Energy consumption equipment data monitoring and energy optimization system and method based on Internet of Things

Abstract

The invention relates to a data monitoring technology, and discloses an energy consumption equipment data monitoring and energy optimization method and device based on the Internet of Things, and the method comprises the steps: obtaining an operation parameter set of energy consumption equipment in a preset time period, carrying out the denoising processing of the operation parameter set, obtaining a denoised operation parameter set, and carrying out the denoising processing of the denoised operation parameter set; calculating an operation stability coefficient according to the de-noising operation parameter set, if the operation stability coefficient is smaller than a preset stability threshold value, calculating an adjustment parameter and adjusting the operation voltage and the operation current, otherwise, calculating an operation efficiency coefficient of the energy consumption equipment, and if the operation efficiency coefficient is larger than or equal to a preset efficiency coefficient threshold value, adjusting the operation voltage and the operation current. And if yes, returning to the step of acquiring the operating parameter set, otherwise, calculating an optimization parameter according to the de-noising operating parameter set, and adjusting the operating voltage and the operating current of the energy consumption equipment according to the optimization parameter. According to the invention, the efficiency of energy consumption equipment data monitoring and energy optimization can be improved.

Description

Technical Field

[0001] The present invention relates to the field of data monitoring technology, and in particular to an energy-consuming equipment data monitoring and energy optimization system and method based on the Internet of Things. Background Art

[0002] In today's increasingly tense global energy situation and increasingly prominent environmental problems, energy conservation and emission reduction have become the focus of widespread concern in all sectors of society. With the rapid development of Internet of Things technology, its application in the field of energy management has shown great potential and value. Through intelligent sensors, data acquisition equipment, wireless communication networks, and cloud computing platforms, Internet of Things technology has achieved real-time monitoring, data collection and analysis of energy-consuming equipment, providing strong support for the efficient use and optimal management of energy.

[0003] Traditional energy management systems mostly rely on manual meter reading and regular inspections to obtain energy usage data, which is not only time-consuming and labor-intensive, but also difficult to ensure the real-time and accuracy of the data. In addition, traditional systems lack intelligent data analysis methods, cannot deeply explore the potential value behind the data, and are difficult to achieve accurate management and optimization of energy use. Summary of the invention

[0004] The present invention provides an energy-consuming equipment data monitoring and energy optimization system and method based on the Internet of Things, the main purpose of which is to solve the problem of low efficiency of existing energy management systems.

[0005] To achieve the above-mentioned purpose, the present invention provides an energy-consuming equipment data monitoring and energy optimization system based on the Internet of Things, characterized in that the system includes a data acquisition module, a data processing module, a data calculation module, a stability judgment module and an efficiency judgment module. Among them:

[0006] The data acquisition module is used to acquire a set of operating parameters of the energy-consuming equipment within a preset time period using a preset sensor;

[0007] The data processing module is used to perform denoising on the operating parameter set using a preset Internet of Things platform to obtain a denoised operating parameter set;

[0008] The data calculation module is used to calculate the operation stability coefficient of the energy-consuming equipment according to the denoising operation parameter set;

[0009] The stability judgment module is used to judge whether the operation stability coefficient is greater than a preset stability threshold; if the operation stability coefficient is less than or equal to the preset stability threshold, then calculate the adjustment parameter according to the denoising operation parameter set, adjust the operation voltage and the operation current of the energy-consuming device according to the adjustment parameter; if the operation stability coefficient is greater than the stability threshold, then calculate the operation efficiency coefficient of the energy-consuming device;

[0010] The efficiency judgment module is used to judge whether the operating efficiency coefficient is greater than or equal to a preset efficiency coefficient threshold. If the operating efficiency coefficient is greater than or equal to the efficiency coefficient threshold, the module returns to the step of using a preset sensor to obtain a set of operating parameters of the energy-consuming equipment within a preset time period. If the operating efficiency coefficient is less than the preset efficiency coefficient threshold, the module calculates optimization parameters based on the denoised operating parameter set, and adjusts the operating voltage and operating current of the energy-consuming equipment based on the optimization parameters.

[0011] Optionally, when the data acquisition module uses a preset sensor to acquire a set of operating parameters of an energy-consuming device within a preset time period, it is specifically used to:

[0012] Using a preset current sensor to obtain current parameters within a preset time period;

[0013] Using a preset voltage sensor to obtain voltage parameters within a preset time period;

[0014] Using a preset temperature sensor to obtain temperature parameters within a preset time period;

[0015] Using a preset noise sensor to obtain noise parameters within a preset time period;

[0016] The preset vibration sensor is used to obtain vibration parameters within a preset time period.

[0017] Optionally, when the data processing module performs denoising processing on the operating parameter set by using a preset Internet of Things platform to obtain a denoised operating parameter set, the data processing module is specifically used to:

[0018] Using the Internet of Things platform to divide the set of operating parameters into a plurality of data blocks of preset widths based on a time sequence, to obtain a set of data blocks;

[0019] Calculating the mean of the operating parameters in each data block in the data block set to obtain a mean parameter set;

[0020] The operating parameters in all the data blocks in the data block set are replaced in sequence using the mean values ​​in the mean parameter set to obtain a denoising operating parameter set.

[0021] Optionally, when the data calculation module calculates the operation stability coefficient of the energy-consuming equipment according to the denoising operation parameter set, it is specifically used to:

[0022] Fusing the data at the same sampling time point in the denoising operation parameter set to obtain a fused operation data set;

[0023] Calculate the standard deviation discrimination coefficient according to the fusion operation data set and the denoising operation parameter set;

[0024] The operation stability coefficient of the energy-consuming equipment is calculated based on the sampling time point according to the fused operation data set, the denoised operation parameter set and the standard deviation discrimination coefficient.

[0025] Optionally, when the stability judgment module calculates the standard deviation discrimination coefficient according to the fusion operation data set and the denoising operation parameter set, it is specifically used to:

[0026] The standard deviation discrimination coefficient was calculated using the following formula:

[0027]

[0028] Wherein, σ is the standard deviation discrimination coefficient, μ I represents the mean value of the current parameter in the denoising operation parameter set, μ V represents the mean value of the electric pressure parameter in the denoising operation parameter set, D A is the standard deviation of the fusion run data set, D I is the standard deviation of the current parameter in the denoising operation parameter set, D V is the standard deviation of the voltage parameter in the denoising operation parameter set.

[0029] Optionally, when the stability judgment module calculates the operation stability coefficient of the energy-consuming equipment based on the sampling time point according to the fused operation data set, the denoising operation parameter set and the standard deviation discrimination coefficient, it is specifically used to:

[0030] The operating stability coefficient is calculated using the following formula:

[0031]

[0032] Wherein, S is the operation stability coefficient, n is the number of sampling time points in the fusion operation data set, and A i represents the data of the ith sampling time point of the fusion operation data set, I i represents the current parameter at the ith sampling time point of the denoising operation parameter set, V i represents the voltage parameter at the ith sampling time point of the denoising operation parameter set, μA represents the mean of the fusion running data set, μ I represents the mean value of the current parameter in the denoising operation parameter set, μ V represents the mean value of the electric pressure parameter in the denoising operation parameter set, and σ is the standard deviation discrimination coefficient.

[0033] Optionally, the stability judgment module calculates the adjustment parameter according to the denoising operation parameter set, specifically for:

[0034] Calculating the variance of the temperature parameter and the noise parameter in the denoising operation parameter set to obtain the temperature variance and the noise variance;

[0035] Determining whether the mean value of the temperature parameter in the denoising operation parameter set is greater than a preset temperature threshold;

[0036] If the average value of the temperature parameter is greater than the temperature threshold, adjusting the operating current of the energy-consuming device according to a preset current adjustment step;

[0037] If the mean of the temperature parameter is less than or equal to the temperature threshold, adjusting the operating current according to the temperature variance;

[0038] Determining whether the mean value of the noise parameters in the denoising operation parameter set is greater than a preset noise threshold;

[0039] If the mean value of the noise parameter is greater than the noise threshold, adjusting the operating voltage of the energy-consuming device according to a preset voltage adjustment step;

[0040] If the mean of the noise parameter is less than or equal to the noise threshold, the operating voltage is adjusted according to the noise variance.

[0041] Optionally, the efficiency judgment module calculates the operating efficiency coefficient of the energy-consuming equipment, specifically for:

[0042] The operating efficiency coefficient is calculated using the following formula:

[0043]

[0044] Wherein, M is the operating efficiency coefficient, T i is the temperature parameter at the i-th sampling time point in the denoising operation parameter set, T o is the preset standard operating temperature, T max is the maximum current parameter in the denoising operation parameter set, R i is the noise parameter at the i-th sampling time point in the denoising operation parameter set, R o is the preset standard operating noise, R maxis the maximum noise parameter in the denoising operation parameter set, P i is the vibration parameter at the i-th sampling time point in the denoising operation parameter set, P o is the preset standard vibration parameter, P max The maximum vibration parameter in the denoising operation parameter set.

[0045] Optionally, the efficiency judgment module calculates optimization parameters according to the denoising operation parameter set, and adjusts the operation voltage and the operation current of the energy-consuming device according to the optimization parameters, specifically for:

[0046] According to the current standard deviation and current average value of the current data in the denoising operation parameter set;

[0047] Calculating a current difference between the current average value and a preset standard current, multiplying the sum of the current difference and the current standard deviation by a preset first coefficient to obtain a current optimization parameter, and adjusting the operating current of the energy-consuming device according to the current optimization parameter;

[0048] The voltage difference between the voltage average value and the preset standard voltage is calculated, the sum of the voltage difference and the voltage standard deviation is multiplied by a preset first coefficient to obtain a voltage optimization parameter, and the operating voltage of the energy-consuming device is adjusted according to the voltage optimization parameter.

[0049] In order to solve the above problems, the present invention also provides an energy-consuming equipment data monitoring and energy optimization method based on the Internet of Things, characterized in that the method comprises:

[0050] Using a preset sensor to obtain a set of operating parameters of energy-consuming equipment within a preset time period;

[0051] Performing denoising processing on the operating parameter set by using a preset Internet of Things platform to obtain a denoised operating parameter set;

[0052] Calculating the operation stability coefficient of the energy-consuming equipment according to the denoising operation parameter set;

[0053] Determining whether the operation stability coefficient is greater than a preset stability threshold;

[0054] If the operation stability coefficient is less than or equal to a preset stability threshold, then calculating an adjustment parameter according to the denoising operation parameter set, and adjusting the operation voltage and the operation current of the energy-consuming device according to the adjustment parameter;

[0055] If the operation stability coefficient is greater than the stability threshold, calculating the operation efficiency coefficient of the energy-consuming equipment;

[0056] Determining whether the operating efficiency coefficient is greater than or equal to a preset efficiency coefficient threshold;

[0057] If the operating efficiency coefficient is greater than or equal to the efficiency coefficient threshold, returning to the step of using a preset sensor to obtain a set of operating parameters of the energy-consuming device within a preset time period;

[0058] If the operating efficiency coefficient is less than a preset efficiency coefficient threshold, an optimization parameter is calculated according to the denoising operating parameter set, and the operating voltage and the operating current of the energy-consuming device are adjusted according to the optimization parameter.

[0059] In an embodiment of the present invention, a set of operating parameters of an energy-consuming device within a preset time length is obtained by using a preset sensor, and the operating parameter set is denoised by using a preset Internet of Things platform to obtain a denoised operating parameter set. An operating stability coefficient of the energy-consuming device is calculated according to the denoised operating parameter set, and it is determined whether the operating stability coefficient is greater than a preset stability threshold. If the operating stability coefficient is less than or equal to the preset stability threshold, an adjustment parameter is calculated according to the denoised operating parameter set, and an operating voltage and an operating current of the energy-consuming device are adjusted according to the adjustment parameter. If the operating stability coefficient is greater than the stability threshold, an operating efficiency coefficient of the energy-consuming device is calculated, and it is determined whether the operating efficiency coefficient is greater than or equal to a preset efficiency coefficient threshold. If the operating efficiency coefficient is greater than or equal to the efficiency coefficient threshold, the step of obtaining the set of operating parameters of the energy-consuming device within a preset time length by using the preset sensor is returned. If the operating efficiency coefficient is less than the preset efficiency coefficient threshold, an optimization parameter is calculated according to the denoised operating parameter set, and the operating voltage and the operating current of the energy-consuming device are adjusted according to the optimization parameter. Therefore, the energy-consuming equipment data monitoring and energy optimization system and method based on the Internet of Things proposed in the present invention can solve the problem of low accuracy when making product recommendations. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 A functional module diagram of an energy-consuming equipment data monitoring and energy optimization system based on the Internet of Things provided by an embodiment of the present invention;

[0061] Figure 2 A schematic diagram of a flow chart of a method for monitoring energy-consuming equipment data and optimizing energy based on the Internet of Things provided in one embodiment of the present invention;

[0062] Figure 3 A schematic diagram of the structure of an electronic device for implementing the energy-consuming device data monitoring and energy optimization method based on the Internet of Things provided in one embodiment of the present invention.

[0063] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0064] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0065] The embodiment of the present application provides an energy-consuming device data monitoring and energy optimization system based on the Internet of Things. The execution subject of the energy-consuming device data monitoring and energy optimization system based on the Internet of Things includes but is not limited to at least one of the electronic devices such as the server, the terminal, etc. that can be configured to execute the method provided in the embodiment of the present application. In other words, the energy-consuming device data monitoring and energy optimization system based on the Internet of Things can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0066] Reference Figure 1 , which is a functional module diagram of an energy-consuming equipment data monitoring and energy optimization system based on the Internet of Things provided by an embodiment of the present invention.

[0067] S1. Using a preset sensor to obtain a set of operating parameters of energy-consuming equipment within a preset time period.

[0068] In the embodiment of the present invention, the sensor includes a current sensor, a voltage sensor, a temperature sensor, a noise sensor and a vibration sensor.

[0069] The energy-consuming equipment data monitoring and energy optimization system 100 based on the Internet of Things of the present invention can be installed in an electronic device. According to the functions to be implemented, the energy-consuming equipment data monitoring and energy optimization system 100 based on the Internet of Things can include a data acquisition module 101, a data processing module 102, a data calculation module 103, a stability judgment module 104 and an efficiency judgment module 105. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0070] In the following, in combination with specific embodiments, each component and specific workflow of the energy consumption equipment data monitoring and energy optimization system based on the Internet of Things are described respectively:

[0071] The data acquisition module 101 is used to acquire a set of operating parameters of energy-consuming equipment within a preset time period using a preset sensor;

[0072] The data processing module 102 is used to perform denoising on the operating parameter set using a preset Internet of Things platform to obtain a denoised operating parameter set;

[0073] The data calculation module 103 is used to calculate the operation stability coefficient of the energy-consuming equipment according to the denoising operation parameter set;

[0074] The stability judgment module 104 is used to judge whether the operation stability coefficient is greater than a preset stability threshold. If the operation stability coefficient is less than or equal to the preset stability threshold, an adjustment parameter is calculated according to the denoising operation parameter set, and an operation voltage and an operation current of the energy-consuming device are adjusted according to the adjustment parameter. If the operation stability coefficient is greater than the stability threshold, an operation efficiency coefficient of the energy-consuming device is calculated.

[0075] The efficiency judgment module 105 is used to judge whether the operating efficiency coefficient is greater than or equal to a preset efficiency coefficient threshold. If the operating efficiency coefficient is greater than or equal to the efficiency coefficient threshold, the module returns to the step of obtaining the operating parameter set of the energy-consuming equipment within a preset time period using a preset sensor. If the operating efficiency coefficient is less than the preset efficiency coefficient threshold, the optimization parameters are calculated according to the denoised operating parameter set, and the operating voltage and operating current of the energy-consuming equipment are adjusted according to the optimization parameters.

[0076] The data acquisition module 101 is used to acquire a set of operating parameters of energy-consuming equipment within a preset time period using a preset sensor.

[0077] In the embodiment of the present invention, the operating parameter set includes current parameters, voltage parameters, temperature parameters, noise parameters and vibration parameters.

[0078] In the embodiment of the present invention, the energy-consuming device may be a device or equipment that consumes electrical energy.

[0079] In the embodiment of the present invention, the step of obtaining a set of operating parameters of an energy-consuming device within a preset time period by using a preset sensor includes:

[0080] Using a preset current sensor to obtain current parameters within a preset time period;

[0081] Using a preset voltage sensor to obtain voltage parameters within a preset time period;

[0082] Using a preset temperature sensor to obtain temperature parameters within a preset time period;

[0083] Using a preset noise sensor to obtain noise parameters within a preset time period;

[0084] The preset vibration sensor is used to obtain vibration parameters within a preset time period.

[0085] In detail, the vibration sensor may be a displacement sensor, which detects the displacement of the energy-consuming device in various directions and converts it into vibration parameters of the energy-consuming device.

[0086] In the embodiment of the present invention, the preset duration refers to the duration of collecting data, and the preset duration needs to be set according to actual needs. A longer preset duration can obtain more detailed operating parameters, which can improve the accuracy of data analysis, but will reduce the efficiency of data analysis. Correspondingly, a shorter preset duration will reduce the accuracy of data analysis, but can improve the efficiency of data analysis.

[0087] In the embodiment of the present invention, by using preset sensors to obtain current parameters, voltage parameters, temperature parameters, noise parameters and vibration parameters of energy-consuming equipment within a preset time period, an operating parameter set is obtained, thereby improving the efficiency of subsequent calculation of the operating stability coefficient.

[0088] The data processing module 102 is used to perform denoising on the operating parameter set using a preset Internet of Things platform to obtain a denoised operating parameter set.

[0089] In the embodiment of the present invention, the Internet of Things platform is a comprehensive service platform for connecting and managing Internet of Things devices, collecting and analyzing data, and supporting application development and deployment.

[0090] In the embodiment of the present invention, the denoising process is an important step in data processing, which aims to remove noise in the data and make the data smoother to improve the data quality.

[0091] In the embodiment of the present invention, the denoising process is performed on the operating parameter set by using a preset Internet of Things platform to obtain the denoised operating parameter set, including:

[0092] Using the Internet of Things platform to divide the set of operating parameters into a plurality of data blocks of preset widths based on a time sequence, to obtain a set of data blocks;

[0093] Calculating the mean of the operating parameters in each data block in the data block set to obtain a mean parameter set;

[0094] The operating parameters in all the data blocks in the data block set are replaced in sequence using the mean values ​​in the mean parameter set to obtain a denoising operating parameter set.

[0095] In the embodiment of the present invention, the operation parameter set is denoised by using a preset Internet of Things platform to obtain a denoised operation parameter set, thereby improving the quality of data and the accuracy of subsequent calculation of the operation stability coefficient.

[0096] The data calculation module 103 is used to calculate the operation stability coefficient of the energy-consuming equipment according to the denoising operation parameter set.

[0097] In an embodiment of the present invention, the operation stability coefficient is a parameter used to represent the operation stability of the energy-consuming equipment, and needs to be obtained by comprehensive calculation based on the current parameter, voltage parameter, temperature parameter, noise parameter and vibration parameter in the denoising operation parameter set.

[0098] In the embodiment of the present invention, the step of calculating the operation stability coefficient of the energy-consuming device according to the denoising operation parameter set includes:

[0099] Fusing the data at the same sampling time point in the denoising operation parameter set to obtain a fused operation data set;

[0100] Calculate the standard deviation discrimination coefficient according to the fusion operation data set and the denoising operation parameter set;

[0101] The operation stability coefficient of the energy-consuming equipment is calculated based on the sampling time point according to the fused operation data set, the denoised operation parameter set and the standard deviation discrimination coefficient.

[0102] In detail, the calculating the standard deviation discrimination coefficient according to the fusion operation data set and the denoising operation parameter set includes:

[0103] The standard deviation discrimination coefficient was calculated using the following formula:

[0104]

[0105] Wherein, σ is the standard deviation discrimination coefficient, μ I represents the mean value of the current parameter in the denoising operation parameter set, μ V represents the mean value of the electric pressure parameter in the denoising operation parameter set, D A is the standard deviation of the fusion run data set, D I is the standard deviation of the current parameter in the denoising operation parameter set, D V is the standard deviation of the voltage parameter in the denoising operation parameter set.

[0106] In detail, the calculating the operation stability coefficient of the energy-consuming equipment based on the sampling time point according to the fused operation data set, the denoised operation parameter set and the standard deviation discrimination coefficient includes:

[0107] The operating stability coefficient is calculated using the following formula:

[0108]

[0109] Wherein, S is the operation stability coefficient, n is the number of sampling time points in the fusion operation data set, and A i represents the data of the ith sampling time point of the fusion operation data set, I i represents the current parameter at the ith sampling time point of the denoising operation parameter set, V i represents the voltage parameter at the ith sampling time point of the denoising operation parameter set, μ A represents the mean of the fusion running data set, μ I represents the mean value of the current parameter in the denoising operation parameter set, μ V represents the mean value of the electric pressure parameter in the denoising operation parameter set, and σ is the standard deviation discrimination coefficient.

[0110] In the embodiment of the present invention, by calculating the operation stability coefficient of the energy-consuming equipment according to the denoising operation parameter set, the efficiency of subsequent determination of whether the operation stability coefficient is greater than a preset stability threshold is improved.

[0111] The stability judgment module 104 is used to judge whether the operating stability coefficient is greater than a preset stability threshold. If the operating stability coefficient is less than or equal to the preset stability threshold, the adjustment parameters are calculated according to the denoising operating parameter set, and the operating voltage and operating current of the energy-consuming equipment are adjusted according to the adjustment parameters. If the operating stability coefficient is greater than the stability threshold, the operating efficiency coefficient of the energy-consuming equipment is calculated.

[0112] In an embodiment of the present invention, when the operating stability coefficient is less than or equal to a preset stability threshold, it indicates that the operation of the energy-consuming equipment is unstable and there is a safety hazard. Therefore, it is necessary to adjust the operating current and operating voltage of the energy-consuming equipment to improve the operating stability of the energy-consuming equipment.

[0113] In the embodiment of the present invention, the step of calculating the adjustment parameter according to the denoising operation parameter set includes:

[0114] Calculating the variance of the temperature parameter and the noise parameter in the denoising operation parameter set to obtain the temperature variance and the noise variance;

[0115] Determining whether the mean value of the temperature parameter in the denoising operation parameter set is greater than a preset temperature threshold;

[0116] If the average value of the temperature parameter is greater than the temperature threshold, adjusting the operating current of the energy-consuming device according to a preset current adjustment step;

[0117] If the mean of the temperature parameter is less than or equal to the temperature threshold, adjusting the operating current according to the temperature variance;

[0118] Determining whether the mean value of the noise parameters in the denoising operation parameter set is greater than a preset noise threshold;

[0119] If the mean value of the noise parameter is greater than the noise threshold, adjusting the operating voltage of the energy-consuming device according to a preset voltage adjustment step;

[0120] If the mean of the noise parameter is less than or equal to the noise threshold, the operating voltage is adjusted according to the noise variance.

[0121] In detail, adjusting the operating current according to the temperature variance refers to multiplying the temperature variance by a proportionality coefficient to obtain a current adjustment value, and adjusting the operating current according to the current.

[0122] In detail, adjusting the operating voltage according to the noise variance refers to multiplying the noise variance by a proportionality coefficient to obtain a voltage adjustment value, and adjusting the voltage to adjust the operating voltage.

[0123] In an embodiment of the present invention, when the operating stability coefficient is less than or equal to a preset stability threshold, the operating stability of the equipment is improved by calculating the adjustment parameters based on the denoising operating parameter set and adjusting the operating voltage and operating current of the energy-consuming equipment according to the adjustment parameters.

[0124] In the embodiment of the present invention, the operation efficiency coefficient of the energy-consuming equipment is calculated based on the difference between the temperature parameters, noise parameters, vibration parameters of the energy-consuming equipment and standard parameters.

[0125] In the embodiment of the present invention, the calculating the operating efficiency coefficient of the energy-consuming equipment includes:

[0126] The operating efficiency coefficient is calculated using the following formula:

[0127]

[0128] Wherein, M is the operating efficiency coefficient, T i is the temperature parameter at the i-th sampling time point in the denoising operation parameter set, T o is the preset standard operating temperature, T max is the maximum current parameter in the denoising operation parameter set, R i is the noise parameter at the i-th sampling time point in the denoising operation parameter set, R o is the preset standard operating noise, R max is the maximum noise parameter in the denoising operation parameter set, P iis the vibration parameter at the i-th sampling time point in the denoising operation parameter set, P o is the preset standard vibration parameter, P max The maximum vibration parameter in the denoising operation parameter set.

[0129] In the embodiment of the present invention, the standard operating temperature, the standard operating noise, and the standard vibration parameters are all data measured when the energy-consuming equipment is at a high operating efficiency.

[0130] In an embodiment of the present invention, when the operating stability coefficient is greater than the stability threshold, the operating efficiency coefficient of the energy-consuming equipment is calculated, thereby improving the efficiency of subsequent determination of whether the operating efficiency coefficient is greater than or equal to a preset efficiency coefficient threshold.

[0131] The efficiency judgment module 105 is used to judge whether the operating efficiency coefficient is greater than or equal to a preset efficiency coefficient threshold. If the operating efficiency coefficient is greater than or equal to the efficiency coefficient threshold, the module returns to the step of obtaining the operating parameter set of the energy-consuming equipment within a preset time period using a preset sensor. If the operating efficiency coefficient is less than the preset efficiency coefficient threshold, the optimization parameters are calculated according to the denoised operating parameter set, and the operating voltage and operating current of the energy-consuming equipment are adjusted according to the optimization parameters.

[0132] In an embodiment of the present invention, when the operating efficiency coefficient is greater than or equal to the efficiency coefficient threshold, it means that the energy-consuming equipment is operating stably and the operating efficiency meets the requirements. The step of using a preset sensor to obtain a set of operating parameters of the energy-consuming equipment within a preset time period is re-executed to carry out a new round of monitoring and optimization.

[0133] In an embodiment of the present invention, when the operating efficiency coefficient is less than a preset efficiency coefficient threshold, it indicates that the operating efficiency of the energy-consuming device at this time does not meet expectations, and therefore the operating current and operating voltage of the energy-consuming device need to be adjusted to improve the operating efficiency of the energy-consuming device.

[0134] In an embodiment of the present invention, the step of calculating the optimization parameters according to the denoising operation parameter set and adjusting the operation voltage and the operation current of the energy-consuming device according to the optimization parameters includes:

[0135] According to the current standard deviation and current average value of the current data in the denoising operation parameter set;

[0136] Calculating a current difference between the current average value and a preset standard current, multiplying the sum of the current difference and the current standard deviation by a preset first coefficient to obtain a current optimization parameter, and adjusting the operating current of the energy-consuming device according to the current optimization parameter;

[0137] The voltage difference between the voltage average value and the preset standard voltage is calculated, the sum of the voltage difference and the voltage standard deviation is multiplied by a preset first coefficient to obtain a voltage optimization parameter, and the operating voltage of the energy-consuming device is adjusted according to the voltage optimization parameter.

[0138] In an embodiment of the present invention, when the operating efficiency coefficient is less than a preset efficiency coefficient threshold, the operating efficiency of the energy-consuming equipment is improved by calculating the optimization parameters based on the denoising operating parameter set, and adjusting the operating voltage and operating current of the energy-consuming equipment according to the optimization parameters, thereby improving the energy utilization rate.

[0139] like Figure 2 FIG. 1 is a flow chart of a method for monitoring energy-consuming equipment data and optimizing energy based on the Internet of Things provided by an embodiment of the present invention. In this embodiment, the method for monitoring energy-consuming equipment data and optimizing energy based on the Internet of Things includes:

[0140] S1. Using a preset sensor to obtain a set of operating parameters of energy-consuming equipment within a preset time period.

[0141] S2. Perform denoising on the operating parameter set using a preset Internet of Things platform to obtain a denoised operating parameter set.

[0142] S3. Calculate the operation stability coefficient of the energy-consuming equipment according to the denoising operation parameter set.

[0143] S4. Determine whether the operation stability coefficient is greater than a preset stability threshold.

[0144] If the operation stability coefficient is less than or equal to the preset stability threshold, execute S5, calculate adjustment parameters according to the denoising operation parameter set, and adjust the operation voltage and the operation current of the energy-consuming device according to the adjustment parameters.

[0145] If the operation stability coefficient is greater than the stability threshold, execute S6 to calculate the operation efficiency coefficient of the energy-consuming equipment.

[0146] S7. Determine whether the operating efficiency coefficient is greater than or equal to a preset efficiency coefficient threshold.

[0147] If the operating efficiency coefficient is greater than or equal to the efficiency coefficient threshold, the process returns to S1, the step of using a preset sensor to obtain a set of operating parameters of the energy-consuming equipment within a preset time period.

[0148] If the operating efficiency coefficient is less than a preset efficiency coefficient threshold, S8 is executed to calculate optimization parameters according to the denoising operating parameter set, and the operating voltage and operating current of the energy-consuming device are adjusted according to the optimization parameters.

[0149] like Figure 3 , which is a schematic diagram of the structure of an electronic device of an energy-consuming device data monitoring and energy optimization method based on the Internet of Things provided in an embodiment of the present invention.

[0150] The electronic device 1 may include a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as an energy-consuming equipment data monitoring and energy optimization program based on the Internet of Things.

[0151] In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips. The processor 10 is the control core (ControlUnit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes or executes programs or modules stored in the memory 11 (such as data monitoring and energy optimization programs for energy-consuming devices based on the Internet of Things, etc.), and calls data stored in the memory 11 to execute various functions of the electronic device and process data.

[0152] The memory 11 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (for example, SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. In some embodiments, the memory 11 may be an internal storage unit of an electronic device, such as a mobile hard disk of the electronic device. In other embodiments, the memory 11 may also be an external storage device of an electronic device, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Further, the memory 11 may also include both an internal storage unit of the electronic device and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device, such as the code of the energy-consuming device data monitoring and energy optimization program based on the Internet of Things, but also can be used to temporarily store data that has been output or is to be output.

[0153] The communication bus 12 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0154] The communication interface 13 is used for communication between the above-mentioned electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally, the user interface may also be a standard wired interface, a wireless interface. Optionally, in this embodiment, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode, organic light-emitting diode) touch device, etc. Among them, the display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device and to display a visual user interface.

[0155] The figure only shows an electronic device with components. Those skilled in the art will understand that the structure shown in the figure does not constitute a limitation on the electronic device, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0156] For example, although not shown, the electronic device may also include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0157] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0158] The energy-consuming equipment data monitoring and energy optimization program based on the Internet of Things stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve:

[0159] Using a preset sensor to obtain a set of operating parameters of energy-consuming equipment within a preset time period;

[0160] Performing denoising processing on the operating parameter set by using a preset Internet of Things platform to obtain a denoised operating parameter set;

[0161] Calculating the operation stability coefficient of the energy-consuming equipment according to the denoising operation parameter set;

[0162] Determining whether the operation stability coefficient is greater than a preset stability threshold;

[0163] If the operation stability coefficient is less than or equal to a preset stability threshold, then calculating an adjustment parameter according to the denoising operation parameter set, and adjusting the operation voltage and the operation current of the energy-consuming device according to the adjustment parameter;

[0164] If the operation stability coefficient is greater than the stability threshold, calculating the operation efficiency coefficient of the energy-consuming equipment;

[0165] Determining whether the operating efficiency coefficient is greater than or equal to a preset efficiency coefficient threshold;

[0166] If the operating efficiency coefficient is greater than or equal to the efficiency coefficient threshold, returning to the step of using a preset sensor to obtain a set of operating parameters of the energy-consuming device within a preset time period;

[0167] If the operating efficiency coefficient is less than a preset efficiency coefficient threshold, an optimization parameter is calculated according to the denoising operating parameter set, and the operating voltage and the operating current of the energy-consuming device are adjusted according to the optimization parameter.

[0168] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to the description of the relevant steps in the corresponding embodiment of the accompanying drawings, which will not be repeated here.

[0169] Furthermore, if the module / unit integrated in the electronic device 1 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0170] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can implement:

[0171] Using a preset sensor to obtain a set of operating parameters of energy-consuming equipment within a preset time period;

[0172] Performing denoising processing on the operating parameter set by using a preset Internet of Things platform to obtain a denoised operating parameter set;

[0173] Calculating the operation stability coefficient of the energy-consuming equipment according to the denoising operation parameter set;

[0174] Determining whether the operation stability coefficient is greater than a preset stability threshold;

[0175] If the operation stability coefficient is less than or equal to a preset stability threshold, then calculating an adjustment parameter according to the denoising operation parameter set, and adjusting the operation voltage and the operation current of the energy-consuming device according to the adjustment parameter;

[0176] If the operation stability coefficient is greater than the stability threshold, calculating the operation efficiency coefficient of the energy-consuming equipment;

[0177] Determining whether the operating efficiency coefficient is greater than or equal to a preset efficiency coefficient threshold;

[0178] If the operating efficiency coefficient is greater than or equal to the efficiency coefficient threshold, returning to the step of using a preset sensor to obtain a set of operating parameters of the energy-consuming device within a preset time period;

[0179] If the operating efficiency coefficient is less than a preset efficiency coefficient threshold, an optimization parameter is calculated according to the denoising operating parameter set, and the operating voltage and the operating current of the energy-consuming device are adjusted according to the optimization parameter.

[0180] In the embodiments provided by the present invention, it should be understood that the disclosed devices, systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0181] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0182] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0183] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0184] Therefore, no matter from which point of view, the embodiments should be regarded as illustrative and non-restrictive, and the scope of the present invention is limited by the appended claims rather than the above description, so it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any attached figure mark in the claims should not be regarded as limiting the claims involved.

[0185] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0186] In addition, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the system claim can also be implemented by one unit or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.

[0187] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. An energy-consuming equipment data monitoring and energy optimization system based on the Internet of Things, characterized in that: The system includes a data acquisition module, a data processing module, a data calculation module, a stability judgment module and an efficiency judgment module. The data acquisition module is used to acquire a set of operating parameters of the energy-consuming equipment within a preset time period using a preset sensor; The data processing module is used to perform denoising on the operating parameter set using a preset Internet of Things platform to obtain a denoised operating parameter set; The data calculation module is used to calculate the operation stability coefficient of the energy-consuming equipment according to the denoising operation parameter set; The stability judgment module is used to judge whether the operation stability coefficient is greater than a preset stability threshold; if the operation stability coefficient is less than or equal to the preset stability threshold, then calculate the adjustment parameter according to the denoising operation parameter set, adjust the operation voltage and the operation current of the energy-consuming device according to the adjustment parameter; if the operation stability coefficient is greater than the stability threshold, then calculate the operation efficiency coefficient of the energy-consuming device; The efficiency judgment module is used to judge whether the operating efficiency coefficient is greater than or equal to a preset efficiency coefficient threshold. If the operating efficiency coefficient is greater than or equal to the efficiency coefficient threshold, the module returns to the step of using a preset sensor to obtain a set of operating parameters of the energy-consuming equipment within a preset time period. If the operating efficiency coefficient is less than the preset efficiency coefficient threshold, the module calculates optimization parameters based on the denoised operating parameter set, and adjusts the operating voltage and operating current of the energy-consuming equipment based on the optimization parameters.

2. The method for monitoring energy-consuming equipment data and optimizing energy based on the Internet of Things according to claim 1, characterized in that: When the data acquisition module uses a preset sensor to acquire a set of operating parameters of the energy-consuming device within a preset time period, it is specifically used to: Using a preset current sensor to obtain current parameters within a preset time period; Using a preset voltage sensor to obtain voltage parameters within a preset time period; Using a preset temperature sensor to obtain temperature parameters within a preset time period; Using a preset noise sensor to obtain noise parameters within a preset time period; The preset vibration sensor is used to obtain vibration parameters within a preset time period.

3. The method for monitoring energy-consuming equipment data and optimizing energy based on the Internet of Things according to claim 1, characterized in that: When the data processing module performs denoising processing on the operating parameter set using the preset Internet of Things platform to obtain the denoised operating parameter set, it is specifically used to: Using the Internet of Things platform to divide the set of operating parameters into a plurality of data blocks of preset widths based on a time sequence, to obtain a set of data blocks; Calculating the mean of the operating parameters in each data block in the data block set to obtain a mean parameter set; The operating parameters in all the data blocks in the data block set are replaced in sequence using the mean values ​​in the mean parameter set to obtain a denoising operating parameter set.

4. The method for monitoring energy-consuming equipment data and optimizing energy based on the Internet of Things according to claim 1, characterized in that: When the data calculation module calculates the operation stability coefficient of the energy-consuming equipment according to the denoising operation parameter set, the data calculation module is specifically used to: Fusing the data at the same sampling time point in the denoising operation parameter set to obtain a fused operation data set; Calculate the standard deviation discrimination coefficient according to the fusion operation data set and the denoising operation parameter set; The operation stability coefficient of the energy-consuming equipment is calculated based on the sampling time point according to the fused operation data set, the denoised operation parameter set and the standard deviation discrimination coefficient.

5. The method for monitoring energy-consuming equipment data and optimizing energy based on the Internet of Things according to claim 4, characterized in that: When the stability judgment module calculates the standard deviation discrimination coefficient according to the fusion operation data set and the denoising operation parameter set, it is specifically used to: The standard deviation discrimination coefficient was calculated using the following formula: Wherein, σ is the standard deviation discrimination coefficient, μ I represents the mean value of the current parameter in the denoising operation parameter set, μ V represents the mean value of the electric pressure parameter in the denoising operation parameter set, D A is the standard deviation of the fusion run data set, D I is the standard deviation of the current parameter in the denoising operation parameter set, D V is the standard deviation of the voltage parameter in the denoising operation parameter set.

6. The method for monitoring energy-consuming equipment data and optimizing energy based on the Internet of Things according to claim 4, characterized in that: When the stability judgment module calculates the operation stability coefficient of the energy-consuming equipment based on the sampling time point according to the fused operation data set, the denoised operation parameter set and the standard deviation discrimination coefficient, it is specifically used to: The operating stability coefficient is calculated using the following formula: Wherein, S is the operation stability coefficient, n is the number of sampling time points in the fusion operation data set, and A i represents the data of the ith sampling time point of the fusion operation data set, I i represents the current parameter at the ith sampling time point of the denoising operation parameter set, V i represents the voltage parameter at the ith sampling time point of the denoising operation parameter set, μ A represents the mean of the fusion running data set, μ I represents the mean value of the current parameter in the denoising operation parameter set, μ V represents the mean value of the electric pressure parameter in the denoising operation parameter set, and σ is the standard deviation discrimination coefficient.

7. The method for monitoring energy-consuming equipment data and optimizing energy based on the Internet of Things according to claim 1, characterized in that: The stability judgment module calculates the adjustment parameter according to the denoising operation parameter set, specifically for: Calculating the variance of the temperature parameter and the noise parameter in the denoising operation parameter set to obtain the temperature variance and the noise variance; Determining whether the mean value of the temperature parameter in the denoising operation parameter set is greater than a preset temperature threshold; If the average value of the temperature parameter is greater than the temperature threshold, adjusting the operating current of the energy-consuming device according to a preset current adjustment step; If the mean of the temperature parameter is less than or equal to the temperature threshold, adjusting the operating current according to the temperature variance; Determining whether the mean value of the noise parameters in the denoising operation parameter set is greater than a preset noise threshold; If the mean value of the noise parameter is greater than the noise threshold, adjusting the operating voltage of the energy-consuming device according to a preset voltage adjustment step; If the mean of the noise parameter is less than or equal to the noise threshold, the operating voltage is adjusted according to the noise variance.

8. The method for monitoring energy-consuming equipment data and optimizing energy based on the Internet of Things according to claim 1, characterized in that: The efficiency judgment module is used to calculate the operating efficiency coefficient of the energy-consuming equipment, specifically: The operating efficiency coefficient is calculated using the following formula: Wherein, M is the operating efficiency coefficient, T i is the temperature parameter at the i-th sampling time point in the denoising operation parameter set, T o is the preset standard operating temperature, T max is the maximum current parameter in the denoising operation parameter set, R i is the noise parameter at the i-th sampling time point in the denoising operation parameter set, R o is the preset standard operating noise, R max is the maximum noise parameter in the denoising operation parameter set, P i is the vibration parameter at the i-th sampling time point in the denoising operation parameter set, P o is the preset standard vibration parameter, P max The maximum vibration parameter in the denoising operation parameter set.

9. The method for monitoring energy-consuming equipment data and optimizing energy based on the Internet of Things according to claim 1, characterized in that: The efficiency judgment module calculates the optimization parameters according to the denoising operation parameter set, and adjusts the operation voltage and the operation current of the energy-consuming device according to the optimization parameters, specifically for: According to the current standard deviation and current average value of the current data in the denoising operation parameter set; Calculating a current difference between the current average value and a preset standard current, multiplying the sum of the current difference and the current standard deviation by a preset first coefficient to obtain a current optimization parameter, and adjusting the operating current of the energy-consuming device according to the current optimization parameter; The voltage difference between the voltage average value and the preset standard voltage is calculated, the sum of the voltage difference and the voltage standard deviation is multiplied by a preset first coefficient to obtain a voltage optimization parameter, and the operating voltage of the energy-consuming device is adjusted according to the voltage optimization parameter.

10. A method for monitoring energy-consuming equipment data and optimizing energy based on the Internet of Things, characterized in that: The method comprises: Using a preset sensor to obtain a set of operating parameters of the energy-consuming equipment within a preset time period; De-noising the operating parameter set using a preset Internet of Things platform to obtain a de-noised operating parameter set; Calculating the operation stability coefficient of the energy-consuming equipment according to the denoising operation parameter set; Determining whether the operation stability coefficient is greater than a preset stability threshold; If the operation stability coefficient is less than or equal to a preset stability threshold, then calculating an adjustment parameter according to the denoising operation parameter set, and adjusting the operation voltage and the operation current of the energy-consuming device according to the adjustment parameter; If the operation stability coefficient is greater than the stability threshold, calculating the operation efficiency coefficient of the energy-consuming equipment; Determining whether the operating efficiency coefficient is greater than or equal to a preset efficiency coefficient threshold; If the operating efficiency coefficient is greater than or equal to the efficiency coefficient threshold, returning to the step of using a preset sensor to obtain a set of operating parameters of the energy-consuming device within a preset time period; If the operating efficiency coefficient is less than a preset efficiency coefficient threshold, an optimization parameter is calculated according to the denoising operating parameter set, and the operating voltage and the operating current of the energy-consuming device are adjusted according to the optimization parameter.

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