Compressor energy consumption monitoring method, device and equipment

Abstract

The invention provides a compressor energy consumption monitoring method, device and equipment, relates to the technical field of compressor monitoring, and aims to solve the problem that fault diagnosis and early warning cannot be efficiently and accurately realized according to a compressor energy consumption monitoring result in a general technology. The compressor energy consumption monitoring method comprises the steps of obtaining historical operation monitoring data of a motor-driven compressor, and generating a compressor efficiency wear factor according to the historical operation monitoring data; the real-time motor power of the motor-driven compressor is obtained, and the estimated output power of the motor-driven compressor is generated according to the real-time motor power and the compressor efficiency wear factor; the actual output power of the compressor driven by the motor is obtained, and an output power difference value is generated according to the actual output power and the estimated output power; and determining a compressor energy consumption monitoring result according to the output power difference value.

Description

Technical Field

[0001] The present application relates to the technical field of compressor monitoring, and in particular to a method, device and equipment for monitoring compressor energy consumption. Background Art

[0002] Currently, pipeline booster stations are a crucial link in energy transportation. Failure of the motor-driven compressor, a core component of these stations, can directly impact the stability and economic viability of the entire energy supply chain. Compressor failure is closely linked to compressor energy consumption. Therefore, monitoring compressor energy consumption can provide early warning of compressor failures.

[0003] However, the existing compressor energy consumption monitoring method is to monitor information manually and determine whether the energy consumption is abnormal by setting a fixed rated power. This has the problems of serious manpower consumption and large errors. Summary of the Invention

[0004] The embodiments of the present disclosure provide a compressor energy consumption monitoring method, device and equipment, aiming to solve the problem of how to efficiently and accurately monitor the energy consumption of the compressor in real time.

[0005] To achieve the above objectives, this application adopts the following technical solutions:

[0006] In a first aspect, a compressor energy consumption monitoring method is provided, comprising: obtaining historical operation monitoring data of a motor-driven compressor, and generating a compressor efficiency wear factor based on the historical operation monitoring data; obtaining real-time motor power of the motor-driven compressor, and generating an estimated output power of the motor-driven compressor based on the real-time motor power and the compressor efficiency wear factor; obtaining the actual output power of the motor-driven compressor, and generating an output power difference based on the actual output power and the estimated output power; and determining a compressor energy consumption monitoring result based on the output power difference.

[0007] In some embodiments, the historical operation monitoring data includes: historical monitoring load data, historical monitoring temperature data, and historical monitoring start and stop data; the historical monitoring load data includes: historical suction pressure, historical exhaust flow rate, and historical speed; generating the compressor efficiency wear factor based on the historical operation monitoring data includes: generating historical load fluctuation data of the motor-driven compressor based on the historical monitoring load data; the historical load fluctuation data satisfies the following formula:

[0008]

[0009] Among them, L hs (t) is the historical load fluctuation data corresponding to time point t; α1 is the historical suction pressure weight; P inh (t) is the historical suction pressure corresponding to time point t; α2 is the weight of historical monitoring temperature data; Ths (t) is the historical monitoring temperature data corresponding to time point t; α h is the historical exhaust flow weight; Q hs (t) is the historical exhaust flow corresponding to time point t; Q s is the rated exhaust flow of the compressor; α4 is the historical speed weight; N hs (t) is the historical speed corresponding to time point t; N s is the rated speed of the compressor; the operating status evaluation index of the motor-driven compressor is generated based on the historical monitoring start and stop data and the historical monitoring load data; the operating status evaluation index satisfies the following formula:

[0010]

[0011] Where S(t) is the operating status evaluation index corresponding to time point t; κ is the start-stop impact coefficient; N os (t) is the number of compressor starts from 0 to time point t; v (t) is the proportion of time between 0 and time point t when the historical load fluctuation data is greater than or equal to the preset load fluctuation data; the number of starts is determined based on the historical monitoring start and stop data; the compressor efficiency wear factor is generated based on the historical monitoring load data, historical monitoring temperature data, historical load fluctuation data and the operating status evaluation index.

[0012] In some embodiments, the compressor efficiency wear factor satisfies the following formula:

[0013]

[0014] Where Wf(t) is the compressor efficiency wear factor corresponding to time point t; T max is the historical time length of historical operation monitoring data; λ1 is the first load coefficient; s1 is the load sensitivity coefficient; δ is the nonlinear coefficient; s2 is the temperature sensitivity coefficient; λ2 is the second load coefficient; ΔL re (t) is the variance of the historical load fluctuation data corresponding to time 0 to time point t; s3 is the load fluctuation sensitivity coefficient; λ3 is the state fluctuation coefficient.

[0015] In some embodiments, obtaining real-time motor power of a motor-driven compressor and generating an estimated output power of the motor-driven compressor based on the real-time motor power and a compressor efficiency wear factor includes: obtaining motor electrical information of the motor-driven compressor and generating the real-time motor power based on the motor electrical information; the motor electrical information includes: real-time motor voltage, real-time motor current, and motor power factor; the real-time motor power satisfies the following formula:

[0016] P in (t)=U(t)·I(t)·cos(Φ·t);

[0017] Among them, P in (t) is the real-time motor power corresponding to time point t, U(t) is the real-time motor voltage corresponding to time point t, I(t) is the real-time motor current corresponding to time point t, and cos(Φ·t) is the motor power factor corresponding to time point t. The estimated efficiency of the motor-driven compressor is generated based on the compressor efficiency wear factor. The estimated efficiency satisfies the following formula:

[0018] η(t)=η0·(1-ε·Wf(t));

[0019] Where η(t) is the estimated efficiency at time point t; η0 is the rated efficiency of the compressor; ε is the efficiency influence coefficient; Wf(t) is the compressor efficiency wear factor at time point t; the estimated output power is generated based on the real-time motor power and the estimated efficiency; the estimated output power satisfies the following formula:

[0020] P com (t) = P in (t)·η elc ·η mec η(t);

[0021] Among them, P com (t) is the estimated output power corresponding to time point t; P in (t) is the real-time motor power corresponding to time point t; η elc is the energy conversion efficiency of the motor; η mec It is the energy conversion efficiency of the motor-driven compressor.

[0022] In some embodiments, obtaining the actual output power of the motor-driven compressor includes: obtaining the actual efficiency of the motor-driven compressor; generating the actual output power according to the actual efficiency and the real-time motor power; the actual output power satisfies the following formula:

[0023] P wr =P in (t)·η elc ·η mec ·η pr ;

[0024] Among them, P wr is the actual output power; η elc is the energy conversion efficiency of the motor; η mec is the energy conversion efficiency of the motor-driven compressor; η pr For actual efficiency.

[0025] In some embodiments, the compressor energy consumption monitoring result is determined based on the output power difference, including: when the output power difference exceeds the compressor power deviation range, the compressor energy consumption monitoring result is determined to be energy consumption abnormality, and an energy consumption abnormality reminder is generated; when the output power difference is within the compressor power deviation range, the compressor energy consumption monitoring result is determined to be normal energy consumption.

[0026] In some embodiments, when the real-time operation monitoring data includes real-time monitoring load data and real-time monitoring temperature data, and the real-time monitoring load data includes real-time suction pressure, real-time exhaust flow rate, and real-time speed, the compressor power deviation range is determined by obtaining the real-time operation monitoring data of the motor-driven compressor and generating the real-time operation load of the motor-driven compressor based on the real-time operation monitoring data; the real-time operation load satisfies the following formula:

[0027]

[0028] Among them, L re is the real-time operating load; γ1 is the real-time suction pressure weight; P inh is the real-time suction pressure; γ2 is the real-time monitoring temperature data weight; T re is the real-time monitoring temperature data; γ3 is the real-time exhaust flow weight; Q re is the real-time exhaust flow; Q s is the rated exhaust flow of the compressor; γ4 is the real-time speed weight; N re is the real-time speed; N s is the rated speed of the compressor; the range adjustment coefficient of the compressor power deviation range is determined according to the real-time operating load and historical load fluctuation data; the range adjustment coefficient satisfies the following formula:

[0029]

[0030] Among them, β is the deviation range adjustment coefficient; β0 is the reference adjustment coefficient; L ev The average value of historical load fluctuation data; the compressor power deviation range is generated according to the range adjustment coefficient and the output power difference.

[0031] In some embodiments, generating a compressor power deviation range based on a range adjustment coefficient and an output power difference includes: calculating an output power difference mean and an output power difference standard deviation based on multiple output power differences within a historical period; generating a compressor power deviation range based on the range adjustment coefficient, the output power difference mean, and the output power difference standard deviation; the compressor power deviation range satisfies the following formula:

[0032] [P ev -β·σ,P ev +β·σ];

[0033] Among them, P ev is the mean of the output power difference; σ is the standard deviation of the output power difference.

[0034] In a second aspect, a compressor energy consumption monitoring device is provided, the compressor energy consumption monitoring device comprising: a compressor efficiency wear factor generation module, an estimated output power generation module, an output power difference generation module, and an energy consumption abnormality reminder generation module;

[0035] A compressor efficiency wear factor generation module is used to obtain historical operation monitoring data of the motor-driven compressor and generate a compressor efficiency wear factor based on the historical operation monitoring data;

[0036] An estimated output power generation module is used to obtain the real-time motor power of the motor-driven compressor and generate the estimated output power of the motor-driven compressor based on the real-time motor power and the compressor efficiency wear factor;

[0037] An output power difference generation module is used to obtain the actual output power of the motor-driven compressor and generate an output power difference based on the actual output power and the estimated output power;

[0038] The energy consumption abnormality reminder generation module is used to determine the compressor energy consumption monitoring result based on the output power difference.

[0039] On the third aspect, a compressor energy consumption monitoring device is provided, comprising a memory and a processor; the memory is used to store computer execution instructions, and the processor is connected to the memory through a bus; when the compressor energy consumption monitoring device is running, the processor executes the computer execution instructions stored in the memory, so that the compressor energy consumption monitoring device executes the compressor energy consumption monitoring method of the first aspect.

[0040] The compressor energy consumption monitoring device can be an electronic device or a component within an electronic device, such as a system-on-chip within the electronic device. The system-on-chip is configured to support the electronic device in implementing the functions described in the first aspect and any possible implementation thereof, such as acquiring and determining the data and / or information involved in the compressor energy consumption monitoring method. The system-on-chip includes a chip and may also include other discrete components or circuit structures.

[0041] In a fourth aspect, a computer-readable storage medium is provided, the computer-readable storage medium including computer execution instructions, which, when executed on a computer, enable the computer to execute the compressor energy consumption monitoring method described in the first aspect.

[0042] In a fifth aspect, a computer program product is also provided, which includes a computer program or instructions. When the computer instructions are run on the compressor energy consumption monitoring device, the compressor energy consumption monitoring device executes the compressor energy consumption monitoring method described in the first aspect above.

[0043] It should be noted that the above-mentioned computer instructions may be stored in whole or in part on a computer-readable storage medium. The computer-readable storage medium may be packaged together with the processor of the compressor energy consumption monitoring device, or may be packaged separately from the processor of the compressor energy consumption monitoring device, and this embodiment of the application is not limited thereto.

[0044] The description of the second, third, fourth and fifth aspects of this application can refer to the detailed description of the first aspect.

[0045] In the embodiments of this application, the name of the compressor energy consumption monitoring device does not limit the device or functional module itself. In actual implementation, these devices or functional modules may appear with other names. For example, the receiving unit may also be called a receiving module, a receiver, etc. As long as the functions of each device or functional module are similar to those of this application, they are within the scope of the claims of this application and their equivalents.

[0046] This application provides a compressor energy consumption monitoring method that can obtain historical operating monitoring data of a motor-driven compressor and generate a compressor efficiency wear factor based on the historical operating monitoring data. The method can then obtain the real-time motor power of the motor-driven compressor and generate an estimated output power of the motor-driven compressor based on the real-time motor power and the compressor efficiency wear factor.

[0047] The actual output power of the motor-driven compressor can then be obtained, and the output power difference between the actual output power and the estimated output power can be generated. Subsequently, the compressor energy consumption monitoring result can be determined based on the output power difference.

[0048] As can be seen from the above, this application analyzes the compressor's operating patterns using historical operation monitoring data, accurately modeling the compressor's efficiency wear factor. Furthermore, the application dynamically adjusts the compressor's efficiency wear factor based on continuously updated historical operation monitoring data, more accurately reflecting the compressor's current actual operating status. Next, this application combines real-time motor power and the compressor's efficiency wear factor to more accurately predict the compressor's estimated output power, avoiding the errors caused by relying on a single factor.

[0049] This application then calculates the difference between actual and estimated output power and compares it with the compressor power deviation range, enabling rapid identification of potential compressor performance degradation or failure, effectively avoiding false alarms caused by normal fluctuations in energy consumption. This allows for efficient and accurate fault diagnosis and early warning based on compressor energy consumption monitoring results. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A schematic structural diagram of a compressor energy consumption monitoring system provided in an embodiment of the present application;

[0051] Figure 2 A schematic diagram of the hardware structure of a compressor energy consumption monitoring device provided in an embodiment of the present application;

[0052] Figure 3 A flow chart of a compressor energy consumption monitoring method provided in an embodiment of the present application;

[0053] Figure 4 A schematic structural diagram of a compressor energy consumption monitoring device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0054] The following will be combined with the 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 the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0055] It should be noted that in the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be interpreted as being more preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0056] In order to facilitate a clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, words such as "first" and "second" are used to distinguish between identical or similar items with basically the same functions and effects. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and execution order.

[0057] As mentioned in the background, pipeline booster stations are a crucial link in energy transportation. Failure of the motor-driven compressor, a core component of these stations, directly impacts the stability and economic viability of the entire energy supply chain. Compressor failure is closely linked to compressor energy consumption. Therefore, monitoring compressor energy consumption can provide early warning of compressor failures.

[0058] However, the existing compressor energy consumption monitoring method is to monitor information manually and determine whether the energy consumption is abnormal by setting a fixed rated power. This has the problems of serious manpower consumption and large errors.

[0059] Conventional technologies typically rely on manual monitoring and set fixed power thresholds to identify energy consumption anomalies. This leads to high labor consumption and large errors. Furthermore, this single-minded approach fails to promptly detect potential failures and energy waste. Some conventional technologies focus solely on the current operating data of the motor-driven compressor, ignoring the efficiency degradation caused by prolonged operation. This leads to inaccurate energy consumption monitoring and fault warnings.

[0060] From the above, we can see that general technologies have problems such as high manpower consumption, inability to detect potential faults and energy waste in a timely manner, and inaccurate energy consumption monitoring and fault warning.

[0061] To address the above issues, embodiments of the present application provide a compressor energy consumption monitoring method that can obtain historical operating monitoring data for a motor-driven compressor and generate a compressor efficiency wear factor based on the historical operating monitoring data. Furthermore, the method can obtain the real-time motor power of the motor-driven compressor and generate an estimated output power of the motor-driven compressor based on the real-time motor power and the compressor efficiency wear factor.

[0062] The actual output power of the motor-driven compressor can then be obtained, and the output power difference between the actual output power and the estimated output power can be generated. Subsequently, the compressor energy consumption monitoring result can be determined based on the output power difference.

[0063] As can be seen from the above, this application analyzes the compressor's operating patterns using historical operation monitoring data, accurately modeling the compressor's efficiency wear factor. Furthermore, the application dynamically adjusts the compressor's efficiency wear factor based on continuously updated historical operation monitoring data, more accurately reflecting the compressor's current actual operating status. Next, this application combines real-time motor power and the compressor's efficiency wear factor to more accurately predict the compressor's estimated output power, avoiding the errors caused by relying on a single factor.

[0064] This application then calculates the difference between actual and estimated output power and compares it with the compressor power deviation range, enabling rapid identification of potential compressor performance degradation or failure, effectively avoiding false alarms caused by normal fluctuations in energy consumption. This allows for efficient and accurate fault diagnosis and early warning based on compressor energy consumption monitoring results.

[0065] The implementation environment of the above-mentioned compressor energy consumption monitoring method can be the compressor energy consumption monitoring system provided in the embodiment of the present application.

[0066] Figure 1 This is a schematic diagram of the structure of a compressor energy consumption monitoring system provided in an embodiment of the present application. Figure 1 As shown, the compressor energy consumption monitoring system includes: a compressor energy consumption monitoring device 101 , a data storage device 102 , a motor-driven compressor 103 and an operation monitoring data acquisition device 104 .

[0067] The compressor energy consumption monitoring device 101 includes: a compressor efficiency wear factor generation module 1011 , an estimated output power generation module 1012 , an output power difference generation module 1013 and an energy consumption abnormality reminder generation module 1014 .

[0068] Specifically, the compressor energy consumption monitoring device 101 and the data storage device 102 are communicatively connected, and the compressor energy consumption monitoring device 101 obtains the operation monitoring data (such as real-time operation monitoring data and historical operation monitoring data) of the motor-driven compressor 103 through the operation monitoring data acquisition device 104.

[0069] Specifically, the compressor efficiency wear factor generation module 1011 and the estimated output power generation module 1012 are communicated with each other, the estimated output power generation module 1012 and the output power difference generation module 1013 are communicated with each other, and the output power difference generation module 1013 and the energy consumption abnormality reminder generation module 1014 are communicated with each other.

[0070] In practical applications, the compressor energy consumption monitoring device 101 can be connected to any number of data storage devices 102. The compressor energy consumption monitoring device 101 can be connected to any number of motor-driven compressors 103. For ease of understanding, Figure 1 An example is given in which a compressor energy consumption monitoring device 101 is connected to a data storage device 102 and a compressor energy consumption monitoring device 101 is connected to a motor-driven compressor 103 .

[0071] In an embodiment of the present application, the data storage device 102 is used to provide data for compressor energy consumption monitoring (for example, historical operation monitoring data, etc.) to the compressor energy consumption monitoring device 101, so that the compressor energy consumption monitoring device 101 can implement compressor energy consumption monitoring based on the data sent by the data storage device 102.

[0072] In an embodiment of the present application, the compressor efficiency wear factor generation module 1011 sends the generated compressor efficiency wear factor to the estimated output power generation module 1012, the estimated output power generation module 1012 sends the generated estimated output power to the output power difference generation module 1013, the output power difference generation module 1013 sends the output power difference to the energy consumption abnormality reminder generation module 1014, and the energy consumption abnormality reminder generation module 1014 generates energy consumption monitoring results based on the output power difference.

[0073] Optionally, the physical devices of the compressor energy consumption monitoring device 101 and the data storage device 102 may be servers, terminals, or other types of electronic devices, which is not limited in the embodiments of the present application.

[0074] Optionally, the terminal may be a device that provides voice and / or data connectivity to a user, a handheld device with wireless connection capability, or other processing device connected to a wireless modem. A wireless terminal may communicate with one or more core networks via a radio access network (RAN). A wireless terminal may be a mobile terminal, such as a mobile phone (or "cellular" phone) and a computer with a mobile terminal, or a portable, pocket-sized, handheld, computer-built-in, or vehicle-mounted mobile device that exchanges voice and / or data with a radio access network, such as a mobile phone, tablet computer, laptop computer, netbook, or personal digital assistant (PDA).

[0075] Optionally, the above-mentioned server can be a server in a server cluster (consisting of multiple servers), or a chip in the server, or a system on a chip in the server, or can be implemented through a virtual machine (VM) deployed on a physical machine. This embodiment of the present application does not limit this.

[0076] Optionally, the operation monitoring data acquisition device 104 may be a sensor or a related dedicated monitoring instrument.

[0077] Optionally, the compressor energy consumption monitoring device 101 and the data storage device 102 may be two independent devices, or may be integrated into the same device. When the compressor energy consumption monitoring device 101 and the data storage device 102 are integrated into the same device, the data storage device 102 may be a storage module (e.g., a database, etc.) of the compressor energy consumption monitoring device 101.

[0078] It is easy to understand that when the compressor energy consumption monitoring device 101 and the data storage device 102 are integrated into the same device, the communication method between the compressor energy consumption monitoring device 101 and the data storage device 102 is the communication between the internal modules of the device. In this case, the communication process between the two is the same as the communication process between the compressor energy consumption monitoring device 101 and the data storage device 102 when they are independent of each other.

[0079] For ease of understanding, this application is explained by taking the compressor energy consumption monitoring device 101 and the data storage device 102 as an example in which they are independent of each other.

[0080] The compressor energy consumption monitoring equipment in the compressor energy consumption monitoring system includes: Figure 2 The following are the components included. Figure 2 Taking the compressor energy consumption monitoring device shown as an example, the hardware structure of the compressor energy consumption monitoring device 101 is introduced.

[0081] Figure 2 This is a hardware structure diagram of a compressor energy consumption monitoring device provided in an embodiment of the present application. Figure 2 As shown, the compressor energy consumption monitoring device includes: a processor 201, a memory 202, a communication interface 203, and a bus 204. The processor 201, the memory 202, and the communication interface 203 can be connected via the bus 204.

[0082] Processor 201 is the control center of the compressor energy consumption monitoring device and can be a single processor or a collective term for multiple processing elements. For example, processor 201 can be a general-purpose central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0083] As an embodiment, the processor 201 may include one or more CPUs, such as Figure 2 CPU0 and CPU1 are shown in the figure.

[0084] The memory 202 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0085] The memory 202 may also be an internal storage unit, such as a hard disk or memory. Alternatively, it may be an external storage device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. Furthermore, the memory 202 may include both an internal storage unit and an external storage device. The memory 202 may be used to store an operating system, application programs, a boot loader, data, and other programs. The memory 202 may also be used to temporarily store data that has been output or is about to be output.

[0086] In one possible implementation, memory 202 may exist independently of processor 201 and may be connected to processor 201 via bus 204 for storing instructions or program codes. When processor 201 calls and executes the instructions or program codes stored in memory 202, the compressor energy consumption monitoring method provided in the following embodiments of this application can be implemented.

[0087] In the embodiment of the present application, for the compressor energy consumption monitoring device, the software programs stored in the memory 202 are different, so the functions implemented by the compressor energy consumption monitoring device are different. The functions performed by each device will be described in conjunction with the following flowchart.

[0088] In another possible implementation, the memory 202 may also be integrated with the processor 201 .

[0089] The communication interface 203 is used to connect the compressor energy consumption monitoring device to other devices via a communication network, which may be Ethernet, a wireless access network, a wireless local area network (WLAN), etc. The communication interface 203 may include a receiving unit for receiving data and a sending unit for sending data.

[0090] The bus 204 may be an ISA bus, a PCI bus, or an EISA bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 2 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0091] It should be pointed out that Figure 2 The structure shown in the figure does not constitute a limitation on the compressor energy consumption monitoring device. Figure 2 In addition to the components shown, the compressor energy consumption monitoring device may include more or fewer components than shown, or combine certain components, or arrange the components differently.

[0092] The compressor energy consumption monitoring method provided in the embodiment of the present application is described in detail below with reference to the accompanying drawings.

[0093] The compressor energy consumption monitoring method provided in the embodiment of the present application is applied to Figure 1 The compressor energy consumption monitoring device 101 in the compressor energy consumption monitoring system shown in FIG. Figure 3 As shown, a compressor energy consumption monitoring method provided by an embodiment of the present application includes:

[0094] S301. The compressor energy consumption monitoring device obtains historical operation monitoring data of the motor-driven compressor, and generates a compressor efficiency wear factor based on the historical operation monitoring data.

[0095] Specifically, in order to comprehensively consider the factors affecting the efficiency of the compressor, it is necessary to generate a compressor efficiency wear factor using historical operation monitoring data obtained by the compressor energy consumption monitoring device.

[0096] Optionally, the length of the historical time period of the historical operation monitoring data can be set by relevant staff based on experience and is not limited here.

[0097] For example, historical operation monitoring data within a historical period of 2 years may be obtained.

[0098] Optionally, the influencing factors may be temperature, rotation speed, flow rate, etc., which are not limited here.

[0099] Specifically, the compressor efficiency wear factor is generated according to the historical operation monitoring data. Please refer to the detailed description in some embodiments below, which will not be repeated here.

[0100] S302 : The compressor energy consumption monitoring device obtains the real-time motor power of the motor-driven compressor, and generates an estimated output power of the motor-driven compressor based on the real-time motor power and the compressor efficiency wear factor.

[0101] Specifically, in order to measure the actual output efficiency, it is necessary to determine a standard value under ideal conditions, that is, the estimated output power, through the compressor efficiency wear factor and the real-time motor power.

[0102] Optionally, the real-time motor power may be calculated by measuring the real-time motor voltage and the real-time motor current using relevant instruments.

[0103] Specifically, the real-time motor power is determined, and reference is made to the detailed description in some embodiments below, which will not be repeated here.

[0104] Specifically, the estimated output power of the motor-driven compressor is generated according to the real-time motor power and the compressor efficiency wear factor. Please refer to the detailed description in some embodiments below, which will not be repeated here.

[0105] S303: The compressor energy consumption monitoring device obtains the actual output power of the motor-driven compressor, and generates an output power difference according to the actual output power and the estimated output power.

[0106] Specifically, in order to obtain the output power difference and thus obtain the energy consumption monitoring result, it is necessary to obtain the actual output power and calculate the difference between the actual output power and the estimated output power.

[0107] Specifically, the actual output power cannot be directly measured by an instrument and can be replaced by an infinite approximation. For detailed determination methods, please refer to the detailed description in some embodiments below and will not be repeated here.

[0108] S304. The compressor energy consumption monitoring device determines the compressor energy consumption monitoring result according to the output power difference.

[0109] Specifically, in order to issue an early warning when the result is in an abnormal energy consumption state, it is necessary to determine the energy consumption monitoring result based on the output power difference.

[0110] Specifically, the energy consumption monitoring result is abnormal or normal energy consumption. In the case of abnormal energy consumption, an early warning is issued to instruct relevant staff to perform fault repair. Detailed judgment rules are described in detail in some embodiments below and are not repeated here.

[0111] In some embodiments, in the above S301, the historical operation monitoring data includes: historical monitoring load data, historical monitoring temperature data, and historical monitoring start and stop data; the historical monitoring load data includes: historical suction pressure, historical exhaust flow rate, and historical speed; generating the compressor efficiency wear factor based on the historical operation monitoring data specifically includes:

[0112] The compressor energy consumption monitoring device generates historical load fluctuation data of the motor-driven compressor based on historical monitoring load data; the historical load fluctuation data satisfies the following formula:

[0113]

[0114] Among them, L hs (t) is the historical load fluctuation data corresponding to time point t; α1 is the historical suction pressure weight; P inh (t) is the historical suction pressure corresponding to time point t; α2 is the weight of historical monitoring temperature data; T hs (t) is the historical monitoring temperature data corresponding to time point t; α3 is the historical exhaust flow weight; Q hs (t) is the historical exhaust flow corresponding to time point t; Q s is the rated exhaust flow of the compressor; α4 is the historical speed weight; N hs (t) is the historical speed corresponding to time point t; N s is the rated speed of the compressor.

[0115] Specifically, in order to integrate various data to generate historical load fluctuation data corresponding to each time point t, the historical intake pressure corresponding to time point t, the historical monitoring temperature data corresponding to time point t, the historical exhaust flow corresponding to time point t, and the historical speed corresponding to time point t are extracted from the historical load fluctuation data.

[0116] Optionally, the historical intake pressure weight, historical monitoring temperature data weight, historical exhaust flow weight and historical speed weight can be pre-set values ​​and used to respectively represent the impact of historical intake pressure, historical monitoring temperature data, historical exhaust flow and historical speed on historical load fluctuation data.

[0117] For example, the values ​​of the historical intake pressure weight, the historical monitored temperature data weight, the historical exhaust flow weight, and the historical speed weight may be set to 0.3, 0.1, 0.25, and 0.35, respectively.

[0118] The compressor energy consumption monitoring device generates an operating status evaluation index of the motor-driven compressor based on historical monitoring start and stop data and historical monitoring load data; the operating status evaluation index satisfies the following formula:

[0119]

[0120] Where S(t) is the operating status evaluation index corresponding to time point t; κ is the start-stop impact coefficient; N os (t) is the number of compressor starts from 0 to time point t; v (t) is the percentage of time between time 0 and time point t when the historical load fluctuation data is greater than or equal to the preset load fluctuation data; the number of starts is determined based on the historical monitoring start and stop data.

[0121] Specifically, to comprehensively generate the operating status evaluation index based on the operating status, it is necessary to obtain the number of compressor starts between time 0 and time t, as well as the percentage of time between time 0 and time t when historical load fluctuation data is greater than or equal to the preset load fluctuation data. The start-stop impact coefficient is used to indicate the degree of influence of the number of compressor starts on the operating status evaluation index.

[0122] It is understandable that the start-stop process often brings additional shock or stress concentration to the mechanical parts, bearings and lubrication system of the compressor. Therefore, the historical monitoring start-stop data of the compressor between 0 and time point t is used as a parameter to measure the operating status evaluation index. The proportion of time when the historical load fluctuation data is greater than or equal to the preset load fluctuation data can reflect whether the compressor is often operating in an overloaded state. If it is in an overloaded state for a long time, it will increase wear. Therefore, the proportion of time in the overloaded state is used as a parameter to measure the operating status evaluation index. By setting the denominator to 1+t, the impact of frequent starts and stops in a short period of time can be made more obvious, and the impact of frequent starts and stops in a long period of time can be smoother.

[0123] The compressor energy consumption monitoring device generates a compressor efficiency wear factor based on historical monitoring load data, historical monitoring temperature data, historical load fluctuation data and an operating status evaluation index.

[0124] Specifically, in order to generate a more accurate compressor efficiency wear factor, historical monitoring load data, historical monitoring temperature data, historical load fluctuation data and an operating status evaluation index are integrated.

[0125] In some embodiments, the compressor efficiency wear factor satisfies the following formula:

[0126]

[0127] Where Wf(t) is the compressor efficiency wear factor corresponding to time point t; T maxis the historical time length of historical operation monitoring data; λ1 is the first load coefficient; s1 is the load sensitivity coefficient; δ is the nonlinear coefficient; s2 is the temperature sensitivity coefficient; λ2 is the second load coefficient; ΔL re (t) is the variance of the historical load fluctuation data corresponding to time 0 to time point t; s3 is the load fluctuation sensitivity coefficient; λ3 is the state fluctuation coefficient.

[0128] Specifically, the compressor efficiency wear factor Wf(t) is obtained by integral calculation, which is consistent with the accumulation of the compressor efficiency wear factor over time in actual situations.

[0129] Specifically, through It represents the coupling amplification value of compressor wear after combining historical load fluctuation data and historical monitoring temperature data. It represents the coupling amplification value of the mutual influence between historical load fluctuation data and operating status evaluation index on compressor wear.

[0130] Specifically, the first load coefficient represents the combined impact of historical load fluctuation data and historical monitored temperature data. The second load coefficient and the state fluctuation coefficient represent the combined impact of historical load fluctuation data and the operating state assessment index. The load sensitivity coefficient, temperature sensitivity coefficient, and load fluctuation sensitivity coefficient represent the power relationship between the variances of historical load fluctuation data, historical monitored temperature data, and historical load fluctuation data, respectively.

[0131] It is understandable that the compressor is generally provided with additional protection (for example, the compressor is equipped with more monitoring, frequent lubrication and additional cooling protection). Therefore, the historical monitoring start-stop data and the high load state will have an impact on the compressor efficiency wear factor, but the impact is not unlimited. That is, when the high load state of the equipment and the historical monitoring start-stop data reach a certain value, the impact on the compressor efficiency wear factor will tend to saturation. Therefore, the embodiment of the present application is through The impact on wear is limited, making it more practical.

[0132] Specifically, the historical monitored temperature data is the temperature associated with the compressor, which in this embodiment refers to the external temperature of the compressor. The variance of the historical load fluctuation data is the variance calculated based on the historical load fluctuation data corresponding to each time point from 0 to time point t.

[0133] It can be understood that adding the variance into the formula can reflect the stability of the historical load fluctuation data.

[0134] Optionally, the time length T occupied by historical operation monitoring data max Set it according to the actual situation.

[0135] For example, the first load factor and the second load factor may be set to 0.4 and 0.6 respectively, and the state fluctuation factor may be set to 2. The load sensitivity factor, the temperature sensitivity factor, and the load fluctuation sensitivity factor may be 2, 2, and 3 respectively.

[0136] For example, the historical operating loads corresponding to t1, t2, t3 and t4 are L hs1 , L hs2 , L hs3 and L hs4 The variance corresponding to time point t3 is calculated based on L hs1 , L hs2 and L hs3 The variance corresponding to time point t4 is calculated based on L hs1 , L hs2 , L hs3 and L hs4 Calculated.

[0137] That is, the process of the embodiment of the present application may be as follows: historical operation monitoring data of a motor-driven compressor is obtained; historical monitoring load data, historical monitoring temperature data, and historical monitoring start / stop data are extracted based on the historical operation monitoring data; historical load fluctuation data is generated based on the historical monitoring load data; an operation status evaluation index is generated based on the historical monitoring start / stop data and the historical monitoring load data; and a compressor efficiency wear factor is generated based on the historical monitoring load data, the historical monitoring temperature data, the historical load fluctuation data, and the operation status evaluation index.

[0138] In some embodiments, in the above S302, obtaining the real-time motor power of the motor-driven compressor and generating the estimated output power of the motor-driven compressor based on the real-time motor power and the compressor efficiency wear factor specifically include:

[0139] The compressor energy consumption monitoring device obtains the motor electrical information of the motor-driven compressor and generates real-time motor power based on the motor electrical information. The motor electrical information includes: real-time motor voltage, real-time motor current, and motor power factor. The real-time motor power satisfies the following formula:

[0140] P in (t)=U(t)·I(t)·cos(Φ·t);

[0141] Among them, P in (t) is the real-time motor power corresponding to time point t, U(t) is the real-time motor voltage corresponding to time point t, I(t) is the real-time motor current corresponding to time point t, and cos(Φ·t) is the motor power factor corresponding to time point t.

[0142] Specifically, in order to obtain the real-time motor power corresponding to time point t, it is necessary to calculate it according to the real-time motor voltage corresponding to time point t, the real-time motor current corresponding to time point t, and the motor power factor corresponding to time point t using the power calculation formula.

[0143] Optionally, the real-time motor voltage and the real-time motor current corresponding to the time point t can be obtained by relevant instruments or sensors. The motor power factor can be preset by relevant personnel based on experience.

[0144] The compressor energy consumption monitoring device generates an estimated efficiency of the motor-driven compressor based on the compressor efficiency wear factor; the estimated efficiency satisfies the following formula:

[0145] η(t)=η0·(1-ε·Wf(t));

[0146] Wherein, η(t) is the estimated efficiency corresponding to time point t; η0 is the rated efficiency of the compressor; ε is the efficiency influence coefficient; Wf(t) is the compressor efficiency wear factor corresponding to time point t.

[0147] Specifically, in the embodiment of the present application, the estimated efficiency is determined by establishing a decay model (i.e., the above formula). The efficiency impact coefficient can ensure that the value of ε·Wf(t) is greater than 0 and less than 1, thereby ensuring that η(t) is less than η0.

[0148] Exemplarily, the efficiency impact coefficient is set to 0.6.

[0149] The compressor energy consumption monitoring device generates an estimated output power based on the real-time motor power and estimated efficiency. The estimated output power satisfies the following formula:

[0150] P com (t) = P in (t)·η elc ·η mec η(t);

[0151] Among them, P com (t) is the estimated output power corresponding to time point t; P in (t) is the real-time motor power corresponding to time point t; η elc is the energy conversion efficiency of the motor; η mec It is the energy conversion efficiency of the motor-driven compressor.

[0152] Specifically, the mechanical efficiency (i.e., the energy conversion efficiency of the motor-driven compressor) is the efficiency of converting the mechanical power output on the motor shaft into the useful mechanical power required by the compressor, and the electrical efficiency of the motor (i.e., the energy conversion efficiency of the motor) refers to the efficiency of the motor in converting the input electrical energy into mechanical energy.

[0153] For example, the energy conversion efficiency of the motor-driven compressor may be set to 85% to 90%, and the energy conversion efficiency of the motor may be set to 82% to 98%.

[0154] Optionally, the energy conversion efficiency of the motor-driven compressor and the energy conversion efficiency of the motor may vary with different working conditions. Therefore, their specific values ​​are generally set by relevant staff based on experience.

[0155] It can be understood that in the embodiment of the present application, the relationship between the real-time motor power and the estimated output power is used to model the relationship between the two, thereby achieving the generation of the estimated compressor output power based on the real-time motor power.

[0156] In some embodiments, in the above S303, obtaining the actual output power of the motor-driven compressor specifically includes:

[0157] Compressor energy consumption monitoring equipment obtains the actual efficiency of the motor-driven compressor.

[0158] Specifically, the actual efficiency is pre-set.

[0159] Optionally, when setting the actual efficiency, the actual efficiencies corresponding to different usage stages of the motor-driven compressor can be pre-established based on usage data of a large number of reference compressors. Therefore, when monitoring the current motor-driven compressor, the actual efficiency corresponding to the practical stage corresponding to the current motor-driven compressor can be obtained by analyzing the current motor-driven compressor.

[0160] Specifically, the usage data of the motor-driven compressor is compared with the usage data corresponding to the reference compressor, and the similarity is calculated. The usage data corresponding to the reference compressor with the highest similarity to the motor-driven compressor is set as the actual efficiency of the motor-driven compressor.

[0161] It is understandable that the selected reference compressors are all equipment that are put into normal use and scrapped after reaching the end of their service life, so that the efficiency of the reference compressors corresponding to each use stage can be used as a reference, providing reliable data for setting the actual efficiency.

[0162] Optionally, the actual efficiency can also be set based on the experience of those skilled in the art, and different actual efficiencies can be set directly according to different usage times. The actual efficiency is not limited to the above method. Those skilled in the art can also choose other methods as long as they can ensure that the actual efficiency can be reasonably set. This embodiment of the application does not limit this.

[0163] The compressor energy consumption monitoring device generates the actual output power based on the actual efficiency and real-time motor power. The actual output power satisfies the following formula:

[0164] P wr =P in (t)·η elc ·η mec ·η pr ;

[0165] Among them, P wr is the actual output power; η elc is the energy conversion efficiency of the motor; η mec is the energy conversion efficiency of the motor-driven compressor; η pr For actual efficiency.

[0166] Specifically, the motor power is converted into actual output power through the energy conversion efficiency of the motor, the energy conversion efficiency of the motor-driven compressor, and the actual efficiency.

[0167] In some embodiments, in the above S304, determining the compressor energy consumption monitoring result according to the output power difference specifically includes:

[0168] When the output power difference of the compressor energy consumption monitoring device exceeds the compressor power deviation range, the compressor energy consumption monitoring result is determined to be abnormal energy consumption and an abnormal energy consumption reminder is generated.

[0169] Specifically, in order to accurately generate an energy consumption abnormality reminder when the energy consumption monitoring result is abnormal energy consumption, it is necessary to compare the output power difference with the pre-calculated compressor power deviation range.

[0170] Specifically, the process of determining the compressor power deviation range is described in detail in some embodiments below and is not described here in detail.

[0171] When the output power difference of the compressor energy consumption monitoring device is within the compressor power deviation range, the compressor energy consumption monitoring result is determined to be normal.

[0172] Specifically, in order to monitor that the energy consumption monitoring result is normal, it is necessary to compare the output power difference with the pre-calculated compressor power deviation range.

[0173] That is, the process of the embodiment of the present application may be as follows: calculating the output power difference mean and the output power difference standard deviation based on the output power difference. Acquiring real-time operation monitoring data of the motor-driven compressor. Generating a real-time operating load based on the real-time operation monitoring data. Generating a compressor power deviation range based on the real-time operating load, the output power difference mean, and the output power difference standard deviation. Determining whether the output power difference exceeds the compressor power deviation range; if not, generating a normal energy consumption indication; if so, generating an abnormal energy consumption reminder.

[0174] In some embodiments, when the real-time operation monitoring data includes real-time monitoring load data and real-time monitoring temperature data, and the real-time monitoring load data includes real-time suction pressure, real-time exhaust flow rate, and real-time speed, the compressor power deviation range is determined by obtaining the real-time operation monitoring data of the motor-driven compressor and generating the real-time operation load of the motor-driven compressor based on the real-time operation monitoring data; the real-time operation load satisfies the following formula:

[0175]

[0176] Among them, L re is the real-time operating load; γ1 is the real-time suction pressure weight; P inh is the real-time suction pressure; γ2 is the real-time monitoring temperature data weight; T re is the real-time monitoring temperature data; γ3 is the real-time exhaust flow weight; Q re is the real-time exhaust flow; Q s is the rated exhaust flow of the compressor; γ4 is the real-time speed weight; N re is the real-time speed; N s is the rated speed of the compressor.

[0177] Specifically, the real-time operating load is the energy consumption required by the compressor in the real-time operating state. The greater the real-time suction pressure of the compressor, the greater the power required by the compressor, and the greater the real-time operating load. The real-time monitoring temperature data of the compressor affects the real-time operating load and is also an important factor in calculating the real-time operating load. The compressor exhaust flow rate directly affects the real-time operating load, and the compressor exhaust flow rate is positively correlated with the real-time operating load. The real-time operating load will be affected by the compressor's real-time speed being too high or too low. Therefore, the real-time operating load is determined by comprehensively considering the compressor's real-time suction pressure, compressor ambient temperature, compressor exhaust flow rate, and compressor real-time speed.

[0178] Specifically, the real-time suction pressure weight, the real-time monitoring temperature data weight, the real-time exhaust flow weight and the real-time speed weight are respectively used to represent the numerical values ​​of the impact of the compressor's real-time suction pressure, real-time monitoring temperature data, real-time exhaust flow and real-time speed on the real-time operating load.

[0179] Optionally, the real-time intake pressure weight, real-time monitoring temperature data weight, real-time exhaust flow weight and real-time speed weight can be set to the same value as the historical intake pressure weight, historical monitoring temperature data weight, historical exhaust flow weight and historical speed weight respectively.

[0180] For example, the values ​​of the real-time intake pressure weight, the real-time monitored temperature data weight, the real-time exhaust flow weight, and the real-time speed weight may be 0.3, 0.1, 0.25, and 0.35, respectively.

[0181] The range adjustment coefficient of the compressor power deviation range is determined based on the real-time operating load and historical load fluctuation data; the range adjustment coefficient satisfies the following formula:

[0182]

[0183] Among them, β is the deviation range adjustment coefficient; β0 is the reference adjustment coefficient; L ev The average value of historical load fluctuation data; the compressor power deviation range is generated according to the range adjustment coefficient and the output power difference.

[0184] Specifically, by calculating To express the comprehensive impact of real-time operating load and historical load fluctuation data on the compressor power deviation range.

[0185] It is understandable that if measurement and judgment are performed according to a fixed preset threshold (the same as the compressor power deviation range in this application), misjudgment of faults may occur. In order to avoid this situation, the compressor power deviation range needs to be increased accordingly, so as to better avoid misjudgment of fluctuations in real-time operating load and achieve more accurate fault diagnosis based on compressor energy consumption monitoring.

[0186] Optionally, a deviation range adjustment coefficient may be generated based on the following formula:

[0187]

[0188] Among them, Δβ is the weight adjustment coefficient.

[0189] Specifically, by setting the weight adjustment coefficient, it is possible to indicate the degree of influence of the real-time operating load on the deviation range adjustment coefficient. To enhance the impact of real-time operating load changes on the deviation range adjustment coefficient.

[0190] Optionally, you can also set

[0191] Exemplarily, the weight adjustment coefficient may be set to 0.8.

[0192] Specifically, a maximum deviation range adjustment coefficient is set. Between the deviation range adjustment coefficient generated based on the above formula and the maximum deviation adjustment coefficient, the smaller value is selected as the actual deviation range adjustment coefficient.

[0193] It is understandable that by setting the maximum deviation range adjustment coefficient, it is possible to avoid the deviation range adjustment coefficient from increasing infinitely, which would lead to errors in the compressor energy consumption monitoring results.

[0194] In some embodiments, generating a compressor power deviation range according to the range adjustment coefficient and the output power difference includes:

[0195] The compressor energy consumption monitoring device calculates the output power difference mean and the output power difference standard deviation based on multiple output power differences within a historical period.

[0196] Specifically, in order to determine the output power difference mean and the output power difference standard deviation, calculations need to be performed based on multiple output power differences within a historical period.

[0197] Optionally, the length of the historical time can be determined by relevant staff based on historical experience, and can be 1 month or 1 year, etc., and is not limited here.

[0198] Exemplarily, the output power difference over two historical months is selected.

[0199] The compressor energy consumption monitoring device generates a compressor power deviation range based on the range adjustment coefficient, the output power difference mean, and the output power difference standard deviation. The compressor power deviation range satisfies the following formula:

[0200] [P ev -β·σ,P ev +β·σ];

[0201] Among them, P ev is the mean of the output power difference; σ is the standard deviation of the output power difference.

[0202] Specifically, the output power difference is greater than or equal to P ev -β·σ, and less than or equal to P ev When the value is +β·σ, the energy consumption monitoring result is normal. On the contrary, the energy consumption monitoring result is abnormal.

[0203] The above mainly introduces the solution provided by the embodiment of the present application from the perspective of method. In order to realize the above functions, it includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily appreciate that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in a hardware or computer software driven hardware manner depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0204] In the embodiment of the present application, the compressor energy consumption monitoring device can be divided into functional modules according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated modules can be implemented in the form of hardware or software functional modules. Optionally, the division of modules in the embodiment of the present application is schematic and is only a logical functional division. In actual implementation, other division methods can be used.

[0205] Figure 4 FIG. 1 shows a schematic diagram of the structure of a compressor energy consumption monitoring device provided in an embodiment of the present application. Figure 4 As shown, the compressor energy consumption monitoring device includes: a compressor efficiency wear factor generation module 401, an estimated output power generation module 402, an output power difference generation module 403 and an energy consumption abnormality reminder generation module 404;

[0206] The compressor efficiency wear factor generating module 401 is configured to obtain historical operation monitoring data of the motor-driven compressor and generate a compressor efficiency wear factor based on the historical operation monitoring data.

[0207] The estimated output power generation module 402 is configured to obtain the real-time motor power of the motor-driven compressor and generate the estimated output power of the motor-driven compressor according to the real-time motor power and the compressor efficiency wear factor.

[0208] The output power difference generating module 403 is configured to obtain the actual output power of the motor-driven compressor and generate an output power difference based on the actual output power and the estimated output power.

[0209] The energy consumption abnormality reminder generating module 404 is used to determine the compressor energy consumption monitoring result according to the output power difference.

[0210] In some embodiments, the historical operation monitoring data includes: historical monitoring load data, historical monitoring temperature data, and historical monitoring start and stop data; the historical monitoring load data includes: historical suction pressure, historical exhaust flow rate, and historical speed; the compressor efficiency wear factor generation module 401 is specifically used to:

[0211] Generate historical load fluctuation data of the motor-driven compressor based on historical monitoring load data; the historical load fluctuation data satisfies the following formula:

[0212]

[0213] Among them, L hs (t) is the historical load fluctuation data corresponding to time point t; α1 is the historical suction pressure weight; P inh(t) is the historical suction pressure corresponding to time point t; α2 is the weight of historical monitoring temperature data; T hs (t) is the historical monitoring temperature data corresponding to time point t; α3 is the historical exhaust flow weight; Q hs (t) is the historical exhaust flow corresponding to time point t; Q s is the rated exhaust flow of the compressor; α4 is the historical speed weight; N hs (t) is the historical speed corresponding to time point t; N s is the rated speed of the compressor.

[0214] The operating status evaluation index of the motor-driven compressor is generated based on the historical monitoring start-stop data and the historical monitoring load data. The operating status evaluation index satisfies the following formula:

[0215]

[0216] Where S(t) is the operating status evaluation index corresponding to time point t; κ is the start-stop impact coefficient; N os (t) is the number of compressor starts from 0 to time point t; v (t) is the percentage of time between time 0 and time point t when the historical load fluctuation data is greater than or equal to the preset load fluctuation data; the number of starts is determined based on the historical monitoring start and stop data.

[0217] The compressor efficiency wear factor is generated based on historical monitoring load data, historical monitoring temperature data, historical load fluctuation data and an operating status evaluation index.

[0218] In some embodiments, the compressor efficiency wear factor satisfies the following formula:

[0219]

[0220] Where Wf(t) is the compressor efficiency wear factor corresponding to time point t; T max is the historical time length of historical operation monitoring data; λ1 is the first load coefficient; s1 is the load sensitivity coefficient; δ is the nonlinear coefficient; s2 is the temperature sensitivity coefficient; λ2 is the second load coefficient; ΔL re (t) is the variance of the historical load fluctuation data corresponding to time 0 to time point t; s3 is the load fluctuation sensitivity coefficient; λ3 is the state fluctuation coefficient.

[0221] In some embodiments, the estimated output power generation module 402 is specifically configured to:

[0222] The motor electrical information of the motor-driven compressor is obtained, and the real-time motor power is generated based on the motor electrical information; the motor electrical information includes: real-time motor voltage, real-time motor current, and motor power factor; the real-time motor power satisfies the following formula:

[0223] P in (t)=U(t)·I(t)·cos(Φ·t);

[0224] Among them, P in (t) is the real-time motor power corresponding to time point t, U(t) is the real-time motor voltage corresponding to time point t, I(t) is the real-time motor current corresponding to time point t, and cos(Φ·t) is the motor power factor corresponding to time point t.

[0225] The estimated efficiency of the motor-driven compressor is generated based on the compressor efficiency wear factor; the estimated efficiency satisfies the following formula:

[0226] η(t)=η0·(1-ε·Wf(t));

[0227] Wherein, η(t) is the estimated efficiency corresponding to time point t; η0 is the rated efficiency of the compressor; ε is the efficiency influence coefficient; Wf(t) is the compressor efficiency wear factor corresponding to time point t.

[0228] The estimated output power is generated based on the real-time motor power and estimated efficiency. The estimated output power satisfies the following formula:

[0229] P com (t) = P in (t)·η elc ·η mec η(t);

[0230] Among them, P com (t) is the estimated output power corresponding to time point t; P in (t) is the real-time motor power corresponding to time point t; η elc is the energy conversion efficiency of the motor; η mec It is the energy conversion efficiency of the motor-driven compressor.

[0231] In some embodiments, the output power difference generating module 403 is specifically configured to:

[0232] Get the actual efficiency of the motor-driven compressor.

[0233] The actual output power is generated based on the actual efficiency and real-time motor power; the actual output power satisfies the following formula:

[0234] P wr =P in (t)·η elc ·ηmec ·η pr ;

[0235] Among them, P wr is the actual output power; η elc is the energy conversion efficiency of the motor; η nec is the energy conversion efficiency of the motor-driven compressor; η pr For actual efficiency.

[0236] In some embodiments, the energy consumption abnormality reminder generating module 404 is specifically configured to:

[0237] When the output power difference exceeds the compressor power deviation range, the compressor energy consumption monitoring result is determined to be energy consumption abnormality, and an energy consumption abnormality reminder is generated.

[0238] When the output power difference is within the compressor power deviation range, it is determined that the compressor energy consumption monitoring result is normal.

[0239] In some embodiments, when the real-time operation monitoring data includes real-time monitoring load data and real-time monitoring temperature data, and the real-time monitoring load data includes real-time suction pressure, real-time exhaust flow rate, and real-time speed, the compressor power deviation range is determined by obtaining the real-time operation monitoring data of the motor-driven compressor and generating the real-time operation load of the motor-driven compressor based on the real-time operation monitoring data; the real-time operation load satisfies the following formula:

[0240]

[0241] Among them, L re is the real-time operating load; γ1 is the real-time suction pressure weight; P inh is the real-time suction pressure; γ2 is the real-time monitoring temperature data weight; T re is the real-time monitoring temperature data; γ3 is the real-time exhaust flow weight; Q re is the real-time exhaust flow; Q s is the rated exhaust flow of the compressor; γ4 is the real-time speed weight; N re is the real-time speed; N s is the rated speed of the compressor. The range adjustment coefficient of the compressor power deviation range is determined based on the real-time operating load and historical load fluctuation data; the range adjustment coefficient satisfies the following formula:

[0242]

[0243] Among them, β is the deviation range adjustment coefficient; β0 is the reference adjustment coefficient; L ev The average value of historical load fluctuation data. The compressor power deviation range is generated based on the range adjustment coefficient and the output power difference.

[0244] In some embodiments, the energy consumption abnormality reminder generating module 404 is specifically configured to:

[0245] The output power difference mean and the output power difference standard deviation are calculated based on multiple output power differences within a historical period.

[0246] The compressor power deviation range is generated based on the range adjustment coefficient, the output power difference mean, and the output power difference standard deviation. The compressor power deviation range satisfies the following formula:

[0247] [P ev -β·σ,P ev +β·σ];

[0248] Among them, P ev is the mean of the output power difference; σ is the standard deviation of the output power difference.

[0249] An embodiment of the present application also provides a computer-readable storage medium, which includes computer-executable instructions. When the computer-executable instructions are executed on a computer, the computer executes the compressor energy consumption monitoring method provided in the above embodiment.

[0250] An embodiment of the present application also provides a computer program, which can be directly loaded into a memory and contains software code. After being loaded and executed by a computer, the computer program can implement the compressor energy consumption monitoring method provided in the above embodiment.

[0251] Those skilled in the art will appreciate that, in one or more of the examples above, the functions described herein can be implemented using hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer-readable storage media and communication media, wherein communication media include any medium that facilitates the transmission of a computer program from one place to another. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0252] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0253] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules or units is merely a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place, or they may be distributed in multiple different places. Some or all of the units can be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0254] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or in other words, the part that contributes to the general technology or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for making a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

[0255] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A compressor energy consumption monitoring method, characterized in that: include: Acquiring historical operation monitoring data of a motor-driven compressor, and generating a compressor efficiency wear factor based on the historical operation monitoring data; Acquiring real-time motor power of the motor-driven compressor, and generating an estimated output power of the motor-driven compressor based on the real-time motor power and the compressor efficiency wear factor; Acquiring an actual output power of the motor-driven compressor, and generating an output power difference based on the actual output power and the estimated output power; The compressor energy consumption monitoring result is determined according to the output power difference.

2. The method according to claim 1, characterized in that The historical operation monitoring data includes: historical monitoring load data, historical monitoring temperature data and historical monitoring start and stop data; the historical monitoring load data includes: historical suction pressure, historical exhaust flow and historical speed; the compressor efficiency wear factor generated according to the historical operation monitoring data includes: The historical load fluctuation data of the motor-driven compressor is generated based on the historical monitoring load data; the historical load fluctuation data satisfies the following formula: Among them, L hs (t) is the historical load fluctuation data corresponding to time point t; α1 is the historical suction pressure weight; P inh (t) is the historical suction pressure corresponding to time point t; α2 is the weight of historical monitoring temperature data; T hs (t) is the historical monitoring temperature data corresponding to time point t; α3 is the historical exhaust flow weight; Q hs (t) is the historical exhaust flow corresponding to time point t; Q s is the rated exhaust flow of the compressor; α4 is the historical speed weight; N hs (t) is the historical speed corresponding to time point t; N s is the rated speed of the compressor; An operating status evaluation index of the motor-driven compressor is generated based on the historical monitoring start-stop data and the historical monitoring load data; the operating status evaluation index satisfies the following formula: Where S(t) is the operating status evaluation index corresponding to time point t; κ is the start-stop impact coefficient; N os (t) is the number of compressor starts from 0 to time point t; v (t) is the time percentage between time 0 and time point t when the historical load fluctuation data is greater than or equal to the preset load fluctuation data; the number of starts is determined based on the historical monitoring start-stop data; The compressor efficiency wear factor is generated according to the historical monitored load data, the historical monitored temperature data, the historical load fluctuation data, and the operating status evaluation index.

3. The method according to claim 2, characterized in that The compressor efficiency wear factor satisfies the following formula: Where Wf(t) is the compressor efficiency wear factor corresponding to time point t; T max is the historical time length of the historical operation monitoring data; λ1 is the first load coefficient; s1 is the load sensitivity coefficient; δ is the nonlinear coefficient; s2 is the temperature sensitivity coefficient; λ2 is the second load coefficient; ΔL re (t) is the variance of the historical load fluctuation data corresponding to time 0 to time point t; s3 is the load fluctuation sensitivity coefficient; λ3 is the state fluctuation coefficient.

4. The method according to claim 1, wherein The acquiring the real-time motor power of the motor-driven compressor and generating the estimated output power of the motor-driven compressor according to the real-time motor power and the compressor efficiency wear factor includes: Acquire motor electrical information of the motor-driven compressor and generate the real-time motor power based on the motor electrical information; the motor electrical information includes: real-time motor voltage, real-time motor current, and motor power factor; the real-time motor power satisfies the following formula: P in (t)=U(t)·I(t)·cos(Φ·t); Among them, P in (t) is the real-time motor power corresponding to time point t, U(t) is the real-time motor voltage corresponding to time point t, I(t) is the real-time motor current corresponding to time point t, and cos(Φ·t) is the motor power factor corresponding to time point t; An estimated efficiency of the motor-driven compressor is generated according to the compressor efficiency wear factor; the estimated efficiency satisfies the following formula: η(t)=η0·(1-ε·Wf(t)); Wherein, η(t) is the estimated efficiency corresponding to time point t; η0 is the rated efficiency of the compressor; ε is the efficiency influence coefficient; Wf(t) is the compressor efficiency wear factor corresponding to time point t; The estimated output power is generated according to the real-time motor power and the estimated efficiency; the estimated output power satisfies the following formula: P com (t)=P in (t)·h elc ·or mec ·η(t); Among them, P com (t) is the estimated output power corresponding to time point t; P in (t) is the real-time motor power corresponding to time point t; η elc is the energy conversion efficiency of the motor; η mec The energy conversion efficiency of the motor-driven compressor.

5. The method according to claim 1, wherein The obtaining of the actual output power of the motor-driven compressor includes: Obtaining actual efficiency of the motor-driven compressor; The actual output power is generated according to the actual efficiency and the real-time motor power; the actual output power satisfies the following formula: P wr =P in (t)·h elc ·or mec ·or pr ; Among them, P wr is the actual output power; η elc is the energy conversion efficiency of the motor; η mec is the energy conversion efficiency of the motor-driven compressor; η pr is the actual efficiency.

6. The method according to claim 1, wherein Determining the compressor energy consumption monitoring result according to the output power difference includes: When the output power difference exceeds the compressor power deviation range, determining that the compressor energy consumption monitoring result is energy consumption abnormality, and generating an energy consumption abnormality reminder; When the output power difference is within the compressor power deviation range, it is determined that the compressor energy consumption monitoring result is normal.

7. The method according to claim 6, characterized in that When the real-time operation monitoring data includes real-time monitoring load data and real-time monitoring temperature data, and the real-time monitoring load data includes real-time suction pressure, real-time exhaust flow rate, and real-time speed, the compressor power deviation range is determined by: Real-time operation monitoring data of the motor-driven compressor is obtained, and a real-time operation load of the motor-driven compressor is generated according to the real-time operation monitoring data; the real-time operation load satisfies the following formula: Among them, L re is the real-time operating load; γ1 is the real-time suction pressure weight; P inh is the real-time suction pressure; γ2 is the real-time monitoring temperature data weight; T re is the real-time monitoring temperature data; γ3 is the real-time exhaust flow weight; Q re is the real-time exhaust flow rate; Q s is the rated exhaust flow of the compressor; γ4 is the real-time speed weight; N re is the real-time speed; N s is the rated speed of the compressor; The range adjustment coefficient of the compressor power deviation range is determined according to the real-time operating load and the historical load fluctuation data; the range adjustment coefficient satisfies the following formula: Wherein, β is the deviation range adjustment coefficient; β0 is the reference adjustment coefficient; L ev is the average value of historical load fluctuation data; The compressor power deviation range is generated according to the range adjustment coefficient and the output power difference.

8. The method according to claim 7, characterized in that Generating the compressor power deviation range according to the range adjustment coefficient and the output power difference includes: Calculate the output power difference mean and the output power difference standard deviation based on multiple output power differences within a historical period; The compressor power deviation range is generated according to the range adjustment coefficient, the output power difference mean, and the output power difference standard deviation; the compressor power deviation range satisfies the following formula: [P ev -b·s,P ev +b·s]; Among them, P ev is the mean of the output power difference; σ is the standard deviation of the output power difference.

9. A compressor energy consumption monitoring device, characterized in that: include: Compressor efficiency wear factor generation module, estimated output power generation module, output power difference generation module, and energy consumption abnormality reminder generation module; The compressor efficiency wear factor generating module is used to obtain historical operation monitoring data of the motor-driven compressor and generate the compressor efficiency wear factor based on the historical operation monitoring data; The estimated output power generation module is configured to obtain the real-time motor power of the motor-driven compressor and generate the estimated output power of the motor-driven compressor based on the real-time motor power and the compressor efficiency wear factor; The output power difference generating module is configured to obtain the actual output power of the motor-driven compressor and generate an output power difference based on the actual output power and the estimated output power; The energy consumption abnormality reminder generation module is used to determine the compressor energy consumption monitoring result according to the output power difference.

10. A compressor energy consumption monitoring device, characterized in that: include: processor and memory; The memory is used to store one or more programs, which include computer-executable instructions. When the compressor energy consumption monitoring device is running, the processor executes the computer-executable instructions stored in the memory to enable the compressor energy consumption monitoring device to perform the method described in any one of claims 1 to 8.

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