Intensive tag system

Abstract

The invention relates to the technical field of Internet of Things, in particular to an intensive tag system, which comprises basic tags distributed on each device to realize asset identity recognition and data wireless transmission, and electronic codes are built in the basic tags as digital identity cards; the acquisition module acquires environment parameters and equipment parameters, and the communication module transmits the environment parameters and the equipment parameters to the analysis module based on a preset transmission rule; the analysis module determines an environment influence coefficient of the environment on the equipment according to the equipment type, the environment parameters, the equipment parameters and an environment-equipment model so as to determine an equipment state, and determines an abnormal area according to the equipment state and the equipment position information; and the early warning module carries out early warning on the staff according to the digital identity card and the abnormal area. According to the invention, a full-closed-loop management system of data acquisition, wireless transmission, intelligent analysis and early warning response is formed, and the identity identification and state monitoring of assets are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to an intensive labeling system. Background Art

[0002] In modern industrial production and business operations, a large number of devices are distributed across diverse areas, with complex and ever-changing operating conditions. Existing technologies utilize RFID to achieve real-time equipment management, status monitoring, and fault warnings. For example, CNC machine tools can use RFID systems to collect data such as current, power consumption, and vibration to determine their operating status. After key power plant equipment is equipped with RFID tags, inspectors can read equipment status, maintenance records, and other information in real time. RFID tags can also be combined with sensors to monitor equipment operating status in real time. In smart manufacturing, RFID tags on production equipment can record operating status, maintenance records, and service life.

[0003] Chinese patent application publication number: CN119967460A, discloses a method for passive indoor distributed system monitoring and fault location based on RFID tags, the steps of which are: S1: reading the ID information of the RFID tag located at the indoor distributed antenna in the indoor distributed system through the indoor distributed system status monitoring module, and calculating the link loss value of the link from the indoor distributed system status monitoring module to the RFID tag, and then uploading the link loss result to the cloud decision center; S2: the cloud decision center diagnoses the abnormal location in the indoor distributed system based on the data reported by the indoor distributed system status monitoring module, outputs the faulty device or line, and generates a corresponding alarm work order and sends it to the installation and maintenance personnel for subsequent equipment maintenance.

[0004] It can be seen that although the above technical solution can more accurately locate the location of the fault in the link and improve the maintenance efficiency, the following problems still exist: the single status monitoring function is still limited to the communication link, multiple sensors are not integrated, the degree of multi-sensor fusion is low, and the data collection coverage is insufficient. It does not involve multi-source data such as environmental parameters and performance parameters of equipment operation and maintenance. Summary of the Invention

[0005] To this end, the present invention provides an intensive tag system to overcome the problems of traditional RFID asset management systems in the prior art, such as single status monitoring function, low multi-sensor fusion level, and insufficient equipment operation and maintenance data collection coverage.

[0006] To achieve the above objectives, the present invention provides an intensive labeling system, comprising:

[0007] Basic tags, which are distributed on various devices and are used for asset identification and wireless data transmission. The basic tags have built-in electronic codes as digital ID cards;

[0008] A collection module, which is connected to the basic tag and has several built-in sensors for collecting environmental parameters and device parameters. The environmental parameters include ambient temperature and ambient humidity, and the device parameters include operating current, operating temperature, and device location information;

[0009] a communication module connected to the acquisition module, configured to determine a preset transmission rule, and transmit the environmental parameters and the device parameters to the analysis module based on the preset transmission rule;

[0010] an analysis module, connected to the acquisition module and the communication module, respectively, for determining an environmental impact coefficient of the environment on the device based on the environmental parameters, the device parameters, and the environment-device model to determine a device state, and for determining an abnormal area based on the device type, the device state, and the device location information, wherein the device state includes an abnormal state and a normal state;

[0011] An early warning module is connected to the basic tag and the analysis module respectively, and is used to issue corresponding early warning information according to the digital ID card and the abnormal area.

[0012] Furthermore, the intensive tag system further includes a power consumption control module, which is connected to the acquisition module and the analysis module respectively, and is used to determine a power consumption control strategy for data interaction according to the device status, including:

[0013] If the device state is normal, the power consumption control module controls the positioning sensor used to obtain device location information to sleep;

[0014] If the device state is abnormal, the power consumption control module controls the activation of the positioning sensor to collect the device location information.

[0015] Furthermore, the communication module determines the preset transmission rule, including:

[0016] A three-dimensional discrete system is constructed and two sets of pseudo-random sequences are generated according to a plurality of preset parameter keys and a plurality of preset state variable initial values ​​to encrypt the environmental parameters and the device parameters respectively, and encrypted data is generated and transmitted to the analysis module.

[0017] Furthermore, after receiving the encrypted data, the analysis module runs the three-dimensional discrete system based on the preset parameter key and the preset state variable initial value to generate the two sets of pseudo-random sequences, performs an XOR operation on the encrypted data and the two sets of pseudo-random sequences, and restores the environmental parameters and the device parameters.

[0018] The expression of the three-dimensional discrete system is:

[0019]

[0020] Among them, x1, x2, x3 are state variables, a 11 ,a 12 ,a 13 ,a 21 ,a 22 ,a 23 ,a 31 ,a 32 ,a 33 ,ε1,σ1,ε2,σ2 are preset parameter keys, mod(·) represents the modulo operation, mod(ε1x1(i),σ1) and mod(ε2x2(i),σ2) are feedback controllers.

[0021] Furthermore, after receiving the encrypted data, the analysis module runs the three-dimensional discrete system to generate the two sets of pseudo-random sequences, performs XOR operation on the encrypted data and the two sets of pseudo-random sequences, and restores the environmental parameters and the device parameters.

[0022] Furthermore, the analysis module determines the hysteresis temperature and the hysteresis humidity according to the historical environment parameters and the historical equipment parameters, and constructs an environment-equipment model according to the historical equipment parameters, the hysteresis temperature and the hysteresis humidity;

[0023] Wherein, the historical environmental parameters include historical environmental temperature and historical environmental humidity;

[0024] The historical device parameters include historical operating current and historical operating temperature.

[0025] Furthermore, the analysis module constructs a temperature-device autocorrelation function and a humidity-device autocorrelation function based on the historical environmental parameters and the historical device parameters, determines the temperature lag time and the humidity lag time based on the temperature-device autocorrelation function and the humidity-device autocorrelation function, and determines the lag temperature and lag humidity based on the temperature lag time and the humidity lag time.

[0026] Furthermore, the analysis module determines a temperature influence factor and a humidity influence factor according to the environmental parameters, the equipment parameters and the environment-equipment model, and determines an environmental influence coefficient based on the temperature influence factor and the humidity influence factor.

[0027] Furthermore, the analysis module determines the device status according to the environmental impact coefficient and the impact coefficient threshold, wherein:

[0028] If the environmental impact coefficient is greater than the impact coefficient threshold, determining that the device state is an abnormal state;

[0029] If the environmental impact coefficient is less than or equal to the impact coefficient threshold, it is determined that the device state is normal.

[0030] Furthermore, the analysis module determines the device area according to the device location information and the preset area division rule, and determines the abnormal area according to the device status and the device area, wherein the preset area division rule is determined according to the device type,

[0031] If the device state is an abnormal state, the device area is an abnormal area;

[0032] If the device state is a normal state, the device area is a normal area.

[0033] Furthermore, the warning module stores a warning maintenance binding mapping relationship, and determines the sending object of the warning information according to the warning maintenance binding mapping relationship, the digital ID card and the abnormal area to send the warning notification;

[0034] The early warning maintenance binding mapping relationship is a mapping relationship between each device and the corresponding digital ID card and the sending object.

[0035] Compared with the existing technology, the beneficial effect of the present invention is that the present invention proposes a multi-modal fusion intensive tag system, which uses RFID communication technology as a carrier and integrates multiple sensors in a single basic tag, breaking through the limitation of traditional RFID that can only carry identification information and realizing intensive monitoring with multiple functions of one tag. At the same time, an encryption transmission protocol based on physical channel decoupling is designed to realize a ubiquitous self-organizing network between tags to ensure the safe and reliable transmission of multi-dimensional data such as environmental parameters and equipment parameters, and to construct an environment-equipment model to determine the environmental impact coefficient, so as to realize real-time diagnosis of equipment status and precise positioning of abnormal areas, and finally form a full closed-loop management system of "data acquisition-wireless transmission-intelligent analysis-early warning response-low power integration", further realizing the identity identification and status monitoring of important / special assets, improving the intelligence and refinement level of equipment management, ensuring stable operation of equipment, and reducing energy consumption.

[0036] Furthermore, the present invention rationally allocates resources. During normal device operation, the power consumption control module puts the positioning sensor into a dormant state, reducing energy consumption and preventing the positioning sensor from operating unnecessarily during normal operation. Furthermore, when the device is in an abnormal state, the power consumption control module promptly activates the positioning sensor and collects device location information, helping operations personnel quickly locate the abnormal device location and take targeted measures, thereby improving the overall operational efficiency of the device.

[0037] Furthermore, the present invention sets up a three-dimensional discrete system with preset transmission rules, and uses the unique chaotic characteristics of the three-dimensional discrete system to encrypt environmental parameters and equipment parameters during the transmission process, preventing data from being intercepted during transmission, avoiding unauthorized third parties from cracking the information, effectively preventing data leakage and malicious attacks, and building a solid data security line for equipment monitoring and operation and maintenance, ensuring that data transmission is complete, accurate and orderly, and ensuring data reliability.

[0038] Furthermore, the present invention mines the lag relationship between environmental parameters and equipment parameters based on historical environmental parameters and historical equipment parameters, captures the lag effect of environmental changes on equipment, and can achieve more accurate equipment status prediction. It can also issue early warnings when equipment parameters are actually abnormal, so as to reduce sudden failures, avoid over-response to immediate environmental changes, improve the intelligence and refinement of the system, ensure stable operation of equipment, and reduce energy consumption.

[0039] Furthermore, the present invention directly binds the device status to the area. When a single device in the area is abnormal, the area where it is located is quickly marked as an abnormal area, avoiding the need to check each device one by one and improving the efficiency of fault location. At the same time, the preset area division rules are directly linked to the device type, which can ensure that the abnormalities of different types of equipment can be classified into the most reasonable area units, making it convenient for the subsequent early warning module to determine the corresponding device responsible person based on the maintenance binding mapping relationship to send early warning notifications, further realizing the status monitoring of important / special assets, improving the intelligence and refinement level of equipment management, ensuring stable operation of equipment, and reducing energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a connection block diagram of the centralized tag system according to an embodiment of the present invention;

[0041] Figure 2 A flowchart for determining a preset transmission rule according to an embodiment of the present invention;

[0042] Figure 3 A flow chart for determining hysteresis temperature and hysteresis humidity according to an embodiment of the present invention;

[0043] Figure 4 This is a diagram for determining the device status according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0045] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0046] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside", and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0047] Furthermore, it should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0048] See also Figure 1 As shown, Figure 1 This is a connection block diagram of an integrated labeling system according to an embodiment of the present invention. Specifically, the present invention provides an integrated labeling system, including:

[0049] Basic tags, which are distributed on various devices and are used for asset identification and wireless data transmission. The basic tags have built-in electronic codes as digital ID cards;

[0050] A collection module, which is connected to the basic tag and has several built-in sensors for collecting environmental parameters and device parameters. The environmental parameters include ambient temperature and ambient humidity, and the device parameters include operating current, operating temperature, and device location information;

[0051] a communication module connected to the acquisition module, configured to determine a preset transmission rule, and transmit the environmental parameters and the device parameters to the analysis module based on the preset transmission rule;

[0052] an analysis module, connected to the acquisition module and the communication module, respectively, for determining an environmental impact coefficient of the environment on the device based on the environmental parameters, the device parameters, and the environment-device model to determine a device state, and for determining an abnormal area based on the device type, the device state, and the device location information, wherein the device state includes an abnormal state and a normal state;

[0053] An early warning module is connected to the basic tag and the analysis module respectively, and is used to issue corresponding early warning information according to the digital ID card and the abnormal area.

[0054] Understandably, traditional asset management relies on manual records or single RFID tags, which are unable to correlate device status data in real time. This leads to an information gap characterized by "identification without status." Environmental sensors (such as temperature and humidity) and device sensors (such as current and temperature) are deployed independently, resulting in severe data silos. For example, elevated humidity can exacerbate corrosion in device circuits, but traditional systems cannot correlate these data to predict failures. Furthermore, the system lacks the linkage between geolocation and status data, making it difficult to quickly pinpoint specific devices and areas when an anomaly occurs. Basic tags, however, serve as the device's digital ID. Their built-in electronic code uniquely identifies the device and wirelessly transmits data, facilitating rapid access and management of device information. The acquisition module incorporates multiple sensors, allowing for customized acquisition frequencies for different sensor types. This comprehensive collection of environmental and device parameters provides detailed data sources for subsequent device status analysis. For example, ambient temperature and humidity sensors monitor whether the device's operating environment meets requirements, operating current and temperature sensors provide direct information on the device's operating status, and location sensors determine the device's location. The communication module encrypts and transmits the various parameters acquired by the acquisition module to the analysis module according to pre-set transmission rules, ensuring secure and reliable data flow within the system. The analysis module can determine whether the device is in an abnormal or normal state by determining the environmental impact coefficient. It can also identify the abnormal area based on the device's location information, enabling in-depth analysis of the device's status and precise location of the problematic device. The early warning module can determine the device's identity based on the digital ID card of the underlying tag. Combined with the abnormal area determined by the analysis module, it can issue an early warning to staff, allowing them to quickly identify the problematic device and area and take timely action. The power consumption control module can intelligently adjust power consumption based on the device status determined by the analysis module. When the device is operating normally, the positioning sensor is put into sleep mode to reduce unnecessary energy consumption. When the device is abnormal, the positioning sensor is activated and the acquisition frequency of each sensor is increased to ensure that more detailed and accurate information can be obtained for troubleshooting and resolution.

[0055] In a specific embodiment, the intensive tag system also includes an energy collection module (such as a piezoelectric piece + BQ25570 chip), which can convert mechanical energy in the environment such as vibration and pressure into electrical energy to achieve self-powering of the intensive tag system. Through circuit design, it prioritizes power supply to modules such as the acquisition module, analysis module, and early warning module, so that the intensive tag system can still maintain basic functional operation without a battery, provide power outage emergency capabilities, and improve system reliability.

[0056] The present invention proposes a multimodal fusion intensive tag system that uses RFID communication technology as a carrier and integrates multiple sensors in a single basic tag, breaking through the limitation of traditional RFID that can only carry identification information and realizing intensive monitoring with multiple functions in one tag. At the same time, an encrypted transmission protocol based on physical channel decoupling is designed to realize a ubiquitous self-organizing network between tags to ensure the safe and reliable transmission of multi-dimensional data such as environmental parameters and equipment parameters, and to construct an environment-equipment model to determine the environmental impact coefficient, so as to realize real-time diagnosis of equipment status and precise positioning of abnormal areas, and finally form a full closed-loop management system of "data acquisition-wireless transmission-intelligent analysis-early warning response-low power integration", further realizing the identity identification and status monitoring of important / special assets, improving the intelligent and refined level of equipment management, ensuring stable operation of equipment, and reducing energy consumption.

[0057] Specifically, the intensive tag system further includes a power consumption control module, which is connected to the acquisition module and the analysis module respectively, and is used to determine a power consumption control strategy for data interaction according to the device status, including:

[0058] If the device state is normal, the power consumption control module controls the positioning sensor used to obtain device location information to sleep;

[0059] If the device state is abnormal, the power consumption control module controls the activation of the positioning sensor to collect the device location information.

[0060] It is understood that the power consumption control module is connected to the acquisition module and the fusion module respectively, and can obtain device status information in real time and dynamically adjust the operating mode of the positioning sensor according to different device states. When the device is in a normal state, it means that the device is operating stably according to the established process and expectations. At this time, the positioning sensor is not necessary for routine operation monitoring of the device. Based on this, the power consumption control module will issue a command to put the positioning sensor into a dormant state. In the dormant state, the positioning sensor stops collecting location information, avoiding unnecessary power consumption. When the device status changes to an abnormal state, such as a device failure, the power consumption control module can quickly activate the positioning sensor. The acquisition module collects the device location information and transmits it to the analysis module for subsequent determination of the abnormal area of ​​the device.

[0061] This invention rationally allocates resources. During normal equipment operation, the power consumption control module puts the positioning sensor into a dormant state, reducing energy consumption and preventing the positioning sensor from operating unnecessarily during normal equipment operation. Furthermore, when the equipment is in an abnormal state, the power consumption control module can promptly activate the positioning sensor and collect device location information, helping operators quickly locate the abnormal position of the equipment and take targeted measures, thereby improving the overall operational efficiency of the equipment.

[0062] See also Figure 2 As shown, it is a flow chart of determining a preset transmission rule according to an embodiment of the present invention; specifically, the communication module determines the preset transmission rule, including:

[0063] Constructing a three-dimensional discrete system and generating two sets of pseudo-random sequences according to a plurality of preset parameter keys and a plurality of preset state variable initial values ​​to encrypt the environmental parameters and the device parameters respectively, generating encrypted data and transmitting the encrypted data to the analysis module;

[0064] The expression of the three-dimensional discrete system is:

[0065]

[0066] Among them, x1, x2, x3 are state variables, a 11 ,a 12 ,a 13 ,a 21 ,a 22 ,a 23 ,a 31 ,a 32 ,a 33 ,ε1,σ1,ε2,σ2 are the preset parameter keys, mod(·) represents the modulo operation, mod(ε1x1(i),σ1) and mod(ε2x2(i),σ2) are the calculation results of the feedback controller.

[0067] It can be understood that mod(·) represents a modulo operation, through which a nonlinear feedback mechanism can be introduced to form feedback controllers mod(ε1x1(i),σ1) and mod(ε2x2(i),σ2), so that the calculation results of the three-dimensional discrete system fluctuate within a certain range, thereby enhancing the complexity and randomness of the system and helping to generate more difficult-to-predict pseudo-random sequences for encryption.

[0068] In a specific embodiment, the multiple state variable initial values ​​are environment parameter initial values ​​and device parameter initial values, and hash operations can be performed on the environment parameters and the device parameters respectively to obtain the environment parameter initial values ​​and the device parameter initial values.

[0069] Specifically, after receiving the encrypted data, the analysis module runs the three-dimensional discrete system based on the preset parameter key and the preset state variable initial value to generate the two sets of pseudo-random sequences, performs an XOR operation on the encrypted data and the two sets of pseudo-random sequences, and restores the environmental parameters and the device parameters.

[0070] It is understandable that equipment monitoring data often contains sensitive information such as equipment operating status, key performance indicators, and location. Once this data is leaked or tampered with, it may lead to an increased risk of equipment failure. At the production process terminal, the three-dimensional discrete system is highly complex and unpredictable. Its unique chaotic characteristics can encrypt the data during transmission. Even if the data is intercepted during transmission, it is difficult for unauthorized third parties to crack the information, which can effectively prevent data leakage and malicious supply.

[0071] In a specific embodiment, the expression of the three-dimensional discrete system is:

[0072]

[0073] Among them, x1, x2, x3 are state variables, a 11 ,a 12 ,a 13 ,a 21 ,a 22 ,a 23 ,a 31 ,a 32 ,a 33 ,ε1,σ1,ε2,σ2 are preset parameter keys, mod(·) represents the modulo operation, mod(ε1x1(i),σ1) and mod(ε2x2(i),σ2) are feedback controllers. Among them, if the parameter values ​​are as follows:

[0074] a 11 =0.325,a 12 =-0.225,a 13 =-0.955,a 21 =-0.045,a 22 =0.145,a 23 =-0.775,a 31 =0.18,a 32 =-0.18,a 33 =0.37,ε1=6×10 3 ,σ1=1×10 5 ,ε2=4×10 3 ,σ2=2×10 5 When , the three Lyapunov exponents of the three-dimensional discrete system are:

[0075] LE1=1.8915, LE2=1.8877, LE3=1.87,

[0076] Those skilled in the art will recognize that the Lyapunov exponent represents the numerical characteristic of the average exponential divergence rate of adjacent trajectories in phase space and is one of the features used to identify chaotic motion. Since all three Lyapunov exponents are greater than zero, this indicates that the three-dimensional discrete system exhibits chaotic behavior simultaneously in multiple independent directions. Therefore, under the aforementioned parameter values, the three-dimensional discrete system behaves as a hyperchaotic system, and the signals of hyperchaotic systems are more complex and resilient to anomalies.

[0077] In the present invention, the communication module is the encryption end, and the analysis module is the decryption end. The environmental parameters and device parameters are read in bytes and recorded as m1(i) and m2(i). The encryption end uses the hyperchaotic system (three-dimensional discrete system) of the communication module to iteratively generate the state variables x1, x2, x3 (recorded as ) to construct two different pseudo-random sequences to encrypt m1(i) and m2(i). The encrypted environmental parameters and device parameters are recorded as p1(i) and p2(i) respectively. The specific mathematical expressions are:

[0078]

[0079] In the formula, floor(·) means rounding down, and the symbol Represents a bitwise exclusive OR operation.

[0080] Similarly, when the analysis module is decrypting, the hyperchaotic system of the iterative analysis module generates state variables x1, x2, x3 (denoted as ),use Construct two sets of pseudo-random sequences to decrypt p1(i) and p2(i). The decrypted data is recorded as and The specific mathematical expressions are:

[0081]

[0082] When the initial values ​​of the environmental parameters, device parameters and preset parameter keys of the analysis module hyperchaotic system are equal to the initial values ​​of the environmental parameters, device parameters and preset parameter keys of the communication module hyperchaotic system, the state variables are equal and can be correctly decrypted, that is, for each byte, there is Otherwise, decryption fails.

[0083] The present invention sets up a three-dimensional discrete system with preset transmission rules, and utilizes the unique chaotic characteristics of the three-dimensional discrete system to encrypt environmental parameters and equipment parameters during the transmission process, thereby preventing data from being intercepted during transmission and preventing unauthorized third parties from cracking the information, effectively preventing data leakage and malicious attacks, and building a solid data security line for equipment monitoring and operation and maintenance, ensuring that data transmission is complete, accurate and orderly, and ensuring data reliability.

[0084] Specifically, the analysis module determines the hysteresis temperature and the hysteresis humidity according to the historical environment parameters and the historical equipment parameters, and constructs the environment-equipment model according to the historical equipment parameters, the hysteresis temperature and the hysteresis humidity;

[0085] Wherein, the historical environmental parameters include historical environmental temperature and historical environmental humidity;

[0086] The historical device parameters include historical operating current and historical operating temperature.

[0087] It is understandable that the device itself has heat capacity during operation. When the ambient temperature changes, heat needs to be gradually transferred to the interior of the device through conduction, convection, and other methods. The thermal resistance of the multi-layer structure will delay the temperature response, and the corresponding thermal resistance of each layer of the structure will cause a lag in the change of the device's operating temperature. As the device's operating temperature changes, the operating current will also be affected and fluctuate. In addition, when the ambient temperature is lower than the dew point temperature of the device surface, the water vapor in the air will condense into liquid water, which will produce a cumulative effect and cause short circuits and corrosion. Therefore, the impact of ambient humidity on device parameters also has a lag. Changes in ambient temperature and humidity will not be immediately reflected in the device parameters, and there is a certain time delay. This lag relationship can be explored through historical environmental parameters and historical device parameters.

[0088] In a specific embodiment, the environment-device model is constructed with historical device parameters (operating current and operating temperature), hysteresis temperature, and hysteresis humidity as input features, and temperature influence factor and humidity influence factor as output features as follows:

[0089]

[0090] Among them, α1, α2, and α3 are the weight coefficients of the normalized operating temperature, operating current, and hysteresis environmental parameters (hysteresis temperature and hysteresis humidity) of the equipment on the influencing factors.

[0091] Among them, α1 has a value range of 0.3 to 0.35, preferably 0.32, α2 has a value range of 0.3 to 0.35, preferably 0.32, and α3 has a value range of 0.3 to 0.4, preferably 0.36. In implementation, the value ranges and preferred values ​​of α1, α2, and α3 can be determined based on actual conditions and are not specifically limited here or elaborated upon. The sum of α1, α2, and α3 is 1.

[0092] See also Figure 3As shown, it is a flow chart of determining the hysteresis temperature and hysteresis humidity according to an embodiment of the present invention; specifically, the analysis module constructs a temperature-device autocorrelation function and a humidity-device autocorrelation function based on the historical environmental parameters and the historical device parameters, determines the temperature hysteresis time and the humidity hysteresis time according to the temperature-device autocorrelation function and the humidity-device autocorrelation function, respectively, and determines the hysteresis temperature and hysteresis humidity according to the temperature hysteresis time and the humidity hysteresis time.

[0093] It's understandable that the temperature-device autocorrelation function can be used to analyze the correlation between historical ambient temperatures and historical device parameters, identifying the time difference corresponding to the maximum correlation, or temperature lag time. Similarly, the humidity-device autocorrelation function can be used to identify the humidity lag time, which is the effect of humidity changes on device parameters. This allows the lag temperature and lag humidity to be determined.

[0094] In a specific embodiment, the analysis module determines the temperature correlation between the ambient temperature and the device parameters at different lag times τ based on the historical ambient temperature at time point t and the historical device parameters at time point t+τ (which can be obtained according to the correlation coefficient formula), and the value of the temperature correlation is [-1, 1]. By traversing different lag times, the lag time τ at which the temperature correlation reaches a peak can be found, which is the temperature lag time. The humidity lag time is calculated in the same way. According to the temperature lag time, the lag temperature X (t-temperature lag time) corresponding to the measured current ambient temperature at the temperature lag time point in the historical ambient temperature can be extracted. According to the humidity lag time, the lag humidity Y (t-humidity lag time) corresponding to the measured current ambient humidity at the humidity lag time point in the historical ambient humidity can be extracted.

[0095] The present invention mines the hysteresis relationship between environmental parameters and equipment parameters based on historical environmental parameters and historical equipment parameters, captures the hysteresis effect of environmental changes on equipment, can achieve more accurate equipment status prediction, and issue early warning when equipment parameters are actually abnormal, so as to reduce sudden failures, avoid over-response to immediate environmental changes, improve the intelligence and refinement level of the system, ensure stable operation of equipment, and reduce energy consumption.

[0096] Specifically, the analysis module determines a temperature influence factor and a humidity influence factor according to the environmental parameters, the device parameters and the environment-device model, and determines an environment influence coefficient based on the temperature influence factor and the humidity influence factor.

[0097] In a specific embodiment, the temperature influence factor and the humidity influence factor can be calculated by substituting the environmental parameters and the equipment parameters into the environment-equipment model. The environmental influence coefficient = first weight × temperature influence factor + second weight × humidity influence factor, the sum of the first weight and the second weight is 1, and because the ambient temperature has a greater impact on the working state of the equipment than the ambient humidity, the first weight is greater than the second weight, and the value range of the first weight is 0.6 to 0.8. Preferably, the value of the first weight is 0.7, and the value range of the second weight is 0.2 to 0.4. Preferably, the value of the second weight is 0.3. In implementation, the value range and preferred value of the first weight and the second weight can be determined according to actual conditions, and are not specifically limited here and will not be repeated.

[0098] See also Figure 4 As shown, it is a diagram for determining the device status of an embodiment of the present invention. Specifically, the analysis module determines the device status based on the environmental impact coefficient and the impact coefficient threshold, wherein:

[0099] If the environmental impact coefficient is greater than the impact coefficient threshold, determining that the device state is an abnormal state;

[0100] If the environmental impact coefficient is less than or equal to the impact coefficient threshold, it is determined that the device state is normal.

[0101] It is understood that the environmental impact coefficient is a value between 0 and 1, and the impact coefficient threshold is a preset critical value based on the device's environmental tolerance, reliability requirements, and application scenarios. If the environmental impact coefficient is greater than the impact coefficient threshold, it means that the environmental impact exceeds the safety range of the device design, which may lead to performance degradation, failure, or shortened lifespan. If the environmental impact coefficient is less than the impact coefficient threshold, the environmental impact is considered to be within the device's tolerance range and no intervention is required.

[0102] In a specific embodiment, the influence coefficient threshold value range is 0.6 to 0.75. Preferably, the influence coefficient threshold value is 0.65. In implementation, the value range and preferred value of the influence coefficient threshold value can be determined based on the sensitivity of the actual equipment and the influence coefficient corresponding to the historical equipment failure conditions. No specific limitation is made here and no further details are given.

[0103] Specifically, the analysis module determines the device area according to the device location information and the preset area division rule, and determines the abnormal area according to the device status and the device area, wherein the preset area division rule is determined according to the device type,

[0104] If the device state is an abnormal state, the device area is an abnormal area;

[0105] If the device state is a normal state, the device area is a normal area.

[0106] In a specific embodiment, the preset area division rules can be area division based on device type (for example, dividing devices of the same type into the same area, or dividing devices with the same environmental requirements into the same area), so as to divide the location range of the device into several device areas, determine the corresponding device area based on the device location information of each device, and then perform status mapping when the device status is abnormal, define the device area of ​​the corresponding device with abnormal device status as an abnormal area, and define the device area where the device status is normal as a normal area. The abnormal area can automatically trigger the corresponding management and warning strategy.

[0107] Specifically, the warning module stores a warning maintenance binding mapping relationship, and determines the sending object of the warning information according to the warning maintenance binding mapping relationship, the digital ID card and the abnormal area to send the warning notification;

[0108] The early warning maintenance binding mapping relationship is a mapping relationship between each device and the corresponding digital ID card and the sending object.

[0109] In a specific embodiment, when the device status of a single device becomes abnormal, the analysis module can determine the corresponding abnormal area based on the device status of the single device, and query and maintain the binding mapping relationship based on the digital ID card (electronic code) corresponding to the single device, and obtain the responsible person (sending object), the device area, and the device type. The device area is the abnormal area, and the person in charge of the device can be warned by sending a text message to the responsible person, marking the abnormal location through a mobile phone or an operation and maintenance app, and sending an information notification. The device area of ​​the device can be updated in real time according to the device location information.

[0110] The present invention directly binds the device status to the device area. When a single device in the area is abnormal, the area where it is located is quickly marked as an abnormal area, avoiding the need to check each device one by one and improving the efficiency of fault location. At the same time, the preset area division rules are directly linked to the device type, which can ensure that the abnormalities of different types of equipment can be classified into the most reasonable area units, making it convenient for the subsequent early warning module to determine the corresponding device responsible person based on the maintenance binding mapping relationship to send early warning notifications, further realizing the status monitoring of important / special assets, improving the intelligence and refinement level of equipment management, ensuring stable operation of equipment, and reducing energy consumption.

[0111] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

Claims

1. An intensive labeling system, characterized in that: include: Basic tags, which are distributed on various devices and are used for asset identification and wireless data transmission. The basic tags have built-in electronic codes as digital ID cards; A collection module, which is connected to the basic tag and has several built-in sensors for collecting environmental parameters and device parameters. The environmental parameters include ambient temperature and ambient humidity, and the device parameters include operating current, operating temperature, and device location information; a communication module connected to the acquisition module, configured to determine a preset transmission rule, and transmit the environmental parameters and the device parameters to the analysis module based on the preset transmission rule; an analysis module, connected to the acquisition module and the communication module, respectively, for determining an environmental impact coefficient of the environment on the device based on the environmental parameters, the device parameters, and the environment-device model to determine a device state, and for determining an abnormal area based on the device type, the device state, and the device location information, wherein the device state includes an abnormal state and a normal state; An early warning module is connected to the basic tag and the analysis module respectively, and is used to issue corresponding early warning information according to the digital ID card and the abnormal area.

2. The centralized labeling system according to claim 1, characterized in that: The intensive tag system further includes a power consumption control module, which is connected to the acquisition module and the analysis module respectively, and is used to determine a power consumption control strategy for data interaction according to the device status, including: If the device state is normal, the power consumption control module controls the positioning sensor used to obtain device location information to sleep; If the device state is abnormal, the power consumption control module controls the activation of the positioning sensor to collect the device location information.

3. The centralized labeling system according to claim 1, characterized in that: The communication module determines the preset transmission rule, including: A three-dimensional discrete system is constructed and two sets of pseudo-random sequences are generated according to a plurality of preset parameter keys and a plurality of preset state variable initial values ​​to encrypt the environmental parameters and the device parameters respectively, and encrypted data is generated and transmitted to the analysis module.

4. The centralized labeling system according to claim 3, characterized in that: After receiving the encrypted data, the analysis module runs the three-dimensional discrete system based on the preset parameter key and the preset state variable initial value to generate the two sets of pseudo-random sequences, performs an XOR operation on the encrypted data and the two sets of pseudo-random sequences, and restores the environmental parameters and the device parameters.

5. The centralized labeling system according to claim 1, characterized in that: The analysis module determines the hysteresis temperature and the hysteresis humidity according to the historical environmental parameters and the historical equipment parameters, and constructs an environment-equipment model according to the historical equipment parameters, the hysteresis temperature and the hysteresis humidity; Wherein, the historical environmental parameters include historical environmental temperature and historical environmental humidity; The historical device parameters include historical operating current and historical operating temperature.

6. The centralized labeling system according to claim 4, characterized in that: The analysis module constructs a temperature-device autocorrelation function and a humidity-device autocorrelation function according to the historical environmental parameters and the historical device parameters, determines a temperature lag time and a humidity lag time according to the temperature-device autocorrelation function and the humidity-device autocorrelation function, respectively, and determines a lag temperature and a lag humidity according to the temperature lag time and the humidity lag time, respectively.

7. The centralized labeling system according to claim 6, characterized in that: The analysis module determines a temperature influence factor and a humidity influence factor according to the environmental parameters, the equipment parameters and the environment-equipment model, and determines an environmental influence coefficient based on the temperature influence factor and the humidity influence factor.

8. The centralized labeling system according to claim 7, characterized in that: The analysis module determines the device status according to the environmental impact coefficient and the impact coefficient threshold, wherein: If the environmental impact coefficient is greater than the impact coefficient threshold, determining that the device state is an abnormal state; If the environmental impact coefficient is less than or equal to the impact coefficient threshold, it is determined that the device state is normal.

9. The centralized labeling system according to claim 8, characterized in that: The analysis module determines the device area according to the device location information and the preset area division rule, and determines the abnormal area according to the device status and the device area, wherein the preset area division rule is determined according to the device type, If the device state is an abnormal state, the device area is an abnormal area; If the device state is a normal state, the device area is a normal area.

10. The centralized labeling system according to claim 9, characterized in that: The warning module stores a warning maintenance binding mapping relationship, and determines the sending object of the warning information according to the warning maintenance binding mapping relationship, the digital ID card and the abnormal area to send a warning notification; The early warning maintenance binding mapping relationship is a mapping relationship between each device and the corresponding digital ID card and the sending object.

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