Method and system for judging heat exchange abnormity of heat pump evaporator

Abstract

The invention discloses a method and system for judging heat exchange abnormity of a heat pump evaporator, and the method comprises the steps: periodically collecting secondary steam temperature data generated when the heat pump evaporator treats wastewater, and extracting multi-dimensional temperature characterization data including node abnormal frequency, temperature deviation degree and abnormal distribution time sequence characteristics; meanwhile, high-temperature, flat-temperature and low-temperature areas are divided according to the temperature change trend, and a vacuum degree behavior cardinal number reflecting the system adjusting capacity is calculated based on the deviation between the actual response of the vacuum degree of each area and the theoretical expectation; and finally, performing fusion calculation on the temperature characterization data and the vacuum degree behavior cardinal number through a preset quantitative model to obtain a secondary steam temperature anomaly characterization value for comprehensive judgment. According to the method, the defect that correlation analysis of temperature change and vacuum degree adjustment is lacked in the prior art is overcome, and early and accurate recognition and degree quantification of heat exchange abnormity of the heat pump evaporator are achieved.

Description

Technical Field

[0001] This invention belongs to the field of heat pump technology, specifically relating to a method and system for judging heat exchange abnormalities in a heat pump evaporator. Background Technology

[0002] Chemical waste liquids refer to process waste liquids, cooling water, exhaust gas scrubbing water, equipment and site washing water, etc., discharged during chemical production. If these waste liquids are discharged without treatment, they will cause varying degrees and properties of pollution to water bodies. Heat pump evaporators are a new type of high-efficiency, energy-saving evaporation equipment mainly used in the chemical industry. They utilize a circulating working medium that flows between the evaporator and condenser, absorbing heat from the waste liquid and reusing it, thus achieving evaporation and concentration. They can efficiently treat various chemical waste liquids, such as organic wastewater, inorganic wastewater, and high-salt wastewater, evaporating the water to obtain concentrated waste liquid or solid waste.

[0003] In the treatment of high-salt wastewater, heat pump evaporators utilize high-efficiency steam compressors to compress and evaporate secondary steam, increasing its pressure and temperature. This enhanced secondary steam is then pumped into a heater to reheat the raw liquid. The heated liquid continues to evaporate, generating more secondary steam, thus achieving continuous evaporation. To achieve good wastewater treatment results, it is necessary to ensure the stability of the secondary steam temperature within the evaporator. The stability of the secondary steam temperature is related to the vacuum level of the evaporation system.

[0004] In the existing technology, there is a lack of judgment and identification of the response speed of secondary steam temperature changes and heat pump evaporator vacuum adjustment. Summary of the Invention

[0005] To overcome the shortcomings of existing technologies, this invention provides a method and system for judging heat exchange anomalies in heat pump evaporators. By comprehensively analyzing multi-dimensional characterization data related to secondary steam temperature and vacuum behavior baselines reflecting the system's regulation capability, it can achieve early and accurate judgment and quantitative identification of the degree of heat exchange anomalies in heat pump evaporators during wastewater treatment.

[0006] The technical solution for implementing the present invention is as follows: A method for judging heat exchange abnormalities in a heat pump evaporator includes the following steps: The monitoring cycle is preset and divided into multiple time nodes, and the secondary steam temperature data of the heat pump evaporator wastewater treatment at each node is collected. The secondary steam temperature change data within the cycle is processed to extract temperature characterization data containing node anomaly frequency values, node anomaly temperature values, and anomaly interval time values. Based on the temperature change trend of secondary steam, the temperature data is divided into high temperature region, flat temperature region and low temperature region, and the vacuum behavior base is calculated based on the vacuum degree data corresponding to each region. The temperature characterization data is fused with the vacuum behavior base, and the secondary steam temperature anomaly characterization value within the cycle is calculated through a predetermined quantization model. Based on the abnormal secondary steam temperature characterization value, it is possible to identify whether the operating status of the heat pump evaporator is abnormal.

[0007] Furthermore, the secondary steam temperature anomaly characterization value Ttf The calculation model is as follows:

[0008] Where zk represents the cardinality of vacuum behavior, This represents the node anomaly frequency value. This refers to abnormal temperature values ​​at the nodes. These are time values ​​within the abnormal range; Furthermore, obtaining the node anomaly frequency value includes: The secondary steam temperature values ​​at each time point are compared with the preset allowable temperature range, and the number of abnormal points outside the range is counted. The ratio of the number of abnormal nodes to the total number of nodes within a period is taken as the node abnormality frequency value.

[0009] Furthermore, the acquisition of the abnormal node temperature value includes: Calculate the minimum deviation between the temperature value of each abnormal node and the two ends of the allowable temperature range, and use it as the temperature deviation value of that node; The average temperature deviation of all abnormal nodes is obtained by averaging the temperature deviation values ​​of all abnormal nodes. The average temperature value of all normal nodes within the allowable temperature range is taken to obtain the comprehensive temperature value of normal nodes; The ratio of the average temperature deviation of the abnormal node to the comprehensive temperature value of the normal node is taken as the abnormal node temperature value.

[0010] Furthermore, obtaining the time value of the abnormal interval includes: Identify all temporally adjacent temperature anomaly node pairs and determine the adjacent anomaly intervals between each pair of nodes; Count the number of normal temperature nodes contained in each of the adjacent abnormal intervals and the time length of that interval; Calculate the abnormal interval time ratio for each interval, which is the ratio of the number of normal nodes in that interval to the time length. The abnormal interval time value is obtained by summing the abnormal interval time ratios of all adjacent abnormal intervals.

[0011] Furthermore, methods for dividing regions into high-temperature, neutral-temperature, and low-temperature zones include: A coordinate system was constructed with the data acquisition time as the horizontal axis and the temperature as the vertical axis, and the temperature variation curve of the secondary steam was plotted. Using the upper and lower limits of the allowable temperature range as a reference, draw the first temperature boundary line and the second temperature boundary line in the coordinate system; The region corresponding to the portion of the temperature curve above the first temperature boundary line is designated as the high-temperature region, the region corresponding to the portion below the second temperature boundary line is designated as the low-temperature region, and the region corresponding to the portion between the two boundary lines is designated as the flat-temperature region.

[0012] Furthermore, obtaining the vacuum degree behavior base includes: Obtain the vacuum level data corresponding to the flat temperature region, and calculate the vacuum level characterization value of the flat temperature region; Calculate the average value of all temperature data within the flat temperature region, and use it as the standard temperature value for the flat temperature region. The temperature-vacuum influence coefficient is calculated based on the vacuum degree characterization value of the flat temperature region and the temperature standard value of the flat temperature region. Vacuum degree characterization values ​​for high-temperature and low-temperature regions are obtained respectively, and vacuum degree adjustment ratios for high-temperature and low-temperature regions are calculated based on the temperature vacuum influence coefficient. The average value of the vacuum degree adjustment ratio in the high-temperature region and the vacuum degree adjustment ratio in the low-temperature region is used as the base value for vacuum degree behavior.

[0013] A heat pump evaporator heat exchange anomaly detection system includes: The steam temperature acquisition module is used to collect secondary steam temperature data during the wastewater treatment of the heat pump evaporator at multiple time points in a preset cycle. The temperature characterization processing module is used to process the temperature data and extract temperature characterization data including node anomaly frequency values, node anomaly temperature values, and anomaly interval time values. The vacuum degree analysis module is used to divide the secondary steam temperature into high temperature, flat temperature and low temperature regions according to the temperature change trend, and calculate the vacuum degree behavior base based on the vacuum degree data corresponding to each region. The anomaly analysis module is used to input the temperature characterization data and the vacuum behavior base into a predetermined quantization model to calculate the secondary steam temperature anomaly characterization value, and to determine whether the heat pump evaporator is in an abnormal operating state.

[0014] Furthermore, the vacuum degree analysis module is specifically used for: A coordinate system was constructed with the data acquisition time as the horizontal axis and the temperature as the vertical axis, and the temperature variation curve of the secondary steam was plotted. Using the upper and lower limits of the preset allowable temperature range as a reference, draw the first temperature boundary line and the second temperature boundary line in the coordinate system, and divide the high temperature, flat temperature and low temperature regions accordingly. Vacuum degree data for each region is obtained. The temperature vacuum influence coefficient is calculated based on the flat temperature region. Then, the vacuum degree adjustment ratios for the high temperature region and the low temperature region are calculated separately, and the average of the two is used as the vacuum degree behavior base.

[0015] Beneficial effects: 1. This invention comprehensively analyzes the frequency of node anomalies, the degree of temperature deviation, and the distribution of anomalies in sequence that are directly related to the secondary steam temperature, and combines this with the vacuum behavior baseline that reflects the system's regulation capability. This allows for the comprehensive and accurate capture of subtle deterioration in the operating state, enabling early warning and accurate judgment of abnormal conditions.

[0016] 2. This invention transforms the original experience-based anomaly judgment into objective data indicators by constructing a quantitative secondary steam temperature anomaly characterization value (Ttf) and anomaly dynamic value (RZ). This enables the quantitative classification of the degree of anomaly, providing a precise basis for operation and maintenance decisions.

[0017] 3. The method of the present invention can automatically and in real time complete the status judgment and anomaly classification, which significantly reduces the reliance on human experience and the frequency of manual inspection, enabling maintenance personnel to prioritize the handling of high-risk problems according to the clear anomaly level (such as level 1, level 2, and level 3 anomaly signals), thereby improving the pertinence and overall efficiency of maintenance work.

[0018] 4. By calculating the vacuum adjustment ratio in high-temperature and low-temperature regions, this invention can evaluate the response performance and health status of the vacuum adjustment system of the heat pump evaporator when dealing with temperature fluctuations. This helps to identify potential adjustment lag or component aging problems, thereby ensuring the long-term stability of the system.

[0019] 5. The present invention integrates data acquisition, multi-dimensional analysis and intelligent diagnosis modules, providing a complete technical solution for the automated and intelligent online monitoring and health management of the operating status of heat pump evaporators, and improving the level of intelligent equipment management. Attached Figure Description

[0020] Figure 1 This is a flowchart of the steps in a method for judging heat exchange abnormalities in a heat pump evaporator according to an embodiment of the present invention; Figure 2 This is a flowchart of the heat pump evaporator operation status identification method in the heat pump evaporator heat exchange anomaly judgment method according to an embodiment of the present invention; Figure 3This is a flowchart of a heat pump evaporator heat exchange anomaly judgment system according to an embodiment of the present invention. Detailed Implementation

[0021] Example 1 A method for judging heat exchange abnormalities in a heat pump evaporator, such as Figure 1 As shown, it includes the following steps: The preset cycle is divided into several time nodes, and the secondary steam temperature data during the wastewater treatment of the heat pump evaporator is collected at each time node. The temperature characteristics data of the heat pump evaporator during operation are obtained by processing the secondary steam temperature changes collected at time points within the cycle. Based on the changes in secondary steam temperature over time, the secondary steam temperature is divided into high-temperature, flat-temperature, and low-temperature regions. Vacuum degree behavior base is obtained based on the processing of vacuum degree in different temperature regions. By combining the temperature characterization data of the heat pump evaporator during operation with the vacuum behavior baseline, the abnormal secondary steam temperature characterization value during the wastewater treatment of the heat pump evaporator within the cycle is obtained. The operating status and degree of abnormality of the heat pump evaporator during wastewater treatment were identified based on the anomaly characterization value of the secondary steam temperature.

[0022] Example 2 The secondary steam temperature data during the wastewater treatment process of the heat pump evaporator was acquired within the cycle. Specifically: Divide the cycle into several time nodes; Obtain the secondary steam temperature value corresponding to each time point, and compare the secondary steam temperature values ​​of all time points with the preset secondary steam temperature range. If the secondary steam temperature value at a given time point is outside the preset secondary steam temperature range, that time point will be recorded as a temperature anomaly point. If the secondary steam temperature value at a given time point is within the preset secondary steam temperature range, that time point is recorded as a normal temperature point. The number of temperature abnormal nodes within the period is obtained, and the ratio of the number of temperature abnormal nodes to the total number of time nodes within the period is processed to obtain the node abnormality frequency value. The difference between the secondary steam temperature value corresponding to each temperature anomaly node and the two endpoint temperatures of the preset secondary steam temperature range is processed and the absolute value is taken. The two temperature differences are compared and the smallest temperature difference is selected to obtain the node temperature deviation value. The mean temperature deviation of all abnormal temperature nodes is obtained by summing the node temperature deviation values ​​of all abnormal temperature nodes and taking the average value. The average value of the secondary steam temperature at all normal temperature nodes is obtained by summing the secondary steam temperature values ​​of all normal temperature nodes. The abnormal temperature value of a node is obtained by comparing the average temperature deviation of the abnormal node with the comprehensive temperature value of the normal node. Obtain the adjacent abnormal intervals corresponding to adjacent abnormal temperature nodes within the period, and obtain the number of normal temperature nodes within the adjacent abnormal intervals and the duration of adjacent abnormalities. The ratio of the number of normal temperature nodes within the same adjacent abnormal interval to the duration of adjacent abnormal intervals is calculated to obtain the time ratio of the abnormal interval. The abnormal interval time ratios of all adjacent abnormal intervals are summed to obtain the abnormal interval time value; Through formula The abnormal secondary steam temperature Ttf during the wastewater treatment of the heat pump evaporator within the cycle was calculated, where zk represents the vacuum behavior base number. in, This represents the abnormal temperature value at the node. The square of the node's abnormal temperature value is used to emphasize the magnitude of the node's temperature anomaly. This represents the node anomaly frequency value. This represents the exponential function of the squared node anomaly frequency value, used to emphasize the impact of the node anomaly frequency value; These are time values ​​within the abnormal range. This represents the logarithm of the abnormal interval time value plus 1.01. The larger the abnormal interval time value, the larger the time span between adjacent temperature abnormal nodes. In the cycle, the less time the secondary steam temperature abnormality occupies, indicating that the temperature degree of the heat pump evaporator in the cycle is smaller.

[0023] The threshold value for abnormal secondary steam temperature during wastewater treatment of heat pump evaporator within the preset cycle is ttf. The abnormal secondary steam temperature value Ttf during wastewater treatment of heat pump evaporator within the cycle is compared with the threshold value ttf during wastewater treatment of heat pump evaporator within the cycle. If the secondary steam temperature anomaly characterization value Ttf is greater than or equal to the secondary steam temperature anomaly characterization threshold ttf, it indicates that the secondary steam temperature is abnormal when the heat pump evaporator is treating high-salt wastewater, generating an abnormal operation signal for the heat pump evaporator. If the secondary steam temperature anomaly characterization value Ttf is less than the secondary steam temperature anomaly characterization threshold ttf, it indicates that the secondary steam temperature is normal when the heat pump evaporator is treating high-salt wastewater, and a normal operation signal of the heat pump evaporator is generated.

[0024] The process of obtaining the vacuum degree behavior base is as follows: Obtain the secondary steam temperature values ​​corresponding to all time points within the cycle; A planar coordinate system is constructed with the acquisition time of the secondary steam temperature value as the X-axis and the secondary steam temperature value corresponding to each acquisition time point as the Y-axis. Plot the secondary steam temperature values ​​corresponding to all time points in a plane coordinate system, and connect all the points from left to right in the plane coordinate system with a smooth curve to obtain the secondary steam temperature curve. In the plane coordinate system, draw temperature boundary lines parallel to the X-axis at the two endpoints of the preset secondary steam temperature range to obtain the first temperature boundary line and the second temperature boundary line. It should be noted that the preset secondary steam temperature range is an empirical value, which is set by the staff based on the actual secondary steam temperature range obtained by the heat pump evaporator when treating high-salt wastewater. This is because a higher secondary steam temperature means that more heat can be transferred during the evaporation process. While this may improve evaporation efficiency, in some cases, a higher secondary steam temperature may reduce the energy consumption of the steam compressor. In some special material processing processes, high secondary steam temperatures may cause material changes or degradation. Lower secondary steam temperatures may make the system more stable and reduce failures or downtime caused by overheating, but lower secondary steam temperatures mean less heat is transferred during evaporation, which may reduce evaporation efficiency.

[0025] The region where the secondary steam temperature curve lies above the first temperature boundary line is denoted as the high-temperature region. The region where the secondary steam temperature curve lies below the second temperature boundary line is designated as the low-temperature region. The area between the first and second temperature boundary lines of the secondary steam temperature curve is called the flat temperature area (i.e., the normal secondary steam temperature area). Obtain the duration of the flat temperature region on the secondary steam temperature curve, and record it as the flat temperature duration. Divide the flat temperature duration into several flat temperature periods, obtain the vacuum value of the heat pump evaporator corresponding to the middle moment of each flat temperature period, and integrate them to obtain the vacuum value group of the flat temperature region. The vacuum value of the heat pump evaporator corresponding to each flat temperature period is denoted as RZ, where i is the number of flat temperature periods, i = 1, 2, ..., RZ; According to the formula The standard deviation Za of the vacuum degree value group in the flat temperature region was calculated, where Zp is the average value of the deviation group Z1, Z2, Z3, ..., Zn; If the standard deviation Za of the vacuum degree value group in the flat temperature region is greater than or equal to the preset standard deviation Zy, delete the maximum and / or minimum values ​​in the vacuum degree value group data of the flat temperature region, recalculate the standard deviation Za of the vacuum degree value group data of the flat temperature region, until Za is less than the preset standard deviation Zy, then sum and average the remaining data in the vacuum degree value group of the flat temperature region to obtain the vacuum degree characterization value of the flat temperature region. Obtain the secondary steam temperature values ​​corresponding to all time points within the flat temperature region, sum them, and take the average value to obtain the standard temperature value of the flat temperature region. The temperature-vacuum influence coefficient is obtained by calculating the ratio between the vacuum degree characterization value of the flat temperature region and the temperature standard value of the flat temperature region.

[0026] Obtain the duration of the high-temperature region on the secondary steam temperature curve, and record it as the high-temperature duration. Divide the high-temperature duration into several high-temperature periods and obtain the vacuum value of the heat pump evaporator corresponding to the middle moment of each high-temperature period. The vacuum degree values ​​of the heat pump evaporator corresponding to the midpoint of all high-temperature periods are summed and averaged to obtain the vacuum degree characterization value of the high-temperature region. Obtain the secondary steam temperature values ​​corresponding to all time points within the high-temperature region, sum them, and take the average value to obtain the standard temperature value of the high-temperature region; The theoretical value of vacuum degree in high-temperature region is obtained by multiplying the standard value of temperature change in high-temperature region with the temperature vacuum influence coefficient. The difference between the vacuum degree characterization value and the theoretical vacuum degree of the high-temperature region is calculated, and the absolute value is taken to obtain the vacuum degree adjustment value of the high-temperature region. The vacuum adjustment value of the high-temperature region is calculated by comparing it with the vacuum characterization value of the high-temperature region to obtain the vacuum adjustment ratio of the high-temperature region. Because the secondary steam temperature is high, the heat pump evaporator needs to increase its vacuum level to lower the secondary steam temperature in order to adjust it to the preset temperature range. Increasing the vacuum level reduces the vacuum value of the heat pump evaporator. The vacuum level characterization value obtained in the high-temperature region (actually measured, the smaller the better) is processed with the theoretical vacuum level value of the high-temperature region obtained from the flat temperature region (the vacuum level value obtained without vacuum adjustment of the heat pump evaporator) to obtain the vacuum adjustment value of the high-temperature region (the larger the better). Based on the vacuum adjustment value of the high-temperature region, the vacuum adjustment response speed of the heat pump evaporator is identified. The larger the vacuum adjustment value of the high-temperature region, the faster the vacuum adjustment of the heat pump evaporator, and the better the operating condition of the heat pump evaporator. The smaller the vacuum adjustment value of the high-temperature region, the slower the vacuum adjustment of the heat pump evaporator, the aging or damage of the components used for vacuum adjustment, and the worse the operating condition of the heat pump evaporator.

[0027] The duration of the low-temperature region on the secondary steam temperature curve is obtained and recorded as the low-temperature duration. The low-temperature duration is divided into several low-temperature periods, and the vacuum value of the heat pump evaporator corresponding to the middle time of each low-temperature period is obtained. The vacuum degree values ​​of the heat pump evaporator corresponding to the midpoint of all low-temperature periods are summed and averaged to obtain the vacuum degree characterization value of the low-temperature region. Obtain the secondary steam temperature values ​​corresponding to all time points within the low-temperature region, sum them, and take the average value to obtain the standard temperature value of the low-temperature region; The theoretical value of vacuum degree in the low-temperature region is obtained by multiplying the standard value of temperature change in the low-temperature region with the temperature vacuum influence coefficient. The difference between the vacuum degree characterization value and the theoretical vacuum degree of the low-temperature region is calculated, and the absolute value is taken to obtain the vacuum degree adjustment value of the low-temperature region. The vacuum adjustment value of the low-temperature region is calculated by comparing it with the vacuum characterization value of the low-temperature region to obtain the vacuum adjustment ratio of the low-temperature region. Because the secondary steam temperature is low, the heat pump evaporator needs to reduce its vacuum level to raise the secondary steam temperature in order to adjust it to the preset temperature range. Reducing the vacuum level increases the vacuum value of the heat pump evaporator. The vacuum level characterization value obtained in the low-temperature region (actually measured, the higher the better) is processed with the theoretical vacuum level value of the low-temperature region obtained from the flat temperature region (the vacuum level obtained without vacuum adjustment of the heat pump evaporator) to obtain the vacuum adjustment value of the low-temperature region (the higher the better). Based on the vacuum adjustment value of the low-temperature region, the vacuum adjustment response speed of the heat pump evaporator is identified. The larger the vacuum adjustment value of the low-temperature region, the faster the vacuum adjustment of the heat pump evaporator, and the better the operating condition of the heat pump evaporator. The smaller the vacuum adjustment value of the low-temperature region, the slower the vacuum adjustment of the heat pump evaporator, the aging or damage of the components used for vacuum adjustment, and the worse the operating condition of the heat pump evaporator.

[0028] The vacuum degree adjustment ratio in the low-temperature region is summed with the vacuum degree adjustment ratio in the high-temperature region, and the average value is taken to obtain the vacuum degree behavior base.

[0029] Based on abnormal operation signals of the heat pump evaporator; The difference between the abnormal secondary steam temperature characterization value during the heat pump evaporator wastewater treatment cycle and the abnormal secondary steam temperature characterization threshold during the heat pump evaporator wastewater treatment cycle is calculated to obtain the abnormal secondary steam temperature characterization deviation during the heat pump evaporator wastewater treatment cycle. The ratio of the deviation in the characterization of secondary steam temperature anomaly to the threshold for characterization of secondary steam temperature anomaly is calculated to obtain the deviation ratio for characterization of secondary steam temperature anomaly, denoted as Rw. Through formula The abnormal dynamic value RZ of the heat pump evaporator was calculated, where, This is a preset proportional coefficient. Greater than 0; in, The acquisition process is as follows: There are m sets of historical data. Each set of historical data includes the deviation ratio of the anomaly characterization of secondary steam temperature Rw, the vacuum behavior baseline zk, and the abnormal dynamic value of the heat pump evaporator RZ. A linear model is used to fit m sets of historical data. The prepared historical data is substituted into the selected fitting model for fitting, and the mean of the fitting coefficients is used as the preset scaling factor. .

[0030] Based on the abnormal dynamic values ​​of the heat pump evaporator within a preset period, the operating states of the heat pump evaporator are classified. The state classification process is as follows: See Figure 2 The preset limit values ​​for abnormal dynamic values ​​are RZ1 and RZ2, where RZ1 < RZ2; Among them, the extreme values ​​RZ1 and RZ2 of the abnormal dynamic values ​​are empirical values, obtained based on experience: In the actual process, there are many sets of abnormal dynamic values ​​obtained by processing the deviation ratio of the secondary steam temperature anomaly characterization and the vacuum behavior base. The staff identifies the operating status level of the heat pump evaporator based on these many sets of abnormal dynamic values, thereby obtaining a correspondence between the abnormal dynamic value and the operating status level of the heat pump evaporator. Then, based on the operating status of the heat pump evaporator of the abnormal dynamic value, the threshold of the abnormal dynamic value is derived and divided, thereby obtaining the limit values ​​RZ1 and RZ2 of the abnormal dynamic value. By comparing the limit values ​​of the abnormal dynamic value, the identification of the operating status level of the heat pump evaporator corresponding to the abnormal dynamic value is completed. When RZ < RZ1, it indicates that the abnormality of the heat pump evaporator is low, and a first-level abnormality signal of the heat pump evaporator is obtained. When RZ1≤RZ<RZ2, it indicates that the abnormality of the heat pump evaporator operation is moderate, and a level two abnormality signal of the heat pump evaporator operation is obtained. When RZ≥RZ2, it indicates that the heat pump evaporator is in a high degree of abnormality, and a level three abnormality signal for the heat pump evaporator is obtained. By classifying the operating status levels of heat pump evaporators, it is easier for staff to accurately control the degree of abnormality in the operating status of heat pump evaporators, and to achieve real-time and timely maintenance and handling of heat pump evaporators during operation.

[0031] Example 3 A heat pump evaporator heat exchange anomaly detection system, such as Figure 3As shown, it includes: The steam temperature acquisition module has a preset cycle, which is divided into several time nodes. The steam temperature acquisition module is used to collect secondary steam temperature data during the wastewater treatment of the heat pump evaporator at the time nodes. The temperature characterization module and the temperature characterization processing module are used to process the secondary steam temperature changes collected at time points within the cycle to obtain the temperature characterization data during the operation of the heat pump evaporator. The vacuum degree analysis module divides the secondary steam temperature into high-temperature, flat-temperature, and low-temperature regions based on the changes in secondary steam temperature over time. It then obtains the vacuum degree behavior base value based on the processing of vacuum degree in different temperature regions. The linkage processing module is used to combine the temperature characterization data of the heat pump evaporator during operation with the vacuum behavior baseline to obtain the abnormal secondary steam temperature characterization value during the wastewater treatment of the heat pump evaporator within the cycle. The anomaly identification module identifies the operating status and degree of anomaly of the heat pump evaporator during wastewater treatment based on the anomaly characterization value of the secondary steam temperature.

[0032] In summary, the above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for judging heat exchange abnormalities in a heat pump evaporator, characterized in that, Includes the following steps: The monitoring cycle is preset and divided into multiple time nodes, and the secondary steam temperature data of the heat pump evaporator wastewater treatment at each node is collected. The secondary steam temperature change data within the cycle is processed to extract temperature characterization data containing node anomaly frequency values, node anomaly temperature values, and anomaly interval time values. Based on the temperature change trend of secondary steam, the temperature data is divided into high temperature region, flat temperature region and low temperature region, and the vacuum behavior base is calculated based on the vacuum degree data corresponding to each region. The temperature characterization data is fused with the vacuum behavior base, and the secondary steam temperature anomaly characterization value within the cycle is calculated through a predetermined quantization model. Based on the abnormal secondary steam temperature characterization value, it is possible to identify whether the operating status of the heat pump evaporator is abnormal.

2. The method according to claim 1, characterized in that, The secondary steam temperature anomaly characterization value Ttf The calculation model is as follows: Where zk represents the cardinality of vacuum behavior, This represents the node anomaly frequency value. This refers to abnormal temperature values ​​at the nodes. This represents the time value within the abnormal range.

3. The method according to claim 2, characterized in that, The acquisition of the node anomaly frequency value includes: The secondary steam temperature values ​​at each time point are compared with the preset allowable temperature range, and the number of abnormal points outside the range is counted. The ratio of the number of abnormal nodes to the total number of nodes within a period is taken as the node abnormality frequency value.

4. The method according to claim 2, characterized in that, The acquisition of the abnormal temperature value of the node includes: Calculate the minimum deviation between the temperature value of each abnormal node and the two ends of the allowable temperature range, and use it as the temperature deviation value of that node; The average temperature deviation of all abnormal nodes is obtained by averaging the temperature deviation values ​​of all abnormal nodes. The average temperature value of all normal nodes within the allowable temperature range is taken to obtain the comprehensive temperature value of normal nodes; The ratio of the average temperature deviation of the abnormal node to the comprehensive temperature value of the normal node is taken as the abnormal node temperature value.

5. The method according to claim 2, characterized in that, The acquisition of the time value of the abnormal interval includes: Identify all temporally adjacent temperature anomaly node pairs and determine the adjacent anomaly intervals between each pair of nodes; Count the number of normal temperature nodes contained in each of the adjacent abnormal intervals and the time length of that interval; Calculate the abnormal interval time ratio for each interval, which is the ratio of the number of normal nodes in that interval to the time length. The abnormal interval time value is obtained by summing the abnormal interval time ratios of all adjacent abnormal intervals.

6. The method according to any one of claims 1-5, characterized in that, Methods for dividing regions into high-temperature, neutral-temperature, and low-temperature zones include: A coordinate system was constructed with the data acquisition time as the horizontal axis and the temperature as the vertical axis, and the temperature variation curve of the secondary steam was plotted. Using the upper and lower limits of the allowable temperature range as a reference, draw the first temperature boundary line and the second temperature boundary line in the coordinate system; The region corresponding to the portion of the temperature curve above the first temperature boundary line is designated as the high-temperature region, the region corresponding to the portion below the second temperature boundary line is designated as the low-temperature region, and the region corresponding to the portion between the two boundary lines is designated as the flat-temperature region.

7. The method according to claim 6, characterized in that, The acquisition of the vacuum degree behavior base includes: Obtain the vacuum level data corresponding to the flat temperature region, and calculate the vacuum level characterization value of the flat temperature region; Calculate the average value of all temperature data within the flat temperature region, and use it as the standard temperature value for the flat temperature region. The temperature-vacuum influence coefficient is calculated based on the vacuum degree characterization value of the flat temperature region and the temperature standard value of the flat temperature region. Vacuum degree characterization values ​​for high-temperature and low-temperature regions are obtained respectively, and vacuum degree adjustment ratios for high-temperature and low-temperature regions are calculated based on the temperature vacuum influence coefficient. The average value of the vacuum degree adjustment ratio in the high-temperature region and the vacuum degree adjustment ratio in the low-temperature region is used as the base value for vacuum degree behavior.

8. A heat pump evaporator heat exchange anomaly detection system, characterized in that, include: The steam temperature acquisition module is used to collect secondary steam temperature data during the wastewater treatment of the heat pump evaporator at multiple time points in a preset cycle. The temperature characterization processing module is used to process the temperature data and extract temperature characterization data including node anomaly frequency values, node anomaly temperature values, and anomaly interval time values. The vacuum degree analysis module is used to divide the secondary steam temperature into high temperature, flat temperature and low temperature regions according to the temperature change trend, and calculate the vacuum degree behavior base based on the vacuum degree data corresponding to each region. The anomaly analysis module is used to input the temperature characterization data and the vacuum behavior base into a predetermined quantization model to calculate the anomaly characterization value of the secondary steam temperature, and to determine whether the heat pump evaporator is in an abnormal operating state.

9. The system according to claim 8, characterized in that, The vacuum degree analysis module is specifically used for: A coordinate system was constructed with the data acquisition time as the horizontal axis and the temperature as the vertical axis, and the temperature variation curve of the secondary steam was plotted. Using the upper and lower limits of the preset allowable temperature range as a reference, draw the first temperature boundary line and the second temperature boundary line in the coordinate system, and divide the high temperature, flat temperature and low temperature regions accordingly. Vacuum degree data for each region is obtained. The temperature vacuum influence coefficient is calculated based on the flat temperature region. Then, the vacuum degree adjustment ratios for the high temperature region and the low temperature region are calculated separately, and the average of the two is used as the vacuum degree behavior base.

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