Fitting temperature monitoring data random competition access cross-layer optimization method and system

Abstract

The invention provides a fitting temperature monitoring data random competition access cross-layer optimization method and system, and the method comprises the steps: obtaining the battery voltage monitoring data and temperature data of a fitting temperature measurement sensor, and obtaining the receiving sensitivity of a last successful communication process; judging the temperature data based on the voltage monitoring data to obtain a judgment result; and setting or calculating sending power and data sending interval parameters based on the receiving sensitivity of the last successful communication process and the judgment result, and optimizing a communication protocol transmission strategy of the hardware fitting temperature measurement sensor. According to the invention, the random competition access data transmission cross-layer optimization strategy fusing a physical layer, a link layer and an application layer is realized by considering the battery electric quantity of the sensor, the receiving sensitivity and the criticality of monitoring data and aiming at the application requirement of extremely low power consumption of line hardware temperature measurement, so that the operation power consumption of the hardware temperature measurement sensor is further reduced; and the endurance time is prolonged while the priority communication success of the dangerous data is ensured.

Description

Technical Field

[0001] The present invention relates to the field of operation and maintenance of transmission lines, and particularly to a cross-layer optimization method and system for random competition access of fitting temperature monitoring data. Background Art

[0002] With the rapid development of the national economy, the demand for electricity in all walks of life is increasing, and the quality requirements for the power supply provided by the power supply department are also getting higher and higher. Therefore, the safety of the power grid operation of long-distance high-voltage transmission lines is particularly important. Combining with the development of smart grids, more and more intelligent devices are needed to monitor the safety and operation information of the lines.

[0003] Line fittings are the guarantee for the safe and stable operation of the line. In actual operation, the temperature of the fittings will rise due to reasons such as induced circulating current between overhead ground wires, fitting wear, and electrochemical corrosion. If the temperature of the line fittings is monitored in real time and the most real operation data is obtained, the stable operation of the line can be maximally improved, and the most real and reliable guidance can be provided for dispatching, maintenance, and operation. In addition, for some key lines, it can also play a good monitoring role. In daily operation, once the abnormal temperature rise of the fittings is detected, the cause can be immediately found out and measures can be taken to make the power grid operation safer and more reliable.

[0004] At present, most of the fitting temperature sensors are installed on the strain clamps of the line. They are small in size and generally do not have a charging unit such as a solar panel. Therefore, disposable batteries are usually used, which puts very high requirements on the power consumption control of the sensors. At the same time, the sensors use wireless data transmission methods, and the power consumption during data transmission is the largest. Therefore, it is necessary to optimize and control the data transmission process to further improve the battery life of the sensors.

[0005] In order to reduce the power consumption of data transmission, the transmission of temperature measurement data is based on the IEEE802.15.4 protocol. Generally, a non-slotted CSMA-CA channel access mechanism (i.e., a random competition access mechanism) is adopted. When sending a data frame each time, an arbitrarily long period needs to be waited. After this arbitrary backoff time, if the sensor finds that the channel is idle, it will send the data frame; otherwise, if it finds that the channel is busy, it will wait for an arbitrarily long period and then try to access the channel again. For the acknowledgment frame, when sending, the CSMA-CA mechanism is not adopted, that is, after receiving the data frame, the data receiving end directly sends the acknowledgment frame regardless of whether there is a conflict in the current channel. The sensor judges whether the data is successfully sent according to whether the correct acknowledgment frame is received.

[0006] The traditional random competition access method mainly measures the data transmission stability by whether the acknowledgment frame is received by the sensor, without considering the timing monitoring characteristics of the fitting temperature sensor. Summary of the Invention

[0007] To solve the problem that the traditional random access method mainly measures the data transmission stability by confirming whether the frame is received by the sensor, without considering the timing monitoring characteristics of the fitting temperature sensor, the present invention proposes a cross-layer optimization method for random access of fitting temperature monitoring data, including:

[0008] Obtain the battery voltage monitoring data and temperature data of the fitting temperature sensor, and obtain the receiving sensitivity of the previous successful communication process;

[0009] Based on the voltage monitoring data, discriminate the temperature data to obtain a discrimination result;

[0010] Based on the receiving sensitivity of the previous successful communication process and the discrimination result, set or calculate the transmission power and data transmission interval parameters, and optimize the communication protocol transmission strategy of the fitting temperature sensor.

[0011] Optionally, the discriminating the temperature data based on the voltage monitoring data to obtain a discrimination result includes:

[0012] Determine the voltage level based on the voltage monitoring data, and determine the set temperature data threshold from the voltage level;

[0013] Judge whether the temperature data exceeds the set temperature data threshold, and obtain that the temperature data exceeds the set temperature data threshold, or the temperature data does not exceed the set temperature data threshold;

[0014] Wherein, the discrimination result includes: the temperature data exceeds the set temperature data threshold and the temperature data does not exceed the set temperature data threshold.

[0015] Optionally, the setting or calculating the transmission power and data transmission interval parameters based on the receiving sensitivity of the previous successful communication process and the discrimination result, and optimizing the communication protocol transmission strategy of the fitting temperature sensor includes:

[0016] When the discrimination result is that the temperature data exceeds the set temperature data threshold, perform channel listening after each monitoring data is sent until an acknowledgment frame is received. Meanwhile, send data with the maximum transmission power;

[0017] When the discrimination result is that the temperature data does not exceed the set temperature data threshold, calculate the transmission power and data transmission interval parameters according to the voltage monitoring data and the receiving sensitivity, and directly enter the sleep mode after each monitoring data is sent.

[0018] Optionally, the transmission power is calculated according to the following formula:

[0019]

[0020] Wherein, S is the wireless transmission transmit power of the sensor, S0 is the wireless transmission reference transmit power of the sensor, i is the receiving sensitivity level number, t is the fitting temperature monitoring data, and t max is the temperature data threshold value.

[0021] Optionally, the data transmission interval parameter is set according to the following formula:

[0022]

[0023] Wherein, t is the fitting temperature monitoring data, and t max is the temperature data threshold value, t1 is the monitoring interval duration of the fitting temperature sensor, j is the battery voltage level number, and Δt is the data transmission interval parameter.

[0024] On the other hand, the present invention further provides a cross-layer optimization system for random access competition of fitting temperature monitoring data, including:

[0025] A parameter acquisition module, configured to acquire the battery voltage monitoring data and temperature data of the fitting temperature sensor, and acquire the receiving sensitivity of the previous successful communication process;

[0026] A judgment module, configured to discriminate the temperature data based on the voltage monitoring data to obtain a discrimination result;

[0027] An optimization module, configured to set or calculate the transmit power and data transmission interval parameter based on the receiving sensitivity of the previous successful communication process and the discrimination result, and optimize the communication protocol transmission strategy of the fitting temperature sensor.

[0028] Optionally, the judgment module includes:

[0029] A threshold selection sub-module, configured to determine the voltage level based on the voltage monitoring data, and determine the set temperature data threshold value from the voltage level;

[0030] A temperature judgment sub-module, configured to judge whether the temperature data exceeds the set temperature data threshold value, and obtain that the temperature data exceeds the set temperature data threshold value, or the temperature data does not exceed the set temperature data threshold value;

[0031] Wherein, the discrimination result includes: the temperature data exceeds the set temperature data threshold value and the temperature data does not exceed the set temperature data threshold value.

[0032] Optionally, the optimization module is specifically configured to:

[0033] When the discrimination result is that the temperature data exceeds the set temperature data threshold, channel listening is performed after each monitoring data is sent until an acknowledgment frame is received. Meanwhile, data is sent using the maximum transmission power.

[0034] When the discrimination result is that the temperature data does not exceed the set temperature data threshold, the transmission power and data transmission interval parameters are calculated based on the voltage monitoring data and the reception sensitivity. After each monitoring data is sent, the device directly enters the sleep mode.

[0035] Optionally, the optimization module calculates the transmission power according to the following formula:

[0036]

[0037] In the formula, S is the wireless transmission power of the sensor, S0 is the wireless transmission reference power of the sensor, i is the reception sensitivity level number, t is the fitting temperature monitoring data, and t max is the temperature data threshold.

[0038] Optionally, the optimization module calculates the data transmission interval parameter according to the following formula:

[0039]

[0040] In the formula, t is the fitting temperature monitoring data, and t max is the temperature data threshold, t1 is the monitoring interval duration of the fitting temperature sensor, j is the battery voltage level number, and Δt is the data transmission interval parameter.

[0041] On the other hand, the present application also provides a computing device, including: one or more processors;

[0042] The processor is used to execute one or more programs;

[0043] When the one or more programs are executed by the one or more processors, a cross-layer optimization method for random access of fitting temperature monitoring data as described above is implemented.

[0044] On the other hand, the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed, a cross-layer optimization method for random access of fitting temperature monitoring data as described above is implemented.

[0045] Compared with the prior art, the beneficial effects of the present invention are:

[0046] The present invention provides a cross-layer optimization method for random access of fitting temperature monitoring data, including: obtaining the battery voltage monitoring data and temperature data of the fitting temperature sensor, and obtaining the receiving sensitivity of the last successful communication process; discriminating the temperature data based on the voltage monitoring data to obtain a discrimination result; setting or calculating the transmission power and data transmission interval parameters based on the receiving sensitivity of the last successful communication process and the discrimination result, and optimizing the communication protocol transmission strategy of the fitting temperature sensor. By considering the sensor battery power, receiving sensitivity, and urgency of the monitoring data, the present invention realizes a cross-layer optimization strategy for random access data transmission that integrates the physical layer, link layer, and application layer for the application requirements of extremely low power consumption in fitting temperature measurement, further reducing the operating power consumption of the fitting temperature sensor, ensuring the priority successful communication of dangerous data, and improving the battery life. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is a flowchart of a cross-layer optimization method for random access of fitting temperature monitoring data according to the present invention;

[0048] Figure 2 is a data transmission flowchart of the fitting temperature sensor according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] Considering the regular monitoring characteristics of the fitting temperature sensor, the present invention improves the random access and data transmission mechanism of the sensor, comprehensively considers the sensor power, urgency of the monitoring data, and receiving sensitivity, flexibly changes the data transmission strategy, further reduces the data transmission power consumption, and optimizes the battery life of the sensor.

[0050] The data length of the fitting temperature sensor is relatively fixed and the data field is simple and short. Based on the IEEE802.15.4 protocol, the present invention takes the data transmission process of the fitting temperature sensor as the research object, improves the random access and data transmission mechanism of the sensor, includes parameters such as sensor power, urgency of the monitoring data, and receiving sensitivity in the consideration range, and realizes automatic and flexible adjustment of the sensor sending frequency, transmission power, and acknowledgment frame receiving strategy, significantly reducing the data transmission power consumption.

[0051] Embodiment 1

[0052] A cross-layer optimization method for random access of fitting temperature monitoring data, as Figure 1 shown, includes:

[0053] Step 1: Obtain the battery voltage monitoring data and temperature data of the fitting temperature sensor, and obtain the receiving sensitivity of the last successful communication process;

[0054] Step 2: Discriminate the temperature data based on the voltage monitoring data to obtain a discrimination result;

[0055] Step 3: Based on the receiving sensitivity of the previous successful communication process and the discrimination result, set or calculate the transmission power and data transmission interval parameters to optimize the communication protocol transmission strategy of the fitting temperature measurement sensor.

[0056] The following Figure 2 further introduces a cross-layer optimization method for random access of fitting temperature monitoring data provided by the present invention:

[0057] Under default conditions, the monitoring interval of the fitting temperature measurement sensor is 10 minutes, denoted as t1. That is, the monitoring results are reported to the data receiving device via wireless transmission once every 10 minutes. The following optimizes based on this mode.

[0058] Step 1: Obtain the battery voltage monitoring data and temperature data of the fitting temperature measurement sensor, and obtain the receiving sensitivity of the previous successful communication process, specifically including:

[0059] 1) Conduct battery voltage monitoring. The initial voltage V0 of the battery of the fitting temperature measurement sensor is 3.6V, and 2.6V is the working cut-off voltage. That is, when the remaining voltage is lower than 2.6V, the device is considered to be in a power-off state. The battery voltage is divided every 0.2V, denoted as V j (j = 1 to 5);

[0060] 2) Conduct receiving sensitivity monitoring. In the IEEE802.15.4 protocol, the receiving sensitivity is calculated during channel sensing. The receiving sensitivity is related to the distance between the sensor and the data receiving device. The closer the distance, the lower the receiving sensitivity. Taking -90dBm as the cut-off receiving sensitivity, when it is lower than this value, the communication can be considered interrupted. Therefore, the receiving sensitivity is divided into one gear every 10dBm, and is divided into a total of 7 gears above -30dBm, -30dBm to -40dBm, -40dBm to -50dBm, -50dBm to -60dBm, -60dBm to -70dBm, -70dBm to -80dBm, -80dBm to -90dBm, denoted as R i (i = 1 to 7). Correspondingly, the wireless transmission transmit power S of the sensor is based on 0dBm, that is, S0 = 0dBm, and is dynamically adjusted according to the receiving sensitivity.

[0061] 3) Collect temperature data. Collect the fitting temperature data according to the monitoring interval duration.

[0062] The fitting temperature measurement sensor is fixed on the bolt of the strain clamp through a pressure plate, and the temperature sensor is in contact with the strain clamp to realize on-line measurement of the strain clamp temperature, and the fitting temperature is collected through the temperature sensor.

[0063] Step 2: Discriminate the temperature data based on the voltage monitoring data to obtain a discrimination result, specifically including:

[0064] Perform temperature data discrimination. Set the temperature data threshold to t according to different voltage levels max . The discrimination result is that the temperature data exceeds the set temperature data threshold t max and the temperature data does not exceed the set temperature data threshold t max .

[0065] Step 3: Based on the receiving sensitivity of the previous successful communication process and the discrimination result, set or calculate the transmission power and data transmission interval parameters, and optimize the communication protocol transmission strategy of the fitting temperature measurement sensor, specifically including:

[0066] When the fitting temperature monitoring data t > t max , then perform channel listening after each monitoring data is sent until an acknowledgment frame is received. At the same time, use the maximum transmission power S max for data transmission (10 dBm) to ensure data arrival; when the fitting temperature monitoring data t ≤ t max , then do not listen to the channel for an acknowledgment frame after each monitoring data is sent, directly enter the sleep mode, and regard each data transmission as a broadcast form to further reduce the operating power consumption.

[0067] Integrate the above criteria to optimize the communication protocol transmission strategy of the fitting temperature measurement sensor:

[0068] When sending data once, the transmission power of the physical layer is determined by the receiving sensitivity obtained from the previous successful communication process, and the transmission power is changed until the next receiving sensitivity is obtained. Therefore, the physical layer transmission power S parameter in the communication process is set as:

[0069]

[0070] In the formula, S is the wireless transmission power of the sensor, S0 is the wireless transmission reference power of the sensor, i is the receiving sensitivity level number, t is the fitting temperature monitoring data, t max is the temperature data threshold.

[0071] At the same time, the data transmission interval parameter in the communication process is set as:

[0072]

[0073] In the formula, t is the fitting temperature monitoring data, t max is the temperature data threshold, t1 is the monitoring interval duration of the fitting temperature measurement sensor, j is the battery voltage level number, and Δt is the data transmission interval parameter.

[0074] A cross-layer optimization method for random access of fitting temperature monitoring data provided by the present invention is as follows Figure 2 shown and the specific content is as follows:

[0075] The fitting temperature sensor is started;

[0076] The temperature data is read;

[0077] Is the temperature above the threshold?

[0078] When the temperature is above the threshold, set the maximum transmission power and the shortest data transmission interval, and continue to determine whether an acknowledgment frame is received. If an acknowledgment frame is received, enter the sleep state; otherwise, send again until an acknowledgment frame is received;

[0079] When the temperature is not above the threshold, calculate the corresponding transmission power and data transmission interval parameters according to the battery voltage and receiving sensitivity, send the monitoring data and enter the sleep state.

[0080] By considering the battery power of the sensor, receiving sensitivity, and criticality of the monitoring data, the present invention realizes a cross-layer optimization strategy for random access data transmission that integrates the physical layer, link layer, and application layer based on the IEEE802.15.4 protocol for the application requirement of extremely low power consumption of fitting temperature measurement. It further reduces the operating power consumption of the fitting temperature measurement sensor, ensures the priority communication success of dangerous data, and improves the battery life.

[0081] Embodiment 2

[0082] The fitting temperature measurement sensor is powered by a 3.6V 1000mAh lithium thionyl chloride battery, which is small in size and does not have functional components such as photovoltaic energy harvesting. The fitting temperature measurement sensor is fixed on the bolt of the strain clamp through a pressing plate, and the temperature sensor is in close contact with the strain clamp through a contact method to realize the on-line measurement of the strain clamp temperature.

[0083] The fitting temperature measurement sensor communicates stably with the data transmission base station on the tower based on the IEEE802.15.4 protocol, and the communication distance is basically within 50 meters. After receiving the temperature monitoring data, the data transmission base station transmits the data back to the background main station through methods such as a 4G remote communication unit.

[0084] When the temperature is within the normal range of line operation, before each data transmission, the sensor automatically calculates the transmission power and data transmission interval according to its own state, effectively extending the on-line time; when the temperature at the monitoring point is abnormal and situations such as bolt loosening and abnormal heating of the clamp may occur, the transmission power is automatically adjusted to the maximum and the data transmission interval is adjusted to the shortest to ensure that the alarm data reaches the data transmission base station as quickly as possible. Furthermore, according to the monitoring data and status data of the sensor, cross-layer unified optimization of the communication protocol and application data is realized.

[0085] Example 3

[0086] Based on the same inventive concept, the present invention also provides a cross-layer optimization system for random competition access of fitting temperature monitoring data, including:

[0087] A parameter acquisition module, configured to acquire the battery voltage monitoring data and temperature data of the fitting temperature sensor, and acquire the receiving sensitivity of the previous successful communication process;

[0088] A judgment module, configured to discriminate the temperature data based on the voltage monitoring data to obtain a discrimination result;

[0089] An optimization module, configured to set or calculate the transmission power and data transmission interval parameters based on the receiving sensitivity of the previous successful communication process and the discrimination result, and optimize the communication protocol transmission strategy of the fitting temperature sensor.

[0090] Optionally, the judgment module includes:

[0091] A threshold selection sub-module, configured to determine the voltage level based on the voltage monitoring data, and determine the set temperature data threshold from the voltage level;

[0092] A temperature judgment sub-module, configured to judge whether the temperature data exceeds the set temperature data threshold, and obtain that the temperature data exceeds the set temperature data threshold, or the temperature data does not exceed the set temperature data threshold;

[0093] Wherein, the discrimination result includes: the temperature data exceeds the set temperature data threshold and the temperature data does not exceed the set temperature data threshold.

[0094] Optionally, the optimization module is specifically configured to:

[0095] When the discrimination result is that the temperature data exceeds the set temperature data threshold, perform channel listening after each monitoring data is sent until an acknowledgment frame is received. At the same time, use the maximum transmission power for data transmission;

[0096] When the discrimination result is that the temperature data does not exceed the set temperature data threshold, calculate the transmission power and data transmission interval parameters according to the voltage monitoring data and the receiving sensitivity, and directly enter the sleep mode after each monitoring data is sent.

[0097] Optionally, the optimization module calculates the transmission power according to the following formula:

[0098]

[0099] Wherein, S is the wireless transmission transmit power of the sensor, S0 is the wireless transmission reference transmit power of the sensor, i is the receiving sensitivity level number, t is the fitting temperature monitoring data, and t max is the temperature data threshold value.

[0100] Optionally, the optimization module calculates the data sending interval parameter according to the following formula:

[0101]

[0102] Wherein, t is the fitting temperature monitoring data, and t max is the temperature data threshold value, t1 is the monitoring interval duration of the fitting temperature sensor, j is the battery voltage level number, and Δt is the data sending interval parameter.

[0103] Embodiment 3:

[0104] Based on the same inventive concept, the present invention further provides a computer device, which includes a processor and a memory. The memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function, so as to implement the steps of a random access cross-layer optimization method for fitting temperature monitoring data in the above embodiment.

[0105] Embodiment 4:

[0106] Based on the same inventive concept, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory). The computer-readable storage medium is a memory device in a computer device, used to store programs and data. It can be understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and, of course, the extended storage medium supported by the computer device. The computer-readable storage medium provides a storage space, and this storage space stores the operating system of the terminal. Moreover, in this storage space, there is also stored one or more instructions suitable for being loaded and executed by a processor. These instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The one or more instructions stored in the computer-readable storage medium can be loaded and executed by the processor to implement the steps of a cross-layer optimization method for random access of fitting temperature monitoring data in the above-mentioned embodiments.

[0107] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0108] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0109] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and this instruction device implements the functions in Figure 1 one flow or multiple flows and / or blocksFigure 1 The functions specified in one or more boxes.

[0110] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide for implementing the steps of the functions specified in one Figure 1 process or multiple processes and / or boxes Figure 1 or more boxes.

[0111] The above are only embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A cross-layer optimization method for random competition access of fitting temperature monitoring data, characterized in that Including: Obtain the battery voltage monitoring data and temperature data of the fitting temperature measurement sensor, and obtain the receiving sensitivity of the last successful communication process; Discriminate the temperature data based on the voltage monitoring data to obtain a discrimination result; Based on the receiving sensitivity of the last successful communication process and the discrimination result, set or calculate the transmission power and data transmission interval parameters to optimize the communication protocol transmission strategy of the fitting temperature measurement sensor.

2. The method according to claim 1, characterized in that, The discriminating the temperature data based on the voltage monitoring data to obtain a discrimination result includes: Determine the voltage level based on the voltage monitoring data, and determine the set temperature data threshold from the voltage level; Judge whether the temperature data exceeds the set temperature data threshold, and obtain that the temperature data exceeds the set temperature data threshold, or the temperature data does not exceed the set temperature data threshold; Wherein, the discrimination result includes: the temperature data exceeds the set temperature data threshold and the temperature data does not exceed the set temperature data threshold.

3. The method according to claim 1, wherein The setting or calculating the transmission power and data transmission interval parameters based on the receiving sensitivity of the last successful communication process and the discrimination result to optimize the communication protocol transmission strategy of the fitting temperature measurement sensor includes: When the discrimination result is that the temperature data exceeds the set temperature data threshold, perform channel listening after each monitoring data is sent until an acknowledgment frame is received. At the same time, use the maximum transmission power for data transmission; When the discrimination result is that the temperature data does not exceed the set temperature data threshold, calculate the transmission power and data transmission interval parameters according to the voltage monitoring data and the receiving sensitivity, and directly enter the sleep mode after each monitoring data is sent.

4. The method according to claim 3, characterized in that The transmission power is calculated according to the following formula: Where S is the wireless transmission transmit power of the sensor, S0 is the wireless transmission reference transmit power of the sensor, i is the receiving sensitivity level number, t is the fitting temperature monitoring data, and t max is the temperature data threshold value.

5. The method according to claim 3, characterized in that The data transmission interval parameter is set according to the following formula: Where t is the monitoring data of the fitting temperature, t max is the temperature data threshold, t1 is the monitoring interval of the fitting temperature sensor, j is the battery voltage level number, and Δt is the data sending interval parameter.

6. A cross-layer optimization system for random competition access of fitting temperature monitoring data, characterized in that, Including: A parameter acquisition module for obtaining the battery voltage monitoring data and temperature data of the fitting temperature measurement sensor, and obtaining the receiving sensitivity of the last successful communication process; A judgment module for discriminating the temperature data based on the voltage monitoring data to obtain a discrimination result; An optimization module for setting or calculating the transmission power and data transmission interval parameters based on the receiving sensitivity of the last successful communication process and the discrimination result to optimize the communication protocol transmission strategy of the fitting temperature measurement sensor.

7. The system according to claim 6, wherein The judgment module includes: A threshold selection sub-module for determining the voltage level based on the voltage monitoring data and determining the set temperature data threshold from the voltage level; A temperature judgment sub-module for judging whether the temperature data exceeds the set temperature data threshold, and obtaining that the temperature data exceeds the set temperature data threshold, or the temperature data does not exceed the set temperature data threshold; Wherein, the discrimination result includes: the temperature data exceeds the set temperature data threshold and the temperature data does not exceed the set temperature data threshold.

8. The system according to claim 6, wherein The optimization module is specifically used for: When the discrimination result is that the temperature data exceeds the set temperature data threshold, perform channel listening after each monitoring data is sent until an acknowledgment frame is received. At the same time, use the maximum transmission power for data transmission; When the discrimination result indicates that the temperature data does not exceed the set temperature data threshold, calculate the transmission power and data transmission interval parameters based on the voltage monitoring data and reception sensitivity, and directly enter the sleep mode after each transmission of the monitoring data.

9. The system according to claim 8, wherein The optimization module calculates the transmission power according to the following formula: Where S is the wireless transmission transmit power of the sensor, S0 is the wireless transmission reference transmit power of the sensor, t is the fitting temperature monitoring data, and t max is the temperature data threshold, and i is the receiving sensitivity level number.

10. The system according to claim 8, characterized in that, The optimization module calculates the data transmission interval parameter according to the following formula: where t is the monitoring data of the fitting temperature, t max is the temperature data threshold, t1 is the monitoring interval of the temperature measuring sensor of the fitting, j is the battery voltage level number, and Δt is the data sending interval parameter.

11. A computer device, characterized in that, Comprising: One or more processors; The processor is used to store one or more programs; When the one or more programs are executed by the one or more processors, implement a cross-layer optimization method for random access competition of fitting temperature monitoring data as described in any one of claims 1 to 5.

12. A computer-readable storage medium, characterized in that, There is a computer program stored thereon, and when the computer program is executed, implement a cross-layer optimization method for random access competition of fitting temperature monitoring data as described in any one of claims 1 to 5.

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