycol solution, brine, etc.). Combined with the type of cooling medium, consult relevant technical manuals or databases to obtain its physical properties, including density ρ and specific heat capacity c. These physical properties are the key basis for subsequent calculations of cooling medium quality and cold storage efficiency.

[0023] Step 102: Calculate the mass of the cooling medium based on the design parameters of the heat exchanger The total mass M of the cooling medium is calculated based on the density ρ of the cooling medium and the internal volume V of the coil heat exchanger. The calculation formula is: M=V×ρM=V×ρ 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 direct measurement. Through the above calculation, the mass M of the cooling medium is determined, providing the necessary input parameters for the subsequent efficiency calculation.

[0024] Step 103: Set the initial temperature and minimum temperature of the cooling medium According to the operating conditions of the heat exchanger and the experimental requirements, set the initial temperature T of the cooling medium init and the minimum temperature T min . Initial temperature T init Usually the ambient temperature of the cooling medium or the temperature at which the heat exchanger starts to operate; the minimum temperature T min The initial temperature and the minimum temperature directly affect the calculation of the temperature difference data ΔT, which in turn affects the evaluation of the theoretical cold storage capacity.

[0025] Optionally, in step 200 of this embodiment, the sources of the initial temperature and the minimum temperature are clarified, and the initial temperature Tinit and the minimum 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 beginning of the experiment, which may be directly measured by a temperature sensor or set according to the ambient temperature; the minimum 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 of 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 in the process of decreasing from the initial temperature to the minimum temperature, which is used to reflect the potential of the cooling medium to store cold in the heat exchanger. By clarifying the initial temperature and the minimum temperature, the size of the temperature difference data can be directly determined. The temperature difference data is not only an important input for the subsequent theoretical cold storage calculation, but also provides a reference for the performance evaluation of the heat exchanger to ensure that the detection process meets the actual operating conditions.

[0026] Preferably, wavelet denoising and analog-to-digital conversion are performed on the inlet temperature signal, the outlet temperature signal, and the real-time flow rate signal to obtain the inlet temperature, the outlet temperature, and the real-time flow rate, including: Based on the wavelet basis function, the inlet temperature signal, the outlet temperature signal and the real-time flow rate signal are respectively decomposed at multiple scales to obtain wavelet coefficients at different decomposition scales; The denoising threshold is constructed based on the median of the wavelet coefficients at different decomposition scales; Constructing a denoising function using the denoising threshold; Processing the wavelet coefficients at different decomposition scales based on the denoising function to obtain denoised wavelet coefficients; Performing 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, the outlet temperature and the real-time flow rate.

[0027] Preferably, constructing a denoising function using the denoising threshold comprises: The mean square error of the wavelet coefficients at the corresponding decomposition scale is calculated according to the median of the wavelet coefficients at different decomposition scales; The denoising threshold is constructed according to the mean square error of the wavelet coefficients; the denoising threshold is: ;in, represents the denoising threshold, represents the mean square error of the wavelet coefficients at the jth decomposition scale, represents the median value of the wavelet coefficients at the jth decomposition scale, Represents the length of the signal at the jth decomposition scale.

[0028] Preferably, the denoising function is: ;in, Indicates j The decomposition scale k The wavelet coefficients after filtering are Indicates j The decomposition scale k The original wavelet coefficients, Indicates the preset parameters. Represents a symbolic function.

[0029] Specifically, this embodiment performs multi-scale decomposition and construction of denoising thresholds. First, the inlet temperature signal, outlet temperature signal and real-time flow signal are multi-scale decomposed based on the wavelet basis function, 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 their distribution characteristics, the mean square error is further calculated to construct the denoising threshold. The design of the denoising threshold can be adaptively adjusted according to the characteristics of the signal, so as to filter out the noise more accurately.

[0030] Optionally, this embodiment constructs a denoising function and processes wavelet coefficients, constructs a denoising function using a denoising threshold, and processes wavelet coefficients at different decomposition scales. The function of the denoising function is to retain useful components in the signal and suppress noise components based on the size and distribution characteristics of the wavelet coefficients. By processing the wavelet coefficients of each decomposition scale one by one, the denoising function can effectively filter out high-frequency noise while retaining the main characteristic information of the signal, ensuring that the denoised signal is smoother and more realistic.

[0031] Again, after completing the denoising process of the wavelet coefficients, this embodiment performs an inverse wavelet transform on the denoised wavelet coefficients, restores the signal from the wavelet domain to the time domain, and obtains the denoised inlet temperature, outlet temperature and real-time flow rate signals. Subsequently, the denoised signal is converted into an analog-to-digital signal, and the continuous signal is converted into a digital signal to facilitate 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 input for the calculation of cold storage efficiency.

[0032] Preferably, data cleaning is performed on the collected inlet temperature, the outlet temperature, the real-time flow rate and the running time to obtain cleaned data, including: The inlet temperature, the outlet temperature, the real-time flow rate and the running time are grouped according to a preset collection period to obtain a plurality of data groups; Calculate the difference coefficient between the current data group and the previous data group in sequence; Determine whether the value of the coefficient of difference is within a preset range; If the value of the difference coefficient is not within the preset range, the corresponding data group is removed; If the value of the difference coefficient is within a preset range, the corresponding data group is retained until all data groups are traversed to obtain the cleaned data.

[0033] Preferably, the difference coefficient calculation formula is: in, is the coefficient of variation, represents the covariance between the current data set X and the previous data set Y, represents the mean of the current data set X, Represents the mean of the previous data set Y.

[0034] Specifically, according to the preset collection cycle, the collected data of inlet temperature, outlet temperature, real-time flow rate and running time are divided into multiple data groups in chronological order in this embodiment. Each data group contains all data points within a collection cycle. Then, the difference coefficient between the current data group and the previous data group is calculated in turn. The difference coefficient is used to quantify the degree of change between the two data groups, which can reflect the stability or abnormal fluctuation of the signal trend. After calculating the difference coefficient of each data group, it is compared with the 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 group that meets the expectations is gradually screened out. All data groups are traversed and judged according to the above method until all data groups are calculated and judged by the difference coefficient. Finally, the retained data group constitutes the cleaned data set. Cleaning data can effectively remove abnormal data caused by noise, equipment failure or other unexpected factors during the collection process, ensuring the accuracy and reliability of the data used in subsequent calculations and analysis, thereby providing high-quality data support for the calculation of cold storage efficiency.

[0035] Preferably, the calculation formula of the cold storage efficiency is: in: It is the actual cold storage capacity of the coil heat exchanger during operation. The theoretical cold storage capacity of the coil heat exchanger under ideal conditions; ; For real-time traffic, is the specific heat capacity of the cooling medium, and are the real-time inlet temperature and outlet temperature of the cooling medium, respectively, 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.

[0036] Furthermore, in the present embodiment, during the operation of the coil heat exchanger, the cleaning data collected in real time, including the real-time flow rate, inlet temperature, outlet temperature and operation time, are used to calculate the actual storage cold capacity of the cooling medium at each moment point by point. By combining the specific heat capacity of the cooling medium and the real-time inlet and outlet temperature difference, the change of the cold capacity of the heat exchanger during the entire operation cycle can be dynamically reflected. Finally, by accumulating these real-time cold capacities, the actual storage cold capacity of the coil heat exchanger during the entire operation process is obtained. The theoretical cold storage capacity is calculated based on the design parameters of the coil heat exchanger and the physical parameters of the cooling medium. By using the known cooling medium mass and its temperature difference data (i.e., the temperature difference from the initial temperature to the minimum temperature), combined with the specific heat capacity of the cooling medium, the maximum cold capacity that the heat exchanger can store under ideal working conditions can be determined. The calculation of the theoretical cold storage capacity does not depend on real-time data, but is determined by preset conditions and design parameters, and is a reference value for evaluating the actual operating efficiency. The cold storage efficiency is the ratio of the actual storage cold capacity to the theoretical storage cold capacity, which is used to evaluate the operating performance of the coil heat exchanger. By comparing the actual storage capacity calculated from real-time collected and cleaned data with the theoretical storage capacity, the gap between the actual operating state of the heat exchanger and the ideal state can be quantified. The final storage efficiency can provide a scientific basis for system optimization and improvement, and can also reflect the performance of the equipment under different operating conditions.

[0037] Figure 2 The system structure diagram of the embodiment provided by the present invention is as follows: Figure 2 As shown, corresponding to the above method, the present invention also provides a detection system for the cold storage efficiency of a coil heat exchanger, comprising: An initial data determination unit, used to determine the quality, initial temperature and minimum temperature of the cooling medium according to preset detection requirements; A temperature difference data determining unit, used to determine the temperature difference data of the cooling medium dropping from the initial temperature to the minimum temperature; A real-time data acquisition unit is used to collect the inlet temperature signal, outlet temperature signal, real-time flow signal and operation time of the cooling medium in real time during the operation of the coil heat exchanger; A data preprocessing unit, used for performing 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, the outlet temperature, and the real-time flow rate; A data cleaning unit, used for cleaning the collected inlet temperature, outlet temperature, real-time flow rate and running time to obtain cleaned data; The efficiency calculation unit is used to determine the cold storage efficiency according to the cleaning data, the quality of the cooling medium, and the temperature difference data.

[0038] The beneficial effects of the present invention are as follows: (1) The present invention collects the inlet temperature, outlet temperature and flow rate signals of the cooling medium in real time and performs wavelet denoising processing, which significantly reduces the influence of signal noise, thereby improving the accuracy and reliability of the data. This high-precision data provides a solid foundation for the calculation of cold storage efficiency.

[0039] (2) The present invention introduces analog-to-digital conversion and wavelet denoising technology to make signal processing more scientific and effective. This method can effectively filter out high-frequency noise, retain useful signal information, and ensure that the results after data cleaning more truly reflect the actual operating status of the heat exchanger.

[0040] (3) The method of the present invention systematically determines the quality, initial temperature and minimum temperature of the cooling medium by presetting the detection requirements, thus forming a standardized detection process. This standardization makes the detection process simpler, reduces manual intervention, improves the automation level of the detection, and is suitable for large-scale applications.

[0041] (4) The present invention collects and processes data in real time, so that the detection process can be carried out under the actual conditions of the heat exchanger operation, and can timely reflect the operating status of the system and the changes in the cold storage efficiency. This is of great significance for optimizing the operating parameters of the heat exchanger and improving the overall energy efficiency of the system.

[0042] (5) The method of the present invention is not only applicable to different types of coil heat exchangers, but can also be flexibly adjusted according to different cooling media. It has strong adaptability and can meet the needs of various industrial applications.

[0043] (6) The present invention cleans the collected data to remove outliers and noise, ensuring that the final calculated cold storage efficiency is more credible. This process enhances the scientific nature of data analysis and facilitates subsequent performance evaluation and optimization.

[0044] (7) The accurate cold storage efficiency detection of the present invention can help users better understand the performance of the heat exchanger, thereby optimizing its operating parameters, reducing energy consumption, improving the overall energy efficiency of the system, and helping to achieve the goal of energy conservation and emission reduction.

[0045] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between 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 method part.

[0046] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for detecting the cold storage efficiency of a coil heat exchanger, characterized in that: include: The quality, initial temperature and minimum temperature of the cooling medium need to be determined by the preset test; 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, the inlet temperature signal, outlet temperature signal, real-time flow signal and operation time of the cooling medium are collected in real time; Performing 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, the outlet temperature, and the real-time flow rate; Cleaning the collected inlet temperature, outlet temperature, real-time flow rate and running time to obtain cleaned data; The cold storage efficiency is determined according to the cleaning data, the quality of the cooling medium, and the temperature difference data.

2. The method for detecting the cold storage efficiency of a coil heat exchanger according to claim 1, characterized in that: The inlet temperature signal, the outlet temperature signal, and the real-time flow rate signal are subjected to wavelet denoising and analog-to-digital conversion to obtain the inlet temperature, the outlet temperature, and the real-time flow rate, including: Based on the wavelet basis function, the inlet temperature signal, the outlet temperature signal and the real-time flow rate signal are respectively decomposed at multiple scales to obtain wavelet coefficients at different decomposition scales; The denoising threshold is constructed based on the median of the wavelet coefficients at different decomposition scales; Constructing a denoising function using the denoising threshold; Processing the wavelet coefficients at different decomposition scales based on the denoising function to obtain denoised wavelet coefficients; Performing 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, the outlet temperature and the real-time flow rate.

3. The method for detecting the cold storage efficiency of a coil heat exchanger according to claim 2, characterized in that: The denoising function is constructed using the denoising threshold, including: The mean square error of the wavelet coefficients at the corresponding decomposition scale is calculated according to the median of the wavelet coefficients at different decomposition scales; The denoising threshold is constructed according to the mean square error of the wavelet coefficients; the denoising threshold is: ;in, represents the denoising threshold, represents the mean square error of the wavelet coefficients at the jth decomposition scale, represents the median value of the wavelet coefficients at the jth decomposition scale, Represents the length of the signal at the jth decomposition scale.

4. The method for detecting the cold storage efficiency of a coil heat exchanger according to claim 3, characterized in that: The denoising function is: ;in, Indicates j The decomposition scale k The wavelet coefficients after filtering are Indicates j The decomposition scale k The original wavelet coefficients, Indicates the preset parameters. Represents a symbolic function.

5. The method for detecting the cold storage efficiency of a coil heat exchanger according to claim 1, characterized in that: The collected inlet temperature, outlet temperature, real-time flow rate and running time are cleaned to obtain cleaned data, including: The inlet temperature, the outlet temperature, the real-time flow rate and the running time are grouped according to a preset collection period to obtain a plurality of data groups; Calculate the difference coefficient between the current data group and the previous data group in sequence; Determine whether the value of the coefficient of difference is within a preset range; If the value of the difference coefficient is not within the preset range, the corresponding data group is removed; If the value of the difference coefficient is within a preset range, the corresponding data group is retained until all data groups are traversed to obtain the cleaned data.

6. The method for detecting the cold storage efficiency of a coil heat exchanger according to claim 5, characterized in that: The coefficient of difference calculation formula is: in, is the coefficient of variation, represents the covariance between the current data set X and the previous data set Y, represents the mean of the current data set X, Represents the mean of the previous data set Y.

7. The method for detecting the cold storage efficiency of a coil heat exchanger according to claim 1, characterized in that: The cold storage efficiency The calculation formula is: in: It is the actual cold storage capacity of the coil heat exchanger during operation. is the theoretical cold storage capacity of the coil heat exchanger under ideal conditions; ; For real-time traffic, is the specific heat capacity of the cooling medium, and are the real-time inlet temperature and outlet temperature of the cooling medium, respectively, 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.

8. A detection system for the cold storage efficiency of a coil heat exchanger, characterized in that: include: An initial data determination unit, used to determine the quality, initial temperature and minimum temperature of the cooling medium according to preset detection requirements; A temperature difference data determining unit, used to determine the temperature difference data of the cooling medium dropping from the initial temperature to the minimum temperature; A real-time data acquisition unit is used to collect the inlet temperature signal, outlet temperature signal, real-time flow signal and operation time of the cooling medium in real time during the operation of the coil heat exchanger; A data preprocessing unit, used for performing 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, the outlet temperature, and the real-time flow rate; A data cleaning unit, used for cleaning the collected inlet temperature, outlet temperature, real-time flow rate and running time to obtain cleaned data; The efficiency calculation unit is used to determine the cold storage efficiency according to the cleaning data, the quality of the cooling medium, and the temperature difference data.

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