A method for overheat protection of a network communication device

Abstract

The application discloses a kind of overheating protection methods of network communication equipment, it is related to communication equipment technical field, comprising: in the interior of network communication equipment, according to functional module layout and thermal coupling structure, set multiple temperature perception nodes;During the operation of equipment, control system is based on the historical temperature data collected by temperature perception node, extracts heat dissipation path state parameter, and calculates thermal resistance variation value accordingly;When thermal resistance variation value is greater than the preset thermal resistance degradation threshold value, determine that heat dissipation path exists heat conduction ability decline phenomenon;The application constructs the thermal response perception network based on multiple point temperature perception node, by comprehensively considering functional module layout and thermal coupling structure, the perception accuracy of equipment to different heat source distribution and heat diffusion path is improved, can make control system accurately master the spatial distribution and dynamic change trend of equipment internal thermal state, to provide basic support for subsequent state analysis and risk determination.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of communication equipment, in particular to a network communication equipment overheat protection method. BACKGROUND

[0002] In network communication equipment, such as routers, switches, PoE power supply equipment and the like, due to long-term operation in a high-bandwidth, high-load and high-density integrated environment, heat aggregation exists in different degrees in the internal function modules; in order to guarantee system stability and hardware reliability, a heat management mechanism has become an important link in the design of the equipment, and higher requirements are put forward for the real-time performance and accuracy of overheat protection in a scenario in which communication link continuity is required.

[0003] The existing heat protection mechanism usually collects temperature data in the equipment operation process based on the temperature sensors arranged internally, and triggers fan speed adjustment, processor frequency reduction, module hibernation and the like protection strategies when the temperature exceeds the set threshold; some systems also introduce redundant design or set multiple temperature control responses to adapt to different application scenarios; these schemes improve the thermal stability of equipment operation to a certain extent, and have been widely applied to various types of communication equipment.

[0004] However, in the equipment environment in which the heat conduction path is complex, the heat dissipation structure is heterogeneous or the thermal coupling effect exists, it may be difficult to identify structural thermal conduction degradation or atypical thermal failure risks in time only by relying on the temperature threshold determination; for example, some heat accumulation phenomena may be "covered up" because the overall temperature has not exceeded the limit, and these potential risks, if not identified and responded in time, may still affect the long-term stability of the system; therefore, it is necessary to further explore a heat anomaly identification and protection mechanism with more forward-looking and multi-dimensional judgment ability, and the application provides a network communication equipment overheat protection method. SUMMARY

[0005] The application aims to provide a network communication equipment overheat protection method to solve the problems mentioned in the background.

[0006] The application can be implemented by the following technical scheme: a network communication equipment overheat protection method, which comprises the following steps:

[0007] Step 1: Establish a multi-point temperature sensing node system

[0008] In the network communication equipment, a plurality of temperature sensing nodes are arranged according to the function module layout and thermal coupling structure.

[0009] Step 2: Extract the heat dissipation path state parameters

[0010] In the normal operation cycle, the control system extracts the following thermal response parameters based on the historical temperature data collected by each temperature sensing node:

[0011] The temperature rise rate of each node under unit load;

[0012] The response delay between fan speed change and node temperature change;

[0013] The recovery time constant required for each node temperature to fall back to steady state;

[0014] The temperature difference gradient between multiple nodes near the same heat source;

[0015] The thermal resistance change value is obtained by quantifying the temperature rise rate change under unit load, the temperature response delay time caused by fan speed change, the recovery time constant change rate required for the node temperature to fall back to steady state, and the temperature difference gradient offset between nodes near the same heat source, and calculating the weighted sum according to the preset weight;

[0016] When the thermal resistance change value is greater than the preset thermal resistance degradation threshold, it is determined that the path has a decrease in heat conduction ability;

[0017] Step three, determine the local thermal abnormal state:

[0018] The control system analyzes the operating state of each temperature sensing node in the continuous monitoring period, including:

[0019] a1, the temperature rise rate of the temperature sensing node is greater than or equal to the preset multiple of the temperature rise rate of its adjacent temperature sensing node;

[0020] a2, the stable temperature of the temperature sensing node is higher than its historical average temperature;

[0021] a3, the temperature change of the temperature sensing node does not accompany the synchronous rise of the main temperature or the shell temperature of the whole machine;

[0022] When all conditions a1, a2 and a3 are met, it is determined that the region corresponding to the temperature sensing node is in a local thermal abnormal state:

[0023] Step four, identify the hidden heat accumulation risk:

[0024] Jointly analyze the thermal resistance change value calculated in step two and the local thermal abnormal state identified in step three, including:

[0025] b1, the thermal resistance change value is greater than or equal to the thermal resistance degradation threshold;

[0026] b2, the local thermal abnormal state has been established;

[0027] b3, the main temperature monitoring mechanism has not triggered any overheating response signal in the current period;

[0028] When b1, b2, b3, the control system outputs a hidden heat accumulation risk identification signal;

[0029] Step five, execute local protection control response:

[0030] After the control system receives the hidden heat accumulation risk identification signal, according to the functional importance and operating load level of the module to which the risk area belongs, the corresponding local protection control strategy is executed;

[0031] Step six, update structure state evolution information:

[0032] During the execution of the protection control strategy and in the subsequent operation stage, the control system continuously records the thermal response parameters of each temperature sensing node (including temperature rise rate per unit load, temperature response delay, temperature recovery time constant), records the execution parameters of the executed local protection control strategy (used to represent the dynamic relationship between control action and device response), and collects and updates the heat resistance change value representing the change of heat conduction capacity, and accordingly constructs the device structure state evolution information set;

[0033] Based on the structure state evolution information set, the control system dynamically corrects the time evolution curve of the heat resistance change value, thereby optimizing the subsequent overheating protection threshold setting and device maintenance cycle arrangement strategy.

[0034] Further technical improvements of the present application are that when laying the temperature sensing nodes, the laying optimization is performed in combination with the functional level evaluation results of each functional module and the thermal coupling topological relationship between the modules, including:

[0035] A1, collect and quantify the influence parameters of each functional module in the communication path, power supply path and system operation stability, and calculate the functional level weight coefficient of the module;

[0036] A2, according to the physical arrangement structure, heat conduction path and heat conduction medium parameters of the functional module, calculate the thermal coupling strength coefficient between the modules, and construct the thermal coupling topological relationship between the modules;

[0037] A3, according to the functional level weight coefficient and the thermal coupling topological relationship, perform optimization calculation, determine the modules whose functional level weight coefficient is greater than a preset threshold or whose thermal coupling strength with the already laid temperature sensing nodes is lower than a preset lower limit as the preferred laying position of the temperature sensing nodes, and skip the modules whose functional level weight coefficient is lower than the lower limit and are covered by the coupling radius;

[0038] A4, generate a laying scheme according to the optimization results, and perform actual installation of sensors and system configuration adaptation.

[0039] Further technical improvements of the present application are as follows: in the process of extracting the heat dissipation path state parameters, the control system further calculates the temperature rise rate of each temperature sensing node under unit load respectively, and combines the structural thermal resistance from the temperature sensing node to the shell or the heat dissipation channel to obtain the judgment value of the temperature rise and the structural thermal resistance product of the temperature sensing node ;

[0040] When the coupling strength is greater than the preset lower limit value, and the condition that the main temperature monitoring mechanism does not trigger any overheating response signal in the current monitoring period is not met, it is determined that the region corresponding to the temperature sensing node has a structural heat conduction capacity decline trend, an auxiliary identification signal is output, and the auxiliary identification signal and the thermal resistance change value are jointly used as the input basis for subsequent local thermal anomaly state judgment and hidden heat accumulation risk identification.

[0041] Further technical improvements of the present application are as follows: in the process of extracting the heat dissipation path state parameters, when the control system extracts the recovery time constant required for the temperature of each temperature sensing node to fall back to the steady state, a steady state recognition boundary condition is set, the boundary condition includes a time section in which the node temperature change rate is lower than a preset steady state threshold value;

[0042] and in the time section that meets the steady state boundary condition, the temperature rise rate under unit load, the temperature response delay time caused by fan speed change and the temperature difference gradient offset are extracted, the correlation factor between the thermal response parameters is calculated, and the collaborative weighting coefficient is constructed based on the correlation factor. The collaborative weighting coefficient is applied to the weighting calculation process of the thermal resistance change value to enhance the physical correlation consistency between the thermal response parameters.

[0043] Further technical improvements of the present application are as follows: the control system calculates the temperature rise trend offset value and the fall back trend offset value of each node based on the temperature change trajectory of each temperature sensing node in the historical load period, and compares the temperature change trends of multiple temperature sensing nodes in the same load period;

[0044] When the temperature rise trend offset value or the fall back trend offset value of any temperature sensing node exceeds a set consistency judgment threshold value, the temperature data corresponding to the temperature sensing node is marked as unstable data and is excluded, and does not participate in the extraction of the thermal response parameters;

[0045] When the temperature rise trend offset value and the fall back trend offset value of all the compared temperature sensing nodes are within the consistency judgment threshold value, it is determined that the batch of temperature data meets the consistency condition, and is allowed to be used as the input data of the thermal response parameters.

[0046] Further technical improvements of the present application are as follows: the control system collects the external environment temperature parameter of the running environment of the network communication equipment in the process of executing the thermal resistance deterioration threshold determination and the local thermal anomaly state recognition;

[0047] When the external environment temperature is in the preset high temperature interval or the preset low temperature interval, the control system dynamically corrects the thermal resistance deterioration threshold and the temperature rise rate determination multiple based on the historical corresponding relationship between the external environment temperature and the thermal response parameter, so that the threshold determination result adapts to different environment temperature conditions, so as to avoid false triggering caused by external environment temperature fluctuation.

[0048] Further technical improvements of the present application are as follows: the control system collects the external environment temperature parameter of the running environment of the network communication equipment in the process of executing the thermal resistance deterioration threshold determination and the local thermal anomaly state recognition;

[0049] The communication behavior characteristics include network port data flow change rate, protocol stack switching frequency, central processing unit task switching times and device internal bus conflict frequency.

[0050] When the predicted thermal load level exceeds the preset thermal risk threshold, the control system executes at least one active heat dissipation control strategy including fan speed increase, module dynamic load reduction and running thread migration in advance under the condition that the temperature does not reach the overheat protection threshold.

[0051] Further technical improvements of the present application are as follows: in step six, the step of dynamically correcting the thermal resistance change value includes:

[0052] After the control system executes the local protection control strategy, the response effectiveness of the equipment to the protection action is evaluated based on the corresponding relationship between the temperature recovery curve of each temperature sensing node in the set time window and the executed control strategy parameter;

[0053] When the response effectiveness is lower than the preset threshold, a weighted offset algorithm is applied to the time evolution curve of the thermal resistance change value to improve the sensitivity of the thermal resistance deterioration judgment in the subsequent period;

[0054] When the response effectiveness continuously meets the stability standard, the thermal resistance change trend is smoothed to reduce the misjudgment probability and prolong the equipment maintenance cycle prediction time.

[0055] Compared with the prior art, the present application has the following beneficial effects:

[0056] The application constructs a thermal response sensing network based on multi-point temperature sensing nodes, improves the sensing accuracy of the device to different heat source distribution and heat diffusion path by comprehensively considering the function module layout and thermal coupling structure, can make the control system accurately master the spatial distribution and dynamic change trend of the internal thermal state of the device, thereby providing basic support for subsequent state analysis and risk judgment;

[0057] And, the application realizes dynamic identification of the thermal structure deterioration trend by establishing the quantitative correlation between the thermal response parameters and the thermal resistance change value; at the same time, by introducing the local thermal anomaly judgment logic and the masking type thermal accumulation risk identification mechanism, the identification ability of the complex thermal risk of local thermal runaway although the main temperature is not abnormal is effectively improved, and the thermal safety guarantee level of the device operation is enhanced;

[0058] On the other hand, the application realizes self-adaptive correction and threshold optimization of the thermal resistance judgment model through structure state evolution information set and feedback learning, realizes real-time recording and dynamic analysis of the protection strategy execution effect and the thermal response process, constructs a thermal protection closed loop system with self-learning ability, compared with the static threshold control scheme, the application can adjust the thermal management strategy according to the device itself operation history and environmental change, improves the adaptability and thermal control precision under long-term operation, has strong engineering applicability and popularization value; BRIEF DESCRIPTION OF DRAWINGS

[0059] In order to facilitate the understanding of those skilled in the art, the application will be further described below in conjunction with the drawings.

[0060] Figure 1 The method logic diagram of the application is shown. DETAILED DESCRIPTION

[0061] In order to further illustrate the technical means and effects adopted by the application to achieve the predetermined application purpose, the specific implementation, structure, features and effects according to the application are described in detail as follows in combination with the drawings and preferred embodiments.

[0062] Example 1

[0063] Please refer to Figure 1 The application provides a kind of overheating protection method of network communication equipment, including, a kind of overheating protection method of network communication equipment, the method includes the following steps:

[0064] Step one, establish multi-point temperature sensing node system:

[0065] In the network communication equipment, according to its function module layout and thermal coupling structure, set multiple temperature sensing nodes;

[0066] Temperature sensing nodes are arranged around typical heat generating units and establish data communication channels with the device control system to realize multi-point temperature data collection and time synchronization processing.

[0067] Specifically, the functional module layout is the physical arrangement and spatial distribution relationship of the internal functional units of the network communication device, including but not limited to PoE power supply module, Ethernet PHY chip set, radio frequency transceiver module, main controller, power conversion module, data processing chip, etc. The functional module layout determines the heat generating area, ventilation path, shell structure and heat density distribution characteristics of each module, and is the primary spatial reference basis in the temperature sensing node arrangement strategy.

[0068] The thermal coupling structure is the thermal path coupling relationship between multiple functional modules in the device due to the shared heat conduction channel, the existence of physical contact interface or structural thermal bridge, so that heat can be conducted, diffused or fed back between modules, including but not limited to:

[0069] Multiple modules share the same heat sink or copper foil layer;

[0070] Adjacent modules are connected through metal supports, heat sinks, and aluminum shells;

[0071] High heat density elements on the same circuit board are arranged compactly, and heat is superimposed on each other;

[0072] The thermal coupling structure will cause the temperature of adjacent modules to rise synchronously after a certain module generates heat, thereby forming a thermal influence linkage area, which is a factor that must be considered in temperature monitoring layout.

[0073] In this embodiment, the rules for arranging temperature sensing nodes based on functional module layout and thermal coupling structure are as follows:

[0074] For functional modules with high power density, continuous heat generating load or frequent working state (such as PoE power supply module, PHY array, power module), at least one temperature sensing node is set up around it to monitor the temperature rise in real time;

[0075] For module pairs or module groups with thermal coupling relationship, temperature sensing nodes are preferentially set at the thermal influence intersection area or the end of the common thermal path to capture local high temperature points in the heat diffusion process;

[0076] In the closed area, ventilation dead angle or poor heat convection area inside the device, if there is a heat accumulation trend according to the functional layout, an independent temperature sensing node should also be arranged as a local heat risk monitoring point;

[0077] The total number of temperature sensing nodes is determined comprehensively according to the number of modules, heat density level and structural thermal resistance characteristics; the spatial distance between adjacent nodes should not be greater than the typical thermal diffusion radius in the structure to ensure the accuracy of thermal response.

[0078] In the process of temperature sensing node deployment, the deployment optimization is performed in combination with the function level evaluation results of each function module and the thermal coupling topological relationship between modules, including:

[0079] A1, collect and quantify the influence parameters of each function module in the communication path, power supply path and system running stability, and calculate the function level weight coefficient of the module;

[0080] Specifically, the control system extracts the following three types of influence parameters according to the role of each function module in the communication path, power supply path or control path inside the network communication equipment:

[0081] The transmission level coefficient (L) of the position of the module in the data link: if the module is located in the main communication link or the core switching node, the L value takes high weight;

[0082] The electrical power level coefficient (P) of the module power supply capacity or PoE output load: high-power modules correspond to high-risk heat sources;

[0083] Module failure influence coefficient (F): according to historical failure influence records or backup fault tolerance capability, evaluate the system level influence that module failure may cause;

[0084] Then normalize L, P and F, and calculate the function level weight coefficient W of each module;

[0085] W= ; In the formula, 、 、 The weight parameter of the corresponding item is preset to ensure that the function level evaluation has quantitative basis.

[0086] A2, according to the physical arrangement structure, heat conduction path and heat conduction medium parameters of the function module, calculate the thermal coupling strength coefficient between modules, and construct the thermal coupling topological relationship between modules;

[0087] Specifically, according to the device structure arrangement and the thermal connection relationship between modules, the thermal coupling strength coefficient H between modules is calculated, which is composed of the following technical parameters:

[0088] The physical distance (d) between two modules;

[0089] The thermal conductivity (λ) of the intermediate heat conduction medium;

[0090] The contact area or the effective heat conduction cross section (A) of the path;

[0091] The passive heat dissipation path blocking factor (K) between heat paths;

[0092] Subsequently, the heat coupling strength between the mold i and the mold j is calculated by using the formula H = λ·A / (d·K) , and a heat coupling weighted graph between the modules is established.

[0093] A3, performing optimization calculation according to the function level weight coefficient and the heat coupling topological relationship, determining the module whose function level weight coefficient is greater than a preset threshold or whose heat coupling strength with the temperature sensing node that has been arranged is lower than a preset lower limit as a priority arrangement position of the temperature sensing node, and skipping the module whose function level weight coefficient is lower than the lower limit and which has been covered by the coupling radius;

[0094] Specifically, based on the function level weight coefficient W calculated in the A1 step and the heat coupling graph established in the A2 step, the following arrangement optimization algorithm is performed:

[0095] a31, sorting all function modules in descending order of W value;

[0096] a32, starting from the module with the highest W value, traversing the heat coupling graph in sequence, and preferentially arranging the temperature sensing node on the module that meets one of the following conditions:

[0097] The W value of the module is greater than or equal to a set function level arrangement threshold;

[0098] There is a sensing node in the heat coupling adjacent module of the module, and the coupling strength between the module and the configured node is <coupling strength lower limit value ;

[0099] a33, if there is a covering node within the heat coupling radius of the module and the W of the module is less than the function level lower limit , the configuration can be skipped.

[0100] A4, generating an arrangement scheme according to the optimization result, and performing actual installation of the sensor and system configuration adaptation.

[0101] Specifically, according to the module sensing arrangement list generated by the optimization algorithm, the system outputs a sensor arrangement scheme, including:

[0102] The arrangement position of the node in the structural space;

[0103] The connected module number and function level;

[0104] The mapping relationship with the heat coupling path;

[0105] Optional wiring path and transmission channel configuration parameters;

[0106] The arrangement scheme is written into the device configuration file or the control chip firmware as the structural design and system control parameters, realizing hardware landing and online control adaptation of the arrangement result.

[0107] Step two, extract heat dissipation path state parameters:

[0108] In the normal operation cycle of the device, the control system extracts the following thermal response parameters based on the historical temperature data collected by each temperature sensing node:

[0109] The temperature rise rate of each node under unit load;

[0110] The response delay between fan speed change and node temperature change;

[0111] The recovery time constant required for each node temperature to fall back to steady state;

[0112] The temperature difference gradient between multiple nodes near the same heat source;

[0113] By quantitatively processing the temperature rise rate change under unit load, the temperature response delay time caused by fan speed change, the recovery time constant required for the node temperature to fall back to steady state, and the temperature difference gradient offset between nodes near the same heat source, and calculating the thermal resistance change value by weighting according to the preset weight;

[0114] When the thermal resistance change value is greater than the preset thermal resistance degradation threshold, it is determined that the path has a decrease in heat conduction ability;

[0115] In this embodiment, the control system calculates the temperature rise trend offset value and the fall back trend offset value of each node based on the temperature change trajectory of each temperature sensing node in the historical load cycle, and compares the temperature change trends of multiple temperature sensing nodes in the same load cycle;

[0116] When the temperature rise trend offset value or the fall back trend offset value of any temperature sensing node exceeds the set consistency determination threshold, the temperature data corresponding to the temperature sensing node is marked as unstable data and is excluded, and does not participate in the extraction of thermal response parameters;

[0117] When the temperature rise trend offset value and the fall back trend offset value of all temperature sensing nodes participating in comparison are within the consistency determination threshold, it is determined that the batch of temperature data meets the consistency condition, and is allowed to be used as input data of thermal response parameters.

[0118] Step three, determine the local thermal abnormal state:

[0119] The control system analyzes the operating state of each temperature sensing node in the continuous monitoring period, including:

[0120] a1, the temperature rise rate of the temperature sensing node is greater than or equal to the preset multiple of the temperature rise rate of its adjacent temperature sensing nodes;

[0121] a2, the stable temperature of the temperature sensing node is higher than its historical average temperature;

[0122] a3, the temperature sensing node temperature change is not accompanied by a synchronous rise in the main temperature or the shell temperature of the entire machine;

[0123] When all of a1, a2, and a3 are met, it is determined that the area corresponding to the temperature sensing node is in a local thermal anomaly state:

[0124] Step four, identify the risk of hidden heat accumulation:

[0125] Jointly analyze the thermal resistance change value calculated in step two and the local thermal anomaly state identified in step three, including:

[0126] b1, the thermal resistance change value is greater than or equal to the thermal resistance degradation threshold;

[0127] b2, the local thermal anomaly state has been established;

[0128] b3, the main temperature monitoring mechanism has not triggered any overheating response signal in the current period;

[0129] When b1, b2, and b3 are met, the control system outputs a hidden heat accumulation risk identification signal;

[0130] Step five, execute local protection control response:

[0131] After the control system receives the hidden heat accumulation risk identification signal, according to the functional importance and operating load level of the module to which the risk area belongs, execute the corresponding local protection control strategy, including but not limited to:

[0132] Dynamically increase the fan speed of the risk area;

[0133] Reduce the operating frequency or power consumption limit of the risk module;

[0134] Enable backup paths or temporarily shield the risk module;

[0135] Report to the remote platform to trigger maintenance scheduling;

[0136] Step six, update the structure state evolution information:

[0137] During the execution of the protection control strategy and in the subsequent running stage, the control system continuously records the thermal response parameters of each temperature sensing node (including the temperature rise rate per unit load, temperature response delay, temperature recovery time constant), records the execution parameters of the executed local protection control strategy (used to represent the dynamic relationship between control action and device response), and collects and updates the thermal resistance change value representing the change in thermal conductivity. According to this, the structure state evolution information set of the device is constructed;

[0138] The control system dynamically corrects the time evolution curve of the thermal resistance change value based on the structure state evolution information set, thereby optimizing the subsequent overheat protection threshold setting and device maintenance cycle arrangement strategy.

[0139] The step of dynamically correcting the thermal resistance change value comprises:

[0140] After executing the local protection control strategy, the control system evaluates the response effectiveness of the device to the protection action based on the correspondence between the temperature recovery curve of each temperature sensing node within the set time window and the executed control strategy parameters;

[0141] When the response effectiveness is lower than the preset threshold, a weighted offset algorithm is applied to the time evolution curve of the thermal resistance change value to improve the sensitivity of thermal resistance degradation judgment in the subsequent cycle;

[0142] When the response effectiveness continuously meets the stability standard, the thermal resistance change trend is smoothed to reduce the probability of misjudgment and prolong the prediction time of the device maintenance cycle.

[0143] Specifically, the control system records the temperature recovery curve of each temperature sensing node within the set time window after each execution of the local protection control strategy, and records the execution parameters of the local protection control strategy at the same time;

[0144] The execution parameters include the execution duration, execution intensity, target module involved, speed adjustment amplitude of the controlled fan, or load reduction degree, etc. The control system evaluates the response effectiveness of the device to the protection action by analyzing the correspondence between the back-off rate, back-to-stable time, and temperature change trend of the temperature recovery curve and the execution parameters;

[0145] In this embodiment, the control system compares the temperature recovery curve with the preset reference recovery curve. If the temperature recovery curve does not reach the target back-to-stable interval within the set time window, the back-off rate is lower than the reference rate, or a rebound upward trend occurs, it is determined that the response effectiveness is lower than the preset response threshold;

[0146] At this time, the control system applies a weighted offset algorithm to the time evolution curve of the thermal resistance change value, increases the weight of the degradation trend in the thermal resistance change curve, and improves the sensitivity of thermal resistance degradation judgment in the subsequent cycle, thereby identifying the potential risk of reduced heat conduction capacity in advance.

[0147] And the control system collects preset communication behavior characteristics within the continuous operation cycle, and matches with the preset thermal load mapping model to predict the thermal load level that the device will reach within the future predetermined time window;

[0148] The communication behavior features include network port data traffic change rate, protocol stack switching frequency, central processing unit task switching times and device internal bus collision frequency.

[0149] When the predicted heat load level exceeds the preset heat risk threshold, the control system pre-executes at least one active heat dissipation control strategy including fan speed increase, module dynamic load reduction and running thread migration under the condition that the temperature does not reach the overheat protection threshold.

[0150] Embodiment 2

[0151] A heat protection method for a network communication device, the method comprising the following steps:

[0152] Step one, establish a multi-point temperature sensing node system:

[0153] In the network communication device, according to the functional module layout and thermal coupling structure, a plurality of temperature sensing nodes are set;

[0154] Step two, extract heat dissipation path state parameters:

[0155] In the normal running period of the device, the control system extracts the following thermal response parameters based on the historical temperature data collected by each temperature sensing node:

[0156] The temperature rise rate of each node under unit load;

[0157] The response delay between fan speed change and node temperature change;

[0158] The recovery time constant required for the temperature of each node to fall back to steady state;

[0159] The temperature difference gradient between multiple nodes near the same heat source;

[0160] By quantitatively processing the temperature rise rate change under unit load, the temperature response delay time caused by fan speed change, the recovery time constant required for the temperature of the node to fall back to steady state, and the temperature difference gradient offset between nodes near the same heat source, and calculating the heat resistance change value by weighting according to the preset weight, the heat resistance change value is obtained;

[0161] When the heat resistance change value is greater than the preset heat resistance degradation threshold, it is determined that the heat conduction ability of the path is decreased;

[0162] In the process of extracting the heat dissipation path state parameters, the control system further calculates the temperature rise rate of each temperature sensing node under unit load, and combines the structural thermal resistance from the temperature sensing node to the shell or the heat dissipation channel to obtain the determination value of the product of the temperature rise of the temperature sensing node and the structural thermal resistance ;

[0163] Determination value characterizing the heat accumulation trend of a certain node under the condition of weak local thermal conductivity, the greater the product, the more likely it is to occur local overheating under the same heat dissipation conditions;

[0164] When greater than the preset lower limit of coupling strength, and the condition of "the main temperature monitoring mechanism does not trigger any overheating response signal" is not met in the current monitoring period, it is determined that the region corresponding to the temperature sensing node has a structural heat conduction capacity decline trend, an auxiliary identification signal is output, and the auxiliary identification signal and the thermal resistance change value are jointly used as the input basis for subsequent local thermal abnormal state judgment and hidden heat accumulation risk identification.

[0165] Specifically, when the control system judges the hidden heat accumulation risk in step four, it further uses the auxiliary identification signal output based on the product of the temperature rise rate and the structural thermal resistance in step two as an input factor for heat dissipation path state judgment. When the auxiliary identification signal exists and the conditions of local thermal abnormal state judgment and main temperature monitoring mechanism not triggering abnormal response signal are met, a hidden heat accumulation risk identification signal can also be output, thereby improving the identification ability of atypical overheating risk caused by structural thermal degradation.

[0166] Step three, judge the local thermal abnormal state:

[0167] The control system analyzes the operating state of each temperature sensing node in the continuous monitoring period, including:

[0168] a1, the temperature rise rate of the temperature sensing node is greater than or equal to the preset multiple of the temperature rise rate of its adjacent temperature sensing node;

[0169] a2, the stable temperature of the temperature sensing node is higher than its historical average temperature;

[0170] a3, the temperature change of the temperature sensing node is not accompanied by the synchronous rise of the main temperature or the shell temperature of the whole machine;

[0171] In this embodiment, when the product of the temperature rise and the structural thermal resistance of a certain temperature sensing node exceeds the lower limit of coupling strength, it indicates that the node produces a disproportionate heat accumulation trend under unit load. At this time, even if the a1, a2 and a3 conditions are not completely met, this signal can be used as a pre-judgment trigger factor of local thermal abnormal state, that is:

[0172] If a temperature sensing node does not completely meet the a1-a3 conditions, but the corresponding value exceeds the lower limit of coupling strength, the system can include the node in the high heat risk monitoring object, trigger the subsequent state tracking mechanism, and regard it as a "to be diagnosed" abnormal node;

[0173] Step four, identify the hidden heat accumulation risk:

[0174] The thermal resistance change value calculated in step two is combined with the local thermal anomaly state identified in step three for joint analysis, including:

[0175] And the judgment logic in step four will become:

[0176] b11, the thermal resistance change value is greater than or equal to the thermal resistance degradation determination threshold, or there is an auxiliary identification signal;

[0177] b2, the local thermal anomaly state has been established;

[0178] b3, the main temperature monitoring mechanism in the current period has not triggered any overheating response signal;

[0179] When b11, b2, and b3 are met at the same time, the control system outputs a hidden heat accumulation risk identification signal.

[0180] Step five, execute local protection control response:

[0181] After the control system receives the hidden heat accumulation risk identification signal, according to the functional importance and operating load level of the module to which the risk area belongs, the corresponding local protection control strategy is executed;

[0182] Step six, update the structure state evolution information:

[0183] The control system continuously records the thermal response parameters of each temperature sensing node (including temperature rise rate per unit load, temperature response delay, temperature recovery time constant) during the execution of the protection control strategy and in the subsequent running stage, records the execution parameters of the executed local protection control strategy (used to represent the dynamic relationship between control action and device response), and collects and updates the thermal resistance change value representing the change of heat conduction ability, and accordingly constructs the device structure state evolution information set;

[0184] The control system dynamically corrects the time evolution curve of the thermal resistance change value based on the structure state evolution information set, thereby optimizing the subsequent overheating protection threshold setting and device maintenance cycle arrangement strategy.

[0185] Embodiment 3

[0186] A method for overheat protection of a network communication device, the method comprising the following steps:

[0187] Step one, in the network communication device, a plurality of temperature sensing nodes are set according to the functional module layout and thermal coupling structure;

[0188] Step two, extract the heat dissipation path state parameters:

[0189] In the normal running period of the device, the control system extracts the following thermal response parameters based on the historical temperature data collected by each temperature sensing node:

[0190] temperature rise rate of each node under unit load;

[0191] response delay between fan speed change and node temperature change;

[0192] recovery time constant required for temperature of each node to fall back to steady state;

[0193] temperature difference gradient between multiple nodes near the same heat source;

[0194] when the heat resistance change value is greater than the preset heat resistance degradation threshold, it is determined that the path has a heat conduction capacity decline phenomenon;

[0195] Compared with Embodiment 1 and Embodiment 2, in the process of extracting the heat dissipation path state parameters, Embodiment 3 sets the steady state identification boundary condition, takes the time period in which the node temperature change rate is lower than the preset steady state threshold as the effective extraction section of the recovery time constant, and takes the steady state period as the reference window to extract other thermal response parameters, including the temperature rise rate under unit load, the temperature response delay time caused by fan speed change, and the temperature difference gradient offset between multiple nodes near the same heat source;

[0196] Subsequently, based on the change trend and statistical coupling relationship between multiple sets of thermal response parameters, the correlation factor between the parameter pairs is calculated. In this embodiment, the calculation steps of the correlation factor include:

[0197] Firstly, the control system combines all available thermal response parameters in pairs to construct a parameter pair set;

[0198] The thermal response parameters at least include: temperature rise rate change under unit load, temperature response delay caused by fan speed change, recovery time constant change rate required for node temperature to fall back to steady state, and temperature difference gradient offset between multiple nodes. The parameter pairs formed thereby include, for example: combination of temperature rise rate and response delay, combination of temperature rise rate and temperature recovery time, combination of response delay and temperature difference gradient, etc.

[0199] Then, the control system extracts the change data of each parameter pair under multiple historical operation cycles, and arranges them in time sequence to form a data sequence with comparability. The control system ensures that the values of two parameters in the same time period correspond one by one, thereby maintaining consistency in time dimension;

[0200] Next, the control system calculates the correlation factor between the parameter pairs by statistical analysis method. The correlation factor is used to measure the degree of cooperation between two parameters, that is, whether the change of one parameter is statistically accompanied by the synchronous change of another parameter;

[0201] The correlation factor has a value range between -1 and 1, a positive value indicates that the two parameters have consistent trends, a negative value indicates that the trends are opposite, and the greater the absolute value, the stronger the correlation;

[0202] Finally, the system compares the correlation factor of all calculated parameter pairs with the set correlation validity threshold value, and only when the absolute value of the correlation factor of a parameter pair is greater than or equal to the correlation validity threshold value, it is determined that there is a significant statistical coupling relationship between the parameter pair, and it is used as a reference basis for subsequent thermal response model construction, feature compression or risk identification;

[0203] If the correlation factor is lower than the correlation validity threshold value, it is considered that there is no obvious correlation between the change trends of the parameter pair, and it is removed;

[0204] The temperature rise rate change ratio under unit load, the temperature response delay time caused by fan speed change, the recovery time constant change rate required for the node temperature to fall back to steady state, and the temperature difference gradient offset between nodes near the same heat source are quantitatively processed, and weighted calculation is performed according to the preset weight, and the correlation factor is introduced as a cooperative weighting coefficient to obtain the thermal resistance change value;

[0205] Compared with weighting only according to the preset static weight, the cooperative weighting mechanism can reflect the actual contribution and thermal physical consistency of each parameter under the current operating state, thereby enhancing the early response ability of the thermal resistance change value to the decline trend of the heat conduction ability, and improving the comprehensive identification accuracy of the local thermal abnormal state and the hidden heat accumulation risk.

[0206] Step three, the control system analyzes the operating state of the temperature sensing node, if the temperature rise rate of the temperature sensing node is higher than the preset multiple of the temperature rise rate of the adjacent node, and the stable temperature is higher than the historical average temperature, and the temperature change is not accompanied by the main temperature or the shell temperature rise, it is determined that it is in a local thermal abnormal state;

[0207] Step four, if the thermal resistance change value is greater than the thermal resistance degradation determination threshold value, the local thermal abnormal state is established, and the main temperature monitoring mechanism has not triggered the thermal response signal, the control system outputs the hidden heat accumulation risk identification signal;

[0208] Step five, the control system executes the preset local protection control strategy according to the functional importance and operating load level of the module to which the risk area belongs;

[0209] Step six, the control system records the thermal response parameters, control strategy execution parameters and thermal resistance change value of each temperature sensing node, constructs the structure state evolution information set of the device, and dynamically modifies the time evolution curve of the thermal resistance change value based on the structure state evolution information set.

[0210] Example 4

[0211] A method for overheat protection of a network communication device, the method comprising the steps of:

[0212] Step one, in the network communication device, a plurality of temperature sensing nodes are set according to the functional module layout and thermal coupling structure;

[0213] Step two, during the operation of the device, the control system extracts the heat dissipation path state parameters based on the historical temperature data collected by the temperature sensing nodes, including but not limited to the temperature rise rate under unit load, fan response delay, temperature recovery time constant and temperature difference gradient, and calculates the thermal resistance change value accordingly;

[0214] When the thermal resistance change value is greater than the preset thermal resistance degradation threshold, it is determined that the heat dissipation path has a decrease in heat conduction capacity;

[0215] Compared with embodiment 1, embodiment 2, embodiment 3, the control system in embodiment 4 collects the external environment temperature parameters of the running environment of the network communication device in the process of executing the thermal resistance degradation threshold determination and local thermal anomaly state recognition;

[0216] When the external environment temperature is in the preset high temperature interval or the preset low temperature interval, the control system dynamically corrects the thermal resistance degradation threshold and the temperature rise rate determination multiple based on the historical corresponding relationship between the external environment temperature and the thermal response parameters, so that the threshold determination result adapts to different environmental temperature conditions, in order to avoid false triggering caused by external environmental temperature fluctuation.

[0217] Specifically, the control system collects the current external environment temperature value in real time through the temperature sensor arranged outside the device running environment, and compares it with the set environment temperature state classification table;

[0218] The classification table divides the external environment temperature into high temperature interval, normal temperature interval and low temperature interval, and each interval corresponds to a set of thermal response adjustment coefficients (including thermal resistance degradation threshold correction coefficient and temperature rise rate correction coefficient).

[0219] When the currently collected external environment temperature falls into the high temperature interval or the low temperature interval, the control system selects the corresponding coefficient set from the adjustment coefficient set, which is respectively recorded as: thermal resistance degradation threshold correction coefficient and temperature rise rate determination multiple correction coefficient.

[0220] In the thermal resistance change value and temperature rise rate related determination link, the following correction formula is used for dynamic adjustment:

[0221] Dynamic thermal resistance degradation threshold = system set basic thermal resistance degradation threshold x thermal resistance degradation threshold correction coefficient;

[0222] Dynamic temperature rise rate multiple = basic multiple determination threshold x temperature rise rate determination multiple correction coefficient.

[0223] When the obtained thermal resistance change value ≥ dynamic thermal resistance deterioration threshold value, and the current node temperature rise rate ≥ (adjacent node temperature rise rate × dynamic temperature rise rate multiplier), the control system continues to execute subsequent local thermal abnormality state recognition and concealed heat accumulation risk recognition logic based on dynamic correction determination rules.

[0224] Step three, the control system analyzes the operating state of the temperature sensing node, if the temperature sensing node temperature rise rate is higher than the preset multiplier of the adjacent node temperature rise rate, and the stable temperature is higher than the historical average temperature, and the temperature change is not accompanied by the main temperature or the shell temperature rise, it is determined that it is in a local thermal abnormality state;

[0225] Step four, if the thermal resistance change value is greater than the thermal resistance deterioration determination threshold value, the local thermal abnormality state is established, and the main temperature monitoring mechanism has not triggered the overheat response signal, the control system outputs a concealed heat accumulation risk recognition signal;

[0226] Step five, the control system executes the preset local protection control strategy according to the functional importance and operating load level of the module to which the risk area belongs;

[0227] Step six, the control system records the thermal response parameters, control strategy execution parameters and thermal resistance change values of each temperature sensing node, constructs the structural state evolution information set of the device, and dynamically corrects the time evolution curve of the thermal resistance change value based on the structural state evolution information set.

[0228] The above formulas are dimensionless numerical calculations, the formulas are obtained by collecting a large amount of data to simulate a formula of the most recent real situation, and the preset parameters and threshold values in the formula are set by a person skilled in the art according to the actual situation.

[0229] The above is only a preferred embodiment of the present application, and is not intended to limit the present application in any form. Although the present application has been disclosed as above with a preferred embodiment, it is not intended to limit the present application. Any person skilled in the art can make some changes or modifications to the above disclosed technical content without departing from the scope of the technical solution of the present application, and any simple modification, equivalent change and modification of the above embodiment according to the technical essence of the present application are still within the scope of the technical solution of the present application.

Claims

1. A method for overheat protection of a network communication device, characterized in that, include: Step 1: Inside the network communication equipment, based on the functional module layout and thermal coupling structure, set up multiple temperature sensing nodes; Step 2: During equipment operation, the control system extracts the heat dissipation path status parameters based on the historical temperature data collected by the temperature sensing nodes, and calculates the thermal resistance change value accordingly. When the thermal resistance change value is greater than the preset thermal resistance degradation threshold, it is determined that the heat dissipation path has a reduced heat conduction capacity. Step 3: The control system analyzes the operating status of the temperature sensing node. If the temperature rise rate of the temperature sensing node is higher than the preset multiple of the temperature rise rate of the neighboring nodes, and the stable temperature is higher than its historical average temperature, and the temperature change is not accompanied by an increase in the main temperature or shell temperature, then it is determined to be in a local thermal anomaly state. Step 4: If the change in thermal resistance is greater than the threshold for judging thermal resistance deterioration, a local thermal anomaly is established, and the main temperature monitoring mechanism does not trigger an overheating response signal, then the control system outputs a masked heat accumulation risk identification signal. Step 5: After receiving the cover-up heat accumulation risk identification signal, the control system executes the preset local protection control strategy based on the functional importance and operating load level of the module to which the risk area belongs. Step 6: The control system records the thermal response parameters, control strategy execution parameters, and thermal resistance change values ​​of each temperature sensing node, constructs a set of structural state evolution information for the equipment, and dynamically corrects the time evolution curve of the thermal resistance change value based on this set of structural state evolution information.

2. The overheat protection method for a network communication device according to claim 1, characterized in that, The heat dissipation path status parameters include the following thermal response parameters: The rate of change of temperature rise under unit load, the temperature response delay time caused by fan speed change, the rate of change of recovery time constant required for node temperature to fall back to steady state, and the temperature gradient offset between nodes near the same heat source. The method for obtaining the thermal resistance change value is to calculate the value by weighting the various thermal response parameters according to preset weights.

3. The overheat protection method for a network communication device according to claim 2, characterized in that, When deploying temperature sensing nodes, deployment optimization is performed by combining the functional level evaluation results of each functional module with the thermal coupling topology between modules, including: A1. Collect and quantify the impact parameters of each functional module on the communication path, power supply path and system operation stability, and calculate the functional level weight coefficient of the module. A2. Based on the physical layout, heat conduction path, and heat conduction medium parameters of the functional modules, calculate the thermal coupling strength coefficient between the modules and construct the thermal coupling topology between the modules. A3. Based on the functional level weight coefficient and the thermal coupling topology relationship, perform optimization calculations and determine the modules with functional level weight coefficients greater than the preset threshold or thermal coupling strength with the deployed temperature sensing nodes lower than the preset lower limit as the priority deployment positions for temperature sensing nodes, and skip modules with functional level weight coefficients lower than the lower limit and already covered by the coupling radius. A4. Generate a deployment plan based on the optimization results, and carry out the actual installation of sensors and system configuration adaptation.

4. The overheat protection method for a network communication device according to claim 2, characterized in that, During the process of extracting the state parameters of the heat dissipation path, the control system further calculates the temperature rise rate of each temperature sensing node under a unit load, and combines the structural thermal resistance from the temperature sensing node to the shell or heat dissipation channel to obtain the determination value of the product of the temperature rise and the structural thermal resistance of the temperature sensing node. When the temperature exceeds the preset lower limit of coupling strength and the condition that "the main temperature monitoring mechanism has not triggered any overheating response signal" is not met within the current monitoring cycle, it is determined that the area corresponding to the temperature sensing node has a decreasing trend in structural thermal conductivity. An auxiliary identification signal is output, and this auxiliary identification signal is combined with the thermal resistance change value as the input basis for subsequent local thermal anomaly state determination and covert heat accumulation risk identification.

5. The overheat protection method for a network communication device according to claim 2, characterized in that, During the process of extracting the state parameters of the heat dissipation path, when the control system extracts the recovery time constant required for the temperature of each temperature sensing node to fall back to steady state, it sets steady state identification boundary conditions, including the time period when the node temperature change rate is lower than the preset steady state threshold. Within the time interval that satisfies the steady-state boundary conditions, the temperature rise rate under unit load, the temperature response delay time caused by changes in fan speed, and the temperature gradient offset are extracted. Correlation factors between various thermal response parameters are calculated, and a co-weighted coefficient is constructed based on the correlation factors. The co-weighted coefficient is then applied to the weighted calculation of thermal resistance change values ​​to enhance the physical consistency between thermal response parameters.

6. The overheat protection method for a network communication device according to claim 3, characterized in that, Based on the temperature change trajectory of each temperature sensing node within the historical load cycle, the control system calculates the temperature rise trend offset value and fall trend offset value of each node, and compares the temperature change trends of multiple temperature sensing nodes within the same load cycle. When the temperature rise trend deviation or fall trend deviation of any temperature sensing node exceeds the set consistency judgment threshold, the temperature data corresponding to that temperature sensing node is marked as unstable data and removed, and will not be included in the extraction of thermal response parameters. When the temperature rise trend offset and fall trend offset of all temperature sensing nodes participating in the comparison are within the consistency judgment threshold, it is determined that the batch of temperature data meets the consistency condition and is allowed to be used as input data for thermal response parameters.

7. The overheat protection method for a network communication device according to claim 2, characterized in that, During the process of determining the thermal resistance degradation threshold and identifying local thermal anomalies, the control system collects the external ambient temperature parameters of the operating environment of the network communication equipment. When the external ambient temperature is within the preset high temperature range or the preset low temperature range, the control system dynamically corrects the thermal resistance degradation threshold and the temperature rise rate judgment multiple based on the historical correspondence between the external ambient temperature and the thermal response parameters, so that the threshold judgment result can adapt to different ambient temperature conditions, thereby avoiding false triggering caused by fluctuations in the external ambient temperature.

8. The overheat protection method for a network communication device according to claim 6, characterized in that, The control system collects preset communication behavior characteristics during continuous operation cycles and matches them with preset heat load mapping models to predict the heat load level that the equipment will reach within a predetermined time window in the future. When the predicted heat load level exceeds the preset heat risk threshold, the control system will pre-execute at least one active heat dissipation control strategy, including increasing fan speed, dynamically reducing module load, and migrating running threads, provided that the temperature does not reach the overheat protection threshold.

9. A method for overheat protection of a network communication device according to claim 8, characterized in that, Step six, the step of dynamically correcting the change in thermal resistance, includes: After executing the local protection control strategy, the control system evaluates the effectiveness of the equipment's response to the protection action based on the correspondence between the temperature recovery curves of each temperature sensing node within a set time window and the parameters of the executed control strategy. When the response effectiveness is lower than the preset threshold, a weighted offset algorithm is applied to the time evolution curve of the thermal resistance change value to improve the sensitivity of thermal resistance degradation judgment in subsequent cycles. When the response effectiveness continuously meets the stability criteria, the trend of thermal resistance change is smoothed to reduce the probability of misjudgment and extend the equipment maintenance cycle prediction time.

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