An internet of things power equipment intelligent adaptation docking method and system, and an electronic device

Abstract

This invention discloses an intelligent adaptation and connection method, system, and electronic device for IoT power equipment, comprising: determining an offset based on the voltage and current signals of the power equipment, and determining access identification data by mapping the communication node ID sequentially based on the timestamp of the offset; determining node attributes based on the access identification data, constructing a mapping index, generating mapping comparison information, and generating protocol mapping parameters based on the mapping comparison information; determining available command data based on the protocol mapping parameters, determining port monitoring results based on the available command data, and performing power aggregation based on the port monitoring results to determine load allocation indicators; obtaining current amplitude based on the load allocation indicators, determining parameter comparison information, obtaining operating temperature based on the parameter comparison information, generating composite temperature data, and performing dynamic verification based on the composite temperature data to determine dynamic energy efficiency parameters, and performing adaptation and connection of the power equipment based on the dynamic energy efficiency parameters.

Description

Technical Field

[0001] This invention relates to the field of Internet of Things (IoT) technology, and more specifically, to a method, system, and electronic device for intelligent adaptation and connection of IoT power equipment. Background Technology

[0002] The field of intelligent adaptation technology for power equipment involves the compatibility and interconnectivity between different devices in a power system, covering aspects such as communication protocol parsing, data interaction, load optimization, energy efficiency management, and resource scheduling of power equipment.

[0003] Regarding device communication compatibility, existing technologies primarily employ fixed protocol matching methods. This results in poor compatibility with devices from different manufacturers and models, easily leading to protocol incompatibility or data parsing errors, thus affecting system stability. In terms of load optimization, traditional methods typically rely on preset static load parameters, lacking real-time monitoring and adjustment of device operating status. This can easily lead to uneven load distribution or unreasonable power allocation. Regarding energy efficiency management, existing technologies mostly use fixed power factor adjustment methods, which are difficult to dynamically adjust based on the device's operating environment and power demand. This may result in some devices operating at excessively high or low power, impacting the overall system energy efficiency.

[0004] Therefore, a new method for intelligent adaptation and connection of IoT power devices is needed. Summary of the Invention

[0005] This invention proposes a method, system, and electronic device for intelligent adaptation and connection of IoT power equipment, in order to solve the problem of how to efficiently achieve intelligent adaptation of IoT power equipment.

[0006] To address the aforementioned problems, according to one aspect of the present invention, a smart adaptation and connection method for Internet of Things (IoT) power devices is provided, the method comprising:

[0007] The voltage and current signals of the power equipment are acquired, the offset is determined based on the voltage and current signals, and the communication node ID is sequentially mapped based on the timestamp of the offset to identify identification information, and access identification data is determined based on the identification information.

[0008] Node attributes are determined based on the access identification data, a mapping index is constructed based on the node attributes, mapping comparison information is generated, and protocol mapping parameters are generated based on the mapping comparison information.

[0009] Based on the protocol mapping parameters, determine the available instruction data, determine the port monitoring results based on the available instruction data, and perform power aggregation based on the port monitoring results to determine the load distribution indicators;

[0010] The current amplitude is obtained based on the load distribution index, parameter comparison information is determined based on the current amplitude, the operating temperature is obtained based on the parameter comparison information, temperature composite data is generated, and dynamic verification is performed based on the temperature composite data to determine the energy efficiency dynamic parameters, so as to adapt and connect the power equipment based on the energy efficiency dynamic parameters.

[0011] Preferably, the method involves determining the offset based on the voltage and current signals, mapping the communication node IDs sequentially based on the timestamps of the offsets to identify identification information, and determining access identification data based on the identification information, including:

[0012] The instantaneous signals of the voltage and current signals are read sequentially to determine the peak and average values ​​at each time point. The difference between the peak and average values ​​at each time point is calculated, and waveform verification data is determined based on the difference.

[0013] Based on the waveform verification data, the waveform phase of each sampling segment is compared and the phase offset is recorded. Based on the difference between the phase offset and the preset offset threshold, an offset comparison result is generated.

[0014] Based on the offset comparison results, the timestamp information of each record with phase offset is compared with the known communication node ID to determine the unique identification information, and the corresponding running sequence number is input based on the identification information to generate access identification data based on the running sequence number.

[0015] Preferably, the process includes determining node attributes based on the access identification data, constructing a mapping index based on the node attributes, generating mapping reference information, and generating protocol mapping parameters based on the mapping reference information, including:

[0016] The access identification data is parsed to determine the node identifier, and the corresponding attribute list is queried based on the node identifier. The node is then categorized by locating the node ID and port information to generate node attribute records.

[0017] Based on the node attribute records, read the instruction code and query the execution cycle. Construct a mapping index by pairing the receiving order and the sending time period to generate mapping comparison information.

[0018] Based on the mapping information, each waveform feature is matched and the corresponding table entries are retrieved. By recording the matching electricity meter port index, protocol mapping parameters are generated.

[0019] Preferably, the method involves determining available instruction data based on the protocol mapping parameters, determining port monitoring results based on the available instruction data, and performing power aggregation based on the port monitoring results to determine load distribution metrics, including:

[0020] Based on the protocol mapping parameters, the instruction code is read and the port is verified to be available. The current instruction type is collected and summarized to determine the available instruction data.

[0021] Based on the available data from the instructions, the peak and fluctuating periods of the device current are determined, and the port monitoring results are determined by comparing the recorded timestamps with the port usage.

[0022] Based on the port monitoring results, preset power thresholds are combined and priorities are marked. A scheduling list is formed by pairing node identifiers and action numbers to determine load allocation indicators.

[0023] Preferably, the method involves obtaining the current amplitude based on the load allocation index, determining parameter comparison information based on the current amplitude, obtaining the operating temperature based on the parameter comparison information, generating composite temperature data, and performing dynamic verification based on the composite temperature data to determine dynamic energy efficiency parameters, and then performing power equipment adaptation and connection based on the dynamic energy efficiency parameters, including:

[0024] Based on the load distribution index, the current amplitude is read, the current peak value is obtained, and the current peak value is compared with the reference value to generate parameter comparison information;

[0025] Based on the parameter comparison information, the current operating temperature output by the corresponding temperature sensor is obtained, and interactive verification is performed based on the current operating temperature to generate composite temperature data.

[0026] Based on the temperature synthesis data, the power factor and power value are checked and matched with existing verification standards. Configuration information is updated by recording dynamic output to generate dynamic energy efficiency parameters, and power equipment is adapted and connected based on the dynamic energy efficiency parameters.

[0027] Preferably, the method further includes:

[0028] The load ID is determined based on the energy efficiency dynamic parameters, and a scheduling execution instruction is generated based on the load attributes corresponding to the load ID.

[0029] Based on the scheduling execution instruction, the power requirements of each node are read, and resources are allocated based on the power requirements of each node to generate a resource allocation list, so as to allocate resources based on the resource allocation list.

[0030] Preferably, the method involves determining the load ID based on the energy efficiency dynamic parameters and generating a scheduling execution instruction based on the load attributes corresponding to the load ID, including:

[0031] Based on the energy efficiency dynamic parameters, load IDs are screened and load attributes are obtained. Based on the load attributes, scheduling priorities are selected to generate type filtering results based on the scheduling priorities.

[0032] Based on the filtering results of the aforementioned types, the current port's idle or occupied status is analyzed and the available capacity is read. Idle periods are marked by comparison, and port detection information is generated.

[0033] Based on the port detection information, the motor speed feedback is monitored and compared with the reference range. By recording the switching sequence and the operation and maintenance code to identify the running node, a scheduling execution instruction is generated.

[0034] Preferably, based on the scheduling execution instruction, the power requirements of each node are read, and resources are allocated based on the power requirements of each node to generate a resource allocation list, including:

[0035] Based on the scheduling execution instructions, the power requirements of each node are checked and compared with the limit thresholds, and power comparison information is generated according to the status of nodes that meet or exceed the limit thresholds.

[0036] Based on the power comparison information, the communication frequency band number is verified and compared with the occupancy list. By screening for duplicate conflict markers, frequency band comparison results are generated.

[0037] Based on the frequency band comparison results, the voltage offset is checked and the correction data is recorded. Available ports are selected by retrieving the remaining capacity and the mapping is updated to generate a resource allocation list.

[0038] According to another aspect of the present invention, an intelligent adaptation and connection system for Internet of Things (IoT) power equipment is provided, the system comprising:

[0039] The access identification module is used to acquire voltage and current signals of power equipment, determine offset based on the voltage and current signals, and map communication node IDs sequentially based on the timestamp of the offset to identify identification information, and determine access identification data based on the identification information.

[0040] The protocol conversion module is used to determine node attributes based on the access identification data, construct a mapping index based on the node attributes, generate mapping comparison information, and generate protocol mapping parameters based on the mapping comparison information.

[0041] The load optimization module is used to determine the available data of instructions based on the protocol mapping parameters, determine the port monitoring results based on the available data of instructions, and perform power aggregation based on the port monitoring results to determine the load allocation indicators.

[0042] The energy efficiency control module is used to obtain the current amplitude based on the load distribution index, determine the parameter comparison information based on the current amplitude, obtain the operating temperature based on the parameter comparison information, generate temperature composite data, and perform dynamic verification based on the temperature composite data to determine the energy efficiency dynamic parameters, so as to perform the matching connection of power equipment based on the energy efficiency dynamic parameters.

[0043] According to another aspect of the present invention, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any one of the methods for intelligent adaptation and connection of Internet of Things power devices.

[0044] According to another aspect of the present invention, the present invention provides an electronic device, comprising:

[0045] The aforementioned computer-readable storage medium; and

[0046] One or more processors for executing a program in the computer-readable storage medium.

[0047] This invention provides an intelligent adaptation and connection method, system, and electronic device for IoT power equipment. Compared with existing technologies, its advantages are as follows: Power equipment access identification is based on voltage and current sensor signals. By verifying peak and average values ​​and determining the difference threshold, comparing the phase of each sampling segment waveform and recording the offset, and combining timestamps to sequentially map communication node IDs, accurate extraction of communication node identification information is ensured, avoiding misidentification. Communication protocol conversion and parsing of communication node classification information, retrieval of node IDs and communication port attributes, and reading of instruction codes and execution cycles enable automatic multi-protocol mapping, eliminating protocol conflicts between different devices and improving device compatibility. Load optimization dynamically monitors communication port status, device current fluctuations, and timestamp information, combined with power threshold matching scheduling priorities to ensure reasonable load allocation and reduce power redundancy. Energy efficiency control selects current amplitude, phase reference, and temperature sensor output data, compares power factor and power verification, and forms real-time power adjustment to reduce energy waste. Task scheduling combines load type, port status, and motor speed feedback to match operating time and power capacity, enabling dynamic task adjustment and avoiding power waste and equipment overload caused by high load operation. The method of this invention enables power equipment to dynamically adapt to its operating status, improves the adaptability of the power grid, and optimizes power distribution. Attached Figure Description

[0048] Exemplary embodiments of the present invention can be more fully understood by referring to the following figures:

[0049] Figure 1 A flowchart of an Internet of Things (IoT) power device smart adaptation connection method 100 provided according to an exemplary embodiment of the present invention;

[0050] Figure 2 This is a schematic diagram of the structure of an Internet of Things (IoT) power equipment intelligent adaptation and connection system 200 provided according to an exemplary embodiment of the present invention;

[0051] Figure 3This is a schematic diagram of the structure of an electronic device 300 provided in an exemplary embodiment of the present invention. Detailed Implementation

[0052] Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments of the present invention. It should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0053] It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention.

[0054] Those skilled in the art will understand that the terms "first," "second," etc., in the embodiments of the present invention are only used to distinguish different steps, devices, or modules, and do not represent any specific technical meaning, nor do they indicate a necessary logical order between them.

[0055] It should also be understood that in the embodiments of the present invention, "multiple" can refer to two or more, and "at least one" can refer to one, two or more.

[0056] It should also be understood that any component, data or structure mentioned in the embodiments of the present invention can generally be understood as one or more unless explicitly defined or given contrary instructions in the context.

[0057] Furthermore, the term "and / or" in this invention is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this invention generally indicates that the preceding and following related objects have an "or" relationship.

[0058] It should also be understood that the description of the various embodiments in this invention emphasizes the differences between the various embodiments, and the similarities or similarities can be referred to each other. For the sake of brevity, they will not be described in detail.

[0059] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0060] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use.

[0061] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, they should be considered part of the specification.

[0062] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0063] The embodiments of this invention can be applied to electronic devices such as terminal devices, computer systems, and servers, and can operate together with a wide range of other general-purpose or special-purpose computing system environments or configurations. Well-known examples of terminal devices, computing systems, environments, and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, and servers include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments including any of the above systems, etc.

[0064] Electronic devices such as terminal devices, computer systems, and servers can be described in the general context of computer system executable instructions (such as program modules) executed by a computer system. Typically, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in distributed cloud computing environments, where tasks are executed by remote processing devices linked through communication networks. In distributed cloud computing environments, program modules can reside on local or remote computing system storage media, including storage devices.

[0065] Exemplary methods

[0066] Figure 1 This is a flowchart illustrating an exemplary embodiment of the present invention regarding a smart adaptation and connection method 100 for IoT power devices. This embodiment can be applied to electronic devices, such as… Figure 1 As shown, it includes the following steps:

[0067] Step 101: Obtain the voltage and current signals of the power equipment, determine the offset based on the voltage and current signals, and map the communication node ID sequentially based on the timestamp of the offset to identify the identification information, and determine the access identification data based on the identification information.

[0068] Preferably, the method involves determining the offset based on the voltage and current signals, mapping the communication node IDs sequentially based on the timestamps of the offsets to identify identification information, and determining access identification data based on the identification information, including:

[0069] The instantaneous signals of the voltage and current signals are read sequentially to determine the peak and average values ​​at each time point. The difference between the peak and average values ​​at each time point is calculated, and waveform verification data is determined based on the difference.

[0070] Based on the waveform verification data, the waveform phase of each sampling segment is compared and the phase offset is recorded. Based on the difference between the phase offset and the preset offset threshold, an offset comparison result is generated.

[0071] Based on the offset comparison results, the timestamp information of each record with phase offset is compared with the known communication node ID to determine the unique identification information, and the corresponding running sequence number is input based on the identification information to generate access identification data based on the running sequence number.

[0072] In an embodiment of the present invention, generating access identification data based on the access identification module includes: verifying the peak value and average value and determining the difference threshold based on the voltage sensor and current sensor signals; comparing the waveform phase of each sampling segment and recording the offset; mapping the communication node ID in sequence with the timestamp and identifying the identification information; recording the running sequence number and outputting the tag to generate access identification data.

[0073] The access identification module includes:

[0074] The waveform acquisition submodule reads the instantaneous signal sequentially through voltage and current sensors and extracts the peak and average values. It then compares the difference between the peak and average values ​​and verifies whether the signal exceeds the set range, generating waveform verification data.

[0075] The difference determination submodule compares the waveform phase of each sampling segment based on the waveform verification data and records the phase offset. By comparing the phase offset with the reference benchmark, it monitors the difference and generates the offset comparison result.

[0076] The identification output submodule maps timestamps to communication node IDs based on offset comparison results and filters unique identification information. It generates access identification data by recording the corresponding running sequence number and outputting the label.

[0077] Specifically, in an embodiment of the present invention, based on previously installed and calibrated voltage and current sensors, instantaneous signals of the target power equipment are read at a frequency of 10 times per second. The peak and average values ​​at each moment are sequentially acquired and stored in the acquisition record. The difference is calculated using the defined formula Δ. i =V peak,i -V avg,i V peak,i V represents the peak value at the i-th sampling. avg,i This represents the average value from the same sampling, followed by Δ. iThe difference threshold Γ1 was compared with that obtained statistically from multiple historical measurement experiences. The specific method for setting Γ1 involves continuously monitoring the equipment for 48 hours initially and recording all difference samples. Then, the average value of these difference samples is calculated, and a safety factor α1 is set based on the fluctuation range. For example, if If Δ is 0.3 and α1 is 1.2, then Γ1 is approximately 0.36. i When the value exceeds Γ1, the sampled value is marked as an out-of-tolerance record. The values ​​are then compared and analyzed one by one with the constraints of the voltage range of 0V to 24V and the current range of 0A to 5A. During the comparison, the peak value and the average value of each record are compared item by item. The record is then marked with a serial number and a timestamp. Finally, the waveform verification data is generated after the data is summarized.

[0078] Based on the waveform verification data obtained above, all sampling records are segmented into minutes according to a fixed time window, and phase information is calculated based on the relationship between the peak and average values ​​of the waveform within each segment, using a phase estimation formula. The phase value of each segment is obtained in the following way, where V i and I i Let φ represent the characteristic quantities of the corresponding voltage and current within the segment, respectively. Then, the stable distribution of the phase in each segment is statistically analyzed, and the average phase value of each segment is denoted as φ. mean,i And this is compared with the reference φ ref For comparison, a reference benchmark can be set by continuously recording data for two hours under normal operating conditions and calculating the average phase. Assuming this benchmark is 0.8 radians, when a certain segment of φ occurs... mean,i When the deviation from 0.8 radians exceeds a pre-defined threshold Γ2, a phase anomaly is recorded for that segment. Here, Γ2 is determined based on the distribution standard deviation obtained from previous phase shift monitoring results. For example, if the observed average phase standard deviation is 0.05 radians, Γ2 can be set to 3 × 0.05 = 0.15 radians. If |φ mean,i If -0.8|>0.15, the segment's marking deviation is relatively large. Finally, the abnormal situations and offset details of each segment are summarized to generate the corresponding offset comparison results.

[0079] Based on the offset comparison results obtained above, the timestamp information of each record with phase offset is compared one by one with the known list of communication node IDs. The power equipment type to which the target ID belongs is determined by reading the pre-maintained device-to-communication node ID mapping table. Then, the type information is bound to the timestamp. In the early stage of system deployment, a static scan of all communication nodes can be performed to obtain the mapping list of node IDs and device names. A unique identifier code is attached to each node ID through empirical configuration. Subsequently, if a node ID with a matching timestamp is found to be completely consistent with the mapping list, a confirmation mark is written in the record. If multiple node IDs conflict at the same time, a secondary judgment is required based on the device operation sequence to eliminate unreasonable conflicts. For example, if the interval between two measurements does not exceed 3 seconds, the conclusion of the previous record is referred to, and the real-time fluctuation of the current range of 0A to 5A and the voltage range of 0V to 24V is combined to eliminate nodes that may be false alarms. Finally, the filtered unique identifier information is output in the form of a serial number and synchronously written into the unified node identification summary information. After the summary is completed, the corresponding access identification data is obtained.

[0080] Step 102: Determine node attributes based on the access identification data, construct a mapping index based on the node attributes, generate mapping comparison information, and generate protocol mapping parameters based on the mapping comparison information.

[0081] Preferably, the process includes determining node attributes based on the access identification data, constructing a mapping index based on the node attributes, generating mapping reference information, and generating protocol mapping parameters based on the mapping reference information, including:

[0082] The access identification data is parsed to determine the node identifier, and the corresponding attribute list is queried based on the node identifier. The node is then categorized by locating the node ID and port information to generate node attribute records.

[0083] Based on the node attribute records, read the instruction code and query the execution cycle. Construct a mapping index by pairing the receiving order and the sending time period to generate mapping comparison information.

[0084] Based on the mapping information, each waveform feature is matched and the corresponding table entries are retrieved. By recording the matching electricity meter port index, protocol mapping parameters are generated.

[0085] In an embodiment of the present invention, generating protocol mapping parameters based on the protocol conversion module includes: based on the access identification data, parsing communication node classification information, retrieving node ID and communication port attributes, operation instruction format, reading instruction code and execution cycle, associating receiving order and sending interval when timing is marked, merging waveform feature comparison mapping table, recording energy meter port index, and generating protocol mapping parameters.

[0086] The protocol conversion module includes:

[0087] The node parsing submodule decomposes node identifiers based on access identification data and queries the corresponding attribute list. It categorizes nodes by locating node IDs and port information and generates node attribute records.

[0088] The instruction mapping submodule reads instruction codes and queries execution cycles based on node attribute records, and builds a mapping index by pairing the receiving order with the sending time period to generate mapping comparison information;

[0089] The port recording submodule, based on the mapping information, corresponds to each waveform feature and retrieves the lookup table entries. By recording the matching energy meter port index, it generates protocol mapping parameters.

[0090] Specifically, in the embodiments of the present invention, based on the previously obtained access identification data, the unique identification information and power equipment type contained therein are read, and an attribute list is defined internally to store fields such as node ID, port tag, and equipment category. Then, each node ID is parsed one by one, mapping the node ID to the power equipment type first, and then matching it with the previously recorded port information. The obtained port information and node ID are associated under the same entry. Whenever a node ID is found to be mismatched with an existing port tag, a new entry is created for that node ID, and validity is verified according to a preset range of ports. For example, assuming the common port range is 1 to 10, if the resolved port number is 11, it is considered an out-of-limit port and marked as abnormal. For ports within the range, detailed items such as communication mode, maximum supported bandwidth, and configuration parameters are added to the attribute list. These detailed items can be derived from experience or refer to the numerical descriptions given in the general power equipment manual. For example, the communication mode can be fixed as full-duplex or half-duplex, and the bandwidth setting can be registered according to the maximum value of 100Mbps. If there is a custom bandwidth requirement, the configuration personnel will provide the specific value. Finally, after completing the matching of all node IDs and ports, a unified node attribute record is formed.

[0091] Based on the node attribute records obtained above, the possible instruction sets for each node are first determined by retrieving the device classification field. For example, some power distribution terminals contain start instructions, stop instructions, and data reporting instructions. After retrieving the instruction code, the corresponding execution cycle is read. The execution cycle can be set according to the equipment requirements. For example, an interval of 2 to 3 seconds can be set for start instructions, and an interval of 10 to 15 seconds can be set for data reporting instructions. These cycle data are generally derived from recommended values ​​provided by equipment manufacturers or obtained through actual testing. Then, during the pairing process, it is necessary to determine the order of each instruction during the receiving and sending periods. This can be done using a simple time series matching method, for example, defining t...send,j Let t be the time when the j-th instruction is sent. recv,j The time of receiving this instruction is determined by comparing t. send,j With t recv,j The difference determines the timing sequence. If the difference is greater than a pre-set maximum delay Γ3, the instruction can be regarded as a timeout instruction and recorded. The maximum delay can be specified by the staff according to the system operation requirements. For example, if the average delay is found to be 1 second and the fluctuation range is small during the test, Γ3 = 3 seconds can be selected as the threshold. By integrating the results of these sending and receiving order matching into the mapping index, the node ID, instruction code and execution cycle can be combined to generate the corresponding mapping information.

[0092] Based on the mapping information obtained above, the instruction mapping to which each node ID belongs is retrieved and compared one by one with the previously acquired waveform features. In this process, it is necessary to first find the port number associated with the node ID from the existing lookup table entries and verify the current and voltage amplitudes corresponding to the waveform features to determine whether the port is a high-load port or a normal-load port. For example, if the current amplitude is usually maintained in the range of 4A to 5A and the voltage is approximately between 22V and 24V, it can be initially determined to be a high-load port. Otherwise, if the current amplitude is mostly in the range of 2A to 3A or lower, it is considered a normal-load port. Simultaneously, a superimposed reference value Γ4 can be set to identify abnormal situations. The determination of Γ4 can be based on statistical calculations of long-term port operating data, for example, selecting the average value of the port current peak as... Then select a magnification factor α4 to obtain In the example, if If Γ4 is 2.5A and α4 is 1.5, then Γ4 is approximately 3.75A. If a recorded current peak is higher than 3.75A and the voltage is lower than 20V, it may indicate an abnormality in the port waveform. Based on these matching comparison information and abnormality detection markers, the final confirmed energy meter port index can be extracted. This index, along with the node ID and command mapping system, can be combined to obtain the protocol mapping parameters.

[0093] Step 103: Determine the available instruction data based on the protocol mapping parameters, determine the port monitoring results based on the available instruction data, and perform power aggregation based on the port monitoring results to determine the load distribution indicators.

[0094] Preferably, the method involves determining available instruction data based on the protocol mapping parameters, determining port monitoring results based on the available instruction data, and performing power aggregation based on the port monitoring results to determine load distribution metrics, including:

[0095] Based on the protocol mapping parameters, the instruction code is read and the port is verified to be available. The current instruction type is collected and summarized to determine the available instruction data.

[0096] Based on the available data from the instructions, the peak and fluctuating periods of the device current are determined, and the port monitoring results are determined by comparing the recorded timestamps with the port usage.

[0097] Based on the port monitoring results, preset power thresholds are combined and priorities are marked. A scheduling list is formed by pairing node identifiers and action numbers to determine load allocation indicators.

[0098] In an embodiment of the present invention, generating load allocation indicators based on the load optimization module includes: extracting instruction codes when retrieving operation command types based on the protocol mapping parameters, reading port availability when the communication port status is available, tracking device current fluctuations and recording timestamps when monitoring load data, matching scheduling priorities and merging power threshold summary node identifiers, recording action sequence numbers, and generating load allocation indicators.

[0099] The load optimization module includes:

[0100] The command retrieval submodule reads the command code based on the protocol mapping parameters and verifies whether the port is available. It also collects and summarizes the current command types to generate command availability data.

[0101] The port status submodule focuses on the peak and fluctuation periods of device current based on the available data of the command. It generates port monitoring results by recording timestamps and comparing port usage.

[0102] The power aggregation submodule merges preset power thresholds and marks priorities based on port monitoring results, forms a scheduling list by pairing node identifiers and action sequence numbers, and generates load allocation indicators.

[0103] Specifically, in the embodiments of the present invention, the marked instruction codes are read based on the previously obtained protocol mapping parameters and checked whether they match the operation type registered by the current device. After extracting all instruction codes one by one, they are compared and analyzed with the port usage data collected in advance. Whether a port is available can generally be assessed by referring to the current load ratio and combining it with the port working time. Specifically, the usage ratio can be calculated when reading the port monitoring records. And compare it with the preset benchmark Θ1. Here, Θ1 can be obtained by multiplying the average percentage of the working time of each port of the device in the past week by a safety factor. For example, if the average percentage obtained by statistics is 0.65 and the safety factor is 1.2, then Θ1 = 0.78. When Ω uIf the value is greater than 0.78, the port is determined to be under high load and unavailable; otherwise, the port is determined to be available. After the above verification is completed, the category information corresponding to the batch of instructions is collected, such as high-frequency detection instructions or ordinary maintenance instructions, and these instruction types are classified into several groups. The port availability status is then cross-mapped, and finally the instruction availability data is obtained.

[0104] Based on the previously obtained instructions, we can focus on the peak and fluctuating periods of the device current. Combining this with the established port usage records, we continue to track the actual current magnitude and corresponding timestamps of each port at each moment. We set a reference range, comparing the current between 0A and 5A as a reasonable operating range. When the peak current exceeds 5A, it is considered an overload point. Based on the timestamp information, we calculate the duration of continuous overload. If the duration exceeds the pre-calculated maximum withstand time Δt, [further action is taken]. max Then mark the port as high load and record it as occupied, where Δt max The value can be determined through aging tests or power consumption assessments of the equipment under different load conditions. For example, if the manufacturer-recommended test shows that the port can operate continuously for 100 seconds under a 5A load without failure, then Δt can be taken as the value. max =100 seconds, conversely, if the current remains below 5A and the duration of intermittent peaks is less than Δt max If the port is marked as idle or available and can continue to work, all port statuses are recorded in the same monitoring list, and the final port monitoring results are obtained.

[0105] Based on the port monitoring results obtained above, a preset power threshold is merged and priorities are marked. During implementation, the current power consumption of each port can be collected first, and the power can be categorized according to P... i =V i ×I i Calculated in the manner of V i and I i Let be the voltage and current of the port during the i-th monitoring, respectively. Then, the power values ​​of all ports are summarized and compared with a pre-set power threshold Γ. p For comparison, this threshold can be set based on the maximum power recommendation given in the manufacturer's equipment manual or by multiplying the maximum safe power measured in actual testing by a safety factor. For example, if the maximum safe power of the equipment is 100W and the safety factor is 1.1, then Γ p =110W. When the instantaneous power of a port exceeds 110W, it is marked as a high-risk port and given priority in being assigned corresponding scheduling measures. Conversely, if the power is below 110W, it is considered a normal or low-priority port, and can be prioritized in the list. pThe ports with the highest power consumption are ranked first and marked with a priority value of 1. Ports with power consumption between 60W and 110W are marked with a priority value of 2, and ports with power consumption below 60W are marked with a priority value of 3. Finally, a scheduling list is formed in the process of pairing node identification and action sequence number to obtain the load distribution index.

[0106] Step 104: Obtain the current amplitude based on the load distribution index, determine the parameter comparison information based on the current amplitude, obtain the operating temperature based on the parameter comparison information, generate temperature composite data, and perform dynamic verification based on the temperature composite data to determine the energy efficiency dynamic parameters, so as to perform the matching and connection of power equipment based on the energy efficiency dynamic parameters.

[0107] Preferably, the method involves obtaining the current amplitude based on the load allocation index, determining parameter comparison information based on the current amplitude, obtaining the operating temperature based on the parameter comparison information, generating composite temperature data, and performing dynamic verification based on the composite temperature data to determine dynamic energy efficiency parameters, and then performing power equipment adaptation and connection based on the dynamic energy efficiency parameters, including:

[0108] Based on the load distribution index, the current amplitude is read, the current peak value is obtained, and the current peak value is compared with the reference value to generate parameter comparison information;

[0109] Based on the parameter comparison information, the current operating temperature output by the corresponding temperature sensor is obtained, and interactive verification is performed based on the current operating temperature to generate composite temperature data.

[0110] Based on the temperature synthesis data, the power factor and power value are checked and matched with existing verification standards. Configuration information is updated by recording dynamic output to generate dynamic energy efficiency parameters, and power equipment is adapted and connected based on the dynamic energy efficiency parameters.

[0111] In an embodiment of the present invention, generating dynamic energy efficiency parameters based on the energy efficiency control module includes: when selecting the current amplitude based on the load allocation index, comparing the peak value and the threshold value, comparing the phase reference and the measured value, reading the temperature value when the temperature sensor outputs, integrating the operating temperature and comparing the power factor and power verification, recording the dynamic output quantity, and generating dynamic energy efficiency parameters.

[0112] The energy efficiency control module includes:

[0113] The parameter comparison submodule reads the current amplitude based on the load distribution index and compares the measured peak value with the reference value. It verifies the estimated offset by comparing the phase difference and generates parameter comparison information.

[0114] The temperature integration submodule acquires the temperature sensor output based on parameter comparison information and merges the current operating temperature. It performs interactive verification by recording temperature data and generates composite temperature data.

[0115] The dynamic verification submodule checks the power factor and power value based on temperature synthesis data and matches them with existing verification standards. It also updates configuration information by recording dynamic output quantities and generates dynamic energy efficiency parameters.

[0116] Specifically, in the embodiments of the present invention, based on the load distribution index obtained above, the current amplitude is read and the measured peak value is compared with the reference value. It is necessary to first summarize the maximum current of each port in the system at different times. Each record has a precise timestamp and port identifier. Then, the reference value Ψ is compared. i To determine whether a deviation has occurred, this Ψ i The value can be determined by multiplying the average peak current measured from the same type of port under continuous full load operation by a fluctuation coefficient. For example, if the average peak current is 4A and the fluctuation coefficient is 1.1, then Ψ i = 4.4A. If a newly detected peak value exceeds 4.4A, it is considered to have a significant deviation. This is then used in conjunction with the previously obtained load allocation indicators to trace its priority level. The phase difference can be verified based on φ. diff =|φ measured -φ base | To perform the calculation, here φ base It can be obtained through reference measurement at a specific port, if φ diff Exceeding the previously determined threshold Γ φ Then the phase shift is considered significant, Γ φ A maximum allowable range can be set after monitoring the average phase under no-load or stable load conditions. For example, if the normal phase is 0.7 radians and the allowable deviation is 0.1 radians, then Γ φ =0.1. After completing multiple comparisons of peak current and phase difference, these comparison results are recorded together with the load distribution index to finally generate parameter comparison information.

[0117] Based on the previously obtained parameter comparison information, the temperature sensor output is acquired and the current operating temperature is merged. At this stage, the real-time temperature of each monitoring point can be read from the previously configured temperature monitoring device. These temperature values ​​are then correlated with the corresponding parameter comparison information. The synchronization between temperature acquisition and current or phase detection is determined by comparing timestamps. If both are recorded within the same time window, they are considered matched information and merged into the same analysis record. To filter out invalid data, the temperature operating range can be defined as 0℃ to 90℃. If a recorded temperature is higher than 90℃ or lower than 0℃, it is considered an abnormal sensor reading or that the environment does not meet normal operating conditions, requiring further investigation of the sensor's location or status. For temperature data within the 0℃ to 90℃ range, it is compared with the load conditions corresponding to the parameter comparison information. If the load is in a high-priority state and the temperature value exceeds a pre-set temperature threshold, the data is considered a match.T The time will also be marked separately in the results, here Γ T The safety factor can be used to set the maximum allowable temperature listed in the equipment manual or the peak temperature obtained from field testing. For example, if the equipment manual recommends a maximum operating temperature of 85°C and a safety factor of 1.05, then Γ T =89.25℃, and finally, after completing these integrations and checks, the temperature composite data was obtained.

[0118] Based on the previously obtained temperature composite data, the power factor and power values ​​are checked and matched against existing verification standards. The active power P and apparent power S can be extracted from the real-time power record of the current port, and the power factor can be calculated. If the power factor (PF) deviates from the predefined normal operating range, it is marked as a deviation point during calibration. This normal range can be obtained from the equipment's factory inspection report or from years of operational data statistics. For example, some equipment has an average power factor that is stable between 0.8 and 0.9. If the monitored PF is lower than 0.75 or higher than 0.95, an out-of-limit situation will be recorded, and the corresponding power value also needs to be compared with the threshold Γ. pow For comparison, this threshold can be obtained by multiplying the historical extreme value of the device's actual output power by an empirical coefficient. For example, if the maximum output power of the device is observed to be 150W under test conditions and the empirical coefficient is set to 1.1, then Γ pow =165W. When a power value greater than 165W is detected, or the power factor falls below 0.75 or above 0.95, the ambient temperature will be checked against the previously obtained temperature composite data to see if it is between 0℃ and 90℃. If the temperature is within this range and other indicators are normal, it will be kept under close monitoring. If the temperature also exceeds the limit, further investigation will be required and detailed records will be made in the calibration standard list. Finally, after completing the above verification process, the configuration information will be updated and dynamic energy efficiency parameters will be generated.

[0119] Preferably, the method further includes:

[0120] The load ID is determined based on the energy efficiency dynamic parameters, and a scheduling execution instruction is generated based on the load attributes corresponding to the load ID.

[0121] Based on the scheduling execution instruction, the power requirements of each node are read, and resources are allocated based on the power requirements of each node to generate a resource allocation list, so as to allocate resources based on the resource allocation list.

[0122] Preferably, the method involves determining the load ID based on the energy efficiency dynamic parameters and generating a scheduling execution instruction based on the load attributes corresponding to the load ID, including:

[0123] Based on the energy efficiency dynamic parameters, load IDs are screened and load attributes are obtained. Based on the load attributes, scheduling priorities are selected to generate type filtering results based on the scheduling priorities.

[0124] Based on the filtering results of the aforementioned types, the current port's idle or occupied status is analyzed and the available capacity is read. Idle periods are marked by comparison, and port detection information is generated.

[0125] Based on the port detection information, the motor speed feedback is monitored and compared with the reference range. By recording the switching sequence and the operation and maintenance code to identify the running node, a scheduling execution instruction is generated.

[0126] Preferably, based on the scheduling execution instruction, the power requirements of each node are read, and resources are allocated based on the power requirements of each node to generate a resource allocation list, including:

[0127] Based on the scheduling execution instructions, the power requirements of each node are checked and compared with the limit thresholds, and power comparison information is generated according to the status of nodes that meet or exceed the limit thresholds.

[0128] Based on the power comparison information, the communication frequency band number is verified and compared with the occupancy list. By screening for duplicate conflict markers, frequency band comparison results are generated.

[0129] Based on the frequency band comparison results, the voltage offset is checked and the correction data is recorded. Available ports are selected by retrieving the remaining capacity and the mapping is updated to generate a resource allocation list.

[0130] In embodiments of the present invention, a scheduling execution instruction can also be generated based on the multi-task scheduling module, including: based on the energy efficiency dynamic parameters, retrieving the load type, reading the load ID, determining whether the detection port is idle, listening to the motor speed feedback and comparing it with a preset speed range, matching the running segment and comparing the power supply capacity and counting the load maintenance code, recording the switching sequence, and generating the scheduling execution instruction.

[0131] The multi-task scheduling module includes:

[0132] The load type submodule screens load IDs and obtains load attributes based on dynamic energy efficiency parameters, selects scheduling priorities by comparing load codes, and generates type screening results.

[0133] The port detection submodule analyzes the current port's idle or occupied status based on the type filtering results and reads the available capacity. It then marks the idle periods by comparing them and generates port detection information.

[0134] The speed comparison submodule listens to the motor speed feedback based on port detection information and compares it with the reference range. It generates scheduling execution instructions by recording the switching sequence and the operation and maintenance code to identify the running node.

[0135] Specifically, in the embodiments of the present invention, based on the previously obtained dynamic energy efficiency parameters, the load ID is read and the load attributes are obtained. First, all registered load codes can be found in a pre-compiled load list, and the type label and operating power range of each load can be extracted. Then, the attribute data of each load is compared with the previously obtained dynamic energy efficiency parameters. If it is found that the operating power data of some loads is consistently in the high power range and the temperature record is close to the upper limit such as 90°C, these loads are marked as high priority or specific risk level in the attribute table. If the power of a load is consistently in the range of 20W to 60W and the temperature is below 70°C, it can be regarded as ordinary level, and an additional threshold Θ can also be defined. L To further refine the load level, for example, if the average power is 50W based on the equipment manual or field experience, and a factor of 1.5 is selected as the amplification reference value, then Θ L =50×1.5=75W. When the load power exceeds 75W, it is recorded as a high load and written as a high priority mark. Otherwise, it is recorded as normal or lower priority. Then, these load codes are compared and the scheduling priority required for each type of load in the known operating scenario is summarized. The load attributes are matched with the above priority and stored in a final record to generate the type filtering results.

[0136] Based on the previously obtained type filtering results, analyze the current port's idle or occupied status and read its available capacity. First, check the historical time sequence records of each port to see if the difference between the most recent release time and the time it was occupied again exceeds a certain threshold Δt. This Δt can be calculated by multiplying the average release time obtained from previous experimental tests by a certain correction coefficient. For example, if the average release time is 120 seconds after observing the device for a week and the correction coefficient is 1.2, then Δt = 144 seconds. If the actual idle time is greater than 144 seconds, the port is considered to be completely idle. If the idle time is shorter, it is marked as possibly in a standby occupied state. Then, when reading the available capacity, compare the current current amplitude of the port with the range of 0A to 5A and simultaneously refer to the voltage range of 0V to 24V. If the current is below 1A and the voltage is stable at around 12V, it can be judged to be in a low load segment. Otherwise, if the current is close to 5A or the voltage has reached 24V, it indicates that the remaining capacity of this port is not large, and corresponding annotations need to be made in the analysis results. After the idle comparison of all ports is finally completed, port detection information is generated.

[0137] Based on the port detection information obtained above, the motor speed feedback is monitored and compared with the reference range. First, the nominal speed and allowable speed range can be found in the motor's manufacturing data or user manual. For example, a rated speed of 3000 rpm is considered normal if it falls between 2700 rpm and 3300 rpm. If a sensor continuously detects a speed less than 2700 rpm or more than 3300 rpm within a certain time period, it is marked as an anomaly in the analysis. These anomalies are compared with the idle or occupied status recorded in the port detection information, and combined with the corresponding available capacity, it is determined whether the motor is undergoing load adjustment. If the motor speed fluctuates frequently and is accompanied by a high current load at the port, the impact of the load on the motor can be considered. To confirm the switching sequence, multiple timestamps can be continuously analyzed and adjacent speed changes recorded. For example, Δn = |n i+1 -n i |To determine speed jumps, if Δn is consistently greater than 100 rpm and the corresponding time difference is less than 10 seconds, it indicates a high-frequency switch. In this case, an operation and maintenance code needs to be added to the record to identify the running node and stored in categories, and a scheduling execution instruction needs to be generated.

[0138] In embodiments of the present invention, a resource allocation list can also be generated based on the resource allocation module, including: based on the scheduling execution instruction, reading the power requirements of each node, extracting the requirement value and comparing it with the threshold, reading the communication frequency band number, detecting whether there is a conflict, correcting the voltage offset, comparing the offset with the reference value and recording the correction amount, filtering available ports and comparing the remaining capacity, updating the control mapping and recording the allocation index, and generating a resource allocation list.

[0139] The resource allocation module includes:

[0140] The power reading submodule checks the power demand of each node based on the scheduling execution instructions and compares it with the limit threshold. It generates power comparison information by recording the status of nodes that meet or exceed the range.

[0141] The frequency band calibration submodule verifies the communication frequency band number based on power comparison information and compares it with the occupancy list. It also generates frequency band calibration results by screening for conflicting and duplicate nodes.

[0142] The capacity screening submodule checks the voltage offset based on the frequency band comparison results and records the correction data. It selects available ports by retrieving the remaining capacity and updates the mapping to generate a resource allocation list.

[0143] Specifically, in the embodiments of the present invention, based on the previously obtained scheduling execution instructions, the power demand of each node is checked and compared with the limit threshold. First, the power demand data of different nodes are integrated into a power list. Each node has a time-series corresponding power demand value. For example, a node's demand can reach 120W during peak periods and can be maintained below 60W during normal periods. Then, these demands are compared with the limit threshold Γ. P In comparison, this Γ P It can be determined based on the equipment's operating limits or safety design values. For example, if the equipment's rated maximum power is 200W and a certain safety margin is taken into account, then Γ P =180W. If a node's demand exceeds 180W, it is considered to be in a high-load state; otherwise, it is considered to be in a normal or low-load state. After comparison, nodes that meet the 180W requirement are recorded in one list, while nodes that exceed 180W are placed in another list. Each record will have a specific timestamp and status field for further analysis and filtering to generate power comparison information.

[0144] Based on the power comparison information obtained earlier, verifying the communication frequency band number and comparing it with the occupancy list requires first finding the communication number corresponding to the current node in the maintained frequency band allocation table. If this number does not appear in the occupancy list, it means there is no conflict at the moment; otherwise, if multiple nodes have the same frequency band identifier and the timestamp overlap rate exceeds a certain proportion, it is considered a conflict state. The overlap rate here can be used as... Calculate, where T overlap T represents the length of the conflict period. window To determine the length of the statistical time window, if ρ exceeds a certain baseline value Θ... f This is considered a conflict, and this Θ f It can be determined based on network communication requirements. For example, if it is considered that if the conflict time exceeds 30% within the statistical time window, it will be difficult to maintain normal data exchange, then Θ f =0.3. After a conflict is detected, duplicate nodes will be marked and subsequent processes will be executed to generate frequency band comparison results.

[0145] Based on the frequency band comparison results obtained above, the voltage offset is checked and the correction data is recorded. First, the real-time voltage readings of all conflicting or duplicate nodes are collected and compared with the previously set reference voltage range of 0V to 24V to check for any excessive offset. If the voltage is higher than 24V or lower than 0V, it is determined that the data of that node may have sensor error or line abnormality. At the same time, a correction rule is defined, such as ΔV = V current -V baseIf the absolute value of ΔV is greater than 1V and the duration exceeds 10 seconds, it is considered an abnormal offset and a correction mark is added to the record. When searching for remaining capacity, the current range of each port from 0A to 5A can be used to determine whether it can still support the access of new nodes. For example, if the port is actually operating at around 3A, the remaining 2A capacity can meet the needs of some low- and medium-power nodes. Otherwise, if the port is close to 5A, the allocation must be temporarily suspended. After comparing the available capacity of all ports, a suitable port is found for each node and updated to generate a resource allocation list.

[0146] In the IoT power equipment intelligent adaptation and connection method provided in this embodiment of the invention, the access identification of power equipment is based on voltage and current sensor signals. Peak and average values ​​are checked and the difference threshold is determined. The phase of each sampling segment waveform is compared and the offset is recorded. The communication node ID is mapped sequentially using timestamps to ensure accurate extraction of communication node identification information and avoid misidentification. Communication protocol conversion and parsing of communication node classification information, retrieval of node IDs and communication port attributes, and reading of instruction codes and execution cycles enable automatic multi-protocol mapping, eliminating protocol conflicts between different devices and improving device compatibility. Load optimization dynamically monitors communication port status, device current fluctuations, and timestamp information, and combines power threshold matching with scheduling priorities to ensure reasonable load allocation and reduce power redundancy. Energy efficiency control selects current amplitude, phase reference, and temperature sensor output data, and compares them with power factor and power verification to form real-time power adjustment, reducing energy waste. Task scheduling combines load type, port status, and motor speed feedback to match operating time and power capacity, enabling dynamic task adjustment and avoiding power waste and equipment overload caused by high load operation. Resource allocation involves reading power demand, detecting communication frequency band conflicts, correcting voltage offsets, filtering available ports, and comparing remaining capacity to achieve precise allocation and improve equipment resource utilization efficiency. This processing logic enables power equipment to dynamically adapt to its operating status, improving grid adaptability and optimizing power distribution.

[0147] Exemplary device

[0148] Figure 2 This is a schematic diagram of the structure of an IoT power equipment intelligent adaptation and connection system 200 provided in an exemplary embodiment of the present invention. Figure 2 As shown, this embodiment includes: an access identification module 201, a protocol conversion module 202, a load optimization module 203, and an energy efficiency control module 204.

[0149] Preferably, the access identification module 201 is used to acquire the voltage signal and current signal of the power equipment, determine the offset based on the voltage signal and current signal, and map the communication node ID sequentially based on the timestamp of the offset to identify identification information, and determine access identification data based on the identification information.

[0150] Preferably, the access identification module 201 determines the offset based on the voltage signal and the current signal, maps the communication node ID sequentially based on the timestamp of the offset to identify identification information, and determines access identification data based on the identification information, including:

[0151] The instantaneous signals of the voltage and current signals are read sequentially to determine the peak and average values ​​at each time point. The difference between the peak and average values ​​at each time point is calculated, and waveform verification data is determined based on the difference.

[0152] Based on the waveform verification data, the waveform phase of each sampling segment is compared and the phase offset is recorded. Based on the difference between the phase offset and the preset offset threshold, an offset comparison result is generated.

[0153] Based on the offset comparison results, the timestamp information of each record with phase offset is compared with the known communication node ID to determine the unique identification information, and the corresponding running sequence number is input based on the identification information to generate access identification data based on the running sequence number.

[0154] Preferably, the protocol conversion module 202 is used to determine node attributes based on the access identification data, construct a mapping index based on the node attributes, generate mapping comparison information, and generate protocol mapping parameters based on the mapping comparison information.

[0155] Preferably, the protocol conversion module 202 determines node attributes based on the access identification data, constructs a mapping index based on the node attributes, generates mapping comparison information, and generates protocol mapping parameters based on the mapping comparison information, including:

[0156] The access identification data is parsed to determine the node identifier, and the corresponding attribute list is queried based on the node identifier. The node is then categorized by locating the node ID and port information to generate node attribute records.

[0157] Based on the node attribute records, read the instruction code and query the execution cycle. Construct a mapping index by pairing the receiving order and the sending time period to generate mapping comparison information.

[0158] Based on the mapping information, each waveform feature is matched and the corresponding table entries are retrieved. By recording the matching electricity meter port index, protocol mapping parameters are generated.

[0159] Preferably, the load optimization module 203 is used to determine the available instruction data based on the protocol mapping parameters, determine the port monitoring results based on the available instruction data, and perform power aggregation based on the port monitoring results to determine the load allocation index.

[0160] Preferably, the load optimization module 203 determines available command data based on the protocol mapping parameters, determines port monitoring results based on the available command data, and performs power aggregation based on the port monitoring results to determine load allocation indicators, including:

[0161] Based on the protocol mapping parameters, the instruction code is read and the port is verified to be available. The current instruction type is collected and summarized to determine the available instruction data.

[0162] Based on the available data from the instructions, the peak and fluctuating periods of the device current are determined, and the port monitoring results are determined by comparing the recorded timestamps with the port usage.

[0163] Based on the port monitoring results, preset power thresholds are combined and priorities are marked. A scheduling list is formed by pairing node identifiers and action numbers to determine load allocation indicators.

[0164] Preferably, the energy efficiency control module 204 is used to obtain the current amplitude based on the load distribution index, determine parameter comparison information based on the current amplitude, obtain the operating temperature based on the parameter comparison information, generate temperature composite data, and perform dynamic verification based on the temperature composite data to determine energy efficiency dynamic parameters, so as to perform power equipment adaptation connection based on the energy efficiency dynamic parameters.

[0165] Preferably, the energy efficiency control module 204 obtains the current amplitude based on the load allocation index, determines parameter comparison information based on the current amplitude, obtains the operating temperature based on the parameter comparison information, generates composite temperature data, and performs dynamic verification based on the composite temperature data to determine dynamic energy efficiency parameters, so as to perform adaptive connection of power equipment based on the dynamic energy efficiency parameters, including:

[0166] Based on the load distribution index, the current amplitude is read, the current peak value is obtained, and the current peak value is compared with the reference value to generate parameter comparison information;

[0167] Based on the parameter comparison information, the current operating temperature output by the corresponding temperature sensor is obtained, and interactive verification is performed based on the current operating temperature to generate composite temperature data.

[0168] Based on the temperature synthesis data, the power factor and power value are checked and matched with existing verification standards. Configuration information is updated by recording dynamic output to generate dynamic energy efficiency parameters, and power equipment is adapted and connected based on the dynamic energy efficiency parameters.

[0169] Preferably, the system further includes:

[0170] The multi-task scheduling module is used to determine the load ID based on the energy efficiency dynamic parameters, and generate scheduling execution instructions based on the load attributes corresponding to the load ID;

[0171] The resource allocation module is used to read the power requirements of each node based on the scheduling execution instruction, allocate resources based on the power requirements of each node, generate a resource allocation list, and then allocate resources based on the resource allocation list.

[0172] Preferably, the multi-task scheduling module determines the load ID based on the energy efficiency dynamic parameters, and generates a scheduling execution instruction based on the load attribute corresponding to the load ID, including:

[0173] Based on the energy efficiency dynamic parameters, load IDs are screened and load attributes are obtained. Based on the load attributes, scheduling priorities are selected to generate type filtering results based on the scheduling priorities.

[0174] Based on the filtering results of the aforementioned types, the current port's idle or occupied status is analyzed and the available capacity is read. Idle periods are marked by comparison, and port detection information is generated.

[0175] Based on the port detection information, the motor speed feedback is monitored and compared with the reference range. By recording the switching sequence and the operation and maintenance code to identify the running node, a scheduling execution instruction is generated.

[0176] Preferably, the resource allocation module, based on the scheduling execution instruction, reads the power requirements of each node, and allocates resources based on the power requirements of each node to generate a resource allocation list, including:

[0177] Based on the scheduling execution instructions, the power requirements of each node are checked and compared with the limit thresholds, and power comparison information is generated according to the status of nodes that meet or exceed the limit thresholds.

[0178] Based on the power comparison information, the communication frequency band number is verified and compared with the occupancy list. By screening for duplicate conflict markers, frequency band comparison results are generated.

[0179] Based on the frequency band comparison results, the voltage offset is checked and the correction data is recorded. Available ports are selected by retrieving the remaining capacity and the mapping is updated to generate a resource allocation list.

[0180] The IoT power equipment smart adapter connection system 200 of this invention corresponds to the IoT power equipment smart adapter connection method 100 of another embodiment of this invention, and will not be described again here.

[0181] Exemplary electronic devices

[0182] Figure 3This is the structure of an electronic device provided in an exemplary embodiment of the present invention. The electronic device may be either or both of a first device and a second device, or a standalone device independent of them, which may communicate with the first device and the second device to receive acquired input signals from them. Figure 3 A block diagram of an electronic device according to an embodiment of the present disclosure is shown. Figure 3 As shown, the electronic device 300 includes one or more processors 301 and memory 302.

[0183] The processor 301 may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0184] The memory 302 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 301 may execute the program instructions to implement the methods of the software programs of the various embodiments of this disclosure described above, and / or other desired functions. In one example, the electronic device may further include an input device 303 and an output device 304, these components being interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0185] In addition, the input device 303 may also include, for example, a keyboard, a mouse, etc.

[0186] The output device 304 can output various information to the outside. The output device 304 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0187] Of course, for the sake of simplicity, Figure 3 Only some of the components of the electronic device relevant to this disclosure are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device may include any other suitable components depending on the specific application.

[0188] Exemplary computer program products and computer-readable storage media

[0189] In addition to the methods and apparatus described above, embodiments of this disclosure may also be computer program products comprising computer program instructions that, when executed by a processor, cause the processor to perform the steps of the methods according to various embodiments of this disclosure as described in the "Exemplary Methods" section above.

[0190] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this disclosure. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on a user's computing device, partially on a user's computing device, as a standalone software package, partially on a user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0191] Furthermore, embodiments of this disclosure may also be computer-readable storage media having computer program instructions stored thereon, which, when executed by a processor, cause the processor to perform the steps in the methods according to various embodiments of this disclosure described in the "Exemplary Methods" section above.

[0192] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0193] The basic principles of this disclosure have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this disclosure are merely examples and not limitations, and should not be considered as essential features of each embodiment of this disclosure. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the scope of this disclosure to the necessity of employing the specific details described above.

[0194] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0195] The block diagrams of devices, apparatuses, devices, and systems disclosed herein are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0196] The methods and apparatus of this disclosure may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of this disclosure are not limited to the order specifically described above unless otherwise specifically stated. Furthermore, in some embodiments, this disclosure may also be implemented as a program recorded on a recording medium, the program including machine-readable instructions for implementing the methods according to this disclosure. Thus, this disclosure also covers recording media storing programs for performing the methods according to this disclosure.

[0197] It should also be noted that in the apparatus, devices, and methods of this disclosure, the components or steps are decomposable and / or recombinable. Such decomposition and / or recombination should be considered equivalent to the present disclosure. The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of this disclosure. Therefore, this disclosure is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0198] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this disclosure to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations therein.

Claims

1. A method for intelligent adaptation and connection of Internet of Things (IoT) power equipment, characterized in that, The method includes: The voltage and current signals of the power equipment are acquired, the offset is determined based on the voltage and current signals, and the communication node ID is sequentially mapped based on the timestamp of the offset to identify identification information, and access identification data is determined based on the identification information. Node attributes are determined based on the access identification data, a mapping index is constructed based on the node attributes, mapping comparison information is generated, and protocol mapping parameters are generated based on the mapping comparison information. Based on the protocol mapping parameters, determine the available instruction data, determine the port monitoring results based on the available instruction data, and perform power aggregation based on the port monitoring results to determine the load distribution indicators; The current amplitude is obtained based on the load distribution index, parameter comparison information is determined based on the current amplitude, the operating temperature is obtained based on the parameter comparison information, temperature composite data is generated, and dynamic verification is performed based on the temperature composite data to determine the energy efficiency dynamic parameters, so as to adapt and connect the power equipment based on the energy efficiency dynamic parameters.

2. The method according to claim 1, characterized in that, The step of determining the offset based on the voltage and current signals, mapping the communication node ID sequentially based on the timestamp of the offset to identify identification information, and determining access identification data based on the identification information includes: The instantaneous signals of the voltage and current signals are read sequentially to determine the peak and average values ​​at each time point. The difference between the peak and average values ​​at each time point is calculated, and waveform verification data is determined based on the difference. Based on the waveform verification data, the waveform phase of each sampling segment is compared and the phase offset is recorded. Based on the difference between the phase offset and the preset offset threshold, an offset comparison result is generated. Based on the offset comparison results, the timestamp information of each record with phase offset is compared with the known communication node ID to determine the unique identification information, and the corresponding running sequence number is input based on the identification information to generate access identification data based on the running sequence number.

3. The method according to claim 1, characterized in that, Based on the access identification data, node attributes are determined; based on the node attributes, a mapping index is constructed; mapping reference information is generated; and based on the mapping reference information, protocol mapping parameters are generated, including: The access identification data is parsed to determine the node identifier, and the corresponding attribute list is queried based on the node identifier. The node is then categorized by locating the node ID and port information to generate node attribute records. Based on the node attribute records, read the instruction code and query the execution cycle. Construct a mapping index by pairing the receiving order and the sending time period to generate mapping comparison information. Based on the mapping information, each waveform feature is matched and the corresponding table entries are retrieved. By recording the matching electricity meter port index, protocol mapping parameters are generated.

4. The method according to claim 1, characterized in that, Based on the protocol mapping parameters, available command data is determined; based on the available command data, port monitoring results are determined; and based on the port monitoring results, power aggregation is performed to determine load distribution metrics, including: Based on the protocol mapping parameters, the instruction code is read and the port is verified to be available. The current instruction type is collected and summarized to determine the available instruction data. Based on the available data from the instructions, the peak and fluctuating periods of the device current are determined, and the port monitoring results are determined by comparing the recorded timestamps with the port usage. Based on the port monitoring results, preset power thresholds are combined and priorities are marked. A scheduling list is formed by pairing node identifiers and action numbers to determine load allocation indicators.

5. The method according to claim 1, characterized in that, The current amplitude is obtained based on the load allocation index, parameter comparison information is determined based on the current amplitude, the operating temperature is obtained based on the parameter comparison information, composite temperature data is generated, and dynamic verification is performed based on the composite temperature data to determine dynamic energy efficiency parameters. The power equipment is then adapted and connected based on these dynamic energy efficiency parameters, including: Based on the load distribution index, the current amplitude is read, the current peak value is obtained, and the current peak value is compared with the reference value to generate parameter comparison information; Based on the parameter comparison information, the current operating temperature output by the corresponding temperature sensor is obtained, and interactive verification is performed based on the current operating temperature to generate composite temperature data. Based on the temperature synthesis data, the power factor and power value are checked and matched with existing verification standards. Configuration information is updated by recording dynamic output to generate dynamic energy efficiency parameters, and power equipment is adapted and connected based on the dynamic energy efficiency parameters.

6. The method according to claim 1, characterized in that, The method further includes: The load ID is determined based on the energy efficiency dynamic parameters, and a scheduling execution instruction is generated based on the load attributes corresponding to the load ID. Based on the scheduling execution instruction, the power requirements of each node are read, and resources are allocated based on the power requirements of each node to generate a resource allocation list, so as to allocate resources based on the resource allocation list.

7. The method according to claim 6, characterized in that, The step of determining the load ID based on the energy efficiency dynamic parameters and generating a scheduling execution instruction based on the load attributes corresponding to the load ID includes: Based on the energy efficiency dynamic parameters, load IDs are screened and load attributes are obtained. Based on the load attributes, scheduling priorities are selected to generate type filtering results based on the scheduling priorities. Based on the filtering results of the aforementioned types, the current port's idle or occupied status is analyzed and the available capacity is read. Idle periods are marked by comparison, and port detection information is generated. Based on the port detection information, the motor speed feedback is monitored and compared with the reference range. By recording the switching sequence and the operation and maintenance code to identify the running node, a scheduling execution instruction is generated.

8. The method according to claim 6, characterized in that, The process of reading the power requirements of each node based on the scheduling execution instruction, allocating resources based on the power requirements of each node, and generating a resource allocation list includes: Based on the scheduling execution instructions, the power requirements of each node are checked and compared with the limit thresholds, and power comparison information is generated according to the status of nodes that meet or exceed the limit thresholds. Based on the power comparison information, the communication frequency band number is verified and compared with the occupancy list. By screening for duplicate conflict markers, frequency band comparison results are generated. Based on the frequency band comparison results, the voltage offset is checked and the correction data is recorded. Available ports are selected by retrieving the remaining capacity and the mapping is updated to generate a resource allocation list.

9. An intelligent adaptation and connection system for Internet of Things (IoT) power equipment, characterized in that, The system includes: The access identification module is used to acquire voltage and current signals of power equipment, determine offset based on the voltage and current signals, and map communication node IDs sequentially based on the timestamp of the offset to identify identification information, and determine access identification data based on the identification information. The protocol conversion module is used to determine node attributes based on the access identification data, construct a mapping index based on the node attributes, generate mapping comparison information, and generate protocol mapping parameters based on the mapping comparison information. The load optimization module is used to determine the available data of instructions based on the protocol mapping parameters, determine the port monitoring results based on the available data of instructions, and perform power aggregation based on the port monitoring results to determine the load allocation indicators. The energy efficiency control module is used to obtain the current amplitude based on the load distribution index, determine the parameter comparison information based on the current amplitude, obtain the operating temperature based on the parameter comparison information, generate temperature composite data, and perform dynamic verification based on the temperature composite data to determine the energy efficiency dynamic parameters, so as to perform the matching connection of power equipment based on the energy efficiency dynamic parameters.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the method as described in any one of claims 1-8.

11. An electronic device, characterized in that, include: The computer-readable storage medium as described in claim 10; as well as One or more processors for executing a program in the computer-readable storage medium.

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