Factory carbon emission detection method and device

Abstract

The invention provides a factory carbon emission detection method and device, and relates to the technical field of carbon emission detection. The method comprises the following steps: classifying factory equipment to obtain multiple types of equipment; determining an equipment characteristic database based on the parameter characteristics of each type of equipment in different working modes; determining a target database based on the device feature database and the current features of the multiple types of devices in different combined working modes; and matching the target database with the current total current, and determining the current working equipment and the carbon emission thereof. According to the factory carbon emission detection method and device provided by the invention, the carbon emission quota of the whole factory can be conveniently arranged as a whole, and the fine management of the carbon emission is realized.

Description

Technical Field

[0001] The present application relates to the technical field of carbon emission detection, and in particular to a method and device for detecting carbon emissions in a factory. Background Art

[0002] At present, carbon emission inspection is mainly carried out through indirect measurement methods, estimating carbon emissions by calculating energy consumption and corresponding emission factors. The most commonly used method is to calculate carbon emissions through electricity consumption and carbon emission factors, such as: electric carbon meter. The current electric carbon meter can only measure total carbon emissions, and cannot identify the carbon emissions of various types of equipment individually or in combination, resulting in the factory being unable to carry out classified management. For example: the current total carbon emissions of the factory can be measured through the electric carbon meter, but it is impossible to know which equipment generates the current carbon emissions and in what working mode, so it is difficult to coordinate the carbon emission quota of the entire factory area and realize the fine management of carbon emissions. Summary of the invention

[0003] The present application provides a factory carbon emission detection method and device to solve the defect that it is difficult to achieve fine management of carbon emissions in the prior art.

[0004] In a first aspect, the present application provides a method for detecting carbon emissions from a factory, comprising:

[0005] Classify factory equipment and obtain various types of equipment;

[0006] Determine a device feature database based on parameter features of each type of device in different working modes;

[0007] Determining a target database based on the device feature database and current features of the multiple types of devices in different combined working modes;

[0008] The target database is matched with the current total current to determine the current working equipment and its carbon emissions.

[0009] Optionally, the target database includes current fitting values ​​of the multiple types of equipment in different combined working modes; the current fitting value is determined based on the sum of multiple frequency components of the current of each type of equipment; the combined working mode is determined based on the current working equipment, equipment working stage and equipment working voltage.

[0010] Optionally, the current fitting value is calculated in the following manner:

[0011]

[0012] Wherein, i(t) represents the current fitting value at time t, I0 represents the DC component, M represents the number of frequency components taken, and I krepresents the amplitude of the kth frequency component, kω0 represents the frequency of the kth frequency component, t represents the current time, Represents the initial phase of the kth frequency component.

[0013] Optionally, matching the target database with the current total current to determine the current working equipment and its carbon emissions includes:

[0014] Based on the current total voltage, screening the first matching current in the target database;

[0015] Matching the target order frequency component of the current total current with the first matching current to obtain a second matching current;

[0016] Matching each frequency component of the current total current with the second matching current to obtain a target matching current;

[0017] Based on the target matching current, the current working equipment is determined, and the carbon emissions of the current working equipment are calculated.

[0018] Optionally, the method further comprises:

[0019] After matching the target database with the current total current, if the target matching current cannot be obtained, performing device troubleshooting;

[0020] When the result of the device troubleshooting is normal, optimizing the target database;

[0021] When the result of the equipment inspection is abnormal, an abnormality alarm is issued.

[0022] Optionally, determining a device feature database based on parameter features of each type of device in different working modes includes:

[0023] Learning the current curves and device working time of various types of devices in different working modes to obtain learning results; the working mode is determined based on the device working stage and the device working voltage;

[0024] Based on the learning result, the device feature database is determined.

[0025] Optionally, the method further comprises:

[0026] Comparing the electrical index data of the current working equipment with the preset parameters to obtain a comparison result;

[0027] Based on the comparison result, it is determined whether to issue an abnormality alarm.

[0028] In a second aspect, the present application also provides a factory carbon emission detection device, comprising:

[0029] Classification module, used to classify factory equipment and obtain various types of equipment;

[0030] A first determination module is used to determine a device feature database based on parameter features of various types of devices in different working modes;

[0031] A second determination module is used to determine a target database based on the device feature database and current features of the multiple types of devices in different combined working modes;

[0032] The calculation module is used to match the target database with the current total current to determine the current working equipment and its carbon emissions.

[0033] In a third aspect, the present application further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in the first aspect when executing the program.

[0034] In a fourth aspect, the present application further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect.

[0035] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which implements the method described in the first aspect when executed by a processor.

[0036] The factory carbon emission detection method and device provided in the present application determine the target database by learning the equipment parameter characteristics and fitting the current characteristics under different combination working modes, and determine the current working equipment and the carbon emissions of the current working equipment based on the matching result of the target database and the current total current. The collected information can be automatically judged according to the target database to identify the equipment type under different combination working modes, calculate the carbon emissions for it, and monitor the carbon emissions of the working equipment in real time, so as to facilitate in-depth understanding of the carbon emissions of different equipment, facilitate the overall arrangement of carbon emission quotas for the entire factory area, and realize the fine management of carbon emissions. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the present application or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0038] Figure 1It is a flow chart of the factory carbon emission detection method provided by this application;

[0039] Figure 2 It is a structural schematic diagram of the detection device provided by the present application;

[0040] Figure 3 This is a schematic diagram of the device identification and matching process provided by this application;

[0041] Figure 4 It is a flow chart of the carbon emission management method provided in this application;

[0042] Figure 5 It is a structural schematic diagram of the factory carbon emission detection device provided by this application;

[0043] Figure 6 It is a schematic diagram of the structure of the electronic device provided by this application. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0045] Figure 1 This is a schematic diagram of the process flow of the factory carbon emission detection method provided by this application. Figure 1 An embodiment of the present application provides a factory carbon emission detection method, the execution subject of which may be an electronic device, for example, a detection device.

[0046] Figure 2 Schematic diagram of the structure of the detection device provided by this application. Figure 2 As shown, the detection device is responsible for sampling by the voltage and current sampling circuit, and the analog-to-digital converter (ADC) converts the sampled analog signal into a digital signal. After the digital signal is transmitted to the digital signal processor (DSP), the DSP performs various operations and processing on the digital signal data to calculate the carbon emissions of various types of equipment. The microcontroller unit (MCU) is responsible for managing the peripheral circuit modules, such as: keyboard input module, clock module, display module, storage module, communication module, etc. The communication module transmits the data to the computer host computer for easy management and operation.

[0047] Methods for detecting carbon emissions in factories may include:

[0048] Step 110, classify the factory equipment to obtain multiple types of equipment;

[0049] Step 120: Determine a device feature database based on parameter features of each type of device in different working modes;

[0050] Step 130: determining a target database based on the device feature database and current features of multiple types of devices in different combined working modes;

[0051] Step 140: Match the target database with the current total current to determine the current working equipment and its carbon emissions.

[0052] There are many devices in the factory. In step 110, the detection device may first classify the factory equipment according to the type or similarity, for example: all air conditioners are type 1, all lighting equipment are type 2, factory assembly line equipment is type 3, etc.

[0053] Each type of device will exhibit different characteristics in different working modes, such as different working voltages. In step 120, the detection device can learn parameter characteristics of each type of device in different working modes, thereby obtaining a device characteristic database. Parameter characteristics may include current characteristics, voltage characteristics, etc.

[0054] In step 130, the detection device may learn the current characteristics of various types of equipment in different combination working modes and perform current fitting based on the parameter characteristics in the learned equipment characteristic database, thereby determining a target database.

[0055] Since various parameters of various types of equipment have different characteristics when performing carbon emissions, the equipment can be identified by identifying these characteristics. In step 140, the detection device can roughly screen the current characteristic data in the target database, and then finely match it with the current total current to determine the current working equipment and calculate the carbon emissions of the current working equipment.

[0056] Specifically, the carbon emission measurement method used in this application is an indirect measurement method, and the carbon emission E can be expressed as:

[0057] E=P·C=U·I·cosθ·t·C

[0058] Among them, E represents carbon dioxide emissions, P represents energy consumption, and C represents carbon emission factor; U represents the effective voltage across the device under test, I represents the effective current of the device under test, cosθ represents the power factor of the device under test, and t represents the test duration.

[0059] The carbon emissions of the equipment can be measured by detecting the voltage, current and power factor of the equipment and then performing the above calculations.

[0060] The factory carbon emission detection method provided in the embodiment of the present application determines the target database by learning the equipment parameter characteristics and fitting the current characteristics under different combination working modes, and determines the current working equipment and the carbon emissions of the current working equipment based on the matching result of the target database and the current total current. The collected information can be automatically judged according to the target database to identify the equipment type under different combination working modes, calculate the carbon emissions for it, and monitor the carbon emissions of the working equipment in real time, so as to facilitate in-depth understanding of the carbon emissions of different equipment, facilitate the overall arrangement of carbon emission quotas for the entire factory area, and realize fine management of carbon emissions.

[0061] In one embodiment, the target database includes current fitting values ​​of multiple types of equipment under different combined working modes; the current fitting value is determined based on the sum of multiple frequency components of the current of each type of equipment; the combined working mode is determined based on the current working equipment, equipment working stage and equipment working voltage.

[0062] There are many types of equipment in the factory, and there are many combinations of equipment when they are used. For example, only the assembly line is one mode, only the lighting is another mode, and only the assembly line and air conditioning are another mode. Each device has two working stages, and the working voltage has m working ranges. This leads to a variety of combined working modes. The total number of combined working modes is:

[0063]

[0064] Among them, N2 is the number of various equipment combination working modes, m is the number of voltage working ranges, and n is the number of equipment types.

[0065] The detection device fits the current characteristics of multiple types of equipment in different combined working modes to establish a target database. Specifically, the detection device can expand the Mth frequency component of the current of each type of equipment, and then add the corresponding frequency components of different equipment types to obtain the current characteristic curves under different combined working modes.

[0066] The factory carbon emission detection method provided in the embodiment of the present application determines the target database by fitting the current characteristics under different combination working modes. Based on the target database, the current working equipment and the carbon emissions of the current working equipment can be determined, the carbon emissions of the working equipment can be monitored in real time, and the carbon emissions of different types of equipment under different combination working modes can be determined, which is convenient for the overall arrangement of carbon emission quotas for the entire factory area and the realization of fine management of carbon emissions.

[0067] In one embodiment, the current fitting value is calculated as follows:

[0068]

[0069] Wherein, i(t) represents the current fitting value at time t, I0 represents the DC component, M represents the number of frequency components taken, and I k represents the amplitude of the kth frequency component, kω0 represents the frequency of the kth frequency component, t represents the current time, Represents the initial phase of the kth frequency component.

[0070] Where, the current fitting value i(t) at time t is in A; the DC component I0 is in A; k is an integer: k≤M, M∈N + , unit: times; the number of times the frequency component is taken is M, which can be 21 times, unit: times; the amplitude of the kth frequency component is I k Unit: A; frequency kω0 of the kth frequency component Unit: Hz; initial phase of the kth frequency component Unit: °.

[0071] For N2 kinds of complex combined working modes, the detection device can fit the current characteristics in each working mode to determine the target database.

[0072] The factory carbon emission detection method provided in the embodiment of the present application determines the target database by fitting the current characteristics under different combination working modes using its unique electrical indicator fitting curve. Based on the target database, the current working equipment and the carbon emissions of the current working equipment can be determined, the carbon emissions of the working equipment can be monitored in real time, and the carbon emissions of different types of equipment under different combination working modes can be determined, which is convenient for the overall arrangement of carbon emission quotas for the entire factory area and the realization of fine management of carbon emissions.

[0073] In one embodiment, the target database is matched with the current total current to determine the current working equipment and its carbon emissions, including:

[0074] Based on the current total voltage, screening the first matching current in the target database;

[0075] Matching the target order frequency component of the current total current with the first matching current to obtain a second matching current;

[0076] Matching each frequency component of the current total current with the second matching current to obtain a target matching current;

[0077] Based on the target matching current, the current working equipment is determined, and the carbon emissions of the current working equipment are calculated.

[0078] Figure 3 This is a schematic diagram of the device identification and matching process provided by this application. Figure 3 , the specific steps for matching the target database with the current total current are:

[0079] (1) Data acquisition: The detection device samples the current total current and total voltage respectively.

[0080] (2) Data processing: The detection device performs fast Fourier transform (FFT) on the collected total current.

[0081] (3) Data judgment: The detection device converts the total current after FFT transformation Match with the target database. First, according to the total voltage U collected, select the current characteristics under the matching voltage range in the target database, that is, the first matching current, and first match the 21st frequency component Compare with the data in the target database to quickly filter a part of the data and obtain the second matching current, and then compare the amplitude of the 20th, 19th, ..., 2nd, 50Hz frequency components in turn. Right now If the current amplitude-frequency characteristics of a certain working mode in the target database are consistent, it means that the identification is successful, the target matching current can be obtained, the current working equipment can be determined, and the carbon emissions of the current working equipment can be calculated.

[0082] The factory carbon emissions detection method provided in the embodiment of the present application matches the target database with the current total current to determine the current working equipment and its carbon emissions. It can monitor the carbon emissions of the working equipment in real time and determine the carbon emissions of different types of equipment under different combination working modes, which is convenient for further overall arrangement of carbon emission quotas for the entire factory area and realize fine management of carbon emissions.

[0083] In one embodiment, the factory carbon emission detection method further includes:

[0084] After matching the target database with the current total current, if the target matching current cannot be obtained, perform device troubleshooting;

[0085] If the device troubleshooting results are normal, optimize the target database;

[0086] If the result of the equipment inspection is abnormal, an abnormal alarm will be issued.

[0087] After the detection device matches the target database with the current total current, if the matching target matching current cannot be obtained, that is, the collected data does not match the data in the target database, the device can be checked.

[0088] If the device troubleshooting results are normal, it means that the device is not faulty, and new feature learning can be added to the target database to optimize the target database.

[0089] When the result of the equipment inspection is abnormal, it indicates that the equipment has failed and the detection device can issue an abnormal alarm.

[0090] Specifically, the abnormal alarm can be selected in the form of voice broadcast + text prompt + light flashing + video playback. Voice playback of fault content, such as the name of the faulty device, the fault location, and the fault severity level. Text prompts of the fault content and maintenance suggestions. Video playback of monitoring data of the fault location.

[0091] The factory carbon emission detection method provided in the embodiment of the present application can continuously improve the accuracy and robustness of the target database by optimizing the database, and can prompt management personnel to inspect and repair the equipment through abnormal alarms, so as to facilitate management personnel to monitor the equipment, troubleshoot, reasonably allocate resources, and ensure production efficiency.

[0092] In one embodiment, based on parameter characteristics of various types of devices in different working modes, a device characteristic database is determined, including:

[0093] Study the current curves and working time of various types of equipment in different working modes and obtain the learning results; the working mode is determined based on the working stage and working voltage of the equipment;

[0094] Based on the learning results, a device feature database is determined.

[0095] After the detection device is connected to the power grid, it is classified according to the actual equipment in use, such as air conditioners, computers, workshop product lines, lighting and other equipment. The detection device can learn the characteristics of equipment parameters. Specifically, the characteristics of the equipment are different at different working voltages and working stages. This application divides the characteristics of the equipment into two working stages: the startup stage and the stable stage. Learn different working voltage ranges in two working stages (the working range can be decomposed into m: U1, U2, U3,..., U m ), there are N1 kinds of total working modes.

[0096]

[0097] Wherein, N1 is the total number of working modes, and m is the number of working voltage ranges.

[0098] The detection device can learn the parameter characteristics of the device in these N1 working modes respectively. The main parameter characteristics learned are as follows:

[0099] (1) Current curve. The current curve of the device is one of the main characteristic parameters and the most complex parameter characteristic. The current of the device is different in different working modes. The detection device needs to learn the current characteristics of each working mode.

[0100] (2) Equipment working hours. Factory equipment generally has working hours, such as 8:00-12:00 in the morning and 2:00-6:00 in the afternoon.

[0101] After learning the parameter characteristics of the equipment, the detection device can enter the parameter characteristics into the equipment characteristic database for subsequent use.

[0102] For example, when establishing a device feature database, the features of the air conditioner can be divided into two working stages: startup stage and stable stage. The working voltage is divided into three ranges: U1 (175V~190V), U2 (190V~220V), U3 (220V~265V). The air conditioner working modes are:

[0103] kind

[0104] The detection device can learn the parameter characteristics of the equipment under these six working modes respectively. The learning method is as follows:

[0105] When the device is working in the stable stage and within the voltage range of U1, the FFT transformation is performed on this current. After the transformation, the current at various frequencies is the current characteristic of the device. The signal is mainly a 50Hz power frequency signal, and the amplitude-frequency characteristics of the 3rd, 5th, 7th, and 9th frequencies are more obvious.

[0106] When the device is working in the stable stage and within the voltage range of U2, FFT transformation is performed on this current. After the transformation, the current at various frequencies is the current characteristic of the device.

[0107] When the device is working in the stable stage and within the voltage range of U3, FFT transformation is performed on this current. After the transformation, the current at various frequencies is the current characteristic of the device.

[0108] The factory carbon emission detection method provided in the embodiment of the present application builds an equipment characteristic database by learning the parameter characteristics of various types of equipment in different working modes, provides data preparation for the construction of the target database, and facilitates the real-time monitoring of carbon emissions of various types of equipment.

[0109] In one embodiment, the factory carbon emission detection method further includes:

[0110] Compare the electrical index data of the current working equipment with the preset parameters to obtain a comparison result;

[0111] Based on the comparison results, determine whether to issue an abnormality alarm.

[0112] Figure 4 This is a flow chart of the carbon emission management method provided by this application. Figure 4 , the detection device can manage the factory equipment, the specific steps are as follows:

[0113] (1) Calling the equipment unit database information: The detection device first calls the parameter feature information in the equipment unit database.

[0114] (2) Set various parameters of the equipment: preset various parameters of the equipment according to actual conditions.

[0115] (3) Check the operating status of the equipment: Compare the sampled electrical indicator data with the preset parameters to check whether the operating status of the equipment is normal, helping managers to monitor the equipment.

[0116] (4) Alarm for abnormal equipment: If the operating status is abnormal, the alarm will prompt the management personnel to inspect the equipment or reset the parameters.

[0117] For example, various parameters such as the working time, rated power, maximum power, etc. of the equipment can be preset according to actual conditions. If the electrical index data of the actual operation of the equipment does not match the preset parameters and the equipment operating status is abnormal, the detection device will alarm to prompt the management personnel to inspect the equipment or reset the parameters.

[0118] The factory carbon emission detection method provided in the embodiment of the present application can judge the equipment abnormality and issue an abnormal alarm by comparing the electrical indicator data of the current working equipment with the preset parameters, so as to prompt the management personnel to inspect the equipment or reset the parameters, thereby facilitating the management personnel to troubleshoot the equipment failure, reasonably allocate resources and ensure production efficiency.

[0119] The factory carbon emission detection device provided in the present application is described below. The factory carbon emission detection device described below and the factory carbon emission detection method described above can be referenced to each other.

[0120] Figure 5 This is a schematic diagram of the structure of the factory carbon emission detection device provided by this application. Figure 5 The factory carbon emission detection device provided in the embodiment of the present application may include:

[0121] A classification module 510 is used to classify factory equipment to obtain multiple types of equipment;

[0122] A first determination module 520 is used to determine a device feature database based on parameter features of various types of devices in different working modes;

[0123] A second determination module 530 is used to determine a target database based on the device feature database and the current features of the multiple types of devices in different combined working modes;

[0124] The calculation module 540 is used to match the target database with the current total current to determine the current working equipment and its carbon emissions.

[0125] The factory carbon emission detection device provided in the embodiment of the present application determines the target database by learning the equipment parameter characteristics and fitting the current characteristics under different combination working modes, and determines the current working equipment and the carbon emissions of the current working equipment based on the matching result of the target database and the current total current. It can automatically judge the collected information according to the target database, thereby identifying the equipment type under different combination working modes, and calculate the carbon emissions for it, and monitor the carbon emissions of the working equipment in real time, so as to facilitate in-depth understanding of the carbon emissions of different equipment, facilitate the overall arrangement of carbon emission quotas for the entire factory area, and realize fine management of carbon emissions.

[0126] Specifically, the above-mentioned factory carbon emission detection device provided in the embodiment of the present application can implement all the method steps implemented by the method embodiment in which the above-mentioned execution subject is the detection device, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as the method embodiment will not be described in detail here.

[0127] Figure 6 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 6 As shown, the electronic device may include: a processor 610, a communication interface 620, a memory 630 and a communication bus 640, wherein the processor 610, the communication interface 620 and the memory 630 communicate with each other through the communication bus 640. The processor 610 may call the logic instructions in the memory 630 to execute the factory carbon emission detection method, for example, including:

[0128] Classify factory equipment and obtain various types of equipment;

[0129] Determine a device feature database based on parameter features of each type of device in different working modes;

[0130] Determining a target database based on the device feature database and current features of the multiple types of devices in different combined working modes;

[0131] The target database is matched with the current total current to determine the current working equipment and its carbon emissions.

[0132] In addition, the logic instructions in the above-mentioned memory 630 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art, and the computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to 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 codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk.

[0133] On the other hand, the present application also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the factory carbon emission detection method provided by the above methods are implemented, for example, including:

[0134] Classify factory equipment and obtain various types of equipment;

[0135] Determine a device feature database based on parameter features of each type of device in different working modes;

[0136] Determining a target database based on the device feature database and current features of the multiple types of devices in different combined working modes;

[0137] The target database is matched with the current total current to determine the current working equipment and its carbon emissions.

[0138] In another aspect, the present application further provides a computer program product, the computer program product comprising a computer program, the computer program can be stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer can execute the steps of the factory carbon emission detection method provided by the above methods, for example, including:

[0139] Classify factory equipment and obtain various types of equipment;

[0140] Determine a device feature database based on parameter features of each type of device in different working modes;

[0141] Determining a target database based on the device feature database and current features of the multiple types of devices in different combined working modes;

[0142] The target database is matched with the current total current to determine the current working equipment and its carbon emissions.

[0143] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0144] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0145] It should also be noted that the terms "first", "second", etc. in the embodiments of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first" and "second" are generally of the same type, and the number of objects is not limited. For example, the first object can be one or more.

[0146] In the embodiments of the present application, the term "and / or" describes the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0147] "Determine B based on A" in the embodiments of the present application means that the factor A should be considered when determining B. It is not limited to "B can be determined based on A alone", but should also include: "Determine B based on A and C", "Determine B based on A, C and E", "Determine C based on A, and further determine B based on C", etc. In addition, it can also include taking A as a condition for determining B, for example, "When A meets the first condition, use the first method to determine B"; for example, "When A meets the second condition, determine B", etc.; for example, "When A meets the third condition, determine B based on the first parameter", etc. Of course, it can also be a condition that takes A as a factor for determining B, for example, "When A meets the first condition, use the first method to determine C, and further determine B based on C", etc.

[0148] In the embodiments of the present application, the term "plurality" refers to two or more than two, and other quantifiers are similar.

[0149] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for detecting carbon emissions from a factory, characterized in that: include: Classify factory equipment and obtain various types of equipment; Determine a device feature database based on parameter features of various types of devices in different working modes; Determining a target database based on the device feature database and current features of the multiple types of devices in different combined working modes; The target database is matched with the current total current to determine the current working equipment and its carbon emissions.

2. The factory carbon emission detection method according to claim 1, characterized in that: The target database includes current fitting values ​​of the multiple types of equipment in different combined working modes; the current fitting value is determined based on the sum of multiple frequency components of the current of each type of equipment; the combined working mode is determined based on the current working equipment, equipment working stage and equipment working voltage.

3. The factory carbon emission detection method according to claim 2, characterized in that: The current fitting value is calculated as follows: Wherein, i(t) represents the current fitting value at time t, I0 represents the DC component, M represents the number of frequency components taken, and I k represents the amplitude of the kth frequency component, kω0 represents the frequency of the kth frequency component, t represents the current time, Represents the initial phase of the kth frequency component.

4. The factory carbon emission detection method according to claim 1, characterized in that: The matching of the target database with the current total current to determine the current working equipment and its carbon emissions includes: Based on the current total voltage, screening the first matching current in the target database; Matching the target order frequency component of the current total current with the first matching current to obtain a second matching current; Matching each frequency component of the current total current with the second matching current to obtain a target matching current; Based on the target matching current, the current working equipment is determined, and the carbon emissions of the current working equipment are calculated.

5. The factory carbon emission detection method according to claim 4, characterized in that: The method further comprises: After matching the target database with the current total current, if the target matching current cannot be obtained, performing device troubleshooting; When the result of the device troubleshooting is normal, optimizing the target database; When the result of the equipment inspection is abnormal, an abnormality alarm is issued.

6. The factory carbon emission detection method according to claim 1, characterized in that: The device feature database is determined based on the parameter features of each type of device in different working modes, including: Learning the current curves and device working time of various types of devices in different working modes to obtain learning results; the working mode is determined based on the device working stage and the device working voltage; Based on the learning result, the device feature database is determined.

7. The factory carbon emission detection method according to any one of claims 1 to 6, characterized in that: The method further comprises: Comparing the electrical index data of the current working equipment with the preset parameters to obtain a comparison result; Based on the comparison result, it is determined whether to issue an abnormality alarm.

8. A factory carbon emission detection device, characterized in that: include: Classification module, used to classify factory equipment and obtain various types of equipment; A first determination module is used to determine a device feature database based on parameter features of various types of devices in different working modes; A second determination module is used to determine a target database based on the device feature database and current features of the multiple types of devices in different combined working modes; The calculation module is used to match the target database with the current total current to determine the current working equipment and its carbon emissions.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the factory carbon emission detection method as described in any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the factory carbon emission detection method according to any one of claims 1 to 7 is implemented.

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