An Internet of Things card fault diagnosis system based on data analysis

Abstract

The present invention belongs to the technical field of Internet of Things card supervision, and specifically relates to an Internet of Things card fault diagnosis system based on data analysis, which includes a fault diagnosis platform, an Internet of Things card availability detection module, an Internet of Things card misalignment analysis module, a fault monitoring and identification module, and a management terminal. The present invention analyzes the availability status of the Internet of Things card through the Internet of Things card availability detection module. When generating a high-availability signal, the Internet of Things card misalignment analysis module analyzes the position deviation status of the Internet of Things card, effectively ensuring the use effect of the Internet of Things card. When generating a normal position signal, the fault monitoring and identification module analyzes the configuration rationality of the Internet of Things card. When it is determined that the configuration is reasonable, the operating status during the use of the Internet of Things card is detected and analyzed, which can automatically and accurately identify and diagnose the fault status of the Internet of Things card and give early warnings in a timely manner, further ensuring the use performance of the Internet of Things card, with high intelligence and low supervision difficulty.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things card supervision, and specifically to an Internet of Things card fault diagnosis system based on data analysis. Background Art

[0002] An Internet of Things card is a communication card based on Internet of Things technology, mainly used to achieve communication and data transmission between Internet of Things devices. It is usually embedded in various Internet of Things devices to provide interconnection and information interaction between devices. The core feature of the Internet of Things card is its communication ability based on Internet of Things technology. It uses dedicated communication protocols and network technologies and is one of the important infrastructures for realizing Internet of Things applications;

[0003] Currently, when monitoring and managing Internet of Things cards, it is difficult to automatically and accurately identify and diagnose the fault conditions of Internet of Things cards and give timely warnings. Moreover, before diagnosing the faults of Internet of Things cards, it is impossible to accurately feedback their availability status, and when judging that the Internet of Things card is in a high-availability state, it is impossible to reasonably evaluate its misalignment status in the corresponding device, which is not conducive to the effective supervision of Internet of Things cards, with low intelligence and great supervision difficulty;

[0004] In view of the above technical defects, a solution is proposed now. Summary of the Invention

[0005] The purpose of the present invention is to provide an Internet of Things card fault diagnosis system based on data analysis, which solves the problems that in the prior art, it is difficult to automatically and accurately identify and diagnose the fault conditions of Internet of Things cards and give timely warnings, and before diagnosing the faults of Internet of Things cards, it is impossible to accurately feedback their availability status, and when judging that the Internet of Things card is in a high-availability state, it is impossible to reasonably evaluate its misalignment status in the corresponding device, with low intelligence and great supervision difficulty.

[0006] To achieve the above purpose, the present invention provides the following technical solutions:

[0007] An Internet of Things card fault diagnosis system based on data analysis includes a fault diagnosis platform, an Internet of Things card availability detection module, an Internet of Things card misalignment analysis module, a fault monitoring and identification module, and a management terminal; the Internet of Things card availability detection module analyzes the availability status of the Internet of Things card, generates a high-availability signal or a low-availability signal of the Internet of Things card through the analysis, and sends the low-availability signal to the management terminal through the fault diagnosis platform, and sends the high-availability signal to the Internet of Things card misalignment analysis module through the fault diagnosis platform;

[0008] When the Internet of Things card misalignment analysis module receives a high availability signal, it analyzes the position deviation status of the Internet of Things card, generates a misalignment warning signal or a normal position signal for the Internet of Things card through the analysis, sends the misalignment warning signal to the management terminal through the fault diagnosis platform, and sends the normal position signal to the fault monitoring and identification module through the fault diagnosis platform;

[0009] The fault monitoring and identification module analyzes the configuration rationality of the Internet of Things card. When it judges that the configuration is unreasonable, it generates a fault warning signal for the Internet of Things card. When it judges that the configuration is reasonable, it detects and analyzes the running state during the use of the Internet of Things card, and judges the running quality status of the Internet of Things card in real time through the analysis, and generates a fault warning signal or a safe running signal for the Internet of Things card accordingly, and sends the fault warning signal of the Internet of Things card to the management terminal through the fault diagnosis platform.

[0010] Furthermore, the specific operation process of the Internet of Things card availability detection module includes:

[0011] Collect the number of times the Internet of Things card is inserted into the device and the number of times it is removed from the device in the historical stage, and sum the two to obtain the Internet of Things card insertion and removal value; and collect the production date of the Internet of Things card, calculate the time difference between the current date and the production date of the Internet of Things card to obtain the Internet of Things card usage time value, and obtain the Internet of Things card storage inspection value through the Internet of Things card storage measurement analysis, and obtain the Internet of Things card table inspection value through the Internet of Things card table change analysis;

[0012] Perform numerical calculations on the Internet of Things card insertion and removal value, the Internet of Things card usage time value, the Internet of Things card storage inspection value, and the Internet of Things card table inspection value to obtain the Internet of Things card availability coefficient; compare the Internet of Things card availability coefficient with the preset Internet of Things card availability coefficient threshold. If the Internet of Things card availability coefficient exceeds the preset Internet of Things card availability coefficient threshold, generate a low availability signal for the Internet of Things card; if the Internet of Things card availability coefficient does not exceed the preset Internet of Things card availability coefficient threshold, generate a high availability signal for the Internet of Things card.

[0013] Furthermore, the specific analysis process of the Internet of Things card storage measurement analysis is as follows:

[0014] Collect the measured temperature value and the measured humidity value of the environment where the Internet of Things card is located, calculate the difference between the measured temperature value and the median of the preset measured temperature value range and take the absolute value to obtain the card body storage temperature deviation suitability value, and calculate the difference between the measured humidity value and the median of the preset measured humidity value range and take the absolute value to obtain the card body storage humidity deviation suitability value; and collect the vibration data of the device where the Internet of Things card is located, and perform numerical calculations on the card body storage temperature deviation suitability value, the card body storage humidity deviation suitability value, and the vibration data to obtain the card body storage analysis value; compare the card body storage analysis value with the preset card body storage analysis threshold. If the card body storage analysis value exceeds the preset card body storage analysis threshold, it is judged that the environment where the Internet of Things card is located is in a damage-causing state;

[0015] Obtain the total duration of the environment where the IoT card exists in the damaged state during the historical stage and mark it as the card body damage detection value, and collect the single continuous duration of the environment where the IoT card exists in the damaged state during the historical stage. Mark the occurrence times of the single continuous duration exceeding the preset single continuous duration threshold as the card body excessive damage frequency detection value, and perform numerical calculation on the card body damage detection value and the card body excessive damage frequency detection value to obtain the IoT card detection value.

[0016] Furthermore, the specific analysis process of the IoT card table change analysis is as follows:

[0017] Set a number of table detection points on the surface of the IoT card, mark the distance between any two groups of table detection points as the measured table distance value, perform a difference calculation between the table distance value and the corresponding preset initial table distance value and take the absolute value to obtain the table distance increase and decrease value; compare the table distance increase and decrease value with the preset table distance increase and decrease threshold. If the table distance increase and decrease value exceeds the preset table distance increase and decrease threshold, mark the corresponding table distance increase and decrease value as the table distance abnormal detection value, and perform a ratio calculation on the number of table distance abnormal detection values and the number of table distance increase and decrease values in the IoT card to obtain the table distance number detection value; and perform a summation calculation on all the table distance increase and decrease values of the IoT card and take the average value to obtain the table distance analysis value, and perform numerical calculation on the table distance analysis value and the table distance number detection value to obtain the IoT card table detection value.

[0018] Furthermore, the specific operation process of the IoT card misalignment analysis module includes:

[0019] Set a number of position detection points on the outer contour of the IoT card, collect the initial position coordinates and the current position coordinates of the corresponding position detection points, and obtain the displacement deviation value of the corresponding position detection point based on the current position coordinates and the initial position coordinates; compare the displacement deviation value with the preset displacement deviation value range. If the displacement deviation value exceeds the maximum value of the preset displacement deviation value range, mark the corresponding position detection point as a detachment point; if the displacement deviation value is within the preset displacement deviation value range, mark the corresponding position detection point as a low deviation point; if the displacement deviation value does not exceed the minimum value of the preset displacement deviation value range, mark the corresponding position detection point as a non-deviation point.

[0020] If there is a detachment point on the IoT card, a dislocation warning signal for the IoT card is generated; if there is no detachment point on the IoT card, the ratio of the number of low-offset points to the number of non-offset points on the IoT card is used to mark the low-offset value of the IoT card, and the displacement offset values of all bit-check points on the IoT card are summed and averaged to obtain the position analysis value of the IoT card; the low-offset value and the position analysis value of the IoT card are numerically calculated to obtain the dislocation value of the IoT card, and the dislocation value of the IoT card is numerically compared with the preset IoT card dislocation threshold. If the dislocation value of the IoT card exceeds the preset IoT card dislocation threshold, a dislocation warning signal for the IoT card is generated; if the dislocation value of the IoT card does not exceed the preset IoT card dislocation threshold, a normal position signal for the IoT card is generated.

[0021] Further, the specific operation process of the fault monitoring and identification module includes:

[0022] Compare the configuration data of the IoT card with the standard or expected configuration data to determine whether each item of configuration data meets the requirements, including determining whether the IP address, port number, and security policy are correctly set. If there is configuration data that does not meet the requirements, it is determined that the configuration of the IoT card is unreasonable, and a fault warning signal for the IoT card is generated;

[0023] If it is determined that the configuration of the IoT card is reasonable, during the use of the IoT card, the signal strength detection value, signal quality detection value, and network delay detection value of the IoT card are collected in real time. The signal strength detection value, signal quality detection value, and network delay detection value are numerically calculated to obtain the state value of the IoT card; all the state values of the IoT card during the use process within a unit time are marked in the rectangular coordinate system in the first quadrant, and adjacent two sets of coordinate points are connected by line segments one by one to form a state extension curve;

[0024] The line segments showing a downward trend in the state extension curve are marked as downward trend line segments, the acute angle formed between the corresponding downward trend line segments and the horizontal line is marked as the state decline table value, and the ratio of the number of state decline table values exceeding the preset state decline table threshold is marked as the state sharp decline value; and the average value of all the state values of the IoT card within a unit time is calculated to obtain the state analysis value of the IoT card, and the ratio of the number of state values of the IoT card that do not exceed the preset IoT card state threshold within a unit time is marked as the state non-optimal value;

[0025] The state analysis value, state non-optimal value, and state sharp decline value of the IoT card are numerically calculated to obtain the operation and inspection value of the IoT card; the operation and inspection value of the IoT card is numerically compared with the preset IoT card operation and inspection threshold. If the operation and inspection value of the IoT card exceeds the preset IoT card operation and inspection threshold, a fault warning signal for the IoT card is generated.

[0026] Further, if the operation inspection value of the IoT card does not exceed the preset operation inspection threshold of the IoT card, the power consumption curve of the IoT card within a unit time is collected, and several groups of power consumption coordinate points are marked on the power consumption curve, and the time interval between adjacent two groups of power consumption coordinate points is the same; the vertical distance between adjacent two groups of power consumption coordinate points is marked as the power consumption growth value, and the variance of all power consumption growth values is calculated to obtain the power consumption instability value; the power consumption instability value is numerically compared with the preset power consumption instability threshold. If the power consumption instability value exceeds the preset power consumption instability threshold, a fault warning signal of the IoT card is generated;

[0027] If the power consumption instability value does not exceed the preset power consumption instability threshold, the average value of all power consumption growth values is calculated to obtain the power consumption detection value, and the deviation value between the power consumption detection value and the preset appropriate power consumption detection standard value is marked as the power consumption detection difference value; and the power consumption growth value is numerically compared with the preset power consumption growth threshold. If the power consumption growth value exceeds the preset power consumption growth threshold, the corresponding power consumption growth value is marked as the power consumption abnormal growth value, and the ratio of the number of power consumption abnormal growth values to the number of power consumption growth values is marked as the power consumption abnormal analysis value; the power consumption abnormal analysis value and the power consumption detection difference value are numerically calculated to obtain the power consumption evaluation value, and the power consumption evaluation value is numerically compared with the preset power consumption evaluation threshold. If the power consumption evaluation value exceeds the preset power consumption evaluation threshold, a fault warning signal of the IoT card is generated; if the power consumption evaluation value does not exceed the preset power consumption evaluation threshold, a safe operation signal of the IoT card is generated.

[0028] Further, when it is judged that the environment where the IoT card is located is in a damage-causing state, an IoT card alarm message is generated, and the IoT card alarm message is sent to the management terminal through the fault diagnosis platform, and the management terminal displays the IoT card alarm message and issues a corresponding warning.

[0029] Compared with the prior art, the beneficial effects of the present invention are:

[0030] 1. In the present invention, the availability status of the IoT card is analyzed through the IoT card availability detection module, and a high-availability signal or a low-availability signal of the IoT card is generated through the analysis. After the low-availability signal is generated, the IoT card is scrapped in time. When the high-availability signal is generated, the position deviation status of the IoT card is analyzed through the IoT card misalignment analysis module, and the position of the IoT card is corrected in time after the misalignment warning signal is generated, effectively ensuring the use effect of the IoT card and facilitating the supervision of the IoT card;

[0031] 2. In the present invention, when generating a normal position signal, the configuration rationality of the IoT card is analyzed through a fault monitoring and identification module. When it is determined that the configuration is reasonable, the operating state during the use of the IoT card is detected and analyzed, and the operating quality status of the IoT card is judged in real time, and a fault warning signal or a safe operation signal of the IoT card is generated. It can automatically and accurately identify and diagnose the fault status of the IoT card and give a timely warning, further ensuring the use performance of the IoT card, with high intelligence and low supervision difficulty. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] For the convenience of those skilled in the art to understand, the present invention will be further described below in conjunction with the accompanying drawings;

[0033] Figure 1 It is the overall system block diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0034] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0035] Embodiment 1: As Figure 1 shown, an IoT card fault diagnosis system based on data analysis proposed by the present invention includes a fault diagnosis platform, an IoT card availability detection module, an IoT card misalignment analysis module, and a management terminal, and the fault diagnosis platform is communicatively connected to the IoT card availability detection module, the IoT card misalignment analysis module, and the management terminal;

[0036] Among them, the IoT card availability detection module analyzes the availability status of the IoT card, generates a high-availability signal or a low-availability signal of the IoT card through analysis, and sends the low-availability signal to the management terminal through the fault diagnosis platform. When the management terminal receives the low-availability signal, it issues a corresponding warning to play a reminder role. When the management personnel receive the corresponding reminder, they promptly scrap the IoT card to reduce the management difficulty of the IoT card. The specific operation process of the IoT card availability detection module is as follows:

[0037] The number of times the IoT card is inserted into the device and the number of times it is pulled out of the device in the historical stage are collected, and the sum of the two is calculated to obtain the IoT card insertion / removal value; and the production date of the IoT card is collected, and the time difference between the current date and the production date of the IoT card is calculated to obtain the IoT card usage time value. It should be noted that the larger the values of the IoT card insertion / removal value and the IoT card usage time value, the worse the life status of the IoT card, and the less conducive to ensuring its use stability and use effect.

[0038] And through the storage measurement and analysis of the Internet of Things card to obtain the storage inspection value of the Internet of Things card. The specific analysis process is as follows: collect the measured temperature value and the measured humidity value of the environment where the Internet of Things card is located, calculate the difference between the measured temperature value and the median of the preset measured temperature value range and take the absolute value to obtain the temperature deviation suitability value of the card body, and calculate the difference between the measured humidity value and the median of the preset measured humidity value range and take the absolute value to obtain the humidity deviation suitability value of the card body; and collect the vibration data of the device where the Internet of Things card is located. Among them, the vibration data is a data quantity value representing the sum of the internal vibration amplitude and the internal vibration frequency of the device where the Internet of Things card is located.

[0039] Through the formula TW = eg1*GY + eg2*GS + eg3*GF, perform numerical calculation on the temperature deviation suitability value GY of the card body, the humidity deviation suitability value GS of the card body, and the vibration data GF to obtain the card body analysis value TW; where eg1, eg2, and eg3 are preset proportionality coefficients, and the values of eg1, eg2, and eg3 are all greater than zero; and the larger the value of the card body analysis value TW, the greater the damage suffered by the Internet of Things card at the corresponding moment; compare the card body analysis value TW with the preset card body analysis threshold. If the card body analysis value TW exceeds the preset card body analysis threshold, it indicates that the Internet of Things card suffers greater damage at the corresponding moment, then it is judged that the environment where the Internet of Things card is located is in a damage-causing state.

[0040] It should be noted that when it is judged that the environment where the Internet of Things card is located is in a damage-causing state, generate the Internet of Things card alarm information, and send the Internet of Things card alarm information to the management terminal through the fault diagnosis platform. The management terminal displays the Internet of Things card alarm information and issues a corresponding early warning to play a reminder role, so that the management personnel can conduct investigations in time and take corresponding improvement measures, thereby reducing the damage to the use stability and service life of the Internet of Things card.

[0041] Obtain the total duration of the environment where the Internet of Things card is located in the damage-causing state in the historical stage and mark it as the card body damage time inspection value, and collect the single continuous duration of the environment where the Internet of Things card is located in the damage-causing state in the historical stage. Mark the number of occurrences where the single continuous duration exceeds the preset single continuous duration threshold as the card body excessive damage frequency inspection value, and through the formula TQ = fq1*TS + fq2*TY, perform numerical calculation on the card body damage time inspection value TS and the card body excessive damage frequency inspection value TY to obtain the Internet of Things card storage inspection value TQ; where fq1 and fq2 are preset weight coefficients, fq2 > fq1 > 0; and the larger the value of the Internet of Things card storage inspection value TQ, the more serious the damage condition of the Internet of Things card in the historical stage.

[0042] The Internet of Things (IoT) card table deformation is analyzed to obtain the IoT card table inspection value. The specific analysis process is as follows: A number of table inspection points are set on the surface of the IoT card. The distance between any two groups of table inspection points is marked as the measured table distance value. The difference between the table distance value and the corresponding preset initial table distance value is calculated and the absolute value is taken to obtain the table distance increase / decrease value. The table distance increase / decrease value is compared with the preset table distance increase / decrease threshold value. If the table distance increase / decrease value exceeds the preset table distance increase / decrease threshold value, the corresponding table distance increase / decrease value is marked as the table distance abnormal inspection value.

[0043] The ratio of the number of table distance abnormal inspection values to the number of table distance increase / decrease values in the IoT card is calculated to obtain the table distance numerical inspection value. And the sum of all table distance increase / decrease values of the IoT card is calculated and the average value is taken to obtain the table distance inspection analysis value. The table distance inspection analysis value TP and the table distance numerical inspection value TK are numerically calculated through the formula TR = fy1*TP + fy2*TK to obtain the IoT card table inspection value TR; where, fy1 and fy2 are preset proportionality coefficients, and fy2 > fy1 > 0; moreover, the larger the numerical value of the IoT card table inspection value TR, the greater the probability that the IoT card is deformed and the worse the surface condition of the IoT card.

[0044] Through the formula The IoT card plugging / unplugging value YB, the IoT card usage time value YP, the IoT card storage inspection value TQ, and the IoT card table inspection value TR are numerically calculated to obtain the IoT card availability coefficient YK; where, kp1, kp2, kp3, and kp4 are preset proportionality coefficients, and the values of kp1, kp2, kp3, and kp4 are all positive numbers; moreover, the larger the numerical value of the IoT card availability coefficient YK, the worse the overall availability of the IoT card and the more urgent it is to scrap it in time.

[0045] The IoT card availability coefficient YK is compared with the preset IoT card availability coefficient threshold value. If the IoT card availability coefficient YK exceeds the preset IoT card availability coefficient threshold value, indicating that the overall availability of the IoT card is poor and it needs to be scrapped in time, a low availability signal of the IoT card is generated; if the IoT card availability coefficient YK does not exceed the preset IoT card availability coefficient threshold value, indicating that the overall availability of the IoT card is good, a high availability signal of the IoT card is generated.

[0046] The Internet of Things card availability detection module sends the high-availability signal to the Internet of Things card misalignment analysis module through the fault diagnosis platform. When the Internet of Things card misalignment analysis module receives the high-availability signal, it analyzes the position deviation status of the Internet of Things card, generates a misalignment warning signal or a normal position signal for the Internet of Things card through the analysis, and sends the misalignment warning signal to the management terminal through the fault diagnosis platform. When the management terminal receives the misalignment warning signal, it issues a corresponding warning so that the management personnel can timely correct the position of the Internet of Things card, thereby ensuring the use effect of the Internet of Things card and helping to avoid failures during the use of the Internet of Things card. The specific operation process of the Internet of Things card misalignment analysis module is as follows:

[0047] Set a number of position detection points on the outer contour of the Internet of Things card, collect the initial position coordinates and the current position coordinates of the corresponding position detection points, and obtain the displacement deviation value of the corresponding position detection point based on the current position coordinates and the initial position coordinates; among them, the larger the value of the displacement deviation value, the more obvious the distance change of the corresponding position detection point; compare the displacement deviation value with the preset displacement deviation value range. If the displacement deviation value exceeds the maximum value of the preset displacement deviation value range, mark the corresponding position detection point as a detachment point; if the displacement deviation value is within the preset displacement deviation value range, mark the corresponding position detection point as a low deviation point; if the displacement deviation value does not exceed the minimum value of the preset displacement deviation value range, mark the corresponding position detection point as a non-deviation point;

[0048] If there is a detachment point on the Internet of Things card, indicating that the misalignment condition of the Internet of Things card is relatively serious, generate a misalignment warning signal for the Internet of Things card; if there is no detachment point on the Internet of Things card, mark the ratio of the number of low deviation points to the number of non-deviation points on the Internet of Things card as the low deviation value of the Internet of Things card, and sum and average the displacement deviation values of all position detection points on the Internet of Things card to obtain the position analysis value of the Internet of Things card;

[0049] Numerically calculate the low deviation value RY of the Internet of Things card and the position analysis value RP of the Internet of Things card through the formula RF = ty1 * RY + ty2 * RP, where ty1 and ty2 are preset proportionality coefficients, and ty1 > ty2 > 0; moreover, the larger the value of the misalignment value RF of the Internet of Things card, the more serious the misalignment condition of the Internet of Things card; compare the misalignment value RF of the Internet of Things card with the preset misalignment threshold of the Internet of Things card. If the misalignment value RF of the Internet of Things card exceeds the preset misalignment threshold of the Internet of Things card, indicating that the misalignment condition of the Internet of Things card is relatively serious, generate a misalignment warning signal for the Internet of Things card; if the misalignment value RF of the Internet of Things card does not exceed the preset misalignment threshold of the Internet of Things card, indicating that the position of the Internet of Things card is normal, generate a normal position signal for the Internet of Things card.

[0050] Example 2: As Figure 1As shown, the difference between this embodiment and Embodiment 1 is that the fault diagnosis platform is communicatively connected to the fault monitoring and identification module. The IoT card misalignment analysis module sends the position normal signal to the fault monitoring and identification module through the fault diagnosis platform. When generating the position normal signal, the fault monitoring and identification module analyzes the configuration rationality of the IoT card. When it is judged that the configuration is unreasonable, a fault warning signal for the IoT card is generated. When it is judged that the configuration is reasonable, the operating state during the use of the IoT card is detected and analyzed. By analyzing, the operating quality status of the IoT card is judged in real time, and accordingly a fault warning signal or a safe operation signal for the IoT card is generated, and the fault warning signal of the IoT card is sent to the management terminal through the fault diagnosis platform. When the management terminal receives the fault warning signal, it issues a corresponding warning, enabling the management personnel to understand the fault abnormal information of the corresponding IoT in detail and take corresponding optimization and improvement measures in a timely manner according to needs, thereby ensuring the use performance of the IoT card. The specific operation process of the fault monitoring and identification module is as follows:

[0051] Compare the configuration data of the IoT card with the standard or expected configuration data to judge whether each configuration data meets the requirements. For example, judge whether the IP address, port number, and security policies (such as firewall rules, encryption algorithms, authentication mechanisms, etc.) are correctly set. If there is configuration data that does not meet the requirements, it is judged that the configuration of the IoT card is unreasonable, and a fault warning signal for the IoT card is generated. If all configuration data meet the requirements, it is judged that the configuration of the IoT card is reasonable, and it can accurately judge whether the configuration data of the IoT card is correct and further judge whether there is a fault. When a configuration problem is found, the management personnel can be reminded to make adjustments and repairs in a timely manner to ensure the normal operation of the IoT card;

[0052] If it is judged that the configuration of the IoT card is reasonable, during the use of the IoT card, the signal strength detection value, signal quality detection value, and network delay detection value of the IoT card are collected in real time. Among them, the signal strength detection value is a data quantity value representing the signal strength of the IoT card. If the value of the signal strength detection value is small, there may be network connection problems, such as weak signal, signal loss, etc.; the signal quality detection value is a data quantity value representing the purity and stability of the signal (obtained by analyzing the signal quality indicators, such as bit error rate, signal-to-noise ratio, etc.). If the value of the signal quality detection value is small, there may be data transmission failures; the network delay detection value is a data quantity value representing the data transmission efficiency (obtained by analyzing the network delay indicators, such as round-trip time, delay jitter, etc.). If the value of the network delay detection value is large, it indicates that the network state is poor;

[0053] The signal strength detection value WF, the signal quality detection value WQ, and the network delay detection value WY are numerically calculated through the formula WP = (a1 * WF + a2 * WQ) / (a3 * WY + 1) to obtain the Internet of Things card status value WP; where a1, a2, and a3 are preset proportionality coefficients, and the values of a1, a2, and a3 are all greater than zero; and the larger the value of the Internet of Things card status value WP, the better the network performance of the corresponding Internet of Things card at that moment; all the Internet of Things card status values during the use of the Internet of Things card within a unit time are marked in a rectangular coordinate system in the first quadrant, the X-axis of this rectangular coordinate system represents time, and the Y-axis represents the Internet of Things card status value; adjacent two sets of coordinate points are connected by line segments one by one to form a status extension curve;

[0054] The line segments showing a downward trend in the status extension curve are marked as downward trend line segments, and the acute angle formed between the corresponding downward trend line segments and the horizontal line is marked as the status decline value. Among them, the larger the value of the status decline value, the faster the network performance declines; the proportion of the number of status decline values exceeding the preset status decline threshold is marked as the status sharp decline value, and the average value of all the Internet of Things card status values within a unit time is calculated to obtain the Internet of Things card analysis value, and the proportion of the number of Internet of Things card status values not exceeding the preset Internet of Things card status threshold within a unit time is marked as the status non-optimal value;

[0055] The Internet of Things card analysis value WR, the status non-optimal value WK, and the status sharp decline value WT are numerically calculated through the formula WS = (ew2 + ew3) / ew1 * WR + (ew2 * WK + ew3 * WT) / 2 to obtain the Internet of Things card operation and inspection value WS; where ew1, ew2, and ew3 are preset proportionality coefficients, ew2 > ew3 > ew1 > 0; and the larger the value of the Internet of Things card operation and inspection value WS, the worse the network status performance of the Internet of Things card within a unit time; the Internet of Things card operation and inspection value WS is numerically compared with the preset Internet of Things card operation and inspection threshold. If the Internet of Things card operation and inspection value WS exceeds the preset Internet of Things card operation and inspection threshold, indicating that the network status performance of the Internet of Things card within a unit time is poor, then a fault warning signal for the Internet of Things card is generated.

[0056] If the operation inspection value WS of the Internet of Things card does not exceed the preset operation inspection threshold of the Internet of Things card, it indicates that the network status of the Internet of Things card is relatively good within a unit time. Then, collect the power consumption curve of the Internet of Things card within a unit time, mark several groups of power consumption coordinate points on the power consumption curve, and the time interval between adjacent two groups of power consumption coordinate points is the same; mark the vertical distance between adjacent two groups of power consumption coordinate points as the power consumption growth value. The larger the value of the power consumption growth value, the faster the power consumption speed of the Internet of Things card within this interval duration, and the greater the probability of abnormality; calculate the variance of all power consumption growth values to obtain the power consumption instability value, and compare the power consumption instability value with the preset power consumption instability threshold. If the power consumption instability value exceeds the preset power consumption instability threshold, it indicates that the power consumption of the Internet of Things card fluctuates greatly within a unit time and the power consumption is unstable, then generate a fault warning signal for the Internet of Things card;

[0057] If the power consumption instability value does not exceed the preset power consumption instability threshold, it indicates that the power consumption of the Internet of Things card fluctuates less within a unit time. Then, calculate the mean value of all power consumption growth values to obtain the power consumption detection value, and mark the deviation value between the power consumption detection value and the preset appropriate power consumption detection standard value as the power consumption detection difference value; and compare the power consumption growth value with the preset power consumption growth threshold. If the power consumption growth value exceeds the preset power consumption growth threshold, mark the corresponding power consumption growth value as the power consumption abnormal increase value, and mark the ratio of the number of power consumption abnormal increase values to the number of power consumption growth values as the power consumption abnormal analysis value;

[0058] Perform numerical calculation on the power consumption abnormal analysis value HW and the power consumption detection difference value HY through the formula HX = b1 * HW + b2 * HY to obtain the power consumption evaluation value HX, where b1 and b2 are preset weight coefficients, and b1 > b2 > 0; moreover, the larger the value of the power consumption evaluation value HX, the more abnormal the power consumption of the Internet of Things card within a unit time; compare the power consumption evaluation value HX with the preset power consumption evaluation threshold. If the power consumption evaluation value HX exceeds the preset power consumption evaluation threshold, it indicates that the power consumption of the Internet of Things card is relatively abnormal within a unit time, then generate a fault warning signal for the Internet of Things card; if the power consumption evaluation value HX does not exceed the preset power consumption evaluation threshold, it indicates that the power consumption of the Internet of Things card is relatively normal within a unit time, then generate a safe operation signal for the Internet of Things card.

[0059] Working principle of the present invention: During use, the availability detection module for the Internet of Things card analyzes the availability status of the Internet of Things card, generates a high-availability signal or a low-availability signal for the Internet of Things card through the analysis. After generating the low-availability signal, the Internet of Things card is promptly scrapped. When generating the high-availability signal, the position deviation status of the Internet of Things card is analyzed by the Internet of Things card misalignment analysis module. After generating the misalignment warning signal, the position of the Internet of Things card is corrected in a timely manner to ensure the use effect of the Internet of Things card and help avoid failures during the use of the Internet of Things card. And when generating the normal position signal, the configuration rationality of the Internet of Things card is analyzed by the fault monitoring and identification module. When it is determined that the configuration is reasonable, the operating state during the use of the Internet of Things card is detected and analyzed, the operating quality status of the Internet of Things card is judged in real time, and a fault warning signal or a safe operation signal for the Internet of Things card is generated. When generating the fault warning signal, corresponding optimization and improvement measures are taken, so as to ensure the use performance of the Internet of Things card, with high intelligence and significantly reducing the supervision difficulty for the Internet of Things card.

[0060] The above formulas are all dimensionless and take their numerical values for calculation. The formula is obtained by collecting a large amount of data and performing software simulation to obtain a formula that is closest to the actual situation. The preset parameters in the formula are set by those skilled in the art according to the actual situation. The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not elaborate on all the details and do not limit the present invention to only the specific implementation manners. Obviously, many modifications and variations can be made according to the content of this specification. This specification selects and specifically describes these embodiments to better explain the principle and practical application of the present invention, so that those skilled in the relevant technical field can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. An Internet of Things card fault diagnosis system based on data analysis, characterized in that It includes a fault diagnosis platform, an IoT card availability detection module, an IoT card misalignment analysis module, a fault monitoring and identification module, and a management terminal; the IoT card availability detection module analyzes the availability status of the IoT card, generates a high-availability signal or a low-availability signal of the IoT card through analysis, sends the low-availability signal to the management terminal via the fault diagnosis platform, and sends the high-availability signal to the IoT card misalignment analysis module via the fault diagnosis platform; When the IoT card misalignment analysis module receives the high-availability signal, it analyzes the position deviation status of the IoT card, generates a misalignment warning signal or a normal position signal of the IoT card through analysis, sends the misalignment warning signal to the management terminal via the fault diagnosis platform, and sends the normal position signal to the fault monitoring and identification module via the fault diagnosis platform; The fault monitoring and identification module analyzes the configuration rationality of the IoT card. When it determines that the configuration is unreasonable, it generates a fault warning signal of the IoT card. When it determines that the configuration is reasonable, it detects and analyzes the operating state during the use of the IoT card, and judges the operating quality status of the IoT card in real time through analysis, and accordingly generates a fault warning signal or a safe operation signal of the IoT card, and sends the fault warning signal of the IoT card to the management terminal via the fault diagnosis platform.

2. The IoT card fault diagnosis system based on data analysis according to claim 1, wherein, The specific operation process of the IoT card availability detection module includes: Collect the number of times the IoT card is inserted into the device and the number of times it is removed from the device in the historical stage, and sum the two to obtain the IoT card insertion / removal value; and collect the production date of the IoT card, calculate the time difference between the current date and the production date of the IoT card to obtain the IoT card usage time value, and obtain the IoT card storage inspection value through IoT card storage measurement analysis, and obtain the IoT card table inspection value through IoT card table change analysis; Perform numerical calculation on the IoT card insertion / removal value, the IoT card usage time value, the IoT card storage inspection value, and the IoT card table inspection value to obtain the IoT card availability coefficient; if the IoT card availability coefficient exceeds the preset IoT card availability coefficient threshold, generate a low-availability signal of the IoT card; if the IoT card availability coefficient does not exceed the preset IoT card availability coefficient threshold, generate a high-availability signal of the IoT card.

3. The Internet of Things card fault diagnosis system based on data analysis according to claim 2, wherein The specific analysis process of IoT card storage measurement analysis is as follows: Collect the measured temperature value and the measured humidity value of the environment where the IoT card is located, calculate the difference between the measured temperature value and the median of the preset temperature measured value range and take the absolute value to obtain the card body storage temperature deviation suitability value, calculate the difference between the measured humidity value and the median of the preset humidity measured value range and take the absolute value to obtain the card body storage humidity deviation suitability value; and collect the vibration data of the device where the IoT card is located, and perform numerical calculation on the card body storage temperature deviation suitability value, the card body storage humidity deviation suitability value, and the vibration data to obtain the card body storage analysis value; if the card body storage analysis value exceeds the preset card body storage analysis threshold, it is judged that the environment where the IoT card is located is in a damage-causing state; Obtain the total duration when the environment where the IoT card exists in the historical stage is in a damage-causing state and mark it as the card body damage detection value, and collect the single continuous duration when the environment where the IoT card exists in the historical stage is in a damage-causing state. Mark the occurrence times of the single continuous duration exceeding the preset single continuous duration threshold as the card body excessive damage frequency detection value, and perform numerical calculation on the card body damage detection value and the card body excessive damage frequency detection value to obtain the IoT card storage and detection value.

4. The Internet of Things card fault diagnosis system based on data analysis according to claim 2, wherein, The specific analysis process of IoT card table change analysis is as follows: Set several table detection points on the surface of the IoT card, mark the distance between any two groups of table detection points as the measured table distance value, perform difference calculation on the table distance value and the corresponding preset initial table distance value and take the absolute value to obtain the table distance increase and decrease value; compare the table distance increase and decrease value with the preset table distance increase and decrease threshold. If the table distance increase and decrease value exceeds the preset table distance increase and decrease threshold, mark the corresponding table distance increase and decrease value as the table distance abnormal detection value, and perform ratio calculation on the number of table distance abnormal detection values and the number of table distance increase and decrease values in the IoT card to obtain the table distance number detection value; and perform summation calculation on all the table distance increase and decrease values of the IoT card and take the average value to obtain the table distance detection and analysis value, and perform numerical calculation on the table distance detection and analysis value and the table distance number detection value to obtain the IoT card table detection value.

5. The Internet of Things card fault diagnosis system based on data analysis according to claim 1, characterized in that, The specific operation process of the IoT card misalignment analysis module includes: Set several position detection points on the outer contour of the IoT card, collect the initial position coordinates and the current position coordinates of the corresponding position detection points, and obtain the displacement deviation value of the corresponding position detection points based on the current position coordinates and the initial position coordinates; if the displacement deviation value exceeds the maximum value of the preset displacement deviation value range, mark the corresponding position detection point as a detachment point; if the displacement deviation value is within the preset displacement deviation value range, mark the corresponding position detection point as a low deviation point; if the displacement deviation value does not exceed the minimum value of the preset displacement deviation value range, mark the corresponding position detection point as a non-deviation point; If there is a detachment point on the IoT card, generate a misalignment warning signal for the IoT card; if there is no detachment point on the IoT card, mark the ratio of the number of low deviation points to the number of non-deviation points on the IoT card as the IoT card low deviation value, and perform summation calculation on the displacement deviation values of all the position detection points on the IoT card and take the average value to obtain the IoT card position analysis value; perform numerical calculation on the IoT card low deviation value and the IoT card position analysis value to obtain the IoT card misalignment value. If the IoT card misalignment value exceeds the preset IoT card misalignment threshold, generate a misalignment warning signal for the IoT card; if the IoT card misalignment value does not exceed the preset IoT card misalignment threshold, generate a normal position signal for the IoT card.

6. The Internet of Things card fault diagnosis system based on data analysis according to claim 1, characterized in that, The specific operation process of the fault monitoring and identification module includes: Compare the configuration data of the IoT card with the standard or expected configuration data to judge whether each item of configuration data meets the requirements, including judging whether the IP address, port number, and security policy are correctly set. If there is configuration data that does not meet the requirements, judge that the configuration of the IoT card is unreasonable and generate a fault warning signal for the IoT card; If it is determined that the configuration of the IoT card is reasonable, during the use of the IoT card, the signal strength detection value, signal quality detection value, and network latency detection value of the IoT card are collected in real time, and the signal strength detection value, signal quality detection value, and network latency detection value are numerically calculated to obtain the IoT card status value; all the IoT card status values during the use of the IoT card within a unit time are marked in the rectangular coordinate system in the first quadrant, and adjacent two groups of coordinate points are connected by line segments one by one to form a status extension curve; The line segments showing a downward trend in the status extension curve are marked as downward trend line segments, the acute angle formed between the corresponding downward trend line segments and the horizontal line is marked as the status decline value, and the ratio of the number of status decline values exceeding the preset status decline threshold is marked as the status sharp decline value; and the average value of all the IoT card status values within a unit time is calculated to obtain the IoT card analysis value, and the ratio of the number of IoT card status values not exceeding the preset IoT card status threshold within a unit time is marked as the status non-optimal value; the IoT card analysis value, status non-optimal value, and status sharp decline value are numerically calculated to obtain the IoT card operation and inspection value; if the IoT card operation and inspection value exceeds the preset IoT card operation and inspection threshold, a fault warning signal for the IoT card is generated.

7. The IoT card fault diagnosis system based on data analysis according to claim 6, characterized in that, If the IoT card operation and inspection value does not exceed the preset IoT card operation and inspection threshold, the power consumption curve of the IoT card within a unit time is collected, and several groups of power consumption coordinate points are marked on the power consumption curve, and the time interval between adjacent two groups of power consumption coordinate points is the same; the vertical distance between adjacent two groups of power consumption coordinate points is marked as the power consumption increase value, and the variance of all the power consumption increase values is calculated to obtain the power consumption non-stable value; if the power consumption non-stable value exceeds the preset power consumption non-stable threshold, a fault warning signal for the IoT card is generated; If the power consumption non-stable value does not exceed the preset power consumption non-stable threshold, the average value of all the power consumption increase values is calculated to obtain the power consumption detection value, and the deviation value between the power consumption detection value and the preset appropriate power consumption detection standard value is marked as the power consumption detection difference value; and the power consumption increase value is numerically compared with the preset power consumption increase threshold, if the power consumption increase value exceeds the preset power consumption increase threshold, the corresponding power consumption increase value is marked as the power consumption abnormal increase value, and the ratio of the number of power consumption abnormal increase values to the number of power consumption increase values is marked as the power consumption abnormal analysis value; the power consumption abnormal analysis value and the power consumption detection difference value are numerically calculated to obtain the power consumption evaluation value, if the power consumption evaluation value exceeds the preset power consumption evaluation threshold, a fault warning signal for the IoT card is generated; if the power consumption evaluation value does not exceed the preset power consumption evaluation threshold, a safe operation signal for the IoT card is generated.

8. The Internet of Things card fault diagnosis system based on data analysis according to claim 3, characterized in that When it is determined that the environment where the IoT card is located is in a damage-causing state, an IoT card alarm message is generated, and the IoT card alarm message is sent to the management terminal through the fault diagnosis platform, and the management terminal displays the IoT card alarm message and issues a corresponding warning.

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