Fault Diagnosis Method for Water-Cooled Precision Air Conditioning Units

Abstract

The present application relates to the technical field of fault diagnosis of air-conditioning units, and specifically to a method for fault diagnosis of water-cooled precision air-conditioning units. When applied, the present application can perform multi-dimensional diagnosis, combining compression conditions, compressor vibration, and evaporation and condensation data, covering electrical, mechanical, and thermal system faults. False alarms are eliminated through time correlation, thereby improving diagnostic reliability. Moreover, after calculating the correlation quantity, the correlation between each fault can be quantitatively analyzed, and different levels of fault diagnosis evaluation can be performed for different correlation quantities. The focus can be on monitoring signals with high correlation quantities, and higher priority and more computing power can be provided for signal monitoring with high correlation quantities. The present application significantly improves the fault detection rate and diagnostic efficiency of precision air-conditioning units, performs correlation evaluation on each fault, and can perform multi-dimensional diagnostic evaluation on the fault.

Description

Technical Field

[0001] The present application relates to the technical field of air-conditioning unit fault diagnosis, and in particular to a method for diagnosing faults of water-cooled precision air-conditioning units. Background Art

[0002] Traditional air-conditioning fault diagnosis methods mainly rely on single sensor data for threshold judgment, which makes it difficult to cope with fault diagnosis needs under complex working conditions. Since the various components of the precision air-conditioning system are interrelated during operation, the failures of core components such as compressors, evaporators and condensers are often coupled, and the existing technology lacks collaborative analysis of multi-source data and fault correlation evaluation, resulting in high false alarm rates, inaccurate fault location, delayed maintenance response and other problems. Especially in scenarios such as data centers that have strict requirements on temperature control stability, traditional methods have difficulty in timely detection of early hidden faults and difficulty in providing effective risk level assessment for operation and maintenance decisions, which seriously affects the reliable operation and maintenance efficiency of the air-conditioning system. In the fault diagnosis of water-cooled precision air-conditioning units, how to solve the problem of overly single diagnostic results and lack of correlation detection between different signals in traditional detection methods is a technical problem that needs to be solved in this field. Summary of the Invention

[0003] In view of this, the present application provides a water-cooled precision air-conditioning unit fault diagnosis method, which can solve the problems in traditional detection methods of overly single diagnostic results and lack of correlation detection between different signals.

[0004] In the first aspect, the present application provides a fault diagnosis method for a water-cooled precision air-conditioning unit, comprising: obtaining the compression operating condition of the compressor; comparing the compression operating condition with a first standard operating condition to generate a compression abnormality signal; obtaining vibration data of the compressor; generating a corresponding mechanical fault signal based on the vibration data and the second standard operating condition; obtaining the evaporation and condensation operating conditions of the evaporator and condenser; generating a corresponding evaporation and condensation prompt signal based on the evaporation and condensation operating condition and the third standard operating condition; tracing back a preset historical time length based on the current moment to retrieve all the compression abnormality signals, the mechanical fault signals and the evaporation and condensation prompt signals; comparing the occurrence moments of the compression abnormality signal, the mechanical fault signal and the evaporation and condensation prompt signal to calculate the occurrence correlation quantity between the signals; and generating signal risk assessment data based on the occurrence correlation quantity.

[0005] In combination with the first aspect, in a possible implementation, obtaining the compression condition of the compressor includes: obtaining the compressor exhaust pressure and the compressor intake pressure; and obtaining a detected compression ratio based on the compressor exhaust pressure and the compressor intake pressure; comparing the compression condition with the first standard condition to generate a compression abnormality signal includes: obtaining a design compression ratio of the compressor of the air-conditioning unit; and generating a compression ratio abnormality signal if the difference between the detected compression ratio and the design compression ratio is greater than a preset compression difference.

[0006] In combination with the first aspect, in a possible implementation, obtaining the compression operating condition of the compressor includes: obtaining the compressor suction port pressure and the compressor suction port temperature; calling the corresponding saturation temperature according to the compressor suction port pressure; comparing the compression operating condition with the first standard operating condition to generate a compression abnormality signal includes: obtaining a reference temperature according to the saturation temperature and the corrected temperature; if the compressor suction port temperature is lower than the reference temperature, generating a liquid hammer risk signal.

[0007] In combination with the first aspect, in a possible implementation method, obtaining the compression operating condition of the compressor includes: obtaining the actual power of the compressor and monitoring the compressor speed in real time; comparing the compression operating condition with the first standard operating condition and generating a compression abnormality signal includes: if the actual power exceeds the preset amplitude of the rated power, generating a power abnormality signal to compare the compressor speed and the rated speed; if the fluctuation of the compressor speed relative to the rated speed exceeds a preset fluctuation threshold, generating a speed abnormality signal.

[0008] In combination with the first aspect, in a possible implementation, generating a corresponding mechanical fault signal based on the vibration data and the second standard operating condition includes: converting the vibration data of the time domain signal into frequency domain data; extracting a first spectrum at 1.5 times the rotation frequency and a second spectrum at 3 times the rotation frequency based on the frequency domain data; if the peak value of the first spectrum is greater than a first preset peak value, generating a bearing inner ring fault signal; and if the peak value of the second spectrum is greater than a second preset peak value, generating a roller fault signal.

[0009] In combination with the first aspect, in a possible implementation, the obtaining of the evaporation and condensation operating conditions of the evaporator and the condenser includes: obtaining the evaporator outlet temperature, the evaporator line pressure, the condenser outlet temperature and the condenser line pressure; the generating of the corresponding evaporation and condensation prompt signal according to the evaporation and condensation operating conditions and the third standard operating condition includes: retrieving the evaporator saturation temperature corresponding to the evaporator line pressure, retrieving the condenser saturation temperature corresponding to the condenser line pressure; obtaining the evaporator superheat according to the evaporator outlet temperature and the evaporator saturation temperature; obtaining the evaporator superheat according to the condenser outlet temperature and the condenser saturation temperature Obtain the condenser subcooling; if the evaporator superheat is greater than a first superheat and the evaporator pipeline pressure is lower than a first pressure standard value, generate a refrigerant shortage signal; if the condenser subcooling is less than a second superheat and the condenser pipeline pressure is higher than the second pressure standard value, generate a refrigerant excess signal; and if the evaporator superheat, the evaporator pipeline pressure, the condenser subcooling and the condenser pipeline pressure are all within a threshold fluctuation range; if the evaporator superheat is less than or equal to the first superheat, and the condenser subcooling is greater than or equal to the second superheat, generate a charging normal signal.

[0010] In combination with the first aspect, in a possible implementation, obtaining the evaporation and condensation operating conditions of the evaporator and condenser includes: obtaining the condenser inlet temperature and the condenser outlet temperature; generating the corresponding evaporation and condensation prompt signal based on the evaporation and condensation operating conditions and the third standard operating conditions includes: calculating the condenser inlet and outlet temperature difference based on the condenser inlet temperature and the condenser outlet temperature; if the condenser inlet and outlet temperature difference is less than a first preset temperature difference, generating a refrigerant shortage signal and / or a scaling signal; and if the condenser inlet and outlet temperature difference is greater than a second preset temperature difference, generating a refrigerant temperature too low signal and / or a refrigerant flow too large signal.

[0011] In combination with the first aspect, in a possible implementation, obtaining the evaporation and condensation operating conditions of the evaporator and condenser includes: obtaining the condenser inlet pressure and the condenser outlet pressure; generating the corresponding evaporation and condensation prompt signal based on the evaporation and condensation operating conditions and the third standard operating conditions includes: if the condenser inlet pressure is greater than the first preset pressure, generating a refrigerant excess signal and / or a condenser blockage signal; and if the condenser outlet pressure is less than the second preset pressure, generating a refrigerant leakage signal and / or an expansion valve opening abnormality signal.

[0012] In combination with the first aspect, in a possible implementation method, obtaining the evaporation and condensation operating conditions of the evaporator and condenser includes: adjusting the air-conditioning unit to a set standard operating condition and running it for more than a preset standard time; controlling the thermal imager to be perpendicular to the condenser surface at a preset distance to collect temperature data of the heat exchanger tube bundle area; and dividing the heat exchanger tube bundle area into multiple cell areas; generating corresponding evaporation and condensation prompt signals according to the evaporation and condensation operating conditions and the third standard operating conditions includes: if the temperature change of adjacent cell areas is greater than a preset temperature difference gradient, a refrigerant cross-flow signal is generated; a first number of the cell areas are formed into a test area, and if the temperature difference of the test area is greater than a preset local temperature difference, a refrigerant cross-flow signal is generated; and if the standard deviation of the temperature data of the entire heat exchanger tube bundle area is greater than the third preset temperature difference, a refrigerant cross-flow signal is generated.

[0013] In combination with the first aspect, in a possible implementation method, the comparing the occurrence moments of the compression abnormality signal, the mechanical fault signal and the evaporation and condensation prompt signal, and calculating the occurrence correlation quantity between the signals include: within the historical preset time length, if two or more signals within the preset unit time length occur simultaneously, the corresponding signals are counted as one occurrence correlation quantity; the generating of signal risk assessment data based on the occurrence correlation quantity includes: generating a corresponding fault risk level based on the corresponding occurrence correlation quantities of the compression abnormality signal, the mechanical fault signal and the evaporation and condensation prompt signal.

[0014] Based on the above technical solution, the present invention has the following beneficial effects:

[0015] The present invention performs fault detection on compression conditions, compressor vibration, and evaporation and condensation data, comprehensively covering electrical, mechanical, and thermal system faults, and conducting multi-dimensional diagnostic assessments. It also correlates historical data to avoid single-point false alarms, analyzes fault development trends, and can identify intermittent faults or cumulative damage.

[0016] The present invention calculates the temporal correlation of statistical signals and can eliminate isolated abnormal faults through correlation analysis, thereby focusing on the real fault chain. It quantifies the causal probability between faults through temporal correlation and improves diagnostic reliability.

[0017] The present invention eliminates false alarms through time correlation and improves diagnostic reliability. Moreover, after calculating the correlation quantity, it can quantitatively analyze the correlation between various faults, perform different levels of fault diagnosis evaluation for different correlation quantities, and focus on monitoring signals with high correlation quantities, providing higher priority and more computing power for signal monitoring with high correlation quantities, thereby significantly improving the fault detection rate and diagnostic efficiency of precision air-conditioning units. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1FIG2 is a schematic diagram of the method steps of a water-cooled precision air-conditioning unit fault diagnosis method provided by an embodiment of the present application;

[0019] Figure 2 FIG2 is a schematic diagram of steps of a method for detecting an abnormal compression ratio signal provided by an embodiment of the present application;

[0020] Figure 3 FIG2 is a schematic diagram of a method for detecting a liquid hammer risk signal according to an embodiment of the present application;

[0021] Figure 4 FIG2 is a schematic diagram of steps of a method for detecting abnormal speed signal of a power compressor provided by an embodiment of the present application;

[0022] Figure 5 FIG2 is a schematic diagram of a method for detecting a bearing inner race fault signal and a roller fault signal according to an embodiment of the present application;

[0023] Figure 6 FIG2 is a schematic diagram of a method for detecting a refrigerant shortage signal, a refrigerant excess signal, and a normal charging signal provided by an embodiment of the present application;

[0024] Figure 7 1. A schematic diagram of the steps of a method for detecting a refrigerant shortage signal and / or a scaling signal, a refrigerant temperature too low signal and / or a refrigerant flow too large signal provided by an embodiment of the present application;

[0025] Figure 8 FIG2 is a schematic diagram of steps of a method for detecting a refrigerant excess signal and / or a condenser blockage signal, a refrigerant leakage signal and / or an abnormal expansion valve opening signal provided by an embodiment of the present application;

[0026] Figure 9 FIG2 is a schematic diagram of a method for detecting a refrigerant cross-flow signal according to an embodiment of the present application;

[0027] Figure 10 FIG2 is a schematic diagram of a method for calculating correlation values ​​and matching fault risk levels provided in one embodiment of the present application. DETAILED DESCRIPTION

[0028] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.

[0029] Figure 1The figure shows a method step diagram of a water-cooled precision air-conditioning unit fault diagnosis method provided by an embodiment of the present application. The present application provides a water-cooled precision air-conditioning unit fault diagnosis method. In one embodiment, as Figure 1 As shown, the fault diagnosis method of the water-cooled precision air-conditioning unit includes:

[0030] Step 110: Obtain the compression working condition of the compressor.

[0031] In this step, sensors collect key compressor operating parameters in real time, such as suction / discharge pressure, temperature, power, and compressor speed, providing a data foundation for subsequent fault diagnosis. This step ensures that the data covers the compressor's core operating status and reflects its actual operating efficiency and health.

[0032] Step 120: Compare the compression operating condition with the first standard operating condition and generate a compression abnormality signal.

[0033] In this step, the collected data is compared with the preset standard operating conditions to identify anomalies that deviate from normal values. Generating anomaly signals can trigger early warnings and avoid cascading failures caused by abnormal compressor operating conditions.

[0034] Step 130: Acquire vibration data of the compressor.

[0035] In this step, vibration sensors (such as accelerometers) collect the mechanical vibration spectrum, which can reveal mechanical faults such as bearing wear and rotor imbalance. Vibration analysis can detect hidden mechanical damage and improve the comprehensiveness of fault diagnosis.

[0036] Step 140: Generate a corresponding mechanical fault signal according to the vibration data and the second standard working condition.

[0037] In this step, vibration characteristics (such as amplitude and frequency content) are compared with a standard healthy vibration model to locate the specific fault type. Unlike the electrical anomaly analysis in step 120, this step can detect mechanical faults, improving diagnostic accuracy.

[0038] Step 150: Obtain the evaporation and condensation operating conditions of the evaporator and condenser.

[0039] In this step, key parameters of the evaporator and condenser are collected, such as the temperature of specific components of the evaporator, the operating conditions of the evaporator pipelines, the temperature of specific components of the condenser, the operating conditions of the condenser pipelines, etc., which can be used to evaluate the refrigerant status, etc.

[0040] Step 160: Generate a corresponding evaporation and condensation prompt signal according to the evaporation and condensation operating condition and the third standard operating condition.

[0041] In this step, a prompt signal is generated based on the evaporation and condensation working conditions, which can help determine whether the root cause of the fault is due to refrigerant factors rather than the compressor itself.

[0042] Step 170: Look back to the preset historical time period at the current moment to retrieve all compression abnormality signals, mechanical failure signals, and evaporation and condensation prompt signals.

[0043] In this step, historical data is correlated (for example, historical records with a preset time period of 3, 6, 12, or 24 hours) to avoid single-point false alarms and analyze fault development trends. Time series analysis can identify intermittent faults or cumulative damage (such as slowly increasing vibration).

[0044] Step 180 : Compare the occurrence times of the compression abnormality signal, the mechanical failure signal, and the evaporation and condensation prompt signal, and calculate the occurrence correlation between the signals.

[0045] In this step, the temporal correlation of the signals is statistically analyzed, such as whether the vibration fault is accompanied by evaporation and condensation abnormalities, and the causal probability between faults is quantified. Through correlation analysis, isolated abnormal faults can be eliminated, thereby focusing on the real high-frequency fault chain.

[0046] Step 190: Generate signal risk assessment data based on the occurrence correlation quantity.

[0047] In this step, the risk assessment of the integrated multi-signal correlation output can be used to perform hierarchical diagnostic fault assessment based on the correlation frequency of each signal, and can give priority to predictive maintenance monitoring and focused maintenance monitoring for faults with high correlation.

[0048] When this embodiment is applied, it can perform multi-dimensional diagnosis, combining compression conditions, compressor vibration, evaporation and condensation data, covering electrical, mechanical, and thermal system faults. The causal probability between faults is quantified through time correlation, thereby improving diagnostic reliability. After calculating the correlation quantity, different levels of fault diagnosis evaluation can be performed on different correlation quantities, and the focus can be on monitoring signals with high correlation quantities, which can provide higher priority and more computing power for signal monitoring with high correlation quantities. This method significantly improves the fault detection rate and diagnostic efficiency of precision air-conditioning units, performs correlation evaluation on each fault, and can perform multi-dimensional diagnostic evaluation on the fault.

[0049] Figure 2 FIG. 1 is a schematic diagram of a method for detecting an abnormal compression ratio signal according to an embodiment of the present application. Figure 2 As shown, step 110 includes:

[0050] Step 1101: Obtain the compressor exhaust pressure and the compressor intake pressure.

[0051] In this step, pressure sensors collect real-time pressure at the exhaust and intake ports, reflecting the compressor's actual workload and the refrigerant cycle status. Compared to inferring pressure from current or temperature, direct measurement avoids the cumulative errors caused by indirect data conversion, resulting in more reliable data.

[0052] Step 1102: derive a compression ratio based on the compressor exhaust pressure and the compressor intake pressure.

[0053] In this step, the compression ratio is calculated by dividing the compressor exhaust pressure by the compressor suction pressure. The compression ratio can reflect the matching degree between the compressor's work capacity and the system resistance.

[0054] Step 120 includes:

[0055] Step 1201: Obtain the design compression ratio of the compressor of the air-conditioning unit.

[0056] In this step, the design compression ratio is retrieved from the compressor design parameters, such as the standard value given by the manufacturer, as an objective benchmark for fault judgment, avoiding the subjectivity of the empirical threshold.

[0057] Step 1202: If the difference between the detected compression ratio and the designed compression ratio is greater than the preset compression difference, a compression ratio abnormality signal is generated.

[0058] In this step, the allowable fluctuation range is defined by presetting the compression difference (e.g., ±10%) to avoid false alarms caused by fluctuations in normal operating conditions (e.g., start-stop transients). This allows the detection of significantly abnormal compression ratios to be captured and generates a compression ratio abnormality signal, which can be used for alarm, recording, and analysis.

[0059] This embodiment can monitor the compression ratio and analyze the compression ratio abnormality signal in the compression abnormality signal. The compression ratio abnormality is directly related to the core failure of the compressor (such as valve leakage, system blockage). Through this embodiment, the compression ratio abnormality signal can be analyzed for correlation with the mechanical failure signal and the evaporation and condensation prompt signal.

[0060] Figure 3 FIG. 1 is a schematic diagram of a method for detecting a liquid hammer risk signal according to an embodiment of the present application. Figure 3 As shown, step 110 includes:

[0061] Step 1103: Obtain the compressor suction port pressure and the compressor suction port temperature.

[0062] In this step, the state of the air intake is collected in real time through the pressure sensor and temperature sensor to provide a data basis for liquid hammer judgment.

[0063] Step 1104: derive the corresponding saturation temperature according to the compressor suction port pressure.

[0064] In this step, the saturation temperature corresponding to different inlet pressures is pre-set. This can be the boiling point of the refrigerant at that inlet pressure. The saturation temperature is a critical threshold for determining whether the refrigerant is fully vaporized. If the inlet temperature is lower than this value, there may be unevaporated liquid refrigerant.

[0065] Step 120 includes:

[0066] Step 1203: Obtain a reference temperature according to the saturation temperature and the correction temperature.

[0067] In this step, the saturation temperature is offset and adjusted (e.g., +2°C) based on system characteristics (e.g., pipeline heat loss, sensor error) to avoid misjudgment due to differences between theoretical values ​​and actual operating conditions.

[0068] Step 1204: If the compressor suction port temperature is lower than the reference temperature, a liquid hammer risk signal is generated.

[0069] In this step, if the suction port temperature falls below the reference temperature, the refrigerant is not fully vaporized, and liquid refrigerant may enter the compressor, posing a risk of liquid hammer. Once a liquid hammer risk signal is generated, an audible and visual alarm or control system linkage prompts the operator to adjust the expansion valve opening or check the evaporator liquid supply. Alternatively, the compressor load can be reduced or intermittent operation can be initiated to prevent liquid refrigerant from impacting the cylinder, leading to mechanical failures such as valve plate breakage and bearing damage.

[0070] When this embodiment is applied, the saturation temperature comparison based on thermodynamic principles is more reliable than relying solely on a single parameter of temperature or pressure. By correcting the temperature to adapt to different system configurations (such as long pipelines and high superheat requirements), the limitations of the reference temperature are avoided. This embodiment can issue an early warning before the liquid refrigerant actually enters the compressor to avoid irreversible mechanical damage. For example, when the refrigerant supply on the evaporator side is too much (such as an expansion valve failure), it may cause the suction port temperature to drop rapidly. A liquid shock risk signal can be generated before the liquid shock occurs, thus buying critical time for system adjustment. This embodiment improves the defense capability of precision air-conditioning units against liquid shock, a malicious fault, and is particularly suitable for computer room air-conditioning systems with high reliability requirements. Through this embodiment, the liquid shock risk signal can be analyzed for correlation with the mechanical failure signal and the evaporation and condensation prompt signal.

[0071] Figure 4 FIG. 1 is a schematic diagram of a method for detecting abnormal power and speed signals of a compressor according to an embodiment of the present application. Figure 4 As shown, step 110 includes:

[0072] Step 1105: Acquire the actual power of the compressor and monitor the compressor speed in real time.

[0073] In this step, the speed of the compressor when the compressor is operating power is directly measured by a current, voltage and speed sensor or a power meter to reflect its actual load state.

[0074] Step 120 includes:

[0075] Step 1205: Compare the compressor speed with the rated speed. If the fluctuation of the compressor speed relative to the rated speed exceeds a preset fluctuation threshold, generate a speed abnormality signal. If the actual power exceeds the preset amplitude of the rated power, generate a power abnormality signal.

[0076] In this step, an alarm is triggered when the actual compressor speed exceeds the preset amplitude (settable to ±15%) of the rated power speed to a certain extent. This prevents the compressor from burning out or shortening its life due to long-term abnormal speed and overload. Abnormal speed may be caused by factors such as control system failure, sensor abnormality, mechanical component problems, electrical failure, or external environmental influences. Excessive power may be caused by poor condenser heat dissipation, excessive refrigerant, or increased mechanical friction (such as poor lubrication). Excessive power may indicate a refrigerant leak, insufficient suction pressure, or internal wear of the compressor (such as a leaky valve). Frequency reduction, deceleration, or shutdown can be executed to avoid serious accidents caused by prolonged abnormal power. Abnormal power may be caused by mechanical failure (such as bearing seizure), electrical problems (such as motor winding short circuit), or system-side abnormalities (such as excessive condensing pressure). Through this embodiment, the power abnormality signal can be analyzed for correlation with the mechanical fault signal and the evaporation and condensation prompt signal. Specifically, if the compressor speed is lower than 95% of the rated speed and lasts for more than 10 seconds, an insufficient speed signal is generated; if the compressor speed is higher than 105% of the rated speed and lasts for more than 10 seconds, a speed overload signal is generated; if the compressor speed fluctuates by more than ±8% within 1 minute, a speed instability signal is generated.

[0077] Figure 5 FIG. 1 is a schematic diagram of a method for detecting a bearing inner ring fault signal and a roller fault signal according to an embodiment of the present application. Figure 5 As shown, step 140 includes:

[0078] Step 1401: Convert the vibration data of the time domain signal into frequency domain data.

[0079] In this step, the time-domain vibration waveform is converted into a frequency-domain spectrum using a Fourier transform (FFT). This highlights the frequency components of the vibration signal and facilitates the identification of periodic fault characteristics. Frequency-domain analysis filters out random noise and focuses on characteristic frequencies associated with mechanical faults, such as bearing defect frequencies and roller imbalance frequencies.

[0080] Step 1402: Extract a first spectrum at 1.5 times the rotation frequency and a second spectrum at 3 times the rotation frequency based on the frequency domain data.

[0081] In this step, fault characteristics were located: 1.5 times the revolution frequency is the characteristic frequency component of bearing inner race faults (such as cracks and spalling); 3 times the revolution frequency is the characteristic frequency component of rolling element roller faults (such as wear and chipping). By focusing on specific frequency spectra, the complexity of full spectrum analysis is avoided, improving diagnostic efficiency.

[0082] Step 1403: If the peak value of the first spectrum is greater than a first preset peak value, a bearing inner race fault signal is generated.

[0083] In this step, when the peak value of the first spectrum corresponding to 1.5 times the rotational frequency exceeds a threshold, for example, exceeds 3 times the historical baseline value, it is determined that there is local damage to the inner ring of the bearing, and a fault signal is triggered.

[0084] Step 1404: If the peak value of the second spectrum is greater than the second preset peak value, a roller fault signal is generated.

[0085] In this step, when the peak value of the second spectrum corresponding to 3 times the rotational frequency exceeds a threshold, for example, exceeds three times the historical baseline value, it is determined that the roller is worn or missing, and timely maintenance can prevent the bearing from getting stuck.

[0086] Through this embodiment, the correlation analysis between the bearing inner ring fault signal, the roller fault signal, the compression abnormality signal, and the evaporation and condensation prompt signal can be performed.

[0087] Figure 6 The figure shows a method for detecting a refrigerant shortage signal, a refrigerant excess signal, and a normal charging signal according to an embodiment of the present application. Figure 6 As shown, step 150 includes:

[0088] Step 1501: Obtain the evaporator outlet temperature, evaporator line pressure, condenser outlet temperature, and condenser line pressure.

[0089] In this step, temperature and pressure sensors monitor the evaporator and condenser outlet conditions and line pressures in real time, fully reflecting the refrigerant's phase change process within the heat exchanger. The evaporator outlet temperature and evaporator line pressure correlate with the refrigerant's heat absorption, while the condenser outlet temperature and condenser line pressure correlate with the refrigerant's heat dissipation, providing a data foundation for subsequent superheat / subcooling calculations.

[0090] Step 160 includes:

[0091] Step 1601: retrieve the evaporator saturation temperature corresponding to the evaporator pipeline pressure, and retrieve the condenser saturation temperature corresponding to the condenser pipeline pressure.

[0092] In this step, the measured pressure is converted to a theoretical saturation temperature based on refrigerant physical properties (such as a pressure-saturation temperature table or equation). This serves as a benchmark for determining whether the refrigerant phase change is complete. The saturation temperature changes in real time with pressure, avoiding false positives caused by fixed thresholds (for example, a normal increase in condensing pressure in the condenser line under high load).

[0093] Step 1602: Obtain the evaporator superheat according to the evaporator outlet temperature and the evaporator saturation temperature.

[0094] In this step, superheat = evaporator outlet temperature - evaporator saturation temperature, which reflects whether the refrigerant in the evaporator is completely evaporated.

[0095] Step 1603: Obtain condenser subcooling according to the condenser outlet temperature and the condenser saturation temperature.

[0096] In this step, subcooling degree = condenser saturation temperature - condenser outlet temperature, which reflects whether the refrigerant in the condenser is fully condensed.

[0097] Step 1604: If the evaporator superheat is greater than the first superheat and the evaporator pipeline pressure is lower than the first pressure standard value, a refrigerant shortage signal is generated.

[0098] In this step, if the evaporator superheat exceeds the specified value (e.g., >10°C) and the evaporator line pressure falls below a first pressure threshold (e.g., 0.6 MPa), this indicates that the refrigerant in the evaporator has completely evaporated prematurely, possibly due to leakage or insufficient recharge. Once a refrigerant shortage signal is triggered, a refrigerant shortage signal and / or scaling signal can be generated to initiate refrigerant replenishment or restrict compressor operation to prevent compressor overheating due to refrigerant shortage.

[0099] Step 1605: If the condenser subcooling degree is less than the second superheating degree and the condenser line pressure is higher than the second pressure standard value, a refrigerant excess signal is generated.

[0100] In this step, if the condenser subcooling temperature is too low (e.g., <3°C) and the condenser line pressure is greater than a second pressure threshold (e.g., 0.8 MPa), this indicates insufficient liquid refrigerant in the condenser, possibly due to overcharging or decreased condensing efficiency. Triggering the refrigerant excess signal prevents excess refrigerant from flowing back into the compressor, causing liquid hammer or excessive condensing pressure in the condenser line.

[0101] Step 1606: If the evaporator superheat, the evaporator line pressure, the condenser subcooling, and the condenser line pressure are all within the threshold fluctuation range, if the evaporator superheat is less than or equal to the first superheat, and the condenser subcooling is greater than or equal to the second superheat, then a normal charging signal is generated.

[0102] In this step, if the evaporator superheat, evaporator line pressure, condenser subcooling, and condenser line pressure are all within reasonable ranges, the refrigerant charge and system operation are considered normal and no intervention is required. This provides a quantitative basis for periodic maintenance, eliminating the need to blindly adjust the refrigerant inventory.

[0103] Through this embodiment, the correlation analysis of the compression abnormality signal, mechanical failure signal, refrigerant shortage signal, and refrigerant excess signal can be performed. If two or more signals occur simultaneously within a preset unit time, the corresponding signals are counted as one occurrence of correlation.

[0104] Figure 7 The figure shows a method for detecting a refrigerant shortage signal and / or a fouling signal, a refrigerant temperature too low signal and / or a refrigerant flow too large signal provided by an embodiment of the present application. Figure 7 As shown, step 150 includes:

[0105] Step 1502: Obtain the condenser inlet temperature and the condenser outlet temperature.

[0106] In this step, temperature sensors collect real-time condenser inlet and outlet temperatures, reflecting the heat exchange efficiency of the condensation process. The condenser inlet temperature reflects the compressor exhaust status, while the condenser outlet temperature reflects the condensation effect, providing basic data for temperature difference analysis.

[0107] Step 160 includes:

[0108] Step 1607: Calculate the condenser inlet and outlet temperature difference based on the condenser inlet temperature and the condenser outlet temperature.

[0109] In this step, a temperature differential is quantified, calculating the condenser inlet and outlet temperature difference (the condenser inlet temperature minus the condenser outlet temperature). This directly reflects the refrigerant's ability to dissipate heat within the condenser. A reasonable temperature differential (e.g., 5-15°C) indicates normal condenser heat exchange efficiency. Temperature differentials outside this range indicate a system fault or abnormal operating condition.

[0110] Step 1608: If the temperature difference between the inlet and outlet of the condenser is less than the first preset temperature difference, a refrigerant shortage signal and / or a fouling signal is generated.

[0111] In this step, a small temperature difference between the condenser inlet and outlet (e.g., <3°C) may be caused by insufficient refrigerant flow, leading to premature cooling of the refrigerant in the condenser. This may be caused by insufficient refrigerant or refrigerant scaling, which in turn leads to insufficient heat dissipation. Subsequently, the condenser can be cleaned or the refrigerant charge checked based on the refrigerant insufficiency and / or scaling signals.

[0112] Step 1609: If the temperature difference between the inlet and outlet of the condenser is greater than the second preset temperature difference, a refrigerant temperature too low signal and / or a refrigerant flow too high signal is generated.

[0113] In this step, a large temperature difference between the condenser inlet and outlet (e.g., the second preset temperature difference is set to 20°C) may be caused by low cooling water / air temperature (e.g., low ambient temperature in winter). This may be due to a low refrigerant temperature signal and / or an excessive refrigerant flow signal, leading to excessive condensation. Subsequently, based on the low refrigerant temperature signal and / or the excessive refrigerant flow signal, the refrigerant flow rate can be controlled or the expansion valve opening adjusted to optimize system operation.

[0114] Through this embodiment, correlation analysis can be performed on the compression abnormality signal, the mechanical failure signal, the refrigerant shortage signal and / or the fouling signal, the refrigerant temperature is too low signal and / or the refrigerant flow rate is too large signal.

[0115] Figure 8 FIG. 1 is a schematic diagram of a method for detecting a refrigerant excess signal and / or a condenser blockage signal, a refrigerant leakage signal and / or an abnormal expansion valve opening signal provided by an embodiment of the present application. Figure 8 As shown, step 150 includes:

[0116] Step 1503: Obtain the condenser inlet pressure and the condenser outlet pressure.

[0117] In this step, pressure sensors collect real-time refrigerant pressure at the condenser's inlet and outlet, reflecting the high-pressure system status. Inlet pressure correlates with compressor exhaust performance, while outlet pressure correlates with condensation effectiveness and subsequent throttling, providing data support for pressure anomaly diagnosis.

[0118] Step 160 includes:

[0119] Step 1610: If the condenser inlet pressure is greater than a first preset pressure, a refrigerant excess signal and / or a condenser blockage signal is generated.

[0120] In this step, if the inlet pressure is too high, such as if the first preset pressure exceeds the system's rated value by 15%, it may be due to excessive accumulation of liquid refrigerant in the condenser or condenser blockage, resulting in reduced heat dissipation efficiency. When the refrigerant excess and / or condenser blockage signal is triggered, refrigerant recovery or condenser cleaning can be performed to avoid a high-pressure shutdown of the compressor.

[0121] Step 1611: If the condenser outlet pressure is less than a second preset pressure, a refrigerant leakage signal and / or an expansion valve opening abnormality signal is generated.

[0122] In this step, if the condenser outlet pressure is too low, for example, the second preset pressure is 20% lower than the system's set rated value, this may be due to refrigerant leakage and / or abnormal expansion valve opening, resulting in insufficient system circulation, excessive expansion valve opening, or control failure. Triggering a refrigerant leakage signal and / or abnormal expansion valve opening signal can generate a leak detection alarm or expansion valve calibration prompt to prevent continued deterioration of system efficiency.

[0123] Through this embodiment, correlation analysis can be performed on the compression abnormality signal, the mechanical failure signal, the refrigerant excess signal, and / or the condenser blockage signal.

[0124] Figure 9 FIG. 1 is a schematic diagram of a method for detecting a refrigerant cross-flow signal according to an embodiment of the present application. Figure 9 As shown, step 150 includes:

[0125] Step 1504: Adjust the air-conditioning unit to a set standard operating condition and operate it for a period greater than a preset standard time.

[0126] In this step, the air conditioner is adjusted to a set standard operating condition, with uniform operating parameters such as rated load and fixed ambient temperature, to eliminate variable interference and ensure comparable test results. The system is allowed to operate for a sufficient time (e.g., 30 minutes) to achieve thermal equilibrium and avoid transient temperature fluctuations that could affect diagnostic accuracy.

[0127] Step 1505: Control the thermal imager to be perpendicular to the condenser surface at a preset distance to collect temperature data of the heat exchanger tube bundle area.

[0128] In this step, an infrared thermal imager captures the entire condenser surface temperature distribution, avoiding the blind spots associated with traditional point-based temperature measurement. A fixed distance (e.g., 1 meter) and vertical angle ensure consistent image scale, effectively improving the spatial resolution of the temperature data.

[0129] Step 1506: Divide the heat exchanger tube bundle area into multiple unit cell areas.

[0130] In this step, the thermal image is divided into pixel grid units. Multiple pixel grid units are then grouped into a cell area. For example, a cell area of ​​5×5 pixels, 8×8 pixels, or 10×10 pixels can be grouped into a cell area to locate local temperature anomalies. The cell size can be dynamically adjusted to match the tube bundle density of different condensers.

[0131] Step 160 includes:

[0132] Step 1612: If the temperature change of adjacent cell areas is greater than the preset temperature difference gradient, a refrigerant cross-flow signal is generated.

[0133] In this step, a sudden increase in the temperature difference between adjacent cell areas (for example, the preset temperature gradient is set to 5°C) indicates uneven refrigerant flow, which may be caused by partial pipe blockage or gas-liquid mixing leading to gas cross-talk.

[0134] Step 1613: Group the first number of cell areas into a test area, and if the temperature difference in the test area is greater than the preset local temperature difference, generate a refrigerant cross-flow signal.

[0135] In this step, a test area is formed by combining multiple cell areas. For example, a 3×3 adjacent cell area is combined into a test area. This highlights regional temperature imbalances and avoids misjudgments caused by a single cell area, improving robustness to real cross-flow faults. The temperature difference within the test area is the highest temperature minus the lowest temperature within the test area. The preset local temperature difference can be set to 5°C. A temperature difference greater than the preset local temperature difference indicates regional temperature imbalance, which may be caused by partial pipe blockage or gas-liquid mixing.

[0136] Step 1614: If the standard deviation of the temperature data of the entire heat exchanger tube bundle area is greater than the third preset temperature difference, a refrigerant cross-flow signal is generated.

[0137] In this step, a macro-uniformity assessment is performed to calculate the standard deviation of the temperature in the entire area and quantify the overall heat dissipation uniformity. Exceeding the standard deviation (for example, the third preset temperature difference is set to 8°C) can be considered as abnormal refrigerant distribution at the system level, such as multi-pipe cross-flow or distributor failure.

[0138] Through this embodiment, the correlation analysis of the compression abnormality signal, the mechanical failure signal and the refrigerant cross-flow signal can be performed.

[0139] Figure 10 FIG. 1 is a schematic diagram of a method for calculating correlation values ​​and matching fault risk levels according to an embodiment of the present application. Figure 10 As shown, step 180 includes:

[0140] Step 1801: Within a preset historical time period, if two or more signals occur simultaneously within a preset unit time period, the corresponding signals are counted as one occurrence correlation quantity.

[0141] In this step, by counting the number of co-occurrences of signals within a fixed time window (i.e., a preset unit time length, for example, set to 5 minutes), the correlation between faults is quantified to avoid misjudgment of isolated signals. Multiple fault coupling identification can be achieved. For example, when the compression abnormality signal and the evaporation and condensation prompt signal frequently appear at the same time, it can be determined to be a system-level refrigerant cycle fault rather than a single component problem. Specifically, when two or more signals occur at the same time within the preset unit time length, the signals that occur at the same time are counted as a correlation quantity. For example, within the past 3 hours, the compression abnormality signal, the mechanical fault signal, and the evaporation and condensation prompt signal occur at the same time, then the three signals are counted as a correlation quantity respectively; if the compression abnormality signal and the mechanical fault signal occur at the same time, then the two signals are counted as a correlation quantity respectively. The more correlation quantities a signal has, the more faults the signal may induce.

[0142] Step 190 includes:

[0143] Step 1901: Generate a corresponding fault risk level according to corresponding occurrence correlation quantities of the compression abnormality signal, the mechanical fault signal, and the evaporation and condensation prompt signal.

[0144] In this step, the compression abnormality signal can be subdivided into the compression ratio abnormality signal, the liquid hammer risk signal, and the power and speed abnormality signal; the mechanical fault signal can be subdivided into the bearing inner ring fault signal and the roller fault signal; the evaporation and condensation prompt signal can be subdivided into the refrigerant shortage signal, the refrigerant excess signal, the normal charging signal, the refrigerant shortage signal, the scaling signal, the refrigerant temperature is too low signal, the refrigerant flow is too large signal, the refrigerant excess signal, the condenser blockage signal, the refrigerant leakage signal, the expansion valve opening abnormality signal, and the refrigerant cross-gas signal. The occurrence correlation quantity corresponding to the correlation occurrence in step 180 can be correlated and analyzed among all the above-mentioned 17 subdivision signals, or can be correlated and analyzed among the compression abnormality signal, the mechanical fault signal and the evaporation and condensation prompt signal, or can be correlated and analyzed among the 3 subdivision signals under the compression abnormality signal and the mechanical fault signal and the evaporation and condensation prompt signal, or can be analyzed among the 2 subdivision signals under the compression abnormality signal, the evaporation and condensation prompt signal and the mechanical fault signal, or can be correlated and analyzed among the 12 subdivision signals under the compression abnormality signal, the mechanical fault signal and the evaporation and condensation prompt signal, or can be correlated and analyzed among the 3 subdivision signals under the compression abnormality signal, the 2 subdivision signals under the mechanical fault signal and the evaporation and condensation prompt signal, or can be correlated and analyzed among the 3 subdivision signals under the compression abnormality signal, the mechanical fault signal and the 12 subdivision signals under the evaporation and condensation prompt signal, or can be correlated and analyzed among the 2 subdivision signals under the compression abnormality signal and the mechanical fault signal and the 12 subdivision signals under the evaporation and condensation prompt signal.

[0145] This step categorizes risk dynamics: For example, if the number of correlations is >1 and ≤3, the signal is considered low risk and observation is recommended. For example, if the number of correlations is >3 and ≤6, the signal is considered medium risk, indicating a potential failure trend, triggering an alert and recording. For example, if the number of correlations is >6 and ≤10, the signal is considered medium-high risk, indicating strong correlations between multiple signals and a higher potential failure trend. For example, if the number of correlations is 10 and ≤15, the signal is considered high risk, indicating strong correlations between multiple signals and an immediate shutdown for maintenance. The numbers 3, 6, 10, and 15 are examples. In actual applications, the categorization can be set based on the maximum and minimum number of correlations, or based on expert experience. For example, if the maximum number of correlations is 20 and the minimum number is 5 within a preset historical period, the risk classification can be as follows: 5-8 is low risk, 8-12 is medium risk, 12-16 is medium-high risk, and 16-20 is high risk. This step filters random interference through a time window to highlight the true fault chain. High-correlation signals can more accurately point to system-level fault sources and indicate that high-correlation signals may cause more faults and require higher attention, that is, a higher fault risk level.

[0146] The basic principles of the present application have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, and effects mentioned in this application are merely illustrative and not restrictive, and it should not be assumed that these advantages, strengths, and effects are required of each embodiment of this application. In addition, the specific details disclosed above are merely illustrative and facilitating understanding, and are not restrictive. The above details do not limit this application to necessarily being implemented using the above specific details.

[0147] The block diagrams of the devices, devices, equipment, and systems involved in this application are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As will be appreciated by those skilled in the art, these devices, devices, equipment, and systems can be connected, arranged, or configured in any manner. Words such as "include," "comprise," "have," and the like are open-ended words, meaning "including but not limited to," and can be used interchangeably therewith. The words "or" and "and" used herein refer to the words "and / or" and can be used interchangeably therewith, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to," and can be used interchangeably therewith.

[0148] It should also be noted that in the apparatus, device, and method of the present application, each component or each step can be decomposed and / or recombined, and such decomposition and / or recombination should be regarded as equivalent solutions of the present application.

[0149] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to be applied in the widest sense consistent with the principles and novel features of the present invention.

[0150] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for diagnosing faults in a water-cooled precision air-conditioning unit, characterized in that: include: Obtaining the compression working condition of the compressor; comparing the compression operating condition with a first standard operating condition to generate a compression abnormality signal; acquiring vibration data of the compressor; generating a corresponding mechanical fault signal according to the vibration data and a second standard operating condition; Obtain the evaporation and condensation working conditions of the evaporator and condenser; Generate corresponding evaporation and condensation prompt signals according to the evaporation and condensation working conditions and the third standard working condition; According to the preset time period of the history backtracked at the current moment, all the compression abnormality signals, the mechanical failure signals and the evaporation and condensation prompt signals are retrieved; Comparing the occurrence times of the compression abnormality signal, the mechanical failure signal, and the evaporation and condensation prompt signal, and calculating the occurrence correlation amount between the signals; as well as generating signal risk assessment data based on the occurrence correlation amount; The comparing the occurrence times of the compression abnormality signal, the mechanical failure signal, and the evaporation and condensation prompt signal to calculate the occurrence correlation amount between the signals includes: During the historical preset time period, if two or more signals occur simultaneously within the preset unit time period, the corresponding signals are counted as one occurrence of the correlation quantity; Generating signal risk assessment data according to the occurrence correlation amount includes: A corresponding fault risk level is generated according to the corresponding occurrence-related quantities of the compression abnormality signal, the mechanical fault signal, and the evaporation and condensation prompt signal.

2. The water-cooled precision air conditioning unit fault diagnosis method according to claim 1, characterized in that: The obtaining of the compression working condition of the compressor comprises: Obtaining the compressor discharge port pressure and the compressor suction port pressure; and Detecting the compression ratio based on the compressor exhaust pressure and the compressor intake pressure; The comparing the compression operating condition with the first standard operating condition to generate a compression abnormality signal includes: Obtain the design compression ratio of the compressor of the air conditioning unit; and If the difference between the detected compression ratio and the designed compression ratio is greater than a preset compression difference, a compression ratio abnormality signal is generated.

3. The water-cooled precision air conditioning unit fault diagnosis method according to claim 1, characterized in that: The obtaining of the compression working condition of the compressor comprises: Obtain the compressor suction port pressure and compressor suction port temperature; Adjust the corresponding saturation temperature according to the compressor suction port pressure; The comparing the compression operating condition with the first standard operating condition to generate a compression abnormality signal includes: Obtaining a reference temperature according to the saturation temperature and the correction temperature; If the compressor suction port temperature is lower than the reference temperature, a liquid hammer risk signal is generated.

4. The water-cooled precision air conditioning unit fault diagnosis method according to claim 1, characterized in that: The obtaining of the compression working condition of the compressor comprises: Real-time monitoring of compressor speed; The comparing the compression operating condition with the first standard operating condition to generate a compression abnormality signal includes: The compressor speed is compared with the rated speed. If the fluctuation of the compressor speed relative to the rated speed exceeds a preset fluctuation threshold, a speed abnormality signal is generated.

5. The water-cooled precision air conditioning unit fault diagnosis method according to claim 1, characterized in that: Generating a corresponding mechanical fault signal according to the vibration data and the second standard working condition includes: Converting the vibration data of the time domain signal into frequency domain data; Extracting a first spectrum at 1.5 times the rotation frequency and a second spectrum at 3 times the rotation frequency according to the frequency domain data; If the peak value of the first spectrum is greater than a first preset peak value, generating a bearing inner race fault signal; and If the peak value of the second spectrum is greater than a second preset peak value, a roller fault signal is generated.

6. The water-cooled precision air conditioning unit fault diagnosis method according to claim 1, characterized in that: The obtaining of the evaporation and condensation operating conditions of the evaporator and the condenser comprises: Obtain the evaporator outlet temperature, evaporator line pressure, condenser outlet temperature and condenser line pressure; Generating a corresponding evaporation and condensation prompt signal according to the evaporation and condensation operating condition and the third standard operating condition includes: Retrieving the evaporator saturation temperature corresponding to the evaporator pipeline pressure, and retrieving the condenser saturation temperature corresponding to the condenser pipeline pressure; Obtaining evaporator superheat according to the evaporator outlet temperature and the evaporator saturation temperature; Obtaining condenser subcooling according to the condenser outlet temperature and the condenser saturation temperature; If the evaporator superheat is greater than a first superheat and the evaporator line pressure is lower than a first pressure standard value, a refrigerant shortage signal is generated; If the condenser subcooling degree is less than the second superheating degree and the condenser line pressure is higher than the second pressure standard value, generating a refrigerant excess signal; and If the evaporator superheat, the evaporator line pressure, the condenser subcooling, and the condenser line pressure are all within a threshold fluctuation range, a normal charging signal is generated.

7. The water-cooled precision air conditioning unit fault diagnosis method according to claim 1, characterized in that: The obtaining of the evaporation and condensation operating conditions of the evaporator and the condenser comprises: Get the condenser inlet temperature and condenser outlet temperature; The generating of the corresponding evaporation and condensation prompt signal according to the evaporation and condensation working condition and the third standard working condition includes: Calculating the condenser inlet and outlet temperature difference according to the condenser inlet temperature and the condenser outlet temperature; If the temperature difference between the inlet and outlet of the condenser is less than a first preset temperature difference, generating a refrigerant shortage signal and / or a fouling signal; and If the temperature difference between the inlet and outlet of the condenser is greater than the second preset temperature difference, a refrigerant temperature too low signal and / or a refrigerant flow too large signal is generated.

8. The water-cooled precision air conditioning unit fault diagnosis method according to claim 1, characterized in that: The obtaining of the evaporation and condensation operating conditions of the evaporator and the condenser comprises: Get the condenser inlet pressure and condenser outlet pressure; Generating a corresponding evaporation and condensation prompt signal according to the evaporation and condensation operating condition and the third standard operating condition includes: If the condenser inlet pressure is greater than a first preset pressure, generating a refrigerant excess signal and / or a condenser blockage signal; and If the condenser outlet pressure is lower than a second preset pressure, a refrigerant leakage signal and / or an expansion valve opening abnormality signal is generated.

9. The water-cooled precision air conditioning unit fault diagnosis method according to claim 1, characterized in that: The obtaining of the evaporation and condensation operating conditions of the evaporator and the condenser comprises: Adjusting the air conditioning unit to a set standard operating condition and running it for a period greater than a preset standard time; Controlling the thermal imager to be perpendicular to the condenser surface at a preset distance to collect temperature data of the heat exchanger tube bundle area; and dividing the heat exchanger tube bundle area into a plurality of unit cell areas; Generating a corresponding evaporation and condensation prompt signal according to the evaporation and condensation operating condition and the third standard operating condition includes: If the temperature change of adjacent cell areas is greater than the preset temperature gradient, a refrigerant cross-flow signal is generated; forming a test area with a first number of the cell areas, and generating a refrigerant cross-flow signal if the temperature difference of the test area is greater than a preset local temperature difference; and If the standard deviation of the temperature data of the entire heat exchanger tube bundle area is greater than a third preset temperature difference, a refrigerant cross-flow signal is generated.

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