Energy saving method and system for heating and ventilation combination machine

Abstract

The application discloses an energy-saving method and system of a heating and ventilation combined machine, relates to the technical field of heating ventilation air conditioning, and provides the following scheme, which comprises the following steps: acquiring temperature distribution data of an evaporator pipe wall and flow noise signals of internal refrigerants; pre-processing and Fourier transforming the flow noise signals; extracting main frequency characteristic values; constructing a discrimination interval representing the main frequency characteristic values of different flow states of the refrigerants; calculating a temperature gradient discrete coefficient and an axial phase change trend parameter based on the temperature distribution data; mapping the temperature gradient discrete coefficient to an offset of the interval distance between two adjacent discrimination intervals where the current main frequency characteristic value is located. Through real-time dynamic matching of the main frequency characteristic values and the corrected discrimination interval, an adaptive adjustment strategy of the compressor frequency is constructed, and the adjustment amplitude is corrected in a closed loop through the temperature gradient discrete coefficient, so that a positive feedback vicious circle between initial misjudgment and frequency misadjustment is effectively blocked.

Description

TECHNICAL FIELD

[0001] The present application relates to the HVAC (Heating, Ventilation and Air Conditioning) technical field, and more particularly, to an HVAC combination machine energy-saving method and system. BACKGROUND

[0002] As an integrated system integrating refrigeration, heating and air handling functions, the core energy consumption of the HVAC combination machine comes from the compressor (accounting for 60%~70% of the total system power consumption). The compressor maintains the circulation of gaseous refrigerant, while the evaporator cools the air by using liquid refrigerant phase change heat absorption. The frequency of the compressor directly determines the refrigerant circulation amount and system energy efficiency. The necessity of dynamic adjustment of the frequency lies in the fact that the flow state of the refrigerant changes complexly with the load fluctuation: incomplete evaporation will cause liquid refrigerant backflow to impact the compressor cavity, causing irreversible mechanical damage, while over-evaporation will reduce the heat exchange efficiency and force the compressor to run at a higher frequency. Therefore, the frequency needs to be adjusted according to the real-time flow state to balance the energy efficiency and equipment safety.

[0003] The control system of the existing HVAC combination machine has defects. The system usually only relies on a single type of sensor signal, such as temperature signal, which leads to misjudgment of the flow state of the refrigerant. The fixed threshold value cannot adapt to the dynamic working condition of the refrigerant. For example, the threshold value mutation during the gradual change period of the high load flow state causes the frequency of the compressor to oscillate (increasing 12%~18% start-stop energy consumption), and the threshold value lag during the rapid switching period of the flow state causes over-adjustment or under-adjustment. The two form a positive feedback vicious cycle: the initial misjudgment triggers an incorrect frequency adjustment, further disturbs the stability of the refrigerant flow state, and ultimately leads to a significant increase in system energy consumption. Therefore, an HVAC combination machine energy-saving method and system are proposed to solve this problem. SUMMARY

[0004] To solve the above technical problems, an HVAC combination machine energy-saving method and system are provided, which solve the problems raised in the background art.

[0005] In order to achieve the above purpose, the technical scheme of the present application is as follows:

[0006] In a first aspect, the present application provides an HVAC combination machine energy-saving method, which comprises:

[0007] Obtaining temperature distribution data of the evaporator tube wall and flow noise signals of the refrigerant inside the evaporator tube wall;

[0008] Pretreating and performing Fourier transform on the flow noise signals, extracting the main frequency characteristic value thereof, and constructing a discrimination interval representing the main frequency characteristic value of the refrigerant in different flow states;

[0009] Based on the temperature distribution data, calculating the temperature gradient discrete coefficient and the axial phase change trend parameter;

[0010] The temperature gradient discrete coefficient is mapped to the offset of the boundary distance of the two adjacent discrimination intervals in which the current main frequency characteristic value is located, the axial phase change trend parameter is mapped to the offset direction of the boundary position, and a transition section is generated by performing an offset operation;

[0011] The main frequency characteristic value is compared with the discrimination intervals after the offset operation, and an adjustment strategy of the compressor frequency is dynamically generated according to the comparison result.

[0012] In a second aspect, the present application provides an energy-saving system of a heating and ventilation combined machine, which is used to implement the energy-saving method of the heating and ventilation combined machine.

[0013] A multi-source data acquisition module is configured to acquire temperature distribution data of the evaporator pipe wall and a flow noise signal of the internal refrigerant;

[0014] A discrimination interval generation module is configured to pre-process and perform Fourier transform on the flow noise signal, extract a main frequency characteristic value, and construct discrimination intervals representing the main frequency characteristic values of different flow states of the refrigerant.

[0015] A discrimination interval correction module is configured to calculate a temperature gradient discrete coefficient and an axial phase change trend parameter based on the temperature distribution data, map the temperature gradient discrete coefficient to the offset of the boundary distance of the two adjacent discrimination intervals in which the current main frequency characteristic value is located, map the axial phase change trend parameter to the offset direction of the boundary position, and generate a transition section by performing an offset operation.

[0016] A frequency control decision module is configured to compare the main frequency characteristic value with the discrimination intervals after the offset operation, and dynamically generate an adjustment strategy of the compressor frequency according to the comparison result.

[0017] In a third aspect, the present application provides a computer device, which comprises a memory and a processor, the memory stores a code, and the processor is configured to acquire the code and execute the energy-saving method of the heating and ventilation combined machine.

[0018] In a fourth aspect, the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the energy-saving method of the heating and ventilation combined machine.

[0019] Compared with the prior art, the present application has the following beneficial effects:

[0020] The present application solves the flow state misjudgment problem of the existing system caused by relying on a single temperature signal by synchronously acquiring the temperature distribution data of the evaporator pipe wall and the flow noise signal of the refrigerant, and constructing a double-source verification mechanism.

[0021] The scheme establishes a dynamic threshold generation mechanism through the cooperative calculation and nonlinear mapping of the temperature gradient dispersion coefficient and the axial phase change trend parameter: the dispersion coefficient is quantified as a boundary offset, the phase change trend parameter is analyzed as an offset direction, and the adaptive adjustment of the discrimination threshold is realized through a transition section dynamic generation algorithm, and further introduces the real-time feedback correction of the temperature oscillation data of the suction pipe, solves the problems of compressor frequency instability caused by traditional fixed threshold in high load flow state gradual change period, and dynamic response lag in flow state rapid switching period.

[0022] The application constructs an adaptive adjustment strategy of the compressor frequency through real-time dynamic matching of the main frequency characteristic value and the corrected discrimination interval, and closes the loop correction of the adjustment amplitude through the temperature gradient dispersion coefficient, effectively breaking the positive feedback vicious cycle between the initial misjudgment and the frequency misadjustment. BRIEF DESCRIPTION OF DRAWINGS

[0023] The disclosure of the application will be described with reference to the accompanying drawings. It should be understood that the drawings are only for illustrative purposes, and are not intended to limit the scope of protection of the application. Among them:

[0024] Figure 1 A flow chart of an energy-saving method for a heating and ventilation combined machine proposed in the application;

[0025] Figure 2 A method flow chart of the corrected discrimination interval in the application;

[0026] Figure 3 A structure block diagram of an energy-saving system for a heating and ventilation combined machine proposed in the application. DETAILED DESCRIPTION

[0027] It is easy to understand that, according to the technical scheme of the application, those skilled in the art can propose a plurality of structure modes and implementation modes which can be replaced with each other without changing the essential spirit of the application. Therefore, the following specific embodiments and drawings are only exemplary descriptions of the technical scheme of the application, and should not be regarded as the whole or as a limitation or restriction on the technical scheme of the application.

[0028] In the prior art, the core energy consumption of the heating and ventilation combined machine is concentrated in the compressor link, and the traditional control system has the following technical bottlenecks: first, only a single sensor signal is used for flow state recognition, which increases the probability of working condition misjudgment; second, the fixed threshold discrimination mechanism cannot respond to the change of the dynamic characteristics of the refrigerant, which is specifically manifested as: in the high load flow state gradual change stage, the threshold mutation will trigger the compressor frequency oscillation; in the flow state rapid switching stage, the threshold lag will cause the regulation overshoot or under-regulation phenomenon, and the above defects will form a positive feedback vicious cycle: the false frequency adjustment aggravates the flow state instability, and further leads to a significant increase in system energy consumption.

[0029] To solve the above problems, by analyzing the correlation between the temperature distribution of the evaporator tube wall and the flow noise of the refrigerant, the scheme proposes to construct a dynamic discrimination interval with the temperature gradient discrete coefficient and the noise main frequency characteristic value to overcome the limitations of traditional fixed threshold. Specifically, through the boundary offset mechanism, the temperature parameter is converted into the real-time correction amount of the interval boundary, and the transition section generation algorithm is used to realize the dynamic adjustment of the discrimination interval, thereby forming an adaptive adjustment strategy of multi-source data fusion, effectively eliminating the misjudgment and lag problems.

[0030] Referring to Figures 1-2 An energy-saving method for a heating and ventilation combination machine, comprising:

[0031] Obtain the temperature distribution data of the evaporator tube wall and the flow noise signal of the refrigerant inside it;

[0032] It should be noted that the multi-dimensional temperature information of the evaporator tube wall is collected by a distributed temperature sensor array, which is denoted as temperature distribution data, and the acoustic vibration signal generated by the refrigerant flowing in the evaporator pipe is collected by a piezoelectric acoustic sensor, which is denoted as flow noise signal;

[0033] The flow noise signal is preprocessed and Fourier transformed to extract its main frequency characteristic value, and a discrimination interval representing the main frequency characteristic value of the refrigerant in different flow states is constructed; preprocessing includes noise reduction filtering and signal normalization processing, which can be realized by wavelet threshold denoising combined with moving average filtering to eliminate environmental noise interference;

[0034] In order to facilitate the understanding of the construction process of the discrimination interval, the following will take a specific application scenario as an example to explain:

[0035] The noise main frequency range of the refrigerant under typical flow state is calibrated by experiment to construct 3 basic discrimination intervals:

[0036] The laminar flow interval is [0, 120] (Hz), the physical characteristic is low-frequency stable flow and uniform phase change, and the compressor preset adjustment amount is +5Hz;

[0037] The slow flow interval is (120, 260] (Hz), the physical characteristic is local vortex and phase change rate fluctuation, and the compressor preset adjustment amount is ±3Hz;

[0038] The turbulent flow interval is (260, 400] (Hz), the physical characteristic is high-frequency turbulent flow and is easy to cause liquid knock or evaporation deficiency, and the compressor preset adjustment amount is -8Hz;

[0039] Based on the temperature distribution data, calculate the temperature gradient discrete coefficient and the axial phase change trend parameter;

[0040] mapping the temperature gradient discrete coefficient to a shift of the interval distance between the boundaries, mapping the axial phase change trend parameter to a shift direction of the boundary positions, and performing a shift operation to generate a transition section;

[0041] comparing the main frequency characteristic value with the discriminant interval after the shift operation, and dynamically generating an adjustment strategy for the compressor frequency according to the comparison result.

[0042] In an optional embodiment, calculating the temperature gradient discrete coefficient and the axial phase change trend parameter specifically comprises:

[0043] constructing a two-dimensional temperature matrix based on the temperature distribution data, and dividing the axial dimension and the radial dimension according to the flow direction of the refrigerant;

[0044] calculating a local temperature gradient matrix of the axial dimension and the radial dimension, and taking the ratio of the standard deviation to the mean value of each local temperature gradient matrix as the temperature gradient discrete coefficient; for example, the evaporator tube surface can be divided into a regular grid, and the evaporator tube wall temperature distribution data can be arranged in a matrix structure according to the grid to obtain a two-dimensional temperature matrix;

[0045] dividing the evaporator into a plurality of sub-sections along the flow direction of the refrigerant, calculating the average temperature change rate in each sub-section, and forming an ordered sequence;

[0046] sign marking the change rate difference of adjacent sections in the ordered sequence, and calculating the proportion of the number of sub-sections with the same sign to the total number of sub-sections;

[0047] It should be noted that the average temperature change rate of each sub-section is calculated by linear regression, and the ordered sequence formed can represent the overall change trend of the temperature along the flow direction; the sign of the change rate difference of adjacent sub-sections is determined, and the proportion of the same sign is calculated to identify the stability of the overall change trend, avoiding misjudgment caused by local fluctuations;

[0048] if the proportion exceeds a preset proportion threshold, it is determined as a positive trend, and if there is a sign jump and the proportion is lower than the preset proportion threshold, it is determined as a negative trend, and the determination result is recorded as the axial phase change trend parameter;

[0049] Compared with the prior art, the traditional method only relies on single-dimensional temperature data or fixed threshold for trend judgment, and cannot distinguish the temperature gradient difference between the axial and radial directions, and is sensitive to local abnormal values, while the present application can accurately quantify the discrete degree of the temperature distribution and the trend direction of the phase change process, providing a reliable basis for the adjustment of the compressor frequency, and avoiding the problems of adjustment lag or overshoot caused by local fluctuations or missing of the temperature data.

[0050] In an alternative embodiment, weights are assigned to each local temperature gradient matrix before calculating the temperature gradient dispersion coefficient, specifically including:

[0051] According to the evaporator pipe topology, the high-sensitivity region set and the low-sensitivity region set are divided;

[0052] Exemplarily, the high-sensitivity region can specifically be the refrigerant inlet section (length ≥ 30% of the total length of the evaporator pipe) and the curved pipe section with a curvature radius < 3 times the pipe diameter, and the low-sensitivity region can specifically be the straight pipe section and the outlet section (length ≤ 20% of the total length of the evaporator pipe);

[0053] The flow state parameter of the refrigerant and the evaporator pipe diameter parameter are obtained, and the Reynolds number of the refrigerant is calculated;

[0054] The local temperature gradient matrix in the high-sensitivity region set is assigned a dynamic weight based on the Reynolds number, and the local temperature gradient matrix in the low-sensitivity region set is assigned a fixed weight;

[0055] Specifically, the real-time mass flow rate of the refrigerant is obtained through a mass flow sensor, the fluid dynamic viscosity of the refrigerant is queried based on the type of the refrigerant, and the Reynolds number is calculated according to the Reynolds number variant formula;

[0056] The Reynolds number variant formula is:

[0057] ;

[0058] In the formula, is the Reynolds number, is the mass flow rate, is the evaporator pipe diameter, is the fluid dynamic viscosity;

[0059] It should be noted that the Reynolds number is calculated by obtaining the mass flow rate of the refrigerant and the evaporator pipe diameter, and when the Reynolds number is high, it indicates that the flow is in a turbulent state, at which time a higher dynamic weight is assigned to the local temperature gradient matrix in the high-sensitivity region, and a fixed weight is always used for the low-sensitivity region. Thus, in the calculation process of the temperature gradient dispersion coefficient, the temperature change in the high-sensitivity region is given higher attention, so that the temperature dispersion coefficient can more sensitively reflect the flow state mutation;

[0060] The dynamic weight is calculated through the weight factor formula, and the fixed weight can be 0.8;

[0061] The weight factor formula is:

[0062] ;

[0063] In the formula, is the dynamic weight, is the calibration coefficient, Reynolds number, Reynolds number; the calibration coefficient can be 0.3-0.6, and the critical Reynolds number can be 2000-2300; through dynamic weight distribution, the temperature gradient fluctuation resolution of the high sensitivity area is improved;

[0064] Through the above technical solutions, the application can implement differentiated temperature gradient monitoring strategies for different regions of the evaporator, avoid the problems of insufficient sensitivity or noise interference caused by global unified calculation, make the temperature gradient dispersion coefficient more truly reflect the flow state change trend, and reduce the frequency oscillation or regulation lag caused by flow state misjudgment.

[0065] In an optional implementation, mapping the temperature gradient dispersion coefficient to the offset of the boundary interval thereof, mapping the axial phase change trend parameter to the offset direction of the boundary position thereof, and performing the offset operation to generate the transition section specifically includes:

[0066] Based on the temperature gradient dispersion coefficient, a segmented positive correlation function is constructed to calculate the offset;

[0067] When the axial phase change trend parameter is a positive trend, the offset direction is set to a positive sign, and when the axial phase change trend parameter is a negative trend, the offset direction is a negative sign;

[0068] Performing linear offset on the product of the offset and the offset direction for the adjacent two boundary intervals of the current main frequency characteristic value;

[0069] Generating the transition section according to the boundary after performing the linear offset;

[0070] It should be noted that when the evaporator tube wall temperature distribution is uneven, that is, the temperature gradient dispersion coefficient increases to trigger the segmented positive correlation function to calculate the offset, and the boundary moving direction is determined according to the positive and negative directions of the axial phase change trend; for example, in the positive trend, the boundary of the discrimination interval expands outward to form a transition section, so that the flow state discrimination standard can adapt to the gradually increasing phase change process. This dynamic adjustment mechanism effectively avoids the threshold mutation problem of the fixed discrimination interval in the flow state gradual change period, and realizes the smooth transition of the discrimination standard through the buffering effect of the transition section.

[0071] The segmented positive correlation function is:

[0072] ;

[0073] In the formula, is the offset, is the linear segment slope coefficient, is the logarithmic segment scaling coefficient, is the logarithmic segment intercept, is the temperature gradient dispersion coefficient;

[0074] For the convenience of judging the execution process of the linear shift of the interval, the above-mentioned specific application scenario for constructing the judgment interval is taken as an example for description:

[0075] When the characteristic value of the main frequency is located near the boundary of the slowly varying flow interval, the characteristic value of the main frequency is 125Hz, triggering dynamic correction:

[0076] S1. The temperature gradient dispersion coefficient is calculated as , and the axial phase change trend parameter is a positive trend;

[0077] S2. Calculate the shift: , indicating a shift to the left, that is, to the direction of the smaller boundary value;

[0078] S3. Boundary correction: the upper limit of the laminar flow interval is ;

[0079] S4. Generate a transition section: the transition section is [116.8, 120], which is set between the laminar flow interval and the slowly varying flow interval;

[0080] Exemplarily, 8-12 can be taken, The larger the value, the more aggressive the response to local overheating or subcooling of the evaporator, preventing liquid hammer or evaporator efficiency decline; 4-6 can be taken, Used to compensate for nonlinear acoustic characteristics in high-turbulence state; 0.5 can be taken to ensure the continuity of the logarithmic function at Smoothly connect the linear section and the logarithmic section;

[0081] Compared with the prior art, the traditional method uses a fixed threshold to distinguish the flow state of the refrigerant, which cannot adapt to the dynamic changes of the flow state of the refrigerant. The present scheme establishes a dynamic association between the judgment interval boundary and the flow state characteristics by introducing a double mapping mechanism of the temperature gradient dispersion coefficient and the axial phase change trend parameter;

[0082] Through the above technical scheme, the present application effectively solves the problem of compressor frequency oscillation caused by the traditional fixed judgment threshold. The dynamic generation mechanism of the transition section can accurately capture the gradual change characteristics of the flow state, avoid the frequency step adjustment caused by the threshold mutation, and at the same time, through the matching of the shift direction and the phase change trend, ensure that the adjustment direction of the judgment interval is consistent with the evolution direction of the flow state, and prevent the overshoot phenomenon caused by the adjustment lag.

[0083] In an alternative embodiment, after generating the transition section according to the boundary after performing the linear shift, the transition section is subjected to boundary verification, specifically including:

[0084] Obtain the temperature oscillation time sequence data of the outer wall of the compressor suction pipe, and synchronize the time stamp with the temperature distribution data;

[0085] It should be noted that the dynamic temperature signal reflecting the change of the refrigerant flow state collected by the patch type thermocouple array for multi-point synchronous measurement is used as the temperature oscillation time sequence data for characterizing the pressure fluctuation caused by the flow state mutation in the evaporator;

[0086] The frequency of the periodic fluctuation component with the largest amplitude is extracted as the oscillation main frequency value through frequency domain analysis of the temperature oscillation time sequence data, and the sliding time window is combined with the frequency spectrum peak detection algorithm to realize the frequency domain analysis;

[0087] The center frequency value of the current transition section is calculated, and the absolute deviation and the relative deviation percentage of the oscillation main frequency value and the center frequency value are calculated;

[0088] If the relative deviation percentage exceeds the preset percentage threshold, a secondary deviation is performed according to the deviation direction:

[0089] When the oscillation main frequency value is greater than the center frequency value, the offset is enlarged according to the relative deviation percentage;

[0090] When the oscillation main frequency value is less than the center frequency value, the offset is reduced according to the relative deviation percentage;

[0091] Specifically, the offset is dynamically adjusted according to the deviation direction: the oscillation main frequency value can be regarded as the measured main frequency value, and the center frequency value can be regarded as the main frequency theoretical value. When the offset is enlarged according to the relative deviation percentage, the purpose is to cover the high-frequency disturbance. When the offset is reduced according to the relative deviation percentage, the purpose is to avoid excessive expansion of the discrimination interval. The corrected offset is re-applied to the boundary adjustment to generate a new transition section matching the current flow state characteristics, and to eliminate the boundary positioning deviation of the initial discrimination interval caused by the temperature gradient dispersion coefficient calculation error;

[0092] Based on the corrected offset, the linear offset of the boundary is re-executed to generate a new transition section;

[0093] It should be noted that the center frequency value of the transition section is half of the sum of its boundary values, and the relative deviation percentage is the ratio of the absolute value of the difference between the oscillation main frequency value and the center frequency value to the center frequency value. Exemplarily, the preset percentage threshold can be 15%;

[0094] Through the above technical solutions, the application effectively solves the problem of mismatch between the discrimination interval boundary and the actual flow state characteristics. By introducing a real-time feedback mechanism of the temperature oscillation signal, the discrimination interval boundary is dynamically adjusted by using the secondary offset correction technology, so that the transition section can adapt to the flow state disturbance, avoid the compressor frequency misadjustment caused by the initial offset error, and suppress the overshoot or underadjustment phenomenon of the compressor frequency. Thus, the stability of the refrigerant circulation is maintained under the fast switching of the flow state, and the system energy consumption is reduced.

[0095] In an alternative embodiment, the adjustment strategy of the compressor frequency is dynamically generated according to the comparison result, specifically comprising:

[0096] When the main frequency characteristic value is located in the discrimination interval, the preset frequency adjustment amount corresponding to the flow state is extracted; wherein the preset frequency adjustment amount refers to the compressor frequency adjustment amount preset for different refrigerant flow states, which can be realized by using the optimal frequency adjustment value corresponding to different flow states in the historical operation data, and is used to directly call the corresponding adjustment parameter when the flow state is classified;

[0097] When the main frequency characteristic value is located in the transition section, the gradual frequency adjustment amount is generated based on the distance and direction of the main frequency characteristic value deviating from the center position of the transition section;

[0098] Specifically, when the main frequency characteristic value falls into the discrimination interval, the preset frequency adjustment amount corresponding to the flow state is directly called to perform the compressor frequency adjustment; when the main frequency characteristic value is located in the transition section, the basic value of the adjustment amount is determined according to the percentage distance of the center position of the transition section, and the increment or decrement sign of the adjustment amount is determined in combination with the deviation direction;

[0099] The preset frequency adjustment amount and the gradual frequency adjustment amount are amplitude-modified by the temperature gradient discrete coefficient;

[0100] Through the above technical solution, the present application solves the problem of inaccurate compressor frequency adjustment caused by fixed discrimination threshold in the prior art, and realizes smooth switching of the frequency during the flow state transition period and rapid matching of the target adjustment amount during the flow state mutation period through the dynamic transition section and the temperature gradient modification mechanism, thereby significantly improving the system regulation stability and energy efficiency performance.

[0101] In an alternative embodiment, the preset frequency adjustment amount and the gradual frequency adjustment amount are amplitude-modified by the temperature gradient discrete coefficient, specifically comprising:

[0102] The temperature gradient discrete coefficient of the segmented positive correlation function is extracted, and a modification coefficient is set for each segmented interval;

[0103] Exemplarily, the modification coefficient of the segmented interval may be 1, the modification coefficient of the segmented interval may be 0.8, the modification coefficient of the segmented interval may be 0.5, and the higher the flow type determination uncertainty is, the smaller the frequency adjustment amount needs to be reduced to prevent over-regulation; the maximum allowed step value can be 10 Hz, which is specifically set according to the compressor model;

[0104] The modification coefficient is multiplied by the preset frequency adjustment amount or the gradual frequency adjustment amount to output the final adjustment amount, and the final adjustment amount does not exceed the maximum allowed step value of the compressor;

[0105] Compared with the prior art, the traditional method usually adopts a fixed correction coefficient or a single threshold value to control the adjustment amount, which cannot adapt to the change of the temperature gradient discrete degree, for example, when the refrigerant flow state is in the transition period, the discrete coefficient is low, but the traditional method still adopts a high correction coefficient, which causes the adjustment amount to be too large and causes the compressor to vibrate. The present scheme matches the correction coefficient in the segmented interval, so that the adjustment amount amplitude accurately corresponds to the current flow state characteristics, eliminates the correction deviation caused by the large span of the discrete coefficient, and avoids the stepwise mutation or adjustment lag of the compressor frequency.

[0106] Referring to Figure 3 As shown in the drawings, the present scheme provides an energy-saving system for a heating and ventilation combined machine, which is used to implement the above-mentioned energy-saving method for a heating and ventilation combined machine, and comprises:

[0107] A multi-source data acquisition module is configured to acquire temperature distribution data of the evaporator pipe wall and flow noise signals of the refrigerant inside the evaporator pipe wall.

[0108] A discrimination interval generation module is configured to pre-process and perform Fourier transform on the flow noise signals, extract the main frequency characteristic value thereof, and construct discrimination intervals representing the main frequency characteristic values of different flow states of the refrigerant.

[0109] A discrimination interval correction module is configured to calculate a temperature gradient discrete coefficient and an axial phase change trend parameter based on the temperature distribution data, map the temperature gradient discrete coefficient to an offset of the interval between the boundaries of two adjacent discrimination intervals in which the current main frequency characteristic value is located, map the axial phase change trend parameter to an offset direction of the boundary positions of the two adjacent discrimination intervals, and perform an offset operation to generate a transition section.

[0110] A frequency control decision module is configured to compare the main frequency characteristic value with the discrimination intervals after the offset operation, and dynamically generate an adjustment strategy of the compressor frequency according to the comparison result.

[0111] In addition, in an embodiment, a computer device is provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps in the above embodiments when executing the computer program.

[0112] In an embodiment, a computer readable storage medium is provided, which stores a computer program. The computer program is executed by a processor to implement the steps in the above embodiments.

[0113] In an embodiment, a computer program product or a computer program is provided, which includes computer instructions stored in a computer readable storage medium. A processor of a computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to make the computer device execute the steps in the above embodiments.

[0114] Among them, the memory refers to a hardware module for storing computer programs and running data, which can be realized by a solid state disk or a flash memory chip, and its function is to provide the processor with execution instruction and temporary data storage support. The processor refers to the core operation unit for executing computer program logic, which can be realized by a multi-core central processing chip or an embedded microcontroller, and its function is to complete the refrigerant flow state discrimination and compressor frequency control decision through program instruction analysis and operation. The computer program refers to a code set containing all steps of the HVAC combination machine energy saving method, which can be realized by an executable file written in C language or Python, and its function is to fuse and process the multi-source information of temperature data and flow noise signals, realize real-time discrimination of refrigerant flow state and dynamic adjustment of compressor frequency.

[0115] The technical scope of the present application is not limited to the content in the above description, and those skilled in the art can make various modifications and changes to the above embodiments without departing from the technical idea of the present application, and these modifications and changes should all belong to the protection scope of the present application.

Claims

1. An energy-saving method for HVAC systems, characterized in that, The method includes: Acquire temperature distribution data of the evaporator tube wall and the flow noise signal of the refrigerant inside; The flow noise signal is preprocessed and Fourier transformed to extract its dominant frequency characteristic value, and a discrimination interval characterizing the dominant frequency characteristic value of different flow states of refrigerant is constructed. Based on the temperature distribution data, the temperature gradient dispersion coefficient and axial phase transition trend parameter are calculated; For two adjacent discrimination intervals where the current dominant frequency characteristic value is located, the temperature gradient discrete coefficient is mapped to the offset of its boundary spacing, the axial phase transition trend parameter is mapped to the offset direction of its boundary position, and the offset operation is performed to generate a transition segment. The main frequency characteristic value is compared with the discrimination interval after the offset operation is performed, and the compressor frequency adjustment strategy is dynamically generated based on the comparison result. The process of mapping the temperature gradient discrete coefficient to the offset of its boundary spacing, mapping the axial phase transition trend parameter to the offset direction of its boundary position, and performing the offset operation to generate the transition segment specifically includes: Based on the temperature gradient discrete coefficient, a piecewise positive correlation function is constructed to calculate the offset; When the axial phase transition trend parameter is positive, the offset direction is set to positive; when the axial phase transition trend parameter is negative, the offset direction is set to negative. For the two adjacent discrimination interval boundaries of the current main frequency feature value, perform linear offset by multiplying the offset by the offset direction; Generate a transition segment based on the boundary after performing the linear offset; The piecewise positive correlation function is: ； In the formula, This is the offset. The slope coefficient of the linear segment. The scaling factor is the logarithmic segment scaling factor. For the logarithmic segment intercept, These are the temperature gradient dispersion coefficients; The strategy for dynamically generating compressor frequency adjustment based on comparison results specifically includes: When the dominant frequency characteristic value is within the discrimination interval, the preset frequency adjustment amount of the corresponding flow state is extracted; When the main frequency characteristic value is located within the transition section, a gradual frequency adjustment amount is generated based on its distance and direction from the center of the transition section. The amplitude of the preset frequency adjustment amount and the gradual frequency adjustment amount is corrected by the temperature gradient dispersion coefficient.

2. The energy-saving method for a heating, ventilation, and air conditioning (HVAC) unit according to claim 1, characterized in that, The calculation of the temperature gradient dispersion coefficient and the axial phase transition trend parameters specifically includes: A two-dimensional temperature matrix is ​​constructed based on temperature distribution data, and the axial and radial dimensions are divided according to the refrigerant flow direction. Calculate the local temperature gradient matrices in the axial and radial dimensions, and use the ratio of the standard deviation to the mean of each local temperature gradient matrix as the temperature gradient dispersion coefficient. The evaporator is divided into multiple sub-sections along the refrigerant flow direction. The average temperature change rate in each sub-section is calculated and an ordered sequence is formed. The difference in the rate of change of adjacent segments in the ordered sequence is labeled with a sign, and the proportion of sub-segments with the same sign to the total number of sub-segments is counted. If the ratio exceeds the preset ratio threshold, it is determined to be a positive trend. If there is a sign change and the ratio is lower than the preset ratio threshold, it is determined to be a negative trend. The determination result is recorded as the axial phase change trend parameter.

3. The energy-saving method for a heating, ventilation, and air conditioning (HVAC) unit according to claim 2, characterized in that, Before calculating the temperature gradient discretization coefficients, weights are assigned to each local temperature gradient matrix, specifically including: Based on the evaporator piping topology, high-sensitivity regions and low-sensitivity regions are divided. Obtain the refrigerant flow state parameters and evaporator pipe diameter parameters, and calculate the refrigerant Reynolds number; For local temperature gradient matrices concentrated in highly sensitive regions, dynamic weights are assigned based on the Reynolds number; for local temperature gradient matrices concentrated in low-sensitive regions, fixed weights are set.

4. The energy-saving method for a heating, ventilation, and air conditioning (HVAC) unit according to claim 1, characterized in that, After generating the transition segment based on the boundary after performing the linear offset, the boundary of the transition segment is verified, specifically including: Acquire the time-series data of temperature oscillation on the outer wall of the compressor suction pipe and synchronize the timestamp with the temperature distribution data; Frequency domain analysis was performed on the temperature oscillation time series data, and the frequency of the periodic fluctuation component with the largest amplitude was extracted as the oscillation main frequency value. Calculate the center frequency value of the current transition section, compare the absolute deviation between the oscillation main frequency value and the center frequency value, and calculate the relative deviation percentage. If the relative deviation percentage exceeds the preset percentage threshold, a secondary offset is performed based on the deviation direction: When the oscillation frequency is greater than the center frequency, the offset is increased by a percentage of the relative deviation. When the oscillation frequency is less than the center frequency, the offset is reduced by a percentage of the relative deviation. Based on the corrected offset, the linear offset of the boundary is re-executed to generate a new transition segment.

5. The energy-saving method for a heating, ventilation, and air conditioning (HVAC) unit according to claim 1, characterized in that, The amplitude correction of the preset frequency adjustment amount and the gradual frequency adjustment amount is performed using the temperature gradient dispersion coefficient, specifically including: Extract the segmented intervals of the temperature gradient discrete coefficients in the segmented positive correlation function, and set a correction coefficient for each segmented interval; The correction factor is multiplied by the preset frequency adjustment amount or the gradual frequency adjustment amount to output the final adjustment amount, which does not exceed the compressor's maximum allowable step value.

6. An energy-saving system for HVAC systems, characterized in that, A method for implementing an energy-saving HVAC system as described in any one of claims 1-5 includes: The multi-source data acquisition module is used to acquire temperature distribution data of the evaporator tube wall and the flow noise signal of the refrigerant inside it; The discrimination interval generation module is used to preprocess and perform Fourier transform on the flow noise signal, extract its dominant frequency feature value, and construct a discrimination interval characterizing the dominant frequency feature value of different flow states of the refrigerant; The discrimination interval correction module is used to calculate the temperature gradient dispersion coefficient and the axial phase transition trend parameter based on the temperature distribution data. For two discrimination intervals adjacent to the current main frequency feature value, the temperature gradient dispersion coefficient is mapped to the offset of its boundary spacing, the axial phase transition trend parameter is mapped to the offset direction of its boundary position, and the offset operation is performed to generate a transition segment. The frequency control decision module is used to compare the main frequency characteristic value with the discrimination interval after the offset operation is performed, and dynamically generate the compressor frequency adjustment strategy based on the comparison result.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements an energy-saving method for a heating, ventilation, and air conditioning (HVAC) unit as described in any one of claims 1-5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements an energy-saving method for HVAC systems as described in any one of claims 1-5.

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