A method and system for accessing wireless nodes in power transmission and transformation equipment via the Internet of Things

Abstract

This invention discloses a method and system for wireless node access in the Internet of Things (IoT) for power transmission and transformation equipment. The wireless node access method includes the following steps: deploying sensing units at the wireless nodes of the power transmission and transformation equipment to perceive the equipment status; the sensing units transmit sensing parameter information to a central processing unit for node classification; constructing a channel node allocation matrix based on channel status information and node classification results to dynamically allocate transmission channels; performing adaptive power control based on node communication needs and the channel capacity of the transmission channels; using the dynamically allocated transmission channels as the primary link, constructing a link quality evaluation function to establish backup links, and enabling multi-link collaborative access; and monitoring the overall performance indicators of all nodes in real time and optimizing based on the monitoring results. This invention effectively utilizes wireless resources, reduces channel conflicts, and improves the speed of node access to the network and data transmission efficiency through dynamic channel allocation and multi-link collaborative access.

Description

Technical Field

[0001] This invention relates to the field of Internet of Things (IoT) technology for power transmission and transformation equipment, and in particular to a method and system for wireless node access in the Internet of Things for power transmission and transformation equipment. Background Technology

[0002] With the widespread application of IoT technology in the power transmission and transformation field, a large number of wireless nodes are deployed for real-time monitoring of the operating status of power transmission and transformation equipment. However, traditional wireless node access methods have many shortcomings when facing the complexity of the power transmission and transformation environment. Complex electromagnetic environments and variable temperature and humidity conditions can lead to unstable wireless channel quality, resulting in low node access efficiency, easy data transmission interruption, and affecting the accurate monitoring and timely feedback of the power transmission and transformation equipment status. At the same time, traditional methods fail to fully consider the characteristics of the nodes themselves and environmental factors, leading to unreasonable energy consumption, shortened node lifespan, and increased maintenance costs. Therefore, there is an urgent need for a wireless node access method that can adapt to the complex environment of power transmission and transformation, improve access efficiency and reliability, and reduce energy consumption. Based on this, this invention proposes an IoT wireless node access method and system for power transmission and transformation equipment. Summary of the Invention

[0003] This invention provides a method for wireless node access in the Internet of Things (IoT) for power transmission and transformation equipment, comprising:

[0004] S10. Deploy sensing units at wireless nodes of power transmission and transformation equipment to sense equipment status. The sensing units transmit sensing parameter information to the central processing unit to determine the node category.

[0005] S20. Based on channel state information and node classification results, construct a channel node allocation matrix to dynamically allocate transmission channels;

[0006] S30. Adaptive power control is performed based on the node's communication requirements and the channel capacity of the transmission channel.

[0007] S40: The dynamically allocated transmission channel is the primary link; a link quality assessment function is constructed to establish backup links; and multiple links cooperate for access.

[0008] S50 monitors the overall performance indicators of all nodes in real time and optimizes based on the monitoring results.

[0009] As described above, the method for accessing wireless nodes in the Internet of Things for power transmission and transformation equipment requires the deployment of a sensing unit to determine the node category. This unit senses and preprocesses the state parameters of the power transmission and transformation equipment and the environmental state parameters, and then transmits these parameters to a central processing unit. The central processing unit receives the sensed parameters and defines a fuzzy membership function to determine the node category.

[0010] The above-described method for accessing wireless nodes in the Internet of Things for power transmission and transformation equipment includes sensing parameters for the sensing unit, which are divided into equipment parameters and environmental parameters, including the temperature of the power transmission and transformation equipment, ambient humidity, ambient electromagnetic interference intensity, vibration amplitude of the equipment, and leakage current of the equipment.

[0011] The above-described method for accessing wireless nodes in the Internet of Things for power transmission and transformation equipment involves determining the node category by establishing fuzzy membership functions for vulnerable nodes and core nodes respectively, comparing their magnitudes, and determining the node as a vulnerable node if the vulnerable fuzzy membership function is greater than the core fuzzy membership function; otherwise, it is determined as a core node.

[0012] In the above-described method for accessing wireless nodes in the Internet of Things for power transmission and transformation equipment, the number of rows in the channel node allocation matrix is ​​equal to the total number of nodes, and the number of columns is equal to the total number of available channels.

[0013] The above-described method for accessing wireless nodes in the Internet of Things for power transmission and transformation equipment includes a multi-link collaborative access method, which uses dynamically allocated transmission channels as the main link and constructs a link quality evaluation function to establish backup links.

[0014] As described above, in the IoT wireless node access method for power transmission and transformation equipment, the backup link refers to the node scanning its surrounding neighboring nodes, which may be other ordinary nodes or intermediate nodes with certain forwarding capabilities, and selecting nodes with better signal strength and link quality parameters that meet certain conditions to establish a backup link.

[0015] The present invention also provides an Internet of Things (IoT) wireless node access system for power transmission and transformation equipment, comprising:

[0016] Sensing Unit Module: Sensing units are deployed at the wireless nodes of power transmission and transformation equipment to sense the equipment status. The sensing units transmit the sensing parameter information to the central processing unit for node classification.

[0017] Channel allocation module: Based on channel state information and node classification results, a channel node allocation matrix is ​​constructed to dynamically allocate transmission channels;

[0018] Adaptive power control module: performs adaptive power control based on node communication requirements and the channel capacity of the transmission channel;

[0019] Multi-link module: The dynamically allocated transmission channel is the primary link, a link quality assessment function is constructed to establish backup links, and multiple links are coordinated for access;

[0020] Optimization module: Monitors the overall performance metrics of all nodes in real time and optimizes based on the monitoring results.

[0021] The beneficial effects achieved by this invention are as follows: This invention effectively utilizes wireless resources, reduces channel conflicts, and improves the speed of node access to the network and the efficiency of data transmission through dynamic channel allocation and multi-link cooperative access. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0023] Figure 1 This is a flowchart of a method for accessing wireless nodes in the Internet of Things for power transmission and transformation equipment, provided in Embodiment 1 of this application.

[0024] Figure 2 This is a schematic diagram of an Internet of Things (IoT) wireless node access system for power transmission and transformation equipment provided in Embodiment 2 of this application. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] Example 1

[0027] like Figure 1 As shown, Embodiment 1 of this application provides a method for accessing wireless nodes in the Internet of Things (IoT) of power transmission and transformation equipment, including:

[0028] S10. Deploy sensing units at the wireless nodes of power transmission and transformation equipment to sense the equipment status. The sensing units transmit the sensing parameter information to the central processing unit for node category determination.

[0029] S11. Deploy sensing units to sense and preprocess the status parameters of power transmission and transformation equipment and environmental status parameters, and transmit them to the central processing unit.

[0030] In the deployment area of ​​IoT wireless nodes for power transmission and transformation equipment, the location of sensing units is rationally planned based on the site environment and signal coverage. In open areas, the sensing units are spaced further apart; in areas with dense equipment or significant signal obstruction, the spacing is closer. Each sensing unit integrates a high-precision thermistor sensor, measuring the temperature T of the power transmission and transformation equipment based on the thermistor's resistance changing with temperature. temCapacitive humidity sensors utilize the change in dielectric constant of a moisture-sensitive material after it absorbs moisture, resulting in a change in capacitance. This capacitance value is then converted into a humidity value to measure the ambient humidity (H). hum The magnetic field sensor measures the intensity of environmental electromagnetic interference (I) by measuring the Hall voltage. ele Vibration sensors detect the vibration amplitude Z of equipment by converting mechanical vibration signals into electrical signals and analyzing these signals. vib Zero-sequence current transformer for detecting leakage current in power transmission and transformation equipment (C) leak .

[0031] Each sensing unit collects power transmission and transformation equipment parameters and environmental parameters at preset time intervals, and performs preliminary data processing, including filtering, compression, and anomaly detection, to reduce the amount of data uploaded. Depending on the transmission distance, the sensed parameter data is transmitted to the central processing unit using different wireless communication technologies. The maximum transmission distance does not exceed [a certain limit]. The sensing unit uses Purple Bee communication technology for transmission, where P tx G represents the transmission power. tx and G rx Represents the transmit and receive antenna gains, PL(d0) is the path loss at the central processing unit d0, and RSSI is... min This represents the minimum received signal strength for the central processing unit, and η represents the path loss exponent. The maximum transmission distance does not exceed... The sensing unit uses long-range radio communication technology for transmission, where λ is the signal wavelength, and S rx For receiving sensitivity, L path This is the path loss coefficient.

[0032] S12. The central processing unit receives the sensing parameters and defines a fuzzy membership function to determine the node category.

[0033] After receiving information on power transmission and transformation equipment, environmental parameters, and node attributes, the central processing unit normalizes the received environmental parameters and node attributes to eliminate the influence of different parameter dimensions. A fuzzy membership function is defined to describe the probability that a node belongs to different categories.

[0034] For vulnerable node categories, the following fuzzy membership function is constructed, with the specific formula as follows:

[0035] in, The normalized temperature. The normalized humidity. The normalized electromagnetic interference intensity, The normalized vibration amplitude of the equipment. This is the normalized device leakage current. v is the normalized maximum transmission distance.norm E is the normalized transmission rate. norm denoted as the normalized remaining charge, and 'a' as the number of parameters in the fuzzy membership function.

[0036] For the core node category, the following fuzzy membership function is constructed, with the specific formula as follows: The fuzzy membership degree of each node to both the vulnerable node category and the core node category is calculated, and the two values ​​are compared. If u vulnerable (N)>u core If (N), then the node is determined to be a vulnerable node; otherwise, it is determined to be a core node.

[0037] S20. Based on channel state information and node classification results, construct a channel node allocation matrix to dynamically allocate transmission channels.

[0038] After each wireless node starts up, it sends probe signals at a set period. The receiving end calculates the channel idle rate based on the received signals. Among them, t idle t represents the channel idle time within one observation period. total Represents the total observation time of the channel within one observation period; signal strength P received P represents the signal power received by the receiver. reference Reference power; bit error rate n error n represents the number of bits transmitted in error. total This represents the total number of bits transmitted. Nodes transmit this channel state information to neighboring nodes and the sink node via a distributed self-organizing network protocol.

[0039] The sink node collects channel state information and node classification results from all nodes, using the objective function... Channel allocation is performed to optimize the overall network communication performance. Here, n is the total number of wireless nodes in the network that need channel allocation, and ω... i These are weighting coefficients, related to the node classification. Core nodes, due to their high importance to network stability and data transmission, are assigned higher weights ω. core The weight of vulnerable nodes is relatively low, ω. vulnerable α is the weight of the channel idle rate, R idle,i S is the idle rate of the current channel of the i-th node, β is the weight of the signal strength, and S i P is the signal strength received by the i-th node, γ is the weight of the bit error rate, and P is the signal strength received by the i-th node. error,iIt is the bit error rate of the current channel of the i-th node. For core nodes, high-quality, low-interference channels are allocated first; for vulnerable nodes, a multi-channel redundancy allocation strategy is adopted to allocate multiple channels to them, and the quality parameters of each channel meet certain standards to improve communication reliability.

[0040] The specific allocation method involves constructing a channel node allocation matrix M, where the number of rows equals the total number of nodes n, and the number of columns equals the total number of available channels m. The matrix elements M... ij This represents the channel quality assessment value Q(C) when node i uses channel j. j ), Q(C j )=αR idle,i +βS i +γ(1-P error,i For each row of the allocation matrix M, find the minimum value min of that row. i Then subtract min from each element in that row. i This yields a new matrix M1. For each column of matrix M1, find the minimum value min of that column. j Then subtract the min value from each element in that column. j This yields the transformed matrix M2. Row by row in matrix M2, if a row contains only one zero element, mark that zero element as an independent zero element and remove all other zero elements in the same column. Column by column, if a column contains only one zero element, mark that zero element as an independent zero element and remove all other zero elements in the same row. Repeat these two steps until no new independent zero elements can be found.

[0041] If the number of independent zero elements equals the number of nodes n, then the optimal allocation scheme has been found, and the algorithm ends. At this point, the position (i,j) marked as an independent zero element indicates that node i is assigned to channel j. If the number of independent zero elements is less than the number of nodes n, then check the rows without marked independent zero elements, check the columns containing crossed-out zero elements in the checked rows, and check the rows containing independent zero elements in the checked columns. Repeat these two steps until no more checkmarks are possible. Cover all checked columns and unchecked rows with lines to obtain the minimum set of lines covering all zero elements. Find the minimum value min among the elements not covered by lines. q For rows not covered by a line, subtract the minimum value from each element. q For columns covered by straight lines, add min to each element. q This yields a new matrix M3. Using M3 as the new allocation matrix, we return to step two to continue searching for independent zero elements.

[0042] After the allocation is completed, the channel allocation results will be broadcast to each node.

[0043] S30. Adaptive power control is performed based on the node's communication requirements and the channel capacity of the transmission channel.

[0044] Based on the node's communication needs, the required channel capacity is determined, and then the transmit power is adjusted through adaptive power control to ensure stable communication in complex environments. Transmit power Where R is the node's data transmission rate requirement, L is the coding gain, R / L is the channel capacity, and B is the channel bandwidth, determined according to the node's communication protocol. N0 is the noise power spectral density. G interfere The interference power is obtained by monitoring the strength of the interference signal in the channel. While monitoring the channel state, the node simultaneously detects the power of the interference signal, and the interference power is obtained after calibration and processing. h is the channel fading coefficient. Where x is the transmitted pilot signal and y is the received pilot signal. It is x k The conjugate of x k This represents the k-th sample value in the transmitted pilot signal sequence, where M is the number of samples in the pilot signal.

[0045] The node adjusts its transmission power in real time based on the calculated transmission power to adapt to different communication environments and avoid unnecessary energy consumption. The wireless node has a built-in positioning module that acquires its own location information in real time and calculates the distance d between the node and the sink node by comparing the location data with that of the sink node. converge When a node movement causes a change in distance Δd from the sink node to exceed a distance change threshold Δd thresh Furthermore, the channel fading coefficient change Δh exceeds the channel fading coefficient change threshold Δh. thresh When necessary, adjust the transmission power according to the following rules:

[0046] If only the distance change exceeds the threshold, while the channel fading coefficient change does not exceed the threshold, the transmit power is adjusted proportionally based on the distance change. The transmit power is adjusted to... Where P is the transmit power before adjustment, and sgn() is the sign function used to determine... The positive or negative sign can be determined by the direction of distance change, indicating whether the transmission power increases or decreases. Let θ1 be the distance-related power adjustment coefficient, representing the percentage change in channel fading coefficient. If only the channel fading coefficient changes beyond a threshold, while the distance change does not, the transmit power is adjusted proportionally to the change in channel fading coefficient. θ2 is the percentage change in the channel fading coefficient, h represents the channel fading coefficient before the change, and θ2 is the power adjustment coefficient related to channel fading.

[0047] S40: The dynamically allocated transmission channel is the primary link; a link quality assessment function is constructed to establish backup links; and multiple links cooperate for access.

[0048] The transmission channel dynamically allocated in step S20 is used as the primary link. Simultaneously, neighboring nodes are scanned. These neighboring nodes may be other ordinary nodes or intermediate nodes with some forwarding capability. Nodes with good signal strength and link quality parameters that meet certain conditions are selected to establish backup links, increasing communication reliability. To more accurately assess link quality, a link quality assessment function is constructed. Where B is the link bandwidth, D is the delay, and P is the latency. loss To determine packet loss rate, information can be obtained by exchanging link status packets between nodes. Backup links are managed and maintained by the nodes themselves, and their quality needs to be monitored regularly.

[0049] The node runs a load balancing algorithm that dynamically allocates data based on data traffic and link quality. The weight of each link is calculated based on its quality score. Let the quality score of link b be W(Q). b If the total number of links is F, then the weight of link b is... The calculation formula is For data with high real-time requirements, transmission is prioritized on high-quality links according to link weight. Let the real-time data traffic be T. real The amount of real-time data allocated to link b is For non-real-time device operation status statistics, let its flow rate be T. non-real Data is allocated to relatively low-quality but high-bandwidth links according to link weight. The amount of non-real-time data allocated to link b is...

[0050] When the primary link experiences a sudden increase in packet loss rate exceeding 10% or a latency greater than 100ms, or when performance degrades, the node quickly switches data transmission to the backup link while continuing to monitor the primary link's status. To ensure data transmission continuity during the switch to the backup link, a data caching and retransmission mechanism is employed. The node caches any uncompleted data and retransmits it after switching to the backup link.

[0051] Once the main link recovers, data is redistributed according to the load balancing algorithm. During the main link recovery process, an active probing mechanism is used to detect recovery more quickly. Nodes periodically send probe signals to the main link, and determine whether the main link has recovered based on the responses to the received probe signals. If m consecutive probes receive normal responses, the main link is considered to have recovered.

[0052] S60 monitors the overall performance indicators of all nodes in real time and optimizes based on the monitoring results.

[0053] Throughout the operation of IoT wireless nodes in power transmission and transformation equipment, the overall performance indicators of the nodes are monitored in real time, including network throughput, latency, and packet loss rate. Based on the monitored performance indicators, each module is optimized and adjusted. If the network throughput is low, it is analyzed whether it is due to unreasonable channel allocation or insufficient transmission power. If it is a channel allocation problem, the channel allocation algorithm is rerun, the weight coefficients are adjusted, and the channel allocation scheme is optimized, which can increase the channel resource allocation weight for nodes with high throughput requirements.

[0054] If the latency is significant, check the link quality and load balancing. If it's a link quality issue, for the primary link, try selecting a backup link or adjusting the transmit power to improve link quality; if it's a load balancing issue, adjust the parameters of the load balancing algorithm to redistribute data traffic.

[0055] If the packet loss rate is high, check for channel interference and link stability. If it is caused by channel interference, adjust the transmit power or change the channel; if it is a link stability issue, strengthen the monitoring and maintenance of the link, such as adding reliability judgment conditions for link switching.

[0056] Meanwhile, the location of the environmental sensing units is regularly evaluated and adjusted. As power transmission and transformation equipment operates and the environment changes, the original layout of the environmental sensing units may no longer be optimal. By analyzing the accuracy and completeness of the collected environmental parameter data, and considering signal coverage, the spacing of the environmental sensing units is adjusted to ensure accurate collection of environmental parameters.

[0057] By monitoring and optimizing the system performance as described above, we can continuously improve the performance and stability of the IoT wireless node access system for power transmission and transformation equipment, and ensure the reliable operation of the power transmission and transformation equipment.

[0058] Example 2

[0059] like Figure 2 As shown, Embodiment 2 of this application provides an Internet of Things (IoT) wireless node access system for power transmission and transformation equipment, including:

[0060] The sensing unit module includes a sensing transmission submodule and a central processing unit submodule.

[0061] Sensing and Transmission Submodule: Used to deploy sensing units, sense and preprocess the status parameters of power transmission and transformation equipment and environmental status parameters, and transmit them to the central processing unit.

[0062] In the deployment area of ​​IoT wireless nodes for power transmission and transformation equipment, the location of sensing units is rationally planned based on the site environment and signal coverage. In open areas, the sensing units are spaced further apart; in areas with dense equipment or significant signal obstruction, the spacing is closer. Each sensing unit integrates a high-precision thermistor sensor, measuring the temperature T of the power transmission and transformation equipment based on the thermistor's resistance changing with temperature. tem Capacitive humidity sensors utilize the change in dielectric constant of a moisture-sensitive material after it absorbs moisture, resulting in a change in capacitance. This capacitance value is then converted into a humidity value to measure the ambient humidity (H). hum The magnetic field sensor measures the intensity of environmental electromagnetic interference (I) by measuring the Hall voltage. ele Vibration sensors detect the vibration amplitude Z of equipment by converting mechanical vibration signals into electrical signals and analyzing these signals. vib Zero-sequence current transformer for detecting leakage current in power transmission and transformation equipment (C) leak .

[0063] Each sensing unit collects power transmission and transformation equipment parameters and environmental parameters at preset time intervals, and performs preliminary data processing, including filtering, compression, and anomaly detection, to reduce the amount of data uploaded. Depending on the transmission distance, the sensed parameter data is transmitted to the central processing unit using different wireless communication technologies. The maximum transmission distance does not exceed [a certain limit]. The sensing unit uses Purple Bee communication technology for transmission, where P tx G represents the transmission power. tx and G rx Represents the transmit and receive antenna gains, PL(d0) is the path loss at the central processing unit d0, and RSSI is... min This represents the minimum received signal strength for the central processing unit, and η represents the path loss exponent. The maximum transmission distance does not exceed... The sensing unit uses long-range radio communication technology for transmission, where λ is the signal wavelength, and S rx For receiving sensitivity, L path This is the path loss coefficient.

[0064] Central processing unit submodule: Used to receive sensing parameters and define fuzzy membership functions to determine node categories.

[0065] After receiving information on power transmission and transformation equipment, environmental parameters, and node attributes, the central processing unit normalizes the received environmental parameters and node attributes to eliminate the influence of different parameter dimensions. A fuzzy membership function is defined to describe the probability that a node belongs to different categories.

[0066] For vulnerable node categories, the following fuzzy membership function is constructed, with the specific formula as follows:

[0067] in, The normalized temperature. The normalized humidity. The normalized electromagnetic interference intensity, The normalized vibration amplitude of the equipment. This is the normalized device leakage current. v is the normalized maximum transmission distance. norm E is the normalized transmission rate. norm denoted as the normalized remaining charge, and 'a' as the number of parameters in the fuzzy membership function.

[0068] For the core node category, the following fuzzy membership function is constructed, with the specific formula as follows: The fuzzy membership degree of each node to both the vulnerable node category and the core node category is calculated, and the two values ​​are compared. If u vulnerable (N)>u core If (N), then the node is determined to be a vulnerable node; otherwise, it is determined to be a core node.

[0069] Channel allocation module: Based on channel state information and node classification results, a channel node allocation matrix is ​​constructed to dynamically allocate transmission channels.

[0070] After each wireless node starts up, it sends probe signals at a set period. The receiving end calculates the channel idle rate based on the received signals. Among them, t idle t represents the channel idle time within one observation period. total Represents the total observation time of the channel within one observation period; signal strength P received P represents the signal power received by the receiver. reference Reference power; bit error rate n error n represents the number of bits transmitted in error. total This represents the total number of bits transmitted. Nodes transmit this channel state information to neighboring nodes and the sink node via a distributed self-organizing network protocol.

[0071] The sink node collects channel state information and node classification results from all nodes, using the objective function... Channel allocation is performed to optimize the overall network communication performance. Here, n is the total number of wireless nodes in the network that need channel allocation, and ω... i These are weighting coefficients, related to the node classification. Core nodes, due to their high importance to network stability and data transmission, are assigned higher weights ω. core The weight of vulnerable nodes is relatively low, ω. vulnerable α is the weight of the channel idle rate, R idle,iS is the idle rate of the current channel of the i-th node, β is the weight of the signal strength, and S i P is the signal strength received by the i-th node, γ is the weight of the bit error rate, and P is the signal strength received by the i-th node. error,i It is the bit error rate of the current channel of the i-th node. For core nodes, high-quality, low-interference channels are allocated first; for vulnerable nodes, a multi-channel redundancy allocation strategy is adopted to allocate multiple channels to them, and the quality parameters of each channel meet certain standards to improve communication reliability.

[0072] The specific allocation method involves constructing a channel node allocation matrix M, where the number of rows equals the total number of nodes n, and the number of columns equals the total number of available channels m. The matrix elements M... ij This represents the channel quality assessment value Q(C) when node i uses channel j. j ), Q(C j )=αR idle,i +βS i +γ(1-P error,i For each row of the allocation matrix M, find the minimum value min of that row. i Then subtract min from each element in that row. i This yields a new matrix M1. For each column of matrix M1, find the minimum value min of that column. j Then subtract the min value from each element in that column. j This yields the transformed matrix M2. Row by row in matrix M2, if a row contains only one zero element, mark that zero element as an independent zero element and remove all other zero elements in the same column. Column by column, if a column contains only one zero element, mark that zero element as an independent zero element and remove all other zero elements in the same row. Repeat these two steps until no new independent zero elements can be found.

[0073] If the number of independent zero elements equals the number of nodes n, then the optimal allocation scheme has been found, and the algorithm ends. At this point, the position (i,j) marked as an independent zero element indicates that node i is assigned to channel j. If the number of independent zero elements is less than the number of nodes n, then check the rows without marked independent zero elements, check the columns containing crossed-out zero elements in the checked rows, and check the rows containing independent zero elements in the checked columns. Repeat these two steps until no more checkmarks are possible. Cover all checked columns and unchecked rows with lines to obtain the minimum set of lines covering all zero elements. Find the minimum value min among the elements not covered by lines. q For rows not covered by a line, subtract the minimum value from each element. q For columns covered by straight lines, add min to each element. q This yields a new matrix M3. Using M3 as the new allocation matrix, we return to step two to continue searching for independent zero elements.

[0074] After the allocation is completed, the channel allocation results will be broadcast to each node.

[0075] Adaptive power control module: performs adaptive power control based on node communication requirements and transmission channel capacity.

[0076] Based on the node's communication needs, the required channel capacity is determined, and then the transmit power is adjusted through adaptive power control to ensure stable communication in complex environments. Transmit power Where R is the node's data transmission rate requirement, L is the coding gain, R / L is the channel capacity, and B is the channel bandwidth, determined according to the node's communication protocol. N0 is the noise power spectral density. G interfere The interference power is obtained by monitoring the strength of the interference signal in the channel. While monitoring the channel state, the node simultaneously detects the power of the interference signal, and the interference power is obtained after calibration and processing. h is the channel fading coefficient. Where x is the transmitted pilot signal and y is the received pilot signal. It is x k The conjugate of x k This represents the k-th sample value in the transmitted pilot signal sequence, where M is the number of samples in the pilot signal.

[0077] The node adjusts its transmission power in real time based on the calculated transmission power to adapt to different communication environments and avoid unnecessary energy consumption. The wireless node has a built-in positioning module that acquires its own location information in real time and calculates the distance d between the node and the sink node by comparing the location data with that of the sink node. converge When a node movement causes a change in distance Δd from the sink node to exceed a distance change threshold Δd thresh Furthermore, the channel fading coefficient change Δh exceeds the channel fading coefficient change threshold Δh. thresh When necessary, adjust the transmission power according to the following rules:

[0078] If only the distance change exceeds the threshold, while the channel fading coefficient change does not exceed the threshold, the transmit power is adjusted proportionally based on the distance change. The transmit power is adjusted to... Where P is the transmit power before adjustment, and sgn() is the sign function used to determine... The positive or negative sign can be determined by the direction of distance change, indicating whether the transmission power increases or decreases. Let θ1 be the distance-related power adjustment coefficient, representing the percentage change in channel fading coefficient. If only the channel fading coefficient changes beyond a threshold, while the distance change does not, the transmit power is adjusted proportionally to the change in channel fading coefficient. θ2 is the percentage change in the channel fading coefficient, h represents the channel fading coefficient before the change, and θ2 is the power adjustment coefficient related to channel fading.

[0079] Multi-link module: The dynamically allocated transmission channel is the primary link, a link quality assessment function is constructed to establish backup links, and multiple links are coordinated for access.

[0080] The primary link uses a dynamically allocated transmission channel, while simultaneously scanning neighboring nodes. These neighboring nodes may be other ordinary nodes or intermediate nodes with some forwarding capability. Nodes with good signal strength and link quality parameters that meet certain conditions are selected to establish backup links, increasing communication reliability. To more accurately assess link quality, a link quality evaluation function is constructed. Where B is the link bandwidth, D is the delay, and P is the latency. loss To determine packet loss rate, information can be obtained by exchanging link status packets between nodes. Backup links are managed and maintained by the nodes themselves, and their quality needs to be monitored regularly.

[0081] The node runs a load balancing algorithm that dynamically allocates data based on data traffic and link quality. The weight of each link is calculated based on its quality score. Let the quality score of link b be W(Q). b If the total number of links is F, then the weight of link b is... The calculation formula is For data with high real-time requirements, transmission is prioritized on high-quality links according to link weight. Let the real-time data traffic be T. real The amount of real-time data allocated to link b is For non-real-time device operation status statistics, let its flow rate be T. non-real Data is allocated to relatively low-quality but high-bandwidth links according to link weight. The amount of non-real-time data allocated to link b is...

[0082] When the primary link experiences a sudden increase in packet loss rate exceeding 10% or a latency greater than 100ms, or when performance degrades, the node quickly switches data transmission to the backup link while continuing to monitor the primary link's status. To ensure data transmission continuity during the switch to the backup link, a data caching and retransmission mechanism is employed. The node caches any uncompleted data and retransmits it after switching to the backup link.

[0083] Once the main link recovers, data is redistributed according to the load balancing algorithm. During the main link recovery process, an active probing mechanism is used to detect recovery more quickly. Nodes periodically send probe signals to the main link, and determine whether the main link has recovered based on the responses to the received probe signals. If m consecutive probes receive normal responses, the main link is considered to have recovered.

[0084] Optimization module: Monitors the overall performance metrics of all nodes in real time and optimizes based on the monitoring results.

[0085] Throughout the operation of IoT wireless nodes in power transmission and transformation equipment, the overall performance indicators of the nodes are monitored in real time, including network throughput, latency, and packet loss rate. Based on the monitored performance indicators, each module is optimized and adjusted. If the network throughput is low, it is analyzed whether it is due to unreasonable channel allocation or insufficient transmission power. If it is a channel allocation problem, the channel allocation algorithm is rerun, the weight coefficients are adjusted, and the channel allocation scheme is optimized, which can increase the channel resource allocation weight for nodes with high throughput requirements.

[0086] If the latency is significant, check the link quality and load balancing. If it's a link quality issue, for the primary link, try selecting a backup link or adjusting the transmit power to improve link quality; if it's a load balancing issue, adjust the parameters of the load balancing algorithm to redistribute data traffic.

[0087] If the packet loss rate is high, check for channel interference and link stability. If it is caused by channel interference, adjust the transmit power or change the channel; if it is a link stability issue, strengthen the monitoring and maintenance of the link, such as adding reliability judgment conditions for link switching.

[0088] Meanwhile, the location of the environmental sensing units is regularly evaluated and adjusted. As power transmission and transformation equipment operates and the environment changes, the original layout of the environmental sensing units may no longer be optimal. By analyzing the accuracy and completeness of the collected environmental parameter data, and considering signal coverage, the spacing of the environmental sensing units is adjusted to ensure accurate collection of environmental parameters.

[0089] By monitoring and optimizing the system performance as described above, we can continuously improve the performance and stability of the IoT wireless node access system for power transmission and transformation equipment, and ensure the reliable operation of the power transmission and transformation equipment.

[0090] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made on the basis of the technical solution of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for accessing wireless nodes in power transmission and transformation equipment via the Internet of Things, characterized in that, include: S10. Deploy sensing units at wireless nodes of power transmission and transformation equipment to sense equipment status. The sensing units transmit sensing parameter information to the central processing unit to determine the node category. S20. Based on channel state information and node classification results, construct a channel node allocation matrix to dynamically allocate transmission channels; After each wireless node is started, it sends a probe signal according to a set period. The node transmits the received channel state information to neighboring nodes and the aggregation node through a distributed self-organizing network protocol. The sink node collects channel state information and node classification results from all nodes, using the objective function... To optimize channel allocation and achieve the best overall network communication performance, n represents the total number of wireless nodes in the network that require channel allocation. These are weighting coefficients, related to the node classification. Core nodes, due to their high importance to network stability and data transmission, are assigned higher weights. The weight of vulnerable nodes is relatively low. , It is the weight of the channel idle rate. It is the idle rate of the current channel of the i-th node. It is the weight of the signal strength. It is the signal strength received by the i-th node. It is the weight of the bit error rate. It is the bit error rate of the current channel of the i-th node; The specific allocation method involves constructing a channel node allocation matrix M, where the number of rows equals the total number of nodes n, the number of columns equals the total number of available channels m, and the matrix elements... This represents the channel quality assessment value when node i uses channel j. , For each row of the allocation matrix M, find the minimum value of that row. Then subtract each element in that row. A new matrix is ​​obtained. For the matrix For each column, find the minimum value in that column. Then subtract each element in that column. The transformed matrix is ​​obtained. From the matrix The process involves checking each row. If a row contains only one zero element, that zero element is marked as an independent zero element, and all other zero elements in the same column are removed. The process is repeated column by column. If a column contains only one zero element, that zero element is marked as an independent zero element, and all other zero elements in the same row are removed. This process is repeated until no new independent zero elements can be found. Once the allocation is complete, the channel allocation results are broadcast to all nodes. S30. Adaptive power control is performed based on the node's communication requirements and the channel capacity of the transmission channel. S40: The dynamically allocated transmission channel is the primary link; a link quality assessment function is constructed to establish backup links; and multiple links cooperate for access. S50 monitors the overall performance indicators of all nodes in real time and optimizes based on the monitoring results.

2. The method for accessing wireless nodes in the Internet of Things for power transmission and transformation equipment as described in claim 1, characterized in that, To determine the node category, a sensing unit must first be deployed to sense and preprocess the status parameters of the power transmission and transformation equipment and the environmental status parameters, and then transmit them to the central processing unit. The central processing unit receives the sensed parameters and defines a fuzzy membership function to determine the node category.

3. The method for accessing wireless nodes in the Internet of Things for power transmission and transformation equipment as described in claim 2, characterized in that, The parameters sensed by the sensing unit are divided into equipment parameters and environmental parameters, including the temperature of the power transmission and transformation equipment, the ambient humidity, the intensity of ambient electromagnetic interference, the vibration amplitude of the equipment, and the leakage current of the equipment.

4. The method for accessing wireless nodes in the Internet of Things for power transmission and transformation equipment as described in claim 2, characterized in that, To determine the node category, fuzzy membership functions need to be established for vulnerable nodes and core nodes respectively. The two are compared. If the vulnerable fuzzy membership function is greater than the core fuzzy membership function, then the node is determined to be a vulnerable node. Conversely, it is determined to be a core node.

5. The method for accessing wireless nodes in the Internet of Things for power transmission and transformation equipment as described in claim 1, characterized in that, In the channel node allocation matrix, the number of rows equals the total number of nodes, and the number of columns equals the total number of available channels.

6. The method for accessing wireless nodes in the Internet of Things for power transmission and transformation equipment as described in claim 1, characterized in that, Multi-link collaborative access refers to using dynamically allocated transmission channels as the primary link and constructing a link quality assessment function to establish backup links.

7. The method for accessing wireless nodes in the Internet of Things for power transmission and transformation equipment as described in claim 6, characterized in that, A backup link refers to a node scanning its surrounding neighboring nodes, which are other ordinary nodes or intermediate nodes with forwarding capabilities, and selecting nodes whose signal strength and link quality parameters meet preset conditions to establish a backup link.

8. A wireless node access system for Internet of Things (IoT) in power transmission and transformation equipment, characterized in that, include: Sensing Unit Module: Sensing units are deployed at the wireless nodes of power transmission and transformation equipment to sense the equipment status. The sensing units transmit the sensing parameter information to the central processing unit for node classification. Channel allocation module: Based on channel state information and node classification results, a channel node allocation matrix is ​​constructed to dynamically allocate transmission channels; After each wireless node is started, it sends a probe signal according to a set period. The node transmits the received channel state information to neighboring nodes and the aggregation node through a distributed self-organizing network protocol. The sink node collects channel state information and node classification results from all nodes, using the objective function... To optimize channel allocation and achieve the best overall network communication performance, n represents the total number of wireless nodes in the network that require channel allocation. These are weighting coefficients, related to the node classification. Core nodes, due to their high importance to network stability and data transmission, are assigned higher weights. The weight of vulnerable nodes is relatively low. , It is the weight of the channel idle rate. It is the idle rate of the current channel of the i-th node. It is the weight of the signal strength. It is the signal strength received by the i-th node. It is the weight of the bit error rate. It is the bit error rate of the current channel of the i-th node; The specific allocation method involves constructing a channel node allocation matrix M, where the number of rows equals the total number of nodes n, the number of columns equals the total number of available channels m, and the matrix elements... This represents the channel quality assessment value when node i uses channel j. , For each row of the allocation matrix M, find the minimum value of that row. Then subtract each element in that row. A new matrix is ​​obtained. For the matrix For each column, find the minimum value in that column. Then subtract each element in that column. The transformed matrix is ​​obtained. From the matrix The process involves checking each row. If a row contains only one zero element, that zero element is marked as an independent zero element, and all other zero elements in the same column are removed. The process is repeated column by column. If a column contains only one zero element, that zero element is marked as an independent zero element, and all other zero elements in the same row are removed. This process is repeated until no new independent zero elements can be found. Once the allocation is complete, the channel allocation results are broadcast to all nodes. Adaptive power control module: performs adaptive power control based on node communication requirements and the channel capacity of the transmission channel; Multi-link module: The dynamically allocated transmission channel is the primary link, a link quality assessment function is constructed to establish backup links, and multiple links are coordinated for access; Optimization module: Monitors the overall performance metrics of all nodes in real time and optimizes based on the monitoring results.

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