WO2023198221A1 - 压缩机的喘振检测方法、装置、电子设备和暖通设备 - Google Patents

压缩机的喘振检测方法、装置、电子设备和暖通设备 Download PDF

Info

Publication number
WO2023198221A1
WO2023198221A1 PCT/CN2023/093008 CN2023093008W WO2023198221A1 WO 2023198221 A1 WO2023198221 A1 WO 2023198221A1 CN 2023093008 W CN2023093008 W CN 2023093008W WO 2023198221 A1 WO2023198221 A1 WO 2023198221A1
Authority
WO
WIPO (PCT)
Prior art keywords
surge
compressor
pressure
factor
fluctuation
Prior art date
Application number
PCT/CN2023/093008
Other languages
English (en)
French (fr)
Inventor
贺斌
梁涛
刘雅岚
张毅
Original Assignee
重庆美的通用制冷设备有限公司
美的集团股份有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 重庆美的通用制冷设备有限公司, 美的集团股份有限公司 filed Critical 重庆美的通用制冷设备有限公司
Publication of WO2023198221A1 publication Critical patent/WO2023198221A1/zh

Links

Classifications

    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
    • F04D—NON-POSITIVE-DISPLACEMENT PUMPS
    • F04D27/00—Control, e.g. regulation, of pumps, pumping installations or pumping systems specially adapted for elastic fluids
    • F04D27/001—Testing thereof; Determination or simulation of flow characteristics; Stall or surge detection, e.g. condition monitoring
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B30/00—Energy efficient heating, ventilation or air conditioning [HVAC]
    • Y02B30/70—Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating

Definitions

  • the present disclosure relates to the technical field of air conditioners, and in particular, to a compressor surge detection method, device, electronic equipment and HVAC equipment.
  • Centrifugal compressors have the characteristics of surge. When the surge occurs, the compressor deviates from the design working condition boundary, causing severe vibration and intensified noise. This not only affects the stable operation of the unit, but also may damage the compressor in severe cases. In order to prevent the occurrence of surge, it is necessary to control the compressor to run outside the boundary of the surge curve. However, during the test of the surge boundary curve, surge points are often selected based on the experience of surge sounds or ammeter data fluctuations. Different experimenters Deviations from working conditions will bring different test results of the surge boundary curve. The fitted compressor surge boundary curve itself has poor accuracy and consistency with the same working conditions. A more scientific automatic compression method needs to be provided. Machine surge detection method.
  • surge detection is to prevent unit surge. If anti-surge measures can be taken when the unit just enters surge, that is, at a certain critical point (weak surge), it can improve the accuracy of surge detection and improve the unit's ability to prevent surge.
  • compressor surge monitoring mostly uses a fixed threshold to determine whether surge occurs. If the threshold is set too low, the detection results will have a certain false detection rate; if the threshold is set too high, the detection results will have certain errors. The detection rate, that is, the effectiveness of weak surge detection is reduced.
  • the purpose of the present disclosure is to provide a compressor surge detection method, device, electronic equipment and HVAC equipment to dynamically determine the weighting factor and surge factor of the compressor, based on the weighting factor and surge factor. Whether the compressor surges can improve the accuracy of surge detection and reduce the false detection rate and missed detection rate.
  • some embodiments of the present disclosure provide a surge detection method for a compressor.
  • the method includes: collecting operating data of the compressor; wherein the operating data includes: pressure data, current data and power data; the pressure data includes: Suction pressure data and exhaust pressure data; calculate the surge pressure ratio of the compressor based on the pressure data; calculate the fluctuation index of the compressor based on the operating data; among them, the fluctuation index includes: exhaust pressure fluctuation index, current fluctuation index and power fluctuation Index; determine the weighting factor and surge factor of the compressor based on the fluctuation index and surge pressure ratio; among them, the weighting factors include exhaust pressure weighting factor, current weighting factor and power weighting factor, and the surge factors include: exhaust pressure surge Factor, current surge factor and power surge factor; determine whether the compressor surges based on the weighting factor and surge factor.
  • the above step of collecting the operating data of the compressor includes: collecting the operating data of the compressor through a dynamic sliding window.
  • the above-mentioned step of calculating the surge pressure ratio of the compressor based on pressure data includes: dividing the suction pressure data at multiple moments by the exhaust pressure data at that moment to obtain multiple values of the compressor. Instantaneous pressure ratio; calculate the pressure ratio fluctuation rate of the compressor based on multiple instantaneous pressure ratios; determine the surge pressure ratio of the compressor based on the pressure ratio fluctuation rate and the preset pressure ratio fluctuation rate threshold.
  • the above-mentioned step of determining the surge pressure ratio of the compressor based on the pressure ratio fluctuation rate and a preset pressure ratio fluctuation threshold includes: if the pressure ratio fluctuation rate is greater than or equal to the preset For the pressure ratio fluctuation threshold, the instantaneous pressure ratio at the corresponding moment of the pressure ratio fluctuation is used as the surge pressure ratio of the compressor; if the pressure ratio fluctuation is less than the pressure ratio fluctuation threshold, the surge pressure ratio of the compressor remains unchanged.
  • the above steps of determining the weighting factor and surge factor of the compressor based on the fluctuation index and surge pressure ratio include: determining the weighting factor of the compressor based on the exhaust pressure fluctuation index and surge pressure ratio; The surge factor of the compressor is determined based on the fluctuation index.
  • the above-mentioned step of determining the weighting factor of the compressor based on the exhaust pressure fluctuation index and surge pressure ratio includes: fitting the exhaust pressure fluctuation index and surge pressure ratio at multiple moments, Obtain the relationship curve of the exhaust pressure fluctuation index and surge pressure ratio changing with time; determine the exhaust pressure fluctuation threshold based on the relationship curve; if the exhaust pressure fluctuation index at the target time is less than or equal to the exhaust pressure fluctuation threshold, determine it by the following formula
  • the above-mentioned step of determining the exhaust pressure fluctuation threshold based on the relationship curve includes: determining a first curve in which the exhaust pressure fluctuation index and the surge pressure ratio are linearly related from the relationship curve; converting the first curve The exhaust pressure fluctuation index corresponding to the starting point is used as the exhaust pressure fluctuation threshold.
  • the above-mentioned step of determining the surge factor of the compressor based on the fluctuation index includes: if the fluctuation index is greater than or equal to the surge factor threshold, the surge factor of the compressor is the first value; if the fluctuation index is less than Surge factor threshold, the surge factor of the compressor is the second value.
  • the above method also includes: if the exhaust pressure fluctuation index at the target time is less than or equal to the exhaust pressure fluctuation threshold, using the preset target threshold as the surge factor threshold; if the exhaust pressure fluctuation index at the target time is The pressure fluctuation index is greater than the exhaust pressure fluctuation threshold, and the exhaust pressure fluctuation index at the target time in the first curve is used as the surge factor threshold.
  • the above-mentioned step of determining whether the compressor surges based on the weighting factor and the surge factor includes: calculating the surge index of the compressor based on the weighting factor and the surge factor; if the surge index is greater than or equal to At the preset surge threshold, the compressor surges; if the surge index is less than the surge threshold, the compressor does not surge.
  • some embodiments of the present disclosure also provide a surge detection device for a compressor.
  • the device includes: an operating data collection module configured to collect operating data of the compressor; wherein the operating data includes: pressure data, current data and power data; pressure data includes suction pressure data and discharge pressure data; surge pressure ratio calculation module is set to calculate the surge pressure ratio of the compressor based on pressure data; fluctuation index calculation module is set to calculate based on operating data The fluctuation index of the compressor; where the fluctuation index includes: exhaust pressure fluctuation index, current fluctuation index and power fluctuation index; the weighting factor and surge factor determination module is set to determine the weighting of the compressor based on the fluctuation index and surge pressure ratio factor and surge factor; among them, the weighting factors include exhaust pressure weighting factor, current weighting factor and power weighting factor, surge The factors include: exhaust pressure surge factor, current surge factor and power surge factor; the compressor surge detection module is set to determine whether the compressor surges based on the weighting factor and the surge factor.
  • some embodiments of the present disclosure also provide an electronic device, including a processor and a memory.
  • the memory stores computer-executable instructions that can be executed by the processor.
  • the processor executes the computer-executable instructions to Implement the above compressor surge detection method.
  • some embodiments of the present disclosure also provide a computer-readable storage medium.
  • the computer-readable storage medium stores computer-executable instructions.
  • the computer can Execution of the instructions causes the processor to implement the above-mentioned surge detection method of the compressor.
  • some embodiments of the present disclosure also provide a heating and ventilation equipment, including a processor and a memory.
  • the memory stores computer-executable instructions that can be executed by the processor.
  • the processor executes the computer-executable instructions. To implement the above compressor surge detection method.
  • Figure 1 is a flow chart of a compressor surge detection method provided in some embodiments of the present disclosure
  • Figure 2 is a flow chart of another surge detection method for a compressor provided in some embodiments of the present disclosure
  • Figure 3 is a schematic diagram of a surge pressure ratio provided in some embodiments of the present disclosure.
  • Figure 4 is a schematic diagram of a compressor surge detection method provided in some embodiments of the present disclosure.
  • Figure 5 is a schematic diagram of a relationship curve between exhaust pressure fluctuation index and surge pressure ratio over time provided in some embodiments of the present disclosure
  • Figure 6 is a schematic structural diagram of a surge detection device for a compressor provided in some embodiments of the present disclosure
  • FIG. 7 is a schematic structural diagram of an electronic device provided in some embodiments of the present disclosure.
  • surge detection is to prevent unit surge. If the unit just enters surge, that is, at a certain critical point (weak surge), anti-surge measures can be taken, which not only improves the accuracy of surge detection, but also improves the unit's ability to prevent surge.
  • compressor surge monitoring mostly uses a fixed threshold to determine whether surge occurs. If the threshold is set too low, the detection results will have a certain false detection rate; if the threshold is set too high, the detection results will have certain errors. The detection rate, that is, the effectiveness of weak surge detection is reduced. Based on this, some embodiments of the present disclosure provide a compressor surge detection method, device and electronic equipment, which can dynamically determine the weighting factor and surge factor of the compressor, and determine whether the compressor is based on the weighting factor and the surge factor. When surge occurs, the accuracy of surge detection can be improved and the false detection rate and missed detection rate can be reduced.
  • Some embodiments of the present disclosure provide a surge detection method for a compressor.
  • the surge detection method for a compressor includes the following steps:
  • Step S102 collect the operating data of the compressor; the operating data includes: pressure data, current data and power data; the pressure data includes suction pressure data and exhaust pressure data.
  • the compressor is a driven fluid machine that elevates low-pressure gas to high-pressure gas. It is the heart of the refrigeration system. It sucks in low-temperature and low-pressure refrigerant gas from the suction pipe, drives the piston to compress it through the operation of the motor, and discharges the high-temperature and high-pressure refrigerant gas to the exhaust pipe to provide power for the refrigeration cycle.
  • the compressor in some embodiments of the present disclosure may be a compressor of a chiller, and the chiller may be a centrifugal chiller.
  • the operating data of the compressor is the data required by the compressor during operation, including: pressure data (including suction pressure data and discharge pressure data), current data and power data, which respectively represent the pressure during operation of the compressor (suction pressure and exhaust pressure), current and power.
  • the operating data can be converted into percentage data, that is, the fluctuation index size (percentage data) of this component (the component includes suction pressure, exhaust pressure, current, and power) during surge is used, and It is not the absolute value of the component fluctuation, which is conducive to capturing the universality of the feature and does not change with the change of the experimental object.
  • the pressure range, full load current, and full load power can be used as the denominator when calculating percentage data.
  • Step S104 Calculate the surge pressure ratio of the compressor based on the pressure data.
  • the pressure ratio is the compression ratio.
  • the surge pressure ratio of the compressor can refer to the fluctuation rate obtained by sliding the instantaneous pressure ratio of the compressor. For example, the instantaneous pressure ratio of the compressor at multiple moments can be detected (that is, the suction pressure at that moment divided by the discharge pressure). According to a certain calculation method, the surge pressure ratio can be calculated based on the instantaneous pressure ratio.
  • Step S106 Calculate the fluctuation index of the compressor based on the operating data; where the fluctuation index includes: exhaust pressure fluctuation index, current fluctuation index and power fluctuation index.
  • the fluctuation index of the compressor can represent the fluctuation of a certain component of the compressor within a certain period of time.
  • a dynamic sliding window can be used to collect the operating data of the compressor, and then the fluctuation index of each component within each dynamic sliding window can be calculated, that is, the exhaust pressure fluctuation index, current fluctuation index and power fluctuation index.
  • the significance of using dynamic sliding window sampling data is to maintain the continuous fluctuation characteristics of all collected data points in the time domain and prevent the data fluctuations between unit sampling segments from being coupled and filtered out.
  • Step S108 determine the weighting factor and surge factor of the compressor based on the fluctuation index and surge pressure ratio; where the weighting factors include exhaust pressure weighting factors, current weighting factors and power weighting factors, and the surge factors include: exhaust pressure surge vibration factor, current surge factor and power surge factor.
  • the surge index of the compressor may be calculated by the weighting factor and the surge factor.
  • the surge factor of the compressor can represent the surge situation of a certain component, and the surge factor of the compressor can generally be determined through a threshold value. If the operating volatility index is greater than a certain threshold, the surge factor is a certain value, and if the operating volatility index is less than the threshold, the surge factor is another value.
  • the weighting factor of the compressor can represent the degree of influence of a certain component on surge. The higher the weighting factor of a certain component, the greater the influence of this component on surge.
  • Step S110 Determine whether the compressor surges based on the weighting factor and the surge factor.
  • the surge index of the compressor may be calculated by the weighting factor and the surge factor. If the surge index is large, it can be considered that the compressor surges; if the surge index is small, it can be considered that the compressor does not surge.
  • the weighting factor and surge factor are not set artificially, but are calculated based on the fluctuation index and surge pressure ratio.
  • the weighting factor and surge factor can dynamically change based on the operating data of the compressor, and the calculated surge index is more accurate. For accuracy, the accuracy of compressor surge detection can be improved and the false detection rate and missed detection rate can be reduced.
  • a compressor surge detection method can calculate the surge pressure ratio of the compressor based on the pressure data, calculate the fluctuation index of the compressor based on the operating data, and determine the surge pressure ratio based on the fluctuation index and the surge pressure ratio.
  • the weighting factor and surge factor of the compressor can be dynamically determined, and whether surge occurs in the compressor is determined based on the weighting factor and surge factor, which can improve the accuracy of surge detection and reduce the false detection rate and missed detection rate.
  • Some embodiments of the present disclosure provide another surge detection method for a compressor, which method is implemented on the basis of some of the above embodiments. See the flow chart of another surge detection method for a compressor shown in Figure 2 , the compressor surge detection method in this embodiment includes the following steps:
  • Step S202 collect the operating data of the compressor; the operating data includes: pressure data, current data and power data; the pressure data includes suction pressure data and exhaust pressure data.
  • the operating data of the compressor can be collected through a dynamic sliding window.
  • the period of the dynamic sliding window is the product of the preset number of sampling points and the single-point sampling period, and the number of sampling points is greater than or equal to 3.
  • the common sampling method is ordinary continuous segmented sampling.
  • ordinary continuous segmented sampling has the risk of data fluctuation coupling, that is, the data fluctuation between unit sampling segments is easily filtered out by coupling.
  • the dynamic sliding window sampling data can maintain the continuous fluctuation characteristics of all collected data points in the time domain, without the risk of data fluctuation coupling.
  • Step S204 Calculate the surge pressure ratio of the compressor based on the pressure data.
  • the suction pressure data at multiple moments can be divided by the exhaust pressure data at that moment to obtain multiple instantaneous pressure ratios of the compressor; the pressure ratio fluctuation rate of the compressor can be calculated based on the multiple instantaneous pressure ratios; The pressure ratio fluctuation rate and the preset pressure ratio fluctuation rate threshold determine the surge pressure ratio of the compressor.
  • the suction pressure data and exhaust pressure data at t1, t2 and t3 are collected through dynamic sliding window collection, and the suction pressure data at the above three moments are divided by The exhaust pressure data at this moment can be used to obtain the instantaneous pressure ratio of the above three moments.
  • the surge pressure ratio of the compressor can be determined through the following steps: If the pressure ratio fluctuation rate is greater than or equal to the preset pressure ratio fluctuation rate threshold, the pressure ratio fluctuation rate corresponding to the time The instantaneous pressure ratio is used as the surge pressure ratio of the compressor; if the pressure ratio fluctuation rate is less than the pressure ratio fluctuation rate threshold, the surge pressure ratio of the compressor is kept unchanged.
  • the pressure ratio fluctuation threshold as 1 as an example, if the pressure ratio fluctuations at t1, t2 and t3 are 1.6, 0.6 and 1.2 respectively, you can see the schematic diagram of a surge pressure ratio shown in Figure 3. It is shown that the solid line in Figure 3 is the change process of surge pressure ratio, and the square is the instantaneous pressure ratio at t1 time, t2 time and t3 time. Since the pressure ratio fluctuation rate at t1 and t3 is greater than the pressure ratio fluctuation threshold, and the pressure ratio fluctuation rate at t2 is less than the pressure ratio fluctuation threshold, the surge pressure ratio undergoes a sudden change at t1 and t3.
  • Step S206 Calculate the fluctuation index of the compressor based on the operating data; where the fluctuation index includes: exhaust pressure fluctuation index, current fluctuation index and power fluctuation index.
  • Nb_p is the exhaust pressure fluctuation index
  • Xi_p is the exhaust pressure data in the i-th dynamic sliding window
  • Ai_p is the average exhaust pressure data in the i-th dynamic sliding window
  • ⁇ _p is the preset exhaust pressure data.
  • Nb_c is the current fluctuation index,
  • Xi_c is the current data in the i-th dynamic sliding window,
  • Ai_c is the i-th dynamic sliding window
  • ⁇ _w is the preset power fluctuation index judgment threshold.
  • some embodiments of the present disclosure can calculate the fluctuation index of each component in each dynamic sliding window through the above formula.
  • the exhaust pressure percentage data ratio in the third dynamic sliding window is 0.2. , 1, 1.8, the average value is 1.
  • the exhaust pressure fluctuation index judgment threshold is 0.7
  • Step S208 Determine the weighting factor of the compressor based on the exhaust pressure fluctuation index and surge pressure ratio.
  • the operating data of the compressor is first collected. Calculate the surge pressure ratio and fluctuation index of the compressor, and then calculate the weighting factor and surge factor in two situations based on the corresponding relationship between the exhaust pressure fluctuation index and the exhaust pressure fluctuation threshold at the target time.
  • the first curve in which the exhaust pressure fluctuation index and the surge pressure ratio are linearly related can be determined from the relationship curve (that is, the oblique line in Figure 5 is the first curve); the starting point of the first curve The corresponding exhaust pressure fluctuation index is used as the exhaust pressure fluctuation threshold.
  • Step S210 Determine the surge factor of the compressor based on the fluctuation index.
  • the preset target threshold is used as the surge factor threshold; if the exhaust pressure fluctuation index at the target time is greater than the exhaust pressure For the fluctuation threshold, the exhaust pressure fluctuation index at the target moment in the first curve is used as the surge factor threshold.
  • the target threshold can be 0.2-A1. If the exhaust pressure fluctuation index at the target time is higher than the exhaust pressure fluctuation threshold, the exhaust pressure fluctuation index at the target time in the first curve shown in Figure 5 can be used as the surge factor threshold.
  • the surge factor threshold After the surge factor threshold is determined, if the fluctuation index is greater than or equal to the surge factor threshold, the surge factor of the compressor is the first value; if the fluctuation index is less than the surge factor threshold, the surge factor of the compressor is the second value.
  • the first value of each component may be all 1, and the second value of each component may be all 0.
  • Step S212 Determine whether surge occurs in the compressor based on the weighting factor and the surge factor.
  • the surge index of the compressor can be calculated based on the weighting factor and the surge factor; if the surge index is greater than or equal to the preset surge threshold, the compressor surges; if the surge index is less than the surge threshold, the compressor The machine did not surge.
  • a, b, and c are respectively the weighting factors of the exhaust pressure, current, and power calculated in the aforementioned step S208 in the surge judgment
  • s1, s2, and s3 are respectively the weighted factors of the exhaust pressure, current, and power calculated in the aforementioned step S210.
  • the weighting factors in the above formula can be dynamically calculated, which has better accuracy for surge detection.
  • the surge index F needs to be compared with the surge threshold f1. If the surge index is greater than or equal to the preset surge threshold, the compressor surges; if the surge index is less than the surge threshold, the compressor does not surge. .
  • the value range of f1 can be 0.5-1.0.
  • some embodiments of the present disclosure provide a surge detection device for a compressor.
  • the surge detection device includes: an operating data acquisition module 61, which is configured to collect operating data of the compressor; where the operating data includes: pressure data, current data and power data; the pressure data includes suction pressure data and exhaust pressure data; surge The vibration pressure ratio calculation module 62 is configured to calculate the surge pressure ratio of the compressor based on the pressure data; the fluctuation index calculation module 63 is configured to calculate the fluctuation index of the compressor based on the operating data; where the fluctuation index includes: exhaust pressure fluctuation index , current fluctuation index and power fluctuation index; the weighting factor and surge factor determination module 64 is set to determine based on the fluctuation index and surge pressure ratio.
  • the weighting factor includes the exhaust pressure weighting factor, the current weighting factor and the power weighting factor
  • the surge factor includes: the exhaust pressure surge factor, the current surge factor and the power surge factor.
  • the compressor surge detection module 65 is configured to determine whether the compressor surges based on the weighting factor and the surge factor.
  • a surge detection device for a compressor provided in some embodiments of the present disclosure can calculate the surge pressure ratio of the compressor based on the pressure data, calculate the fluctuation index of the compressor based on the operating data, and determine the surge pressure ratio based on the fluctuation index and the surge pressure ratio.
  • the weighting factor and surge factor of the compressor can be dynamically determined, and whether surge occurs in the compressor is determined based on the weighting factor and surge factor, which can improve the accuracy of surge detection and reduce the false detection rate and missed detection rate.
  • the above-mentioned operating data collection module is configured to collect the operating data of the compressor through a dynamic sliding window.
  • the above-mentioned surge pressure ratio calculation module is configured to divide the suction pressure data at multiple moments by the exhaust pressure data at that moment to obtain multiple instantaneous pressure ratios of the compressor; calculate the pressure of the compressor based on the multiple instantaneous pressure ratios. Specific fluctuation rate; determine the surge pressure ratio of the compressor based on the pressure ratio fluctuation rate and the preset pressure ratio fluctuation rate threshold.
  • the above-mentioned surge pressure ratio calculation module is set to use the instantaneous pressure ratio corresponding to the pressure ratio fluctuation rate as the surge pressure ratio of the compressor if the pressure ratio fluctuation rate is greater than or equal to the preset pressure ratio fluctuation threshold;
  • the specific fluctuation rate is less than the pressure ratio fluctuation rate threshold, keeping the surge pressure ratio of the compressor unchanged.
  • the above-mentioned weighting factor and surge factor determination module is configured to determine the weighting factor of the compressor based on the exhaust pressure fluctuation index and surge pressure ratio; and determine the surge factor of the compressor based on the fluctuation index.
  • the above-mentioned weighting factor and surge factor determination module is set to determine the first curve in which the exhaust pressure fluctuation index and the surge pressure ratio are linearly related from the relationship curve; the exhaust pressure fluctuation index corresponding to the starting point of the first curve is taken as Exhaust pressure fluctuation threshold.
  • the above-mentioned weighting factor and surge factor determination module is set so that if the fluctuation index is greater than or equal to the surge factor threshold, the surge factor of the compressor is the first value; if the fluctuation index is less than the surge factor threshold, the surge factor of the compressor is Second value.
  • the above-mentioned weighting factor and surge factor determination module is also set to use the preset target threshold as the surge factor threshold if the exhaust pressure fluctuation index at the target time is less than or equal to the exhaust pressure fluctuation threshold; if the exhaust pressure fluctuation index at the target time is The pressure fluctuation index is greater than the exhaust pressure fluctuation threshold, and the exhaust pressure fluctuation index at the target time in the first curve is used as the surge factor threshold.
  • the above-mentioned compressor surge detection module is set to calculate the surge index of the compressor based on the weighting factor and the surge factor; if the surge index is greater than or equal to the preset surge threshold, the compressor surges; if the surge index is less than Surge threshold, the compressor does not surge.
  • Surge index s1 is the exhaust pressure surge factor
  • s2 is the current surge factor
  • s3 is the power surge factor
  • a is the exhaust pressure weighting factor
  • b is the current weighting factor
  • c is the power weighting factor.
  • Some embodiments of the present disclosure also provide an electronic device configured to run the surge detection method of the compressor; see FIG. 7 for a schematic structural diagram of an electronic device.
  • the electronic device includes a memory 100 and a processor 101 , wherein the memory 100 is configured to store one or more computer instructions, and the one or more computer instructions are executed by the processor 101 to implement the above compressor surge detection method.
  • the electronic device shown in FIG. 7 also includes a bus 102 and a communication interface 103.
  • the processor 101, the communication interface 103 and the memory 100 are connected through the bus 102.
  • the memory 100 may include high-speed random access memory (RAM), or may also include non-volatile memory (Non-Volatile Memory), such as at least one disk memory.
  • RAM high-speed random access memory
  • Non-Volatile Memory non-volatile memory
  • One less communication interface 103 (which can be wired or wireless) realizes the communication connection between the system network element and at least one other network element, and can use the Internet, wide area network, local network, metropolitan area network, etc.
  • the bus 102 may be an ISA bus, a PCI bus, an EISA bus, etc.
  • the bus can be divided into address bus, data bus, control bus, etc. For ease of presentation, only one bidirectional arrow is used in Figure 7, but it does not mean that there is only one bus or one type of bus.
  • the processor 101 may be an integrated circuit chip with signal processing capabilities. During the implementation process, each step of the above method can be completed by instructions in the form of hardware integrated logic circuits or software in the processor 101 .
  • the above-mentioned processor 101 can be a general-purpose processor, including a central processing unit, a network processor, etc.; it can also be a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic devices, discrete gates, or transistor logic. devices, discrete hardware components.
  • the disclosed methods, steps and logical block diagrams in some embodiments of the present disclosure may be implemented or executed.
  • a general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.
  • the steps of the method disclosed in conjunction with some embodiments of the present disclosure can be directly implemented by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor.
  • the software module can be located in random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers and other mature storage media in this field.
  • the storage medium is located in the memory 100.
  • the processor 101 reads the information in the memory 100 and completes the steps of the methods of some of the foregoing embodiments in combination with its hardware.
  • Some embodiments of the present disclosure also provide a computer-readable storage medium that stores computer-executable instructions.
  • the computer-executable instructions When the computer-executable instructions are called and executed by the processor, the computer-executable instructions prompt processing
  • the device implements the above compressor surge detection method. For specific implementation, please refer to the relevant embodiments in the method, and will not be described again here.
  • the computer program product of the compressor surge detection method, device and electronic equipment provided in some embodiments of the present disclosure includes a computer-readable storage medium storing program code, and the instructions included in the program code can be configured to execute the foregoing method.
  • program code storing program code
  • the instructions included in the program code can be configured to execute the foregoing method.

Landscapes

  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Control Of Positive-Displacement Air Blowers (AREA)
  • Control Of Positive-Displacement Pumps (AREA)

Abstract

提供了一种压缩机的喘振检测方法、装置、电子设备和暖通设备。压缩机的喘振检测方法包括：采集压缩机的运行数据；其中，运行数据包括：压力数据、电流数据和功率数据；压力数据包括吸气压力数据和排气压力数据（S102）；基于压力数据计算压缩机的喘振压比（S104）；基于运行数据计算压缩机的波动指数；其中，波动指数包括：排气压力波动指数、电流波动指数和功率波动指数（S106）；基于波动指数和喘振压比确定压缩机的加权因子和喘振因子；其中，加权因子包括排气压力加权因子、电流加权因子和功率加权因子，喘振因子包括：排气压力喘振因子、电流喘振因子和功率喘振因子（S108）；基于加权因子和喘振因子确定压缩机是否发生喘振（S110）。通过加权因子和喘振因子确定压缩机是否发生喘振，提高了喘振检测的准确率。

Description

压缩机的喘振检测方法、装置、电子设备和暖通设备
相关申请的交叉引用
本公开要求于2022年04月12日提交的申请号为202210382065.1，名称为“压缩机的喘振检测方法、装置和电子设备”的中国专利申请的优先权，其全部内容通过引用结合在本公开中。
技术领域
本公开涉及空调器的技术领域，尤其是涉及一种压缩机的喘振检测方法、装置、电子设备和暖通设备。
背景技术
离心式压缩机具有喘振的特点，喘振时压缩机偏离设计工况边界，会出现剧烈震动，噪声加剧，不仅影响机组稳定运行，严重时更可能损坏压缩机。为防止喘振的发生，需要控制压缩机运行在喘振曲线边界外，但喘振边界曲线测试的过程中，多以喘振声音或电流表数据波动等人为经验选择喘振点，不同的实验员和工况的偏差都会带来不同的喘振边界曲线的测试结果，拟合得到的压缩机喘振边界曲线本身的精确度和同工况一致性较差，需要提供一种更加科学的自动压缩机的喘振检测方法。
压缩机喘振发生的判定没有国际统一的标准，尤其针对不同工况或不同速度和导叶开度情况下的弱喘振判断尤其困难，但作为喘振检测的目的意义在于防止机组喘振，如果在机组刚进入喘振时即一定程度的临界点(弱喘)就能采取防喘措施，在提高喘振检测准确度的同时，可提高机组防喘能力。
然而，相关技术中，压缩机的喘振监测多以固定阈值判断喘振是否发生，如果阈值设置过低，则检测结果存在一定的误检率；如果阈值设置过高，则检测结果存在一定漏检率，即弱喘振检测有效性降低。
公开内容
有鉴于此，本公开的目的在于提供一种压缩机的喘振检测方法、装置、电子设备和暖通设备，以动态确定压缩机的加权因子和喘振因子，基于加权因子和喘振因子确定压缩机是否发生喘振，可以提高喘振检测的准确率，降低误检率和漏检率。
第一方面，本公开一些实施例中提供了一种压缩机的喘振检测方法，方法包括：采集压缩机的运行数据；其中，运行数据包括：压力数据、电流数据和功率数据；压力数据包括 吸气压力数据和排气压力数据；基于压力数据计算压缩机的喘振压比；基于运行数据计算压缩机的波动指数；其中，波动指数包括：排气压力波动指数、电流波动指数和功率波动指数；基于波动指数和喘振压比确定压缩机的加权因子和喘振因子；其中，加权因子包括排气压力加权因子、电流加权因子和功率加权因子，喘振因子包括：排气压力喘振因子、电流喘振因子和功率喘振因子；基于加权因子和喘振因子确定压缩机是否发生喘振。
在本公开一些实施例中，上述采集压缩机的运行数据的步骤，包括：通过动态滑窗采集压缩机的运行数据。
在本公开一些实施例中，上述基于压力数据计算压缩机的喘振压比的步骤，包括：将多个时刻的吸气压力数据除以该时刻的排气压力数据，得到压缩机的多个瞬时压比；基于多个瞬时压比计算压缩机的压比波动率；基于压比波动率和预先设定的压比波动率阈值，确定压缩机的喘振压比。
在本公开一些实施例中，上述基于多个瞬时压比计算压缩机的压比波动率的步骤，包括：通过以下算式基于多个瞬时压比计算压缩机的压比波动率：Npr＝Sum[(Xi-B)2]/(N×σ)；其中，Npr为压缩机的压比波动率，Sum为求和计算，Xi为第i个时刻的瞬时压比，B为多个瞬时压比的平均值，N为多个瞬时压比的数量；σ为预先设定的压比波动率系数。
在本公开一些实施例中，上述基于压比波动率和预先设定的压比波动率阈值，确定压缩机的喘振压比的步骤，包括：如果压比波动率大于或等于预先设定的压比波动率阈值，将压比波动率对应时刻的瞬时压比作为压缩机的喘振压比；如果压比波动率小于压比波动率阈值，保持压缩机的喘振压比不变。
在本公开一些实施例中，上述基于运行数据计算压缩机的波动指数的步骤，包括：通过以下算式基于运行数据计算压缩机的波动指数：Nb_p＝Sum[(Xi_p-Ai_p)2]/3σ_p；Nb_c＝Sum[(Xi_c-Ai_c)2]/3σ_c；Nb_w＝Sum[(Xi_w-Ai_w)2]/3σ_w；其中，Nb_p为排气压力波动指数，Xi_p为第i个动态滑窗内的排气压力数据，Ai_p为第i个动态滑窗内的排气压力数据的平均值，σ_p为预先设定的排气压力波动指数判断阈值；Nb_c为电流波动指数，Xi_c为第i个动态滑窗内的电流数据，Ai_c为第i个动态滑窗内的电流数据的平均值，σ_c为预先设定的电流波动指数判断阈值；Nb_w为功率波动指数，Xi_w为第i个动态滑窗内的功率数据，Ai_w为第i个动态滑窗内的功率数据的平均值，σ_w为预先设定的功率波动指数判断阈值。
在本公开一些实施例中，上述基于波动指数和喘振压比确定压缩机的加权因子和喘振因子的步骤，包括：基于排气压力波动指数和喘振压比确定压缩机的加权因子；基于波动指数确定压缩机的喘振因子。
在本公开一些实施例中，上述基于排气压力波动指数和喘振压比确定压缩机的加权因子的步骤，包括：对多个时刻的排气压力波动指数和喘振压比进行拟合，得到排气压力波动指数和喘振压比随时间变化的关系曲线；基于关系曲线确定排气压力波动阈值；如果目标时刻的排气压力波动指数小于或等于排气压力波动阈值，通过以下算式确定压缩机的加权因子：b＝n×a，a＝c，其中，a为排气压力加权因子，b为电流加权因子，c为功率加权因子，n为预先设定的第一倍率系数，并且n＞1，a+b+c＝1；如果目标时刻的排气压力波动指数大于排气压力波动阈值，通过以下算式确定压缩机的加权因子：a＝m×b，b＝c，其中，m为预先设定的第二倍率系数，并且m＞1。
在本公开一些实施例中，上述基于关系曲线确定排气压力波动阈值的步骤，包括：从关系曲线中确定排气压力波动指数和喘振压比呈线性相关的第一曲线；将第一曲线的起始点对应的排气压力波动指数作为排气压力波动阈值。
在本公开一些实施例中，上述基于波动指数确定压缩机的喘振因子的步骤，包括：如果波动指数大于或等于喘振因子阈值，压缩机的喘振因子为第一值；如果波动指数小于喘振因子阈值，压缩机的喘振因子为第二值。
在本公开一些实施例中，上述法还包括：如果目标时刻的排气压力波动指数小于或等于排气压力波动阈值，将预先设定的目标阈值作为喘振因子阈值；如果目标时刻的排气压力波动指数大于排气压力波动阈值，将第一曲线中目标时刻的排气压力波动指数作为喘振因子阈值。
在本公开一些实施例中，上述基于加权因子和喘振因子确定压缩机是否发生喘振的步骤，包括：基于加权因子和喘振因子计算压缩机的喘振指数；如果喘振指数大于或等于预设的喘振阈值，压缩机发生喘振；如果喘振指数小于喘振阈值，压缩机没有发生喘振。
在本公开一些实施例中，上述于加权因子和喘振因子计算压缩机的喘振指数的步骤，包括：通过下述算式基于加权因子和喘振因子计算压缩机的喘振指数：F＝s1×a+s2×b+s3×c；其中，F为压缩机的喘振指数，s1为排气压力喘振因子，s2为电流喘振因子，s3为功率喘振因子，a为排气压力加权因子，b为电流加权因子，c为功率加权因子。
第二方面，本公开一些实施例中还提供了一种压缩机的喘振检测装置，装置包括：运行数据采集模块，设置成采集压缩机的运行数据；其中，运行数据包括：压力数据、电流数据和功率数据；压力数据包括吸气压力数据和排气压力数据；喘振压比计算模块，设置成基于压力数据计算压缩机的喘振压比；波动指数计算模块，设置成基于运行数据计算压缩机的波动指数；其中，波动指数包括：排气压力波动指数、电流波动指数和功率波动指数；加权因子和喘振因子确定模块，设置成基于波动指数和喘振压比确定压缩机的加权因子和喘振因子；其中，加权因子包括排气压力加权因子、电流加权因子和功率加权因子，喘振 因子包括：排气压力喘振因子、电流喘振因子和功率喘振因子；压缩机喘振检测模块，设置成基于加权因子和喘振因子确定压缩机是否发生喘振。
第三方面，本公开一些实施例中还提供了一种电子设备，包括处理器和存储器，该存储器存储有能够被该处理器执行的计算机可执行指令，该处理器执行该计算机可执行指令以实现上述压缩机的喘振检测方法。
第四方面，本公开一些实施例中还提供了一种计算机可读存储介质，该计算机可读存储介质存储有计算机可执行指令，该计算机可执行指令在被处理器调用和执行时，计算机可执行指令促使处理器实现上述压缩机的喘振检测方法。
第五方面，本公开一些实施例中还提供了一种暖通设备，包括处理器和存储器，该存储器存储有能够被该处理器执行的计算机可执行指令，该处理器执行该计算机可执行指令以实现上述压缩机的喘振检测方法。
本公开的其他特征和优点将在随后的说明书中阐述，或者，部分特征和优点可以从说明书推知或毫无疑义地确定，或者通过实施本公开的上述技术即可得知。
为使本公开的上述目的、特征和优点能更明显易懂，下文特举较佳实施例，并配合所附附图，作详细说明如下。
附图说明
图1为本公开一些实施例中提供的一种压缩机的喘振检测方法的流程图；
图2为本公开一些实施例中提供的另一种压缩机的喘振检测方法的流程图；
图3为本公开一些实施例中提供的一种喘振压比的示意图；
图4为本公开一些实施例中提供的一种压缩机的喘振检测方法的示意图；
图5为本公开一些实施例中提供的一种排气压力波动指数和喘振压比随时间变化的关系曲线的示意图；
图6为本公开一些实施例中提供的一种压缩机的喘振检测装置的结构示意图；
图7为本公开一些实施例中提供的一种电子设备的结构示意图。
具体实施方式
为使本公开实施例的目的、技术方案和优点更加清楚，下面将结合附图对本公开的技术方案进行清楚、完整地描述，显然，所描述的实施例是本公开一部分实施例，而不是全部的实施例。基于本公开中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本公开保护的范围。
目前，压缩机喘振发生的判定没有国际统一的标准，尤其针对不同工况或不同速度和导叶开度情况下的弱喘振判断尤其困难，但作为喘振检测的目的意义在于防止机组喘振，如果在机组刚进入喘振时即一定程度的临界点(弱喘)就能采取防喘措施，在提高喘振检测准确度的同时，可提高机组防喘能力。
然而，相关技术中，压缩机的喘振监测多以固定阈值判断喘振是否发生，如果阈值设置过低，则检测结果存在一定的误检率；如果阈值设置过高，则检测结果存在一定漏检率，即弱喘振检测有效性降低。基于此，本公开一些实施例中提供的一种压缩机的喘振检测方法、装置和电子设备，可以动态确定压缩机的加权因子和喘振因子，基于加权因子和喘振因子确定压缩机是否发生喘振，可以提高喘振检测的准确率，降低误检率和漏检率。
为便于对本实施例进行理解，首先对本公开一些实施例中所公开的一种压缩机的喘振检测方法进行详细介绍。
本公开一些实施例中提供一种压缩机的喘振检测方法，参见图1所示的一种压缩机的喘振检测方法的流程图，该压缩机的喘振检测方法包括如下步骤：
步骤S102，采集压缩机的运行数据；其中，运行数据包括：压力数据、电流数据和功率数据；压力数据包括吸气压力数据和排气压力数据。
压缩机是一种将低压气体提升为高压气体的从动的流体机械，是制冷系统的心脏。它从吸气管吸入低温低压的制冷剂气体，通过电机运转带动活塞对其进行压缩后，向排气管排出高温高压的制冷剂气体，为制冷循环提供动力。本公开一些实施例中的压缩机可以为冷水机组的压缩机，冷水机组可以是离心式冷水机组。
压缩机的运行数据即压缩机在运行中需要的数据，包括：压力数据(包括吸气压力数据和排气压力数据)、电流数据和功率数据，分别表征压缩机运行中的压力(吸气压力和排气压力)、电流和功率。
示例性地，为了统一量纲，可以将运行数据转化为百分比数据，即使用喘振时该分量(分量包括吸气压力、排气压力数电流和功率)的波动指数大小(百分比数据)，而不是分量波动绝对值，有利于抓取特征的普遍性而不随实验对象变化而改变。具体地，可以使用压力量程，满载电流，满载功率作为计算百分比数据时的分母。
步骤S104，基于压力数据计算压缩机的喘振压比。
压比即压缩比，压缩机的喘振压比可以指滑动检测压缩机瞬时压比求得的波动率。例如：可以检测多个时刻的压缩机的瞬时压比(即该时刻的吸气压力除以排气压力)，根据一定的计算方式，可以根据瞬时压比计算得到喘振压比。
步骤S106，基于运行数据计算压缩机的波动指数；其中，波动指数包括：排气压力波动指数、电流波动指数和功率波动指数。
压缩机的波动指数可以表征压缩机在一定时间内某一分量的波动情况。具体地，可以使用动态滑窗采集压缩机的运行数据，之后可以计算每个动态滑窗内的各个分量的波动指数，即排气压力波动指数、电流波动指数和功率波动指数。其中，采用动态滑窗采样数据的意义在于保持时域内所有采集数据点的连续性波动特征，防止单位采样段与段之间的数据波动被耦合滤掉。
步骤S108，基于波动指数和喘振压比确定压缩机的加权因子和喘振因子；其中，加权因子包括排气压力加权因子、电流加权因子和功率加权因子，喘振因子包括：排气压力喘振因子、电流喘振因子和功率喘振因子。
在一些实施例中，可以通过加权因子和喘振因子计算压缩机的喘振指数。其中，压缩机的喘振因子可以表征某一分量的喘振情况，其中，一般可以通过阈值来确定压缩机的喘振因子。如果运行波动指数大于某一阈值，则喘振因子为某一值，如果运行波动指数小于该阈值，则喘振因子为另一值。压缩机的加权因子可以表征某一分量对喘振的影响程度，某一分量的加权因子越高，则该分量对喘振的影响程度越大。
步骤S110，基于加权因子和喘振因子确定压缩机是否发生喘振。
在一些实施例中，可以通过加权因子和喘振因子计算压缩机的喘振指数。如果喘振指数较大，则可以认为压缩机发生喘振；如果喘振指数较小，则可以认为压缩机没有发生喘振。其中，加权因子和喘振因子均不是人为设定，而是根据波动指数和喘振压比计算得到，加权因子和喘振因子可以基于压缩机的运行数据动态变化，计算得到的喘振指数更为精确，可以提高压缩机喘振检测的准确率，降低误检率和漏检率。
本公开一些实施例中提供的一种压缩机的喘振检测方法，可以基于压力数据计算压缩机的喘振压比，基于运行数据计算压缩机的波动指数，基于波动指数和喘振压比确定压缩机的加权因子和喘振因子，并且基于加权因子和喘振因子确定压缩机是否发生喘振。该方式中，可以动态确定压缩机的加权因子和喘振因子，基于加权因子和喘振因子确定压缩机是否发生喘振，可以提高喘振检测的准确率，降低误检率和漏检率。
本公开一些实施例中提供了另一种压缩机的喘振检测方法，该方法在上述一些实施例的基础上实现，参见图2所示的另一种压缩机的喘振检测方法的流程图，本实施例中的压缩机的喘振检测方法包括如下步骤：
步骤S202，采集压缩机的运行数据；其中，运行数据包括：压力数据、电流数据和功率数据；压力数据包括吸气压力数据和排气压力数据。
示例性地，可以通过动态滑窗采集压缩机的运行数据。其中，动态滑窗的周期为预先设定的采样点数与单点采样周期的乘积，采样点数大于或等于3。
对于运行数据的采集，普通的采样手段是普通连续分段采样，然而，普通连续分段采样具有数据波动耦合性风险，即单位采样段与段之间的数据波动容易被耦合滤掉。而动态滑窗采样数据可以保持时域内所有采集数据点的连续性波动特征，没有数据波动耦合性风险。
步骤S204，基于压力数据计算压缩机的喘振压比。
示例性地，可以将多个时刻的吸气压力数据除以该时刻的排气压力数据，得到压缩机的多个瞬时压比；基于多个瞬时压比计算压缩机的压比波动率；基于压比波动率和预先设定的压比波动率阈值，确定压缩机的喘振压比。
例如，通过动态滑窗采集的方式采集了t1时刻、t2时刻和t3时刻(t1＜t2＜t3)的吸气压力数据和排气压力数据，分别将上述三个时刻的吸气压力数据除以该时刻的排气压力数据，就可以得到上述三个时刻的瞬时压比。
示例性地，可以通过以下算式基于多个瞬时压比计算压缩机的压比波动率：Npr＝Sum[(Xi-B)2]/(N×σ)；其中，Npr为压缩机的压比波动率，Sum为求和计算，Xi为第i个时刻的瞬时压比，B为多个瞬时压比的平均值，N为多个瞬时压比的数量；σ为预先设定的压比波动率系数。其中，σ的取值范围可以是0.2-0.5。
计算得多个压比波动率之后，可以通过下述步骤确定压缩机的喘振压比：如果压比波动率大于或等于预先设定的压比波动率阈值，将压比波动率对应时刻的瞬时压比作为压缩机的喘振压比；如果压比波动率小于压比波动率阈值，保持压缩机的喘振压比不变。
以压比波动率阈值为1举例，如果t1时刻、t2时刻和t3时刻的压比波动率分别为1.6、0.6、1.2，可以参见图3所示的一种喘振压比的示意图，可以看出，图3中实线为喘振压比变化过程，正方形为t1时刻、t2时刻和t3时刻的瞬时压比。由于t1时刻、t3时刻的压比波动率大于压比波动率阈值，t2时刻的压比波动率小于压比波动率阈值，则喘振压比在t1时刻、t3时刻发生突变。
步骤S206，基于运行数据计算压缩机的波动指数；其中，波动指数包括：排气压力波动指数、电流波动指数和功率波动指数。
示例性地，可以通过以下算式基于运行数据计算压缩机的波动指数：Nb_p＝Sum[(Xi_p-Ai_p)2]/3σ_p；Nb_c＝Sum[(Xi_c-Ai_c)2]/3σ_c；Nb_w＝Sum[(Xi_w-Ai_w)2]/3σ_w。
其中，Nb_p为排气压力波动指数，Xi_p为第i个动态滑窗内的排气压力数据，Ai_p为第i个动态滑窗内的排气压力数据的平均值，σ_p为预先设定的排气压力波动指数判断阈值；Nb_c为电流波动指数，Xi_c为第i个动态滑窗内的电流数据，Ai_c为第i个动态滑窗 内的电流数据的平均值，σ_c为预先设定的电流波动指数判断阈值；Nb_w为功率波动指数，Xi_w为第i个动态滑窗内的功率数据，Ai_w为第i个动态滑窗内的功率数据的平均值，σ_w为预先设定的功率波动指数判断阈值。
综上，本公开一些实施例可以通过上述算式对每个动态滑窗内的每个分量的波动指数进行计算，举例来说，第3个动态滑窗内的排气压力百分比数据分比为0.2、1、1.8，平均值为1，假设排气压力波动指数判断阈值为0.7，则排气压力波动指数可以为：Nb_p＝Sum[(Xi_p-Ai_p)2]/3σ_p＝[(0.2-1)2+(1-1)2+(1.8-1)2]/(3×0.7)＝0.610。
步骤S208，基于排气压力波动指数和喘振压比确定压缩机的加权因子。
示例性地，可以对多个时刻的排气压力波动指数和喘振压比进行拟合，得到排气压力波动指数和喘振压比随时间变化的关系曲线；基于关系曲线确定排气压力波动阈值；如果目标时刻的排气压力波动指数小于或等于排气压力波动阈值，通过以下算式确定压缩机的加权因子：b＝n×a，a＝c，其中，a为排气压力加权因子，b为电流加权因子，c为功率加权因子，n为预先设定的第一倍率系数，并且n＞1，a+b+c＝1；如果目标时刻的排气压力波动指数大于排气压力波动阈值，通过以下算式确定压缩机的加权因子：a＝m×b，b＝c，其中，m为预先设定的第二倍率系数，并且m＞1。
参见图4所示的一种压缩机的喘振检测方法的示意图，首先采集压缩机的运行数据。计算压缩机的喘振压比和波动指数，之后根据目标时刻的排气压力波动指数与排气压力波动阈值的对应关系分两种情况计算加权因子和喘振因子。
示例性地，可以参见图5所示的一种排气压力波动指数和喘振压比随时间变化的关系曲线的示意图，显著喘振时压缩机的排气压力、电流、功率的波动指数与在一定喘振压比范围内(图5中的Pr1-Pr2)呈线性相关性，压力较电流和功率相比，压力的显著性更强；压缩机弱喘振时，波动率和喘振压比无关联，电流较压力和功率相比，电流显著性更强。
如图5所示，可以从关系曲线中确定排气压力波动指数和喘振压比呈线性相关的第一曲线(即图5中的斜线为第一曲线)；将第一曲线的起始点对应的排气压力波动指数作为排气压力波动阈值。
如果压力波动指数高于第一曲线的起始点A1(即有效下限值)，则排气压力、电流、功率判断加权因子分别取a、b、c，a＝m×b，b＝c，其中，m为预先设定的第二倍率系数，m＞1，m的取值范围为可以2-3，并且a+b+c＝1。
如果压力波动指数低于第一曲线的起始点A1(即有效下限值)，则压力、电流、功率判断加权因子分别取a、b、c，b＝n×a，a＝c，其中，a为排气压力加权因子，b为电流加权因子，c为功率加权因子，n为预先设定的第一倍率系数，n＞1，n的取值范围为可以2-3，并且a+b+c＝1。
步骤S210，基于波动指数确定压缩机的喘振因子。
如图4所示，如果目标时刻的排气压力波动指数小于或等于排气压力波动阈值，将预先设定的目标阈值作为喘振因子阈值；如果目标时刻的排气压力波动指数大于排气压力波动阈值，将第一曲线中目标时刻的排气压力波动指数作为喘振因子阈值。
也就是说，如果目标时刻的排气压力波动指数小于或等于排气压力波动阈值，目标阈值可以取0.2-A1。如果目标时刻的排气压力波动指数打于排气压力波动阈值，可以将图5所示的第一曲线中目标时刻的排气压力波动指数作为喘振因子阈值。
在确定喘振因子阈值之后，如果波动指数大于或等于喘振因子阈值，压缩机的喘振因子为第一值；如果波动指数小于喘振因子阈值，压缩机的喘振因子为第二值。其中，各个分量的第一值可以均为1，各个分量的第二值可以均为0。
步骤S212，基于加权因子和喘振因子确定压缩机是否发生喘振。
示例性地，可以基于加权因子和喘振因子计算压缩机的喘振指数；如果喘振指数大于或等于预设的喘振阈值，压缩机发生喘振；如果喘振指数小于喘振阈值，压缩机没有发生喘振。
其中，可以通过下述算式基于加权因子和喘振因子计算压缩机的喘振指数：F＝s1×a+s2×b+s3×c；其中，F为压缩机的喘振指数，s1为排气压力喘振因子，s2为电流喘振因子，s3为功率喘振因子，a为排气压力加权因子，b为电流加权因子，c为功率加权因子。
其中，a、b、c分别为前述步骤S208计算得到排气压力、电流、功率在喘振判断中的加权因子，s1、s2、s3分别为前述步骤S210计算得到排气压力、电流、功率在喘振判断中的喘振因子，可以看出，上述算式中的加权因子都可以动态计算得到的，对于喘振检测具有更好的准确率。
喘振指数F计算后需要与喘振阈值f1进行对比，如果喘振指数大于或等于预设的喘振阈值，压缩机发生喘振；如果喘振指数小于喘振阈值，压缩机没有发生喘振。其中，f1的取值范围可以是0.5-1.0。
对应于上述方法的一些实施例，本公开一些实施例中提供了一种压缩机的喘振检测装置，参见图6所示的一种压缩机的喘振检测装置的结构示意图，该压缩机的喘振检测装置包括：运行数据采集模块61，设置成采集压缩机的运行数据；其中，运行数据包括：压力数据、电流数据和功率数据；压力数据包括吸气压力数据和排气压力数据；喘振压比计算模块62，设置成基于压力数据计算压缩机的喘振压比；波动指数计算模块63，设置成基于运行数据计算压缩机的波动指数；其中，波动指数包括：排气压力波动指数、电流波动指数和功率波动指数；加权因子和喘振因子确定模块64，设置成基于波动指数和喘振压比确 定压缩机的加权因子和喘振因子；其中，加权因子包括排气压力加权因子、电流加权因子和功率加权因子，喘振因子包括：排气压力喘振因子、电流喘振因子和功率喘振因子；压缩机喘振检测模块65，设置成基于加权因子和喘振因子确定压缩机是否发生喘振。
本公开一些实施例中提供的一种压缩机的喘振检测装置，可以基于压力数据计算压缩机的喘振压比，基于运行数据计算压缩机的波动指数，基于波动指数和喘振压比确定压缩机的加权因子和喘振因子，并且基于加权因子和喘振因子确定压缩机是否发生喘振。该方式中，可以动态确定压缩机的加权因子和喘振因子，基于加权因子和喘振因子确定压缩机是否发生喘振，可以提高喘振检测的准确率，降低误检率和漏检率。
上述运行数据采集模块，设置成通过动态滑窗采集压缩机的运行数据。
上述喘振压比计算模块，设置成将多个时刻的吸气压力数据除以该时刻的排气压力数据，得到压缩机的多个瞬时压比；基于多个瞬时压比计算压缩机的压比波动率；基于压比波动率和预先设定的压比波动率阈值，确定压缩机的喘振压比。
上述喘振压比计算模块，设置成通过以下算式基于多个瞬时压比计算压缩机的压比波动率：Npr＝Sum[(Xi-B)2]/(N×σ)；其中，Npr为压缩机的压比波动率，Sum为求和计算，Xi为第i个时刻的瞬时压比，B为多个瞬时压比的平均值，N为多个瞬时压比的数量；σ为预先设定的压比波动率系数。
上述喘振压比计算模块，设置成如果压比波动率大于或等于预先设定的压比波动率阈值，将压比波动率对应时刻的瞬时压比作为压缩机的喘振压比；如果压比波动率小于压比波动率阈值，保持压缩机的喘振压比不变。
上述波动指数计算模块，设置成通过以下算式基于运行数据计算压缩机的波动指数：Nb_p＝Sum[(Xi_p-Ai_p)2]/3σ_p；Nb_c＝Sum[(Xi_c-Ai_c)2]/3σ_c；Nb_w＝Sum[(Xi_w-Ai_w)2]/3σ_w；其中，Nb_p为排气压力波动指数，Xi_p为第i个动态滑窗内的排气压力数据，Ai_p为第i个动态滑窗内的排气压力数据的平均值，σ_p为预先设定的排气压力波动指数判断阈值；Nb_c为电流波动指数，Xi_c为第i个动态滑窗内的电流数据，Ai_c为第i个动态滑窗内的电流数据的平均值，σ_c为预先设定的电流波动指数判断阈值；Nb_w为功率波动指数，Xi_w为第i个动态滑窗内的功率数据，Ai_w为第i个动态滑窗内的功率数据的平均值，σ_w为预先设定的功率波动指数判断阈值。
上述加权因子和喘振因子确定模块，设置成基于排气压力波动指数和喘振压比确定压缩机的加权因子；基于波动指数确定压缩机的喘振因子。
上述加权因子和喘振因子确定模块，设置成对多个时刻的排气压力波动指数和喘振压比进行拟合，得到排气压力波动指数和喘振压比随时间变化的关系曲线；基于关系曲线确定排气压力波动阈值；如果目标时刻的排气压力波动指数小于或等于排气压力波动阈值，通 过以下算式确定压缩机的加权因子：b＝n×a，a＝c，其中，a为排气压力加权因子，b为电流加权因子，c为功率加权因子，n为预先设定的第一倍率系数，并且n＞1，a+b+c＝1；如果目标时刻的排气压力波动指数大于排气压力波动阈值，通过以下算式确定压缩机的加权因子：a＝m×b，b＝c，其中，m为预先设定的第二倍率系数，并且m＞1。
上述加权因子和喘振因子确定模块，设置成从关系曲线中确定排气压力波动指数和喘振压比呈线性相关的第一曲线；将第一曲线的起始点对应的排气压力波动指数作为排气压力波动阈值。
上述加权因子和喘振因子确定模块，设置成如果波动指数大于或等于喘振因子阈值，压缩机的喘振因子为第一值；如果波动指数小于喘振因子阈值，压缩机的喘振因子为第二值。
上述加权因子和喘振因子确定模块，还设置成如果目标时刻的排气压力波动指数小于或等于排气压力波动阈值，将预先设定的目标阈值作为喘振因子阈值；如果目标时刻的排气压力波动指数大于排气压力波动阈值，将第一曲线中目标时刻的排气压力波动指数作为喘振因子阈值。
上述压缩机喘振检测模块，设置成基于加权因子和喘振因子计算压缩机的喘振指数；如果喘振指数大于或等于预设的喘振阈值，压缩机发生喘振；如果喘振指数小于喘振阈值，压缩机没有发生喘振。
上述压缩机喘振检测模块，设置成通过下述算式基于加权因子和喘振因子计算压缩机的喘振指数：F＝s1×a+s2×b+s3×c；其中，F为压缩机的喘振指数，s1为排气压力喘振因子，s2为电流喘振因子，s3为功率喘振因子，a为排气压力加权因子，b为电流加权因子，c为功率加权因子。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的压缩机的喘振检测装置的具体工作过程，可以参考前述压缩机的喘振检测方法中相关实施例的对应过程，在此不再赘述。
本公开一些实施例中还提供了一种电子设备，设置成运行上述压缩机的喘振检测方法；参见图7所示的一种电子设备的结构示意图，该电子设备包括存储器100和处理器101，其中，存储器100设置成存储一条或多条计算机指令，一条或多条计算机指令被处理器101执行，以实现上述压缩机的喘振检测方法。
进一步地，图7所示的电子设备还包括总线102和通信接口103，处理器101、通信接口103和存储器100通过总线102连接。
其中，存储器100可能包含高速随机存取存储器(RAM，Random Access Memory)，也可能还包括非不稳定的存储器(Non-Volatile Memory)，例如至少一个磁盘存储器。通过至 少一个通信接口103(可以是有线或者无线)实现该系统网元与至少一个其他网元之间的通信连接，可以使用互联网，广域网，本地网，城域网等。总线102可以是ISA总线、PCI总线或EISA总线等。总线可以分为地址总线、数据总线、控制总线等。为便于表示，图7中仅用一个双向箭头表示，但并不表示仅有一根总线或一种类型的总线。
处理器101可能是一种集成电路芯片，具有信号的处理能力。在实现过程中，上述方法的各步骤可以通过处理器101中的硬件的集成逻辑电路或者软件形式的指令完成。上述的处理器101可以是通用处理器，包括中央处理器、网络处理器等；还可以是数字信号处理器、专用集成电路、现场可编程门阵列或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。可以实现或者执行本公开一些实施例中的公开的各方法、步骤及逻辑框图。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。结合本公开一些实施例所公开的方法的步骤可以直接体现为硬件译码处理器执行完成，或者用译码处理器中的硬件及软件模块组合执行完成。软件模块可以位于随机存储器，闪存、只读存储器，可编程只读存储器或者电可擦写可编程存储器、寄存器等本领域成熟的存储介质中。该存储介质位于存储器100，处理器101读取存储器100中的信息，结合其硬件完成前述一些实施例的方法的步骤。
本公开一些实施例中还提供了一种计算机可读存储介质，该计算机可读存储介质存储有计算机可执行指令，该计算机可执行指令在被处理器调用和执行时，计算机可执行指令促使处理器实现上述压缩机的喘振检测方法，具体实现可参见方法中的相关实施例，在此不再赘述。
本公开一些实施例中所提供的压缩机的喘振检测方法、装置和电子设备的计算机程序产品，包括存储了程序代码的计算机可读存储介质，程序代码包括的指令可设置成执行前面方法的一些实施例，具体实现可参见方法中的相关实施例，在此不再赘述。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统和/或装置的具体工作过程，可以参考前述方法中相关实施例的对应过程，在此不再赘述。

Claims (17)

  1. 一种压缩机的喘振检测方法，包括：
    采集压缩机的运行数据；其中，所述运行数据包括：压力数据、电流数据和功率数据；所述压力数据包括吸气压力数据和排气压力数据；
    基于所述压力数据计算所述压缩机的喘振压比；
    基于所述运行数据计算所述压缩机的波动指数；其中，所述波动指数包括：排气压力波动指数、电流波动指数和功率波动指数；
    基于所述波动指数和所述喘振压比确定所述压缩机的加权因子和喘振因子；其中，所述加权因子包括排气压力加权因子、电流加权因子和功率加权因子，所述喘振因子包括：排气压力喘振因子、电流喘振因子和功率喘振因子；
    基于所述加权因子和所述喘振因子确定所述压缩机是否发生喘振。
  2. 根据权利要求1所述的方法，其中，采集压缩机的运行数据的步骤，包括：
    通过动态滑窗采集压缩机的运行数据。
  3. 根据权利要求1或2所述的方法，其中，基于所述压力数据计算所述压缩机的喘振压比的步骤，包括：
    将多个时刻的所述吸气压力数据除以该时刻的所述排气压力数据，得到所述压缩机的多个瞬时压比；
    基于多个所述瞬时压比计算所述压缩机的压比波动率；
    基于所述压比波动率和预先设定的压比波动率阈值，确定所述压缩机的喘振压比。
  4. 根据权利要求3所述的方法，其中，基于多个所述瞬时压比计算所述压缩机的压比波动率的步骤，包括：
    通过以下算式基于多个所述瞬时压比计算所述压缩机的压比波动率：Npr＝Sum[(Xi-B)2]/(N×σ)；
    其中，Npr为所述压缩机的压比波动率，Sum为求和计算，Xi为第i个时刻的所述瞬时压比，B为多个所述瞬时压比的平均值，N为多个所述瞬时压比的数量；σ为预先设定的压比波动率系数。
  5. 根据权利要求3或4所述的方法，其中，基于所述压比波动率和预先设定的压比波动率阈值，确定所述压缩机的喘振压比的步骤，包括：
    如果所述压比波动率大于或等于预先设定的压比波动率阈值，将所述压比波动率对应时刻的瞬时压比作为所述压缩机的喘振压比；
    如果所述压比波动率小于所述压比波动率阈值，保持所述压缩机的喘振压比不变。
  6. 根据权利要求2所述的方法，其中，基于所述运行数据计算所述压缩机的波动指数的步骤，包括：
    通过以下算式基于所述运行数据计算所述压缩机的波动指数：
    Nb_p＝Sum[(Xi_p-Ai_p)2]/3σ_p；
    Nb_c＝Sum[(Xi_c-Ai_c)2]/3σ_c；
    Nb_w＝Sum[(Xi_w-Ai_w)2]/3σ_w；
    其中，Nb_p为排气压力波动指数，Xi_p为第i个动态滑窗内的排气压力数据，Ai_p为第i个动态滑窗内的排气压力数据的平均值，σ_p为预先设定的排气压力波动指数判断阈值；
    Nb_c为电流波动指数，Xi_c为第i个动态滑窗内的电流数据，Ai_c为第i个动态滑窗内的电流数据的平均值，σ_c为预先设定的电流波动指数判断阈值；
    Nb_w为功率波动指数，Xi_w为第i个动态滑窗内的功率数据，Ai_w为第i个动态滑窗内的功率数据的平均值，σ_w为预先设定的功率波动指数判断阈值。
  7. 根据权利要求1-6中任一项所述的方法，其中，基于所述波动指数和所述喘振压比确定所述压缩机的加权因子和喘振因子的步骤，包括：
    基于所述排气压力波动指数和所述喘振压比确定所述压缩机的加权因子；
    基于所述波动指数确定所述压缩机的喘振因子。
  8. 根据权利要求7所述的方法，其中，基于所述排气压力波动指数和所述喘振压比确定所述压缩机的加权因子的步骤，包括：
    对多个时刻的所述排气压力波动指数和所述喘振压比进行拟合，得到所述排气压力波动指数和所述喘振压比随时间变化的关系曲线；
    基于所述关系曲线确定排气压力波动阈值；
    如果目标时刻的所述排气压力波动指数小于或等于所述排气压力波动阈值，通过以下算式确定所述压缩机的加权因子：b＝n×a，a＝c，其中，a为所述排气压力加权因子，b为所述电流加权因子，c为所述功率加权因子，n为预先设定的第一倍率系数，并且n＞1，a+b+c＝1；
    如果目标时刻的所述排气压力波动指数大于所述排气压力波动阈值，通过以下算式确定所述压缩机的加权因子：a＝m×b，b＝c，其中，m为预先设定的第二倍率系数，并且m＞1。
  9. 根据权利要求8所述的方法，其中，基于所述关系曲线确定排气压力波动阈值的步骤，包括：
    从所述关系曲线中确定所述排气压力波动指数和所述喘振压比呈线性相关的第一曲线；
    将所述第一曲线的起始点对应的所述排气压力波动指数作为排气压力波动阈值。
  10. 根据权利要求9所述的方法，其中，基于所述波动指数确定所述压缩机的喘振因子的步骤，包括：
    如果所述波动指数大于或等于喘振因子阈值，所述压缩机的喘振因子为第一值；
    如果所述波动指数小于所述喘振因子阈值，所述压缩机的喘振因子为第二值。
  11. 根据权利要求10所述的方法，其中，所述方法还包括：
    如果目标时刻的所述排气压力波动指数小于或等于所述排气压力波动阈值，将预先设定的目标阈值作为所述喘振因子阈值；
    如果目标时刻的所述排气压力波动指数大于所述排气压力波动阈值，将所述第一曲线中所述目标时刻的排气压力波动指数作为所述喘振因子阈值。
  12. 根据权利要求1-11中任一项所述的方法，其中，基于所述加权因子和所述喘振因子确定所述压缩机是否发生喘振的步骤，包括：
    基于所述加权因子和所述喘振因子计算所述压缩机的喘振指数；
    如果所述喘振指数大于或等于预设的喘振阈值，所述压缩机发生喘振；
    如果所述喘振指数小于所述喘振阈值，所述压缩机没有发生喘振。
  13. 根据权利要求12所述的方法，其中，基于所述加权因子和所述喘振因子计算所述压缩机的喘振指数的步骤，包括：
    通过下述算式基于所述加权因子和所述喘振因子计算所述压缩机的喘振指数：
    F＝s1×a+s2×b+s3×c；
    其中，F为压缩机的喘振指数，s1为所述排气压力喘振因子，s2为所述电流喘振因子，s3为所述功率喘振因子，a为所述排气压力加权因子，b为所述电流加权因子，c为所述功率加权因子。
  14. 一种压缩机的喘振检测装置，所述装置包括：
    运行数据采集模块，设置成采集压缩机的运行数据；其中，所述运行数据包括：压力数据、电流数据和功率数据；所述压力数据包括吸气压力数据和排气压力数据；
    喘振压比计算模块，设置成基于所述压力数据计算所述压缩机的喘振压比；
    波动指数计算模块，设置成基于所述运行数据计算所述压缩机的波动指数；其中，所述波动指数包括：排气压力波动指数、电流波动指数和功率波动指数；
    加权因子和喘振因子确定模块，设置成基于所述波动指数和所述喘振压比确定所述压缩机的加权因子和喘振因子；其中，所述加权因子包括排气压力加权因子、电流加权因子和功率加权因子，所述喘振因子包括：排气压力喘振因子、电流喘振因子和功率喘振因子；
    压缩机喘振检测模块，设置成基于所述加权因子和所述喘振因子确定所述压缩机是否发生喘振。
  15. 一种电子设备，包括处理器和存储器，所述存储器存储有能够被所述处理器执行的计算机可执行指令，所述处理器执行所述计算机可执行指令以实现权利要求1至13任一项所述的压缩机的喘振检测方法。
  16. 一种计算机可读存储介质，所述计算机可读存储介质存储有计算机可执行指令，所述计算机可执行指令在被处理器调用和执行时，计算机可执行指令促使处理器实现权利要求1至13任一项所述的压缩机的喘振检测方法。
  17. 一种暖通设备，包括处理器和存储器，所述存储器存储有能够被所述处理器执行的计算机可执行指令，所述处理器执行所述计算机可执行指令以实现权利要求1至13任一项所述的压缩机的喘振检测方法。
PCT/CN2023/093008 2022-04-12 2023-05-09 压缩机的喘振检测方法、装置、电子设备和暖通设备 WO2023198221A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202210382065.1A CN114688067B (zh) 2022-04-12 2022-04-12 压缩机的喘振检测方法、装置和电子设备
CN202210382065.1 2022-04-12

Publications (1)

Publication Number Publication Date
WO2023198221A1 true WO2023198221A1 (zh) 2023-10-19

Family

ID=82142738

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2023/093008 WO2023198221A1 (zh) 2022-04-12 2023-05-09 压缩机的喘振检测方法、装置、电子设备和暖通设备

Country Status (2)

Country Link
CN (1) CN114688067B (zh)
WO (1) WO2023198221A1 (zh)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116447155A (zh) * 2022-01-10 2023-07-18 重庆美的通用制冷设备有限公司 压缩机的喘振检测方法、装置和电子设备
CN114688067B (zh) * 2022-04-12 2023-07-25 重庆美的通用制冷设备有限公司 压缩机的喘振检测方法、装置和电子设备

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4686834A (en) * 1986-06-09 1987-08-18 American Standard Inc. Centrifugal compressor controller for minimizing power consumption while avoiding surge
CN103857920A (zh) * 2011-10-03 2014-06-11 株式会社Ihi 离心压缩设备及其喘振防止方法
US20170370368A1 (en) * 2016-06-22 2017-12-28 General Electric Company Predicting a Surge Event in a Compressor of a Turbomachine
US20180363541A1 (en) * 2016-03-08 2018-12-20 Mitsubishi Heavy Industries Engine & Turbocharger, Ltd. Surge avoidance control method and surge avoidance control device for exhaust turbine turbocharger
CN109882441A (zh) * 2019-03-11 2019-06-14 重庆美的通用制冷设备有限公司 防喘振控制方法和压缩设备
CN110131193A (zh) * 2018-02-02 2019-08-16 中国航发商用航空发动机有限责任公司 航空发动机喘振故障监测方法和系统
CN114109860A (zh) * 2021-11-09 2022-03-01 珠海格力电器股份有限公司 空压机、空压机控制方法、装置、电子设备及存储介质
CN114688067A (zh) * 2022-04-12 2022-07-01 重庆美的通用制冷设备有限公司 压缩机的喘振检测方法、装置和电子设备

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9695831B2 (en) * 2015-07-02 2017-07-04 Woodward, Inc. Detection and counting of surge cycles in a compressor
CN106678069B (zh) * 2017-03-13 2018-05-01 重庆江增船舶重工有限公司 离心式压缩机防喘振发生的检测方法
CN109458324A (zh) * 2018-10-31 2019-03-12 重庆美的通用制冷设备有限公司 压缩机喘振识别方法、装置及系统
CN113869091A (zh) * 2020-06-30 2021-12-31 中国航发商用航空发动机有限责任公司 喘振判断方法及装置

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4686834A (en) * 1986-06-09 1987-08-18 American Standard Inc. Centrifugal compressor controller for minimizing power consumption while avoiding surge
CN103857920A (zh) * 2011-10-03 2014-06-11 株式会社Ihi 离心压缩设备及其喘振防止方法
US20180363541A1 (en) * 2016-03-08 2018-12-20 Mitsubishi Heavy Industries Engine & Turbocharger, Ltd. Surge avoidance control method and surge avoidance control device for exhaust turbine turbocharger
US20170370368A1 (en) * 2016-06-22 2017-12-28 General Electric Company Predicting a Surge Event in a Compressor of a Turbomachine
CN110131193A (zh) * 2018-02-02 2019-08-16 中国航发商用航空发动机有限责任公司 航空发动机喘振故障监测方法和系统
CN109882441A (zh) * 2019-03-11 2019-06-14 重庆美的通用制冷设备有限公司 防喘振控制方法和压缩设备
CN114109860A (zh) * 2021-11-09 2022-03-01 珠海格力电器股份有限公司 空压机、空压机控制方法、装置、电子设备及存储介质
CN114688067A (zh) * 2022-04-12 2022-07-01 重庆美的通用制冷设备有限公司 压缩机的喘振检测方法、装置和电子设备

Also Published As

Publication number Publication date
CN114688067B (zh) 2023-07-25
CN114688067A (zh) 2022-07-01

Similar Documents

Publication Publication Date Title
WO2023198221A1 (zh) 压缩机的喘振检测方法、装置、电子设备和暖通设备
CN117235557B (zh) 基于大数据分析的电气设备故障快速诊断方法
US10941956B2 (en) Data processing method, refrigerant leakage detection method, system failure detection method and system performance detection method
CN112648710B (zh) 排气温度传感器故障检测方法、装置及空调设备
CN106678069B (zh) 离心式压缩机防喘振发生的检测方法
WO2022012568A1 (zh) 压缩机的控制方法、控制装置和换热系统
WO2023035495A1 (zh) 噪音类型识别方法、空调器、装置及计算机可读存储介质
CN114893936A (zh) 制冰系统进出水控制系统与控制方法
CN111536653A (zh) 噪音控制方法、装置、多联机空调系统及存储介质
CN111765676A (zh) 一种多联机的制冷剂充注量故障诊断方法和装置
CN115127194B (zh) 用于检测中央空调冷水机组故障的方法、设备和介质
CN106445412A (zh) 一种数据卷压缩率的评估方法和系统
CN115095953B (zh) 一种故障诊断模型的训练方法及装置
CN110578983A (zh) 一种空调的控制方法、控制装置及空调
WO2023131186A1 (zh) 压缩机的喘振检测方法、装置和电子设备
CN110942096A (zh) 多联机制冷剂充注量的故障检测方法、装置及电子设备
CN114110999A (zh) 多联机组内机开度控制方法、装置、电子设备及存储介质
TWI751502B (zh) 冰水主機的性能評估方法
WO2023226595A1 (zh) 空调系统及空调系统的脏堵确定方法
CN113553545B (zh) 小电流电器的事件检测方法及系统、设备、存储介质
WO2024051768A1 (zh) 数据处理方法、装置、设备及存储介质
CN115163452B (zh) 一种无实物压缩机检测方法、装置、设备和可读存储介质
CN115218347A (zh) 一种空调的apf匹配方法、装置、空调和存储介质
CN118111069A (zh) 一种空调器防冻结保护控制方法及装置
CN116379343A (zh) 燃气监测方法、装置、电子设备及可读存储介质

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 23787863

Country of ref document: EP

Kind code of ref document: A1