Oil consumption and carbon emission metering method and device based on vibration sensing

Abstract

The embodiment of the invention relates to a fuel consumption and carbon emission metering method and device based on vibration sensing. The fuel consumption and carbon emission metering method comprises the steps that operation information of a target mechanical device on the X axis, the Y axis and the Z axis at a specific node position is collected; performing data processing on the operation information to obtain standard form data; based on the standard form data, matching with a type feature library and a power feature library to identify the mechanical equipment type and the power state of the target mechanical equipment; determining a carbon emission-time curve corresponding to the target mechanical equipment based on the identified mechanical equipment type and power state of the target mechanical equipment; and performing integral calculation on the working time of the target mechanical equipment based on the carbon emission-time curve to obtain the target carbon emission. Therefore, the carbon emission in the construction process of the constructional engineering can be simply, conveniently, quickly and accurately measured.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of carbon measurement of fuel-powered mechanical equipment during the construction process of a building project, and in particular to a method and device for measuring carbon emissions from fuel consumption based on vibration sensing. Background Art

[0002] In the context of "dual carbon", the carbon emissions of the construction industry are high, accounting for about half of all carbon emissions. Therefore, achieving carbon reduction in the construction industry is an important support for the "dual carbon" work.

[0003] Due to the complexity of the entire construction process, especially the complexity of the construction process, it is difficult to accurately measure the carbon emissions of the construction process. Therefore, how to accurately measure the carbon emissions generated by construction fuel machinery in real time has become an urgent problem to be solved. Summary of the invention

[0004] In view of this, in order to solve the above technical problems or part of the technical problems, an embodiment of the present invention provides a fuel consumption and carbon emission measurement method and device based on vibration sensing.

[0005] In a first aspect, an embodiment of the present invention provides a method for measuring fuel consumption and carbon emissions based on vibration sensing, comprising:

[0006] Collect the X, Y, and Z axis operation information of the target mechanical equipment at a specific node position;

[0007] Processing the operation information to obtain standard form data;

[0008] Identify the mechanical equipment type and power status of the target mechanical equipment by matching the standard form data with a type feature library and a power feature library;

[0009] Determine a carbon emission-time curve corresponding to the target mechanical equipment based on the identified mechanical equipment type and power state of the target mechanical equipment;

[0010] The target carbon emission is obtained by integrating the working time of the target mechanical equipment based on the carbon emission-time curve.

[0011] In a possible implementation, the method further includes:

[0012] Based on the preset frequency, the piezoelectric three-axis acceleration sensor is used to collect the vibration acceleration of the target mechanical equipment in the X, Y, and Z axes at a specific node position, the node battery power information, and the node internal temperature information.

[0013] In a possible implementation, the method further includes:

[0014] The vibration acceleration of the X, Y, and Z axes, the node battery power information, and the node internal temperature information are processed to obtain first vibration standard form data and second vibration standard form data, wherein the data processing at least includes noise reduction, format conversion, and data filling.

[0015] In a possible implementation, the method further includes:

[0016] Determine the mechanical equipment type of the target mechanical equipment based on matching and identifying the first vibration standard form data with a type feature library;

[0017] After determining the mechanical equipment type of the target mechanical equipment, matching and identifying are performed based on the second vibration standard form data and a power feature library to determine the power state of the mechanical equipment type of the target mechanical equipment.

[0018] In a possible implementation, the method further includes:

[0019] Extracting the Z-axis vibration amplitude peak value, the Z-axis vibration amplitude median, the Z-axis amplitude waveform and the XY-axis weighted vibration amplitude median from the X, Y and Z axis operation information;

[0020] Matching the Z-axis vibration amplitude peak, the Z-axis vibration amplitude median, the Z-axis amplitude waveform and the XY-axis weighted vibration amplitude median with corresponding parameter ranges in the type feature library;

[0021] When the matching degree meets a preset threshold, the mechanical equipment type of the target mechanical equipment is determined;

[0022] The determined mechanical equipment type is verified by means of a paddle code pre-placed at the specific node position.

[0023] In a possible implementation, the method further includes:

[0024] After determining the mechanical equipment type of the target mechanical equipment, the vibration waveforms in the power feature library are hierarchically divided according to the vibration characteristics according to the preset power state range;

[0025] After the vibration characteristic level division is completed, the vibration waveform is changed into a square wave;

[0026] The second vibration standard form data is matched and identified based on the square wave to determine the power state of the mechanical equipment type of the target mechanical equipment.

[0027] In a possible implementation, the method further includes:

[0028] Determining fuel consumption data under different power states based on the mechanical equipment type and power state of the target mechanical equipment;

[0029] Determine a fuel consumption-time curve within a preset time period based on fuel consumption data under different power states;

[0030] The carbon emission-time curve corresponding to the target mechanical equipment is determined based on the fuel consumption-time curve and the carbon emission factor of the fuel type.

[0031] In a second aspect, an embodiment of the present invention provides a fuel consumption and carbon emission metering device based on vibration sensing, comprising:

[0032] The data acquisition module is used to collect the operating information of the X, Y and Z axes of the target mechanical equipment at a specific node position;

[0033] A data processing module, used for processing the operation information to obtain data in a standard form;

[0034] A matching and identifying module, used for matching the standard form data with a type feature library and a power feature library to identify the mechanical equipment type and power status of the target mechanical equipment;

[0035] A determination module, configured to determine a carbon emission-time curve corresponding to the target mechanical equipment based on the identified mechanical equipment type and power state of the target mechanical equipment;

[0036] The metering module is used to integrate the working time of the target mechanical equipment based on the carbon emission-time curve to obtain the target carbon emission amount.

[0037] In a third aspect, an embodiment of the present invention provides a computer device, comprising: a processor and a memory, wherein the processor is used to execute a vibration sensing-based fuel consumption and carbon emission measurement program stored in the memory to implement the vibration sensing-based fuel consumption and carbon emission measurement method described in the first aspect above.

[0038] In a fourth aspect, an embodiment of the present invention provides a storage medium, including: the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the vibration sensing-based fuel consumption and carbon emission measurement method described in the first aspect above.

[0039] The vibration sensing-based fuel consumption carbon emission measurement scheme provided in the embodiment of the present invention collects the operation information of the X, Y, and Z axes of the target mechanical equipment at a specific node position; processes the operation information to obtain standard form data; identifies the mechanical equipment type and power state of the target mechanical equipment based on the standard form data and the type feature library and the power feature library; determines the carbon emission-time curve corresponding to the target mechanical equipment based on the identified mechanical equipment type and power state of the target mechanical equipment; and integrates the working time of the target mechanical equipment based on the carbon emission-time curve to obtain the target carbon emission. According to this scheme, by collecting the three-axis acceleration information of the target equipment, combined with the equipment type feature library and the partial load power feature library generated by historical test data, the start-stop state, equipment type and power state of the equipment are judged in real time, and the equipment power-time state diagram is drawn. Then, the equipment fuel consumption-time state diagram is calculated based on the equipment power-fuel consumption relationship, and the equipment carbon emission intensity and cumulative carbon emissions are calculated using the fuel consumption carbon emission factor, thereby realizing simple, fast and accurate indirect carbon emission measurement through the collection of equipment vibration information. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A schematic flow chart of a method for measuring fuel consumption and carbon emissions based on vibration sensing provided by an embodiment of the present invention;

[0041] Figure 2 A schematic flow chart of another fuel consumption and carbon emission measurement method based on vibration sensing provided by an embodiment of the present invention;

[0042] Figure 3 A mechanical equipment type identification logic diagram provided by an embodiment of the present invention;

[0043] Figure 4 A mechanical equipment power and start-stop identification logic diagram provided by an embodiment of the present invention;

[0044] Figure 5 A schematic diagram of the structure of a vibration sensing-based fuel consumption and carbon emission metering device provided in an embodiment of the present invention;

[0045] Figure 6 A schematic diagram of the structure of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] To facilitate understanding of the embodiments of the present invention, specific embodiments will be further explained below in conjunction with the accompanying drawings. The embodiments do not constitute a limitation on the embodiments of the present invention.

[0048] Embodiment 1

[0049] Figure 1 A flow chart of a method for measuring fuel consumption and carbon emissions based on vibration sensing provided by an embodiment of the present invention is shown in FIG. Figure 1 As shown, the method specifically includes:

[0050] S11. Collect the operation information of the X, Y, and Z axes of the target mechanical equipment at a specific node position.

[0051] In order to achieve automated measurement of carbon emissions from construction projects and ensure accurate recording of carbon emission data from fuel-consuming machinery and other equipment, the embodiments of the present invention propose an indirect measurement method for fuel consumption within Scope 2 carbon emissions, thereby improving the accuracy of carbon emission accounting during the construction process of construction projects and helping to promote the construction industry to enter the carbon trading market.

[0052] Specific, combined Figure 2 As shown in the flowchart, the vibration sensing-based fuel consumption carbon emission measurement method provided in the embodiment of the present invention consists of two parts: basic information collection and indirect calculation and measurement of equipment carbon emissions. By collecting relevant data such as the three-axis vibration acceleration, temperature and battery power of the equipment, an intelligent recognition method is used to indirectly calculate and measure the carbon emissions of the equipment, thereby realizing remote, real-time and automatic measurement of carbon emissions of fuel-consuming machinery.

[0053] First, a passive wireless terminal node is used to collect the operating information of the target mechanical equipment on the X, Y, and Z axes at a specific node position. The operating information includes at least vibration acceleration, node battery power information, and node internal temperature information, and transmits the data to an edge computing device (e.g., a computer device) via wireless signals. Among them, the minimum frequency of vibration information collection and upload can be achieved 10s / time. The vibration information collection position of different mechanical equipment is relatively fixed. When the position changes significantly, the vibration information needs to be corrected for the changed position.

[0054] It should be noted that the vibration collection terminal of the embodiment of the present invention is fixed by strong magnetic adsorption to achieve a rigid connection between the collection node and the mechanical equipment, which is easy to install; it adopts LORA local area networking to achieve wireless communication within the boundary of the engineering construction project without increasing power consumption, and the layout is more flexible.

[0055] S12, performing data processing on the operation information to obtain standard format data.

[0056] The vibration acceleration of the X, Y, and Z axes, the node battery power information, and the node internal temperature information are processed to obtain the first vibration standard form (standard form 1) data and the second vibration standard form (standard form 2) data, wherein the data processing at least includes noise reduction, format conversion, and data filling. The first vibration standard form data is used to match and identify with the type feature library to determine the mechanical equipment type of the target mechanical equipment; the second vibration standard form data is used to match and identify with the power feature library to determine the power state of the mechanical equipment type of the target mechanical equipment.

[0057] S13. Identify the mechanical equipment type and power status of the target mechanical equipment based on matching the standard form data with a type feature library and a power feature library.

[0058] Based on the matching and identification of the first vibration standard form data and the type feature library, the mechanical equipment type of the target mechanical equipment is determined; after the mechanical equipment type of the target mechanical equipment is determined, the second vibration standard form data is matched and identified with the power feature library to determine the power state of the mechanical equipment type of the target mechanical equipment. The mechanical equipment type and power state are identified, combined with the start-stop judgment, converted into carbon emission intensity and cumulative carbon emissions, and uploaded to the system management platform.

[0059] Specifically, extract the Z-axis vibration amplitude peak value, Z-axis vibration amplitude median, Z-axis amplitude waveform and XY-axis weighted vibration amplitude median from the operation information of the three axes X, Y and Z; match the Z-axis vibration amplitude peak value, Z-axis vibration amplitude median, Z-axis amplitude waveform and XY-axis weighted vibration amplitude median with the corresponding parameter range in the type feature library; when the matching degree meets the preset threshold, determine the mechanical equipment type of the target mechanical equipment; and verify the determined mechanical equipment type through the paddle code pre-placed at the specific node position. The specific execution logic is as shown in the attached figure. Figure 3 shown.

[0060] Furthermore, after determining the mechanical equipment type of the target mechanical equipment, the vibration waveform in the power feature library is hierarchically divided according to the vibration characteristics according to the preset power state range; the vibration waveform after the vibration characteristic hierarchical division is changed into a square wave; based on the square wave, the second vibration standard form data is matched and identified to determine the power state of the mechanical equipment type of the target mechanical equipment.

[0061] It should be noted that when the vibration amplitudes in the X, Y, and Z directions are all less than the set lower limit, the mechanical equipment is judged to be in a shutdown state. The lower limit values ​​for different mechanical equipment types are different, and this judgment must be placed after the mechanical equipment type judgment. The specific execution logic is as follows Figure 4 shown.

[0062] S14. Determine a carbon emission-time curve corresponding to the target mechanical equipment based on the identified mechanical equipment type and power state of the target mechanical equipment.

[0063] S15. Integrate the working time of the target mechanical equipment based on the carbon emission-time curve to obtain a target carbon emission amount.

[0064] After completing the identification of the mechanical equipment type and partial power state, the fuel consumption-time curve during the test time is calculated based on the fuel consumption of the machine under different power states, and then multiplied by the carbon emission factor of diesel or gasoline to obtain the carbon emission-time curve, which is the carbon emission intensity curve of the machine at any time. The time is integrated to obtain the cumulative carbon emissions.

[0065] It should be noted that the present invention can also cooperate with electricity sub-item metering terminals, building materials automatic reading terminals and a complete set of data integration management platforms to realize carbon emission monitoring, statistics, analysis and optimization of the entire process of engineering construction projects, providing a data basis for the dual control of carbon emissions of enterprises.

[0066] The vibration sensing-based fuel consumption and carbon emission measurement method provided in an embodiment of the present invention collects operating information of the target mechanical equipment on the X, Y, and Z axes at a specific node position; processes the operating information to obtain standard form data; identifies the mechanical equipment type and power status of the target mechanical equipment based on matching the standard form data with a type feature library and a power feature library; determines the carbon emission-time curve corresponding to the target mechanical equipment based on the identified mechanical equipment type and power status of the target mechanical equipment; and integrates the working time of the target mechanical equipment based on the carbon emission-time curve to obtain the target carbon emission amount. According to this method, by collecting the three-axis acceleration information of the target equipment, combined with the equipment type feature library and partial load power feature library generated by historical test data, the start and stop state, equipment type and power state of the equipment can be judged in real time, and the equipment power-time state diagram can be drawn. Then, the equipment fuel consumption-time state diagram is calculated based on the equipment power-fuel consumption relationship, and the equipment carbon emission intensity and cumulative carbon emissions are calculated using the fuel consumption carbon emission factor. Then, through the collection of equipment vibration information, the automatic measurement of carbon emissions in the construction of construction projects is realized, and the carbon emission data of fuel-consuming machinery and other equipment are accurately recorded, which improves the accuracy of carbon emission accounting in the construction process of construction projects, and helps to promote the construction industry to enter the carbon trading market.

[0067] Embodiment 2

[0068] Combination Figure 2 As shown in the flowchart, an embodiment of the present invention has developed a carbon metering device that can remotely monitor the carbon emissions of machinery in real time based on a piezoelectric three-axis acceleration sensor. By processing the vibration information into a standard form and intelligently matching it with the type feature library and the power feature library, the type and power status of the mechanical equipment are identified, and functions such as second-level perception of the start / stop of the operating machinery, automatic identification of the type of the operating machinery, and monitoring of the power status of the operating machinery are realized. The data is converted into carbon emission data and uploaded to the carbon metering platform through the Internet of Things, thereby realizing real-time and refined monitoring and statistical management of carbon emissions of construction machinery and equipment.

[0069] First, a passive wireless terminal node is used to collect the operating information of the target mechanical equipment on the X, Y, and Z axes at a specific node position. The operating information includes at least vibration acceleration, node battery power information, and node internal temperature information, and transmits the data to an edge computing device (e.g., a computer device) via wireless signals. Among them, the minimum frequency of vibration information collection and upload can be achieved 10s / time. The vibration information collection position of different mechanical equipment is relatively fixed. When the position changes significantly, the vibration information needs to be corrected for the changed position.

[0070] Furthermore, the vibration acceleration of the X, Y, and Z axes, the node battery power information, and the node internal temperature information are processed to obtain the first vibration standard form (standard form 1) data and the second vibration standard form (standard form 2) data, wherein the data processing at least includes noise reduction, format conversion, and data filling. The first vibration standard form data is used to match and identify with the type feature library to determine the mechanical equipment type of the target mechanical equipment; the second vibration standard form data is used to match and identify with the power feature library to determine the power state of the mechanical equipment type of the target mechanical equipment.

[0071] Furthermore, the vibration standard form 1 and the type feature library are used for preliminary identification, and the manual plucking when placing the acquisition node is used to verify the type of machinery, so as to ensure the accuracy of mechanical equipment type identification when the initial data accumulation is insufficient. The method of using the vibration standard form 1 and the type feature library to identify the type of machinery is mainly to extract the four main parameters of the Z-axis vibration amplitude peak, the Z-axis vibration amplitude median, the Z-axis amplitude waveform, and the XY-axis weighted vibration amplitude median in the three-axis vibration information, and match them with the corresponding parameter ranges in the type feature library. When the degree of matching meets the set requirements, the equipment type of the machinery is determined, and then the plucking code set when placing the acquisition node is used for verification. If it does not meet the requirements, the type feature library is corrected and the parameter weight is adjusted, and the accuracy of mechanical equipment type identification is improved using actual usage data. The specific execution logic is shown in the attached figure. Figure 3 As shown. Among them, the manual paddle is set at the vibration collection node, which consists of a two-digit decimal digital paddle. When the collection node is placed, the corresponding relationship between the digital code and the mechanical type is used to dial the paddle number to the corresponding position, so as to accurately collect the mechanical equipment type information. When the data is accumulated to meet the recognition accuracy requirements, the manual paddle can be cancelled.

[0072] Furthermore, the vibration standard form 2 and the power feature library are used to identify partial power states. Specifically, after the machine type is determined, the vibration features can be divided into four levels: 0-20%, 20%-45%, 45%-75%, and 75%-100%, where the 100% power state is the historical peak value. After the division is completed, the vibration waveform is shaped into a square wave, thereby completing the partial power state matching of this type of machine. The specific execution logic is as shown in the attached figure. Figure 4 shown.

[0073] When the vibration amplitudes in the X, Y, and Z directions are all less than the set lower limit, the mechanical equipment is judged to be in a shutdown state. The lower limit values ​​for different mechanical equipment types are different, and this judgment must be placed after the mechanical type judgment. The specific execution logic is as follows: Figure 4 shown.

[0074] After completing the mechanical equipment type identification and partial power state identification, the fuel consumption-time curve (fuel consumption-time square wave) during the test time is calculated according to the fuel consumption of the machine under different power states, and then multiplied by the carbon emission factor of diesel or gasoline to obtain the carbon emission-time curve (carbon emission intensity-time square wave), which is the carbon emission intensity curve of the machine at any time, and the time is integrated to obtain the cumulative carbon emissions. Among them, the carbon emission factor of diesel or gasoline is known in advance in actual production operations.

[0075] Taking actual application projects as an example, this method, in conjunction with electricity sub-metering terminals, building materials automatic reading terminals and a complete set of data integration management platforms, can provide 1.84% carbon reduction for engineering construction projects, and the cumulative carbon reduction in the whole process reaches 3882.4t, which has produced relatively significant environmental benefits. The application of this method effectively reduces the human resource investment in carbon inventory of engineering construction projects, and the real-time monitoring results can provide convenient construction management means for the project site, and the project service benefits are significant. In addition, enterprise managers can use the online deployed SaaS service to have an overview of the carbon emissions of all engineering construction projects of the enterprise, effectively strengthening the enterprise's remote supervision capabilities of the project, and can coordinate and optimize the total carbon emissions of the enterprise from an overall perspective, helping the enterprise to reduce carbon emissions and disclose ESG.

[0076] The vibration sensing-based fuel consumption and carbon emission measurement method provided in an embodiment of the present invention collects operating information of the target mechanical equipment on the X, Y, and Z axes at a specific node position; processes the operating information to obtain standard form data; identifies the mechanical equipment type and power status of the target mechanical equipment based on matching the standard form data with a type feature library and a power feature library; determines the carbon emission-time curve corresponding to the target mechanical equipment based on the identified mechanical equipment type and power status of the target mechanical equipment; and integrates the working time of the target mechanical equipment based on the carbon emission-time curve to obtain the target carbon emission amount. According to this method, by collecting the three-axis acceleration information of the target equipment, combined with the equipment type feature library and partial load power feature library generated by historical test data, the start and stop state, equipment type and power state of the equipment can be judged in real time, and the equipment power-time state diagram can be drawn. Then, the equipment fuel consumption-time state diagram is calculated based on the equipment power-fuel consumption relationship, and the equipment carbon emission intensity and cumulative carbon emissions are calculated using the fuel consumption carbon emission factor. Then, through the collection of equipment vibration information, the automatic measurement of carbon emissions in the construction of construction projects is realized, and the carbon emission data of fuel-consuming machinery and other equipment are accurately recorded, which improves the accuracy of carbon emission accounting in the construction process of construction projects, and helps to promote the construction industry to enter the carbon trading market.

[0077] Embodiment 3

[0078] Figure 5A structural schematic diagram of a vibration sensing-based fuel consumption and carbon emission metering device provided in an embodiment of the present invention specifically includes:

[0079] The data acquisition module 501 is used to collect the operation information of the target mechanical equipment in the X, Y and Z axes at a specific node position. For detailed description, please refer to the relevant description corresponding to the above method embodiment, which will not be repeated here.

[0080] The data processing module 502 is used to process the operation information to obtain standard format data. For detailed description, please refer to the relevant description of the above method embodiment, which will not be repeated here.

[0081] The matching and identification module 503 is used to identify the mechanical equipment type and power status of the target mechanical equipment by matching the standard form data with the type feature library and the power feature library. For detailed description, please refer to the relevant description corresponding to the above method embodiment, which will not be repeated here.

[0082] The determination module 504 is used to determine the carbon emission-time curve corresponding to the target mechanical equipment based on the identified mechanical equipment type and power state of the target mechanical equipment. For detailed description, please refer to the relevant description corresponding to the above method embodiment, which will not be repeated here.

[0083] The metering module 505 is used to integrate the working time of the target mechanical equipment based on the carbon emission-time curve to obtain the target carbon emission. For detailed description, please refer to the relevant description corresponding to the above method embodiment, which will not be repeated here.

[0084] The vibration sensing-based fuel consumption and carbon emission metering device provided in this embodiment can be as follows: Figure 5 The vibration sensing-based fuel consumption and carbon emission measurement device shown in FIG. Figure 1-2 All steps of the vibration sensing-based fuel consumption and carbon emission measurement method are implemented to achieve Figure 1-2 The technical effect of the vibration sensing-based fuel consumption and carbon emission measurement method shown in the figure is shown in the figure. Figure 1-2 For the sake of brevity, the relevant description is not repeated here.

[0085] Figure 6 A schematic diagram of the structure of a computer device provided by an embodiment of the present invention, Figure 6 The computer device 600 shown includes: at least one processor 601, a memory 602, at least one network interface 604 and other user interfaces 603. The various components in the computer device 600 are coupled together via a bus system 605. It is understood that the bus system 605 is used to achieve connection and communication between these components. In addition to the data bus, the bus system 605 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, the bus system 605 is not described in detail. Figure 6 Various buses are labeled as bus system 605 .

[0086] The user interface 603 may include a display, a keyboard, or a pointing device (eg, a mouse, a trackball, a touch pad, or a touch screen).

[0087] It can be understood that the memory 602 in the embodiment of the present invention can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM bus random access memory (DRRAM). The memory 602 described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0088] In some implementations, the memory 602 stores the following elements, executable units or data structures, or a subset thereof, or an extended set thereof: an operating system 6021 and an application 6022 .

[0089] The operating system 6021 includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., which are used to implement various basic services and process hardware-based tasks. The application 6022 includes various application programs, such as a media player (Media Player), a browser (Browser), etc., which are used to implement various application services. The program for implementing the method of the embodiment of the present invention can be included in the application 6022.

[0090] In the embodiment of the present invention, by calling the program or instruction stored in the memory 602, specifically, the program or instruction stored in the application 6022, the processor 601 is used to execute the method steps provided by each method embodiment, for example, including:

[0091] Collect the operating information of the target mechanical equipment on the X, Y, and Z axes at a specific node position; process the operating information to obtain standard form data; identify the mechanical equipment type and power status of the target mechanical equipment based on the standard form data matched with the type feature library and the power feature library; determine the carbon emission-time curve corresponding to the target mechanical equipment based on the identified mechanical equipment type and power status of the target mechanical equipment; integrate the working time of the target mechanical equipment based on the carbon emission-time curve to obtain the target carbon emission.

[0092] In a possible implementation, based on a preset time frequency, a piezoelectric three-axis acceleration sensor is used to collect the vibration acceleration of the target mechanical equipment in the X, Y, and Z axes at a specific node position, node battery power information, and node internal temperature information.

[0093] In one possible implementation, the vibration acceleration of the X, Y, and Z axes, the node battery power information, and the node internal temperature information are processed to obtain first vibration standard form data and second vibration standard form data, wherein the data processing at least includes noise reduction, format conversion, and data filling.

[0094] In one possible implementation, the mechanical equipment type of the target mechanical equipment is determined based on matching and identifying the first vibration standard form data with a type feature library; after determining the mechanical equipment type of the target mechanical equipment, the power state of the mechanical equipment type of the target mechanical equipment is determined based on matching and identifying the second vibration standard form data with a power feature library.

[0095] In one possible implementation, the Z-axis vibration amplitude peak value, the Z-axis vibration amplitude median, the Z-axis amplitude waveform, and the XY-axis weighted vibration amplitude median are extracted from the operation information of the X, Y, and Z axes; the Z-axis vibration amplitude peak value, the Z-axis vibration amplitude median, the Z-axis amplitude waveform, and the XY-axis weighted vibration amplitude median are matched with the corresponding parameter range in the type feature library; when the matching degree meets a preset threshold, the mechanical equipment type of the target mechanical equipment is determined; and the determined mechanical equipment type is verified by a paddle code pre-placed at the specific node position.

[0096] In one possible implementation, after determining the mechanical equipment type of the target mechanical equipment, the vibration waveforms in the power feature library are hierarchically divided according to vibration characteristics based on a preset power state range; the vibration waveform after the vibration feature hierarchical division is changed into a square wave; and the second vibration standard form data is matched and identified based on the square wave to determine the power state of the mechanical equipment type of the target mechanical equipment.

[0097] In one possible implementation, based on the mechanical equipment type and power state of the target mechanical equipment, the fuel consumption data under different power states is determined; based on the fuel consumption data under different power states, the fuel consumption-time curve within a preset time period is determined; based on the fuel consumption-time curve and the carbon emission factor of the fuel type, the carbon emission-time curve corresponding to the target mechanical equipment is determined.

[0098] The method disclosed in the above embodiment of the present invention can be applied to the processor 601, or implemented by the processor 601. The processor 601 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit in the processor 601 or the instruction in the form of software. The above processor 601 can be a general processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiment of the present invention can be directly embodied as a hardware decoding processor to execute, or the hardware and software units in the decoding processor can be executed. The software unit can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 602, and the processor 601 reads the information in the memory 602 and completes the steps of the above method in combination with its hardware.

[0099] It is understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit may be implemented in one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPDevice, DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), general purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described in the present application, or a combination thereof.

[0100] For software implementation, the technology described herein can be implemented by a unit that performs the functions described herein. The software code can be stored in a memory and executed by a processor. The memory can be implemented in the processor or outside the processor.

[0101] The computer device provided in this embodiment may be Figure 6 The computer device shown in , can execute Figure 1-2 All steps of the vibration sensing-based fuel consumption and carbon emission measurement method are implemented to achieve Figure 1-2 The technical effect of the vibration sensing-based fuel consumption and carbon emission measurement method shown in the figure is shown in the figure. Figure 1-2 For the sake of brevity, the relevant description is not repeated here.

[0102] The embodiment of the present invention also provides a storage medium (computer-readable storage medium). The storage medium here stores one or more programs. The storage medium may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a read-only memory, a flash memory, a hard disk or a solid-state drive; the memory may also include a combination of the above-mentioned types of memory.

[0103] When one or more programs in the storage medium can be executed by one or more processors, the vibration sensing-based fuel consumption and carbon emission measurement method executed on the computer device side can be implemented.

[0104] The processor is used to execute the vibration sensing-based fuel consumption and carbon emission measurement program stored in the memory to implement the following steps of the vibration sensing-based fuel consumption and carbon emission measurement method executed on the computer device side:

[0105] Collect the operating information of the target mechanical equipment on the X, Y, and Z axes at a specific node position; process the operating information to obtain standard form data; identify the mechanical equipment type and power status of the target mechanical equipment based on the standard form data matched with the type feature library and the power feature library; determine the carbon emission-time curve corresponding to the target mechanical equipment based on the identified mechanical equipment type and power status of the target mechanical equipment; integrate the working time of the target mechanical equipment based on the carbon emission-time curve to obtain the target carbon emission.

[0106] In a possible implementation, based on a preset time frequency, a piezoelectric three-axis acceleration sensor is used to collect the vibration acceleration of the target mechanical equipment in the X, Y, and Z axes at a specific node position, node battery power information, and node internal temperature information.

[0107] In one possible implementation, the vibration acceleration of the X, Y, and Z axes, the node battery power information, and the node internal temperature information are processed to obtain first vibration standard form data and second vibration standard form data, wherein the data processing at least includes noise reduction, format conversion, and data filling.

[0108] In one possible implementation, the mechanical equipment type of the target mechanical equipment is determined based on matching and identifying the first vibration standard form data with a type feature library; after determining the mechanical equipment type of the target mechanical equipment, the power state of the mechanical equipment type of the target mechanical equipment is determined based on matching and identifying the second vibration standard form data with a power feature library.

[0109] In one possible implementation, the Z-axis vibration amplitude peak value, the Z-axis vibration amplitude median, the Z-axis amplitude waveform, and the XY-axis weighted vibration amplitude median are extracted from the operation information of the X, Y, and Z axes; the Z-axis vibration amplitude peak value, the Z-axis vibration amplitude median, the Z-axis amplitude waveform, and the XY-axis weighted vibration amplitude median are matched with the corresponding parameter range in the type feature library; when the matching degree meets a preset threshold, the mechanical equipment type of the target mechanical equipment is determined; and the determined mechanical equipment type is verified by a paddle code pre-placed at the specific node position.

[0110] In one possible implementation, after determining the mechanical equipment type of the target mechanical equipment, the vibration waveforms in the power feature library are hierarchically divided according to vibration characteristics based on a preset power state range; the vibration waveform after the vibration feature hierarchical division is changed into a square wave; and the second vibration standard form data is matched and identified based on the square wave to determine the power state of the mechanical equipment type of the target mechanical equipment.

[0111] In one possible implementation, based on the mechanical equipment type and power state of the target mechanical equipment, the fuel consumption data under different power states is determined; based on the fuel consumption data under different power states, the fuel consumption-time curve within a preset time period is determined; based on the fuel consumption-time curve and the carbon emission factor of the fuel type, the carbon emission-time curve corresponding to the target mechanical equipment is determined.

[0112] The professionals should further realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to the function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians 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 the present invention.

[0113] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0114] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for measuring fuel consumption and carbon emissions based on vibration sensing, characterized in that: include: Collect the X, Y, and Z axis operation information of the target mechanical equipment at a specific node position; Processing the operation information to obtain standard form data; Identify the mechanical equipment type and power status of the target mechanical equipment by matching the standard form data with a type feature library and a power feature library; Determine a carbon emission-time curve corresponding to the target mechanical equipment based on the identified mechanical equipment type and power state of the target mechanical equipment; The target carbon emission is obtained by integrating the working time of the target mechanical equipment based on the carbon emission-time curve.

2. The method according to claim 1, characterized in that The acquisition of the X, Y, and Z axis operation information of the target mechanical equipment at a specific node position includes: Based on the preset frequency, the piezoelectric three-axis acceleration sensor is used to collect the vibration acceleration of the target mechanical equipment in the X, Y, and Z axes at a specific node position, the node battery power information, and the node internal temperature information.

3. The method according to claim 2, characterized in that The step of processing the operation information to obtain standard form data includes: The vibration acceleration of the X, Y, and Z axes, the node battery power information, and the node internal temperature information are processed to obtain first vibration standard form data and second vibration standard form data, wherein the data processing at least includes noise reduction, format conversion, and data filling.

4. The method according to claim 3, characterized in that The identifying the mechanical equipment type and power status of the target mechanical equipment based on matching the standard form data with the type feature library and the power feature library includes: Determine the mechanical equipment type of the target mechanical equipment based on matching and identifying the first vibration standard form data with a type feature library; After determining the mechanical equipment type of the target mechanical equipment, matching and identifying are performed based on the second vibration standard form data and a power feature library to determine the power state of the mechanical equipment type of the target mechanical equipment.

5. The method according to claim 4, characterized in that The matching and identifying of the first vibration standard form data with a type feature library to determine the mechanical equipment type of the target mechanical equipment includes: Extracting the Z-axis vibration amplitude peak value, the Z-axis vibration amplitude median, the Z-axis amplitude waveform and the XY-axis weighted vibration amplitude median from the X, Y and Z axis operation information; Matching the Z-axis vibration amplitude peak, the Z-axis vibration amplitude median, the Z-axis amplitude waveform and the XY-axis weighted vibration amplitude median with corresponding parameter ranges in the type feature library; When the matching degree meets a preset threshold, the mechanical equipment type of the target mechanical equipment is determined; The determined mechanical equipment type is verified by means of a paddle code pre-placed at the specific node position.

6. The method according to claim 5, characterized in that After determining the mechanical equipment type of the target mechanical equipment, matching and identifying the second vibration standard form data with a power feature library to determine the power state of the mechanical equipment type of the target mechanical equipment includes: After determining the mechanical equipment type of the target mechanical equipment, the vibration waveforms in the power feature library are hierarchically divided according to the vibration characteristics according to the preset power state range; After the vibration characteristic level division is completed, the vibration waveform is changed into a square wave; The second vibration standard form data is matched and identified based on the square wave to determine the power state of the mechanical equipment type of the target mechanical equipment.

7. The method according to claim 6, characterized in that The step of determining the carbon emission-time curve corresponding to the target mechanical equipment based on the identified mechanical equipment type and power state of the target mechanical equipment includes: Determining fuel consumption data under different power states based on the mechanical equipment type and power state of the target mechanical equipment; Determine a fuel consumption-time curve within a preset time period based on fuel consumption data under different power states; The carbon emission-time curve corresponding to the target mechanical equipment is determined based on the fuel consumption-time curve and the carbon emission factor of the fuel type.

8. A vibration-sensing-based fuel consumption and carbon emission metering device, characterized in that: include: The data acquisition module is used to collect the operating information of the X, Y and Z axes of the target mechanical equipment at a specific node position; A data processing module, used for processing the operation information to obtain data in a standard form; A matching and identifying module, used for matching the standard form data with a type feature library and a power feature library to identify the mechanical equipment type and power status of the target mechanical equipment; A determination module, configured to determine a carbon emission-time curve corresponding to the target mechanical equipment based on the identified mechanical equipment type and power state of the target mechanical equipment; The metering module is used to integrate the working time of the target mechanical equipment based on the carbon emission-time curve to obtain the target carbon emission amount.

9. A computer device, characterized in that: include: A processor and a memory, wherein the processor is used to execute a vibration sensing-based fuel consumption and carbon emission measurement program stored in the memory to implement the vibration sensing-based fuel consumption and carbon emission measurement method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the fuel consumption and carbon emission measurement method based on vibration sensing as described in any one of claims 1 to 7.

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