System and method for supervising running state of terminal equipment based on big data

Abstract

The invention discloses a terminal device operation state supervision system and method based on big data, and relates to the technical field of big data, and the method comprises the steps: obtaining historical communication data of a target terminal device and a plurality of feature terminal devices, and obtaining the feature distance of each terminal device; extracting target data from the communication data corresponding to the target terminal equipment according to the communication data corresponding to each feature terminal equipment in the feature distance; performing feature extraction on the sent and received signals, calculating the signal similarity of the sent and received signals in each target data, and further obtaining an abnormal coefficient of each target data; and setting a target weight, and obtaining an equipment abnormal value of the target terminal equipment according to the abnormal coefficient. According to the method, the device abnormal value is obtained according to the audio information obtained by converting the communication data, the abnormal condition of the communication component on the target terminal device is intelligently judged, processing is carried out according to the abnormal condition, and reliable communication of the target terminal device in different occasions is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and in particular to a terminal device operating status monitoring system and method based on big data. Background Art

[0002] Terminal devices such as walkie-talkies are two-way mobile communication tools used for short-range voice communication. Located at the endpoint of a communication network, they communicate directly with other walkie-talkies via radio frequency signals. They include a microphone for voice input and a speaker for voice output. Walkie-talkies communicate via radio waves in a dedicated frequency band. Because they are independent of the network, they are very practical in relatively isolated environments where communication range is less critical, such as underground parking lots and deep in the mountains. Antennas are crucial components for receiving and transmitting wireless signals. Antennas have a lifespan. When an antenna nears the end of its lifespan, its ability to transmit and receive wireless signals degrades, leading to anomalies such as discrepancies between the converted audio information and the pre-input audio information. This can lead to degraded voice quality, increased communication interference, and other adverse factors that can affect communication. Therefore, based on the converted audio information, the system intelligently identifies anomalies in components such as the antenna on the walkie-talkie and applies appropriate measures to ensure reliable communication in various scenarios. Summary of the Invention

[0003] The purpose of the present invention is to provide a terminal device operating status monitoring system and method based on big data to solve the problems raised in the prior art.

[0004] To achieve the above object, the present invention provides the following technical solutions: A method for monitoring the operating status of terminal equipment based on big data, comprising the following steps: Step S100: Acquire historical communication data between the target terminal device and several characteristic terminal devices, perform pre-processing, analyze the content integrity based on the sent and received signals in each communication data, and obtain the characteristic distance of each terminal device; Step S200: extracting target data from the communication data corresponding to the target terminal device based on the communication data corresponding to each characteristic terminal device within the characteristic distance; Step S300: extracting features from the transmitted and received signals, calculating the signal similarity between the transmitted and received signals in each target data, and then obtaining the abnormality coefficient of each target data; Step S400: Set a target weight according to the communication distance corresponding to each target data, and obtain the device abnormality value of the target terminal device according to the abnormality coefficient. According to the device abnormality value, determine the abnormality of the communication component on the target terminal device.

[0005] Furthermore, step S100 includes: Step S110: Acquire several characteristic terminal devices of the same model as the target terminal device, collect historical communication data between any two terminal devices, and extract the device sending signals, sending audio information, and the device receiving signals and receiving audio information from the communication data; Establish a three-dimensional model of the transmission space. In a communication data, the device sending the signal is E1, and the device receiving the signal is E2. The positions of device E1 and device E2 in the three-dimensional model when sending and receiving audio information are respectively P1 and P2. With position P1 as the starting point and position P2 as the end point, we get the vector V 12 ; The module with the highest height greater than the height threshold in the three-dimensional model is used as the characteristic building module and the vector V 12 The intersecting characteristic building modules are used as labeling modules, and then all labeling modules corresponding to a certain communication data are obtained; In this solution, a characteristic terminal device is a device that has passed various inspections and tests and has qualified communication components. The difference between the communication distance and the characteristic distance is that the communication distance is the distance over which information data is transmitted between two terminal devices. Its length is determined by the straight-line distance between the two terminal devices and the number of marker modules in between. The longer the straight-line distance and the more marker modules in between, the greater the communication distance. The characteristic distance, on the other hand, is the maximum distance over which a terminal device can receive or send audio data. Step S120: Take a panoramic image of the transmission space and convert it into a plane image; take position P1 as the origin, vector V 12 The direction is the positive direction of the horizontal coordinate, vector V 12 The vertical direction is the positive direction of the ordinate, and a plane coordinate system is established; Get the circle centered at position P1, x 2 / a 2 +y 2 / b 2 <1 and x>0, and with position P2 as the center, (xL 12 ) 2 / a 2 +y 2 / b 2 <1 and x <L 12 The second characteristic range, L 12 is the straight-line distance between position P1 and position P2, where a is the first characteristic length, b is the second characteristic length, and 0 <b<L 12 / 2 <a<L 12 ; Get the total area M0 of the feature range, and the area M occupied by all the marking modules within the feature range a , the communication distance between device E1 and device E2 is L 12(1+M a / M0); Step S130: The time when a terminal device sends a certain audio information is used as the sending time, and all terminal devices that receive the certain audio information within a period T after the sending time are marked with a first mark, and all terminal devices that do not receive the certain audio information are marked with a second mark; Get the maximum communication distance L from the user manual of the terminal device max If a terminal device sends an audio message and a first marking device and a second marking device are present at the same time, the maximum communication distance between the terminal device and each first marking device is taken as the distance LM1, and the minimum communication distance between the terminal device and each second marking device is taken as the distance LM2. If the distance LM2 is not less than the distance LM1, the average of the two distances is taken as the characteristic distance of the terminal device; Step S140: If the distance LM2 is smaller than the distance LM1, or the first marking device and the second marking device do not exist at the same time, the characteristic distance of a terminal device is obtained as L=min(k1*LM1, k2*LM2, K3*L max ), min() is to find the minimum value, k1, k2 and k3 are the first, second and third distance coefficients respectively; and so on, the characteristic distances of all terminal devices are obtained.

[0006] It should be noted that terminal devices such as walkie-talkies actually have two concepts: transmission distance and reception distance. However, these are generally considered to be roughly the same. In this solution, the characteristic distance refers to the maximum distance at which a walkie-talkie's transmitted signal can be effectively received, and the maximum distance at which a walkie-talkie can effectively receive signals transmitted by other walkie-talkies. In this embodiment, the communication distance between terminal devices is obtained using a locator deployed on the terminal device.

[0007] Furthermore, step S200 includes: Step S210: Obtain the communication distance between two terminal devices corresponding to a certain communication data, as well as the characteristic distances of the two terminal devices. When each characteristic distance is greater than the communication distance, convert both the transmitted audio information and the received audio information into spectrograms. If the amplitude difference between the two spectrograms of a frequency corresponding to a certain moment is greater than a difference threshold, mark the frequency corresponding to the said moment. If the number of times a certain frequency is marked is greater than a quantity threshold, the certain frequency is regarded as the change frequency, and the amplitude difference extracted when the certain frequency is marked is averaged, and the average value is used as the change amplitude value of the certain frequency; then all the change frequencies and the corresponding change amplitude values ​​are obtained, and based on each change frequency and the corresponding change amplitude value, a functional relationship diagram of the amplitude value changing with the frequency is established; Step S220: Acquire certain communication data corresponding to the target terminal device and a certain characteristic terminal device, and obtain a target spectrum diagram of the target terminal device at a certain time t; and add and subtract the amplitudes corresponding to each frequency in the target spectrum diagram and the function relationship diagram to obtain an addition spectrum diagram and a subtraction spectrum diagram; Then, the variances of the added spectrum graph, the subtracted spectrum graph and the target spectrum graph with the spectrum graph corresponding to a certain characteristic terminal device at a certain time t are obtained. If the minimum variance value is greater than the preset variance threshold, the certain time t is taken as the target time, and all target times are obtained; if the ratio of the sum of the target times to the total time period of sending audio information corresponding to a certain communication data is greater than the time ratio threshold, the certain communication data is taken as the target data.

[0008] It should be noted that for terminal devices such as walkie-talkies with audio input and output, when aging or failure occurs, it will cause abnormal phenomena such as the loss or attenuation of some audio frequency components in the audio signal. This is specifically reflected in the two spectrum diagrams of input and output, where the amplitudes of the corresponding frequencies are different. In this solution, the function relationship diagram is the spectrum diagram corresponding to the terminal device obtained based on the above phenomenon. The horizontal axis of the function relationship diagram is frequency, and the vertical axis is amplitude. This function relationship diagram is obtained by analyzing each characteristic terminal device, so this function relationship diagram is also applicable to the target terminal device; by substituting the function relationship diagram into the communication data corresponding to the target terminal device, the target data can be obtained.

[0009] Furthermore, step S300 includes: Step S310: respectively obtain the amplitude of the transmitted audio information and the received audio information in a certain target data at each moment, and establish the broken lines M1 and M2 of the amplitude change of the transmitted audio information and the received audio information with time, and normalize the amplitude of each moment corresponding to the broken lines M1 and M2 to obtain the broken lines and ; The polyline On the polyline When above, the broken line With polyline The area between is the decline area, and the broken line On the polyline When it is below, the broken line With polyline The area between is the rising area; Step S320: Obtain the total area of ​​the decreasing area and the increasing area, add them together to get the sum of the area, and divide the two total areas by the sum of the area to get the weights corresponding to the two areas; divide the total time when the decreasing amplitude is greater than the amplitude threshold by the total decreasing time to get the deviation value Q of the decreasing area r, divide the total time when the increase is greater than the amplitude threshold by the total increase time to obtain the deviation value Q of the increase area i , and then get the abnormal coefficient C=K of the target data r *Q r +K i *Q i , and normalized, K r is the weight of the drop area, K i is the weight of the rising area.

[0010] When audio signal amplitude is significantly reduced, there's a risk of information loss. Especially at low amplitudes, subtle audio details can be drowned out by background noise, leading to loss of audio information. The primary concern with amplitude increase is signal distortion. Clipping occurs when the audio signal amplitude exceeds the dynamic range of the device or system. Both amplitude reduction and amplitude increase affect audio signal transmission, so the amplitude reduction and amplitude increase of the audio signal, resulting in an abnormal coefficient, can have a significant effect.

[0011] Further, step S400 includes: according to step S100, obtaining the communication distance LT and characteristic range corresponding to a certain target data, and obtaining the ratio h of the area occupied by all the marking modules in the characteristic range to the area of ​​the characteristic range, and obtaining the target weight W=e corresponding to the certain target data. -(k*LT / h) , where e is the natural logarithm, k is the weight coefficient, k>0, when h=0, let W=0; get the device abnormal value Z=∑G g=1C of the target terminal device g *W g , and normalized, G is the total number of target data, C g is the abnormal coefficient of the g-th target data, W g is the target weight of the g-th target data.

[0012] In this scheme, the target weight is determined based on the communication distance and feature range. This is mainly because the communication distance and feature range are both major factors affecting the communication data of the target terminal device. When the communication distance is small, the impact on the device abnormal value is small. When the ratio h is large, the impact on the device abnormal value is large, and the target weight should be large; y=e -x In the equation, y decreases as x increases, so W=e -(k*LT / h) .

[0013] A terminal equipment operation status monitoring system based on big data, including a feature distance obtaining module, a target data obtaining module, an abnormality coefficient calculation module and an abnormality judgment module; Obtaining characteristic distance module: used to obtain historical communication data between the target terminal device and several characteristic terminal devices, and perform preprocessing, analyze the content integrity based on the sending and receiving signals in each communication data, and obtain the characteristic distance of each terminal device; Obtain target data module: used to extract target data from the communication data corresponding to the target terminal device according to the communication data corresponding to each characteristic terminal device within the characteristic distance; Anomaly coefficient calculation module: used to extract features of the transmitted and received signals, calculate the signal similarity of the transmitted and received signals in each target data, and then obtain the anomaly coefficient of each target data; Abnormal situation judgment module: used to set the target weight according to the communication distance corresponding to each target data, and obtain the device abnormality value of the target terminal device according to the abnormal coefficient, and judge the abnormal situation of the communication component on the target terminal device according to the device abnormality value.

[0014] Furthermore, the characteristic distance obtaining module includes a marking module obtaining unit, a plane coordinate system establishing unit, a communication distance analyzing unit and a characteristic distance obtaining unit; Obtaining a marking module unit: used to obtain several characteristic terminal devices of the same model as the target terminal device; establish a three-dimensional model of the transmission space, obtain all characteristic building modules therein, and extract the marking modules therein to obtain all marking modules corresponding to a certain communication data; A plane coordinate system establishing unit is used to capture a panoramic image of the transmission space and convert it into a plane graph; and obtain a first characteristic range and a second characteristic range corresponding to a certain communication data therein, thereby obtaining a communication distance; Communication distance analysis unit: used to obtain the maximum communication distance specified in the user manual of the terminal device. If a terminal device sends an audio message and a first marking device and a second marking device are present at the same time, each marking device is analyzed to obtain a characteristic distance of the terminal device. Obtaining characteristic distance unit: used to obtain the characteristic distance of a terminal device.

[0015] Furthermore, the abnormal coefficient calculation module includes a decrease / increase range region judgment unit and an abnormal coefficient calculation unit; A falling amplitude region determination unit is used to obtain the amplitude of the transmitted audio information and the received audio information in a certain target data at each moment, and to establish a broken line showing the amplitude change of the transmitted audio information and the received audio information over time, and to obtain the falling amplitude region and the rising amplitude region based on the broken line; Abnormal coefficient calculation unit: used to obtain the weights corresponding to the two areas, the deviation value of the decreasing area and the deviation value of the increasing area; obtain the abnormal coefficient of a certain target data.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention provides a terminal device operation status monitoring system and method based on big data, including: obtaining the historical communication data between the target terminal device and several characteristic terminal devices to obtain the characteristic distance of each terminal device; extracting the target data from the communication data corresponding to the target terminal device according to the communication data corresponding to each characteristic terminal device within the characteristic distance; extracting the features of the sent and received signals, calculating the signal similarity of the sent and received signals in each target data, and then obtaining the abnormality coefficient of each target data; setting the target weight, and obtaining the device abnormality value of the target terminal device according to the abnormality coefficient. The present invention obtains the device abnormality value by converting the audio information according to the communication data, intelligently judges the abnormality of the communication components on the target terminal device, and processes it according to the abnormality to ensure the reliable communication of the target terminal device in different occasions. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart of a method for monitoring the operating status of terminal equipment based on big data according to the present invention; Figure 2 This is a structural diagram of a terminal equipment operation status monitoring system based on big data of the present invention. DETAILED DESCRIPTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0019] Example: Figure 1 As shown, the present invention provides a terminal device operation status monitoring system and method technical solution based on big data, including the following steps: Step S100: Obtain historical communication data between the target terminal device and several characteristic terminal devices, perform preprocessing, analyze the content integrity based on the sending and receiving signals in each communication data, and obtain the characteristic distance of each terminal device.

[0020] Step S110: Acquire several characteristic terminal devices of the same model as the target terminal device, collect historical communication data between any two terminal devices, and extract the device sending signals, sending audio information, and the device receiving signals and receiving audio information from the communication data; Establish a three-dimensional model of the transmission space. In a communication data, the device sending the signal is E1, and the device receiving the signal is E2. The positions of device E1 and device E2 in the three-dimensional model when sending and receiving audio information are respectively P1 and P2. With position P1 as the starting point and position P2 as the end point, we get the vector V 12 ; The module with the highest height greater than the height threshold in the three-dimensional model is used as the characteristic building module and the vector V 12 The intersecting characteristic building modules are used as labeling modules, and then all labeling modules corresponding to a certain communication data are obtained; Step S120: Take a panoramic image of the transmission space and convert it into a plane image; take position P1 as the origin, vector V 12 The direction is the positive direction of the horizontal coordinate, vector V 12 The vertical direction is the positive direction of the ordinate, and a plane coordinate system is established; Get the circle centered at position P1, x 2 / a 2 +y 2 / b 2 <1 and x>0, and with position P2 as the center, (xL 12 ) 2 / a 2 +y 2 / b 2 <1 and x <L 12 The second characteristic range, L 12 is the straight-line distance between position P1 and position P2, where a is the first characteristic length, b is the second characteristic length, and 0 <b<L 12 / 2 <a<L 12 ; Get the total area M0 of the feature range, and the area M occupied by all the marking modules within the feature range a , the communication distance between device E1 and device E2 is L 12 (1+M a / M0).

[0021] Step S130: The time when a terminal device sends a certain audio information is used as the sending time, and all terminal devices that receive the certain audio information within a period T after the sending time are marked with a first mark, and all terminal devices that do not receive the certain audio information are marked with a second mark; Get the maximum communication distance L from the user manual of the terminal device maxIf a terminal device sends an audio message and there is a first marking device and a second marking device at the same time, the maximum communication distance between the terminal device and each first marking device is taken as the distance LM1, and the minimum communication distance between the terminal device and each second marking device is taken as the distance LM2. If the distance LM2 is not less than the distance LM1, the average value of the two distances is taken as the characteristic distance of the terminal device.

[0022] Step S140: If the distance LM2 is smaller than the distance LM1, or the first marking device and the second marking device do not exist at the same time, the characteristic distance of a terminal device is obtained as L=min(k1*LM1, k2*LM2, K3*L max ), min() is to find the minimum value, k1, k2 and k3 are the first, second and third distance coefficients respectively; and so on, the characteristic distances of all terminal devices are obtained.

[0023] It should be noted that terminal devices such as walkie-talkies actually have two concepts: transmission distance and reception distance. However, these are generally considered to be roughly the same. In this solution, the characteristic distance refers to the maximum distance at which a walkie-talkie's transmitted signal can be effectively received, and the maximum distance at which a walkie-talkie can effectively receive signals transmitted by other walkie-talkies. In this embodiment, the communication distance between terminal devices is obtained using a locator deployed on the terminal device.

[0024] Step S200: extracting target data from the communication data corresponding to the target terminal device based on the communication data corresponding to each characteristic terminal device within the characteristic distance.

[0025] Step S210: Obtain the communication distance between two terminal devices corresponding to a certain communication data, as well as the characteristic distances of the two terminal devices. When each characteristic distance is greater than the communication distance, convert both the transmitted audio information and the received audio information into spectrograms. If the amplitude difference between the two spectrograms of a frequency corresponding to a certain moment is greater than a difference threshold, mark the frequency corresponding to the said moment. If the number of times a certain frequency is marked is greater than a quantity threshold, the certain frequency is regarded as the change frequency, and the amplitude difference extracted when the certain frequency is marked is averaged, and the average value is used as the change amplitude value of the certain frequency; then all the change frequencies and the corresponding change amplitude values ​​are obtained, and based on each change frequency and the corresponding change amplitude value, a functional relationship diagram of the amplitude value changing with the frequency is established; Step S220: Acquire certain communication data corresponding to the target terminal device and a certain characteristic terminal device, and obtain a target spectrum diagram of the target terminal device at a certain time t; and add and subtract the amplitudes corresponding to each frequency in the target spectrum diagram and the function relationship diagram to obtain an addition spectrum diagram and a subtraction spectrum diagram; Then, the variances of the added spectrum graph, the subtracted spectrum graph and the target spectrum graph with the spectrum graph corresponding to a certain characteristic terminal device at a certain time t are obtained. If the minimum variance value is greater than the preset variance threshold, the certain time t is taken as the target time, and all target times are obtained; if the ratio of the sum of the target times to the total time period of sending audio information corresponding to a certain communication data is greater than the time ratio threshold, the certain communication data is taken as the target data.

[0026] Step S300: extracting features from the transmitted and received signals, calculating the signal similarity of the transmitted and received signals in each target data, and then obtaining the abnormality coefficient of each target data.

[0027] Step S310: respectively obtain the amplitude of the transmitted audio information and the received audio information in a certain target data at each moment, and establish the broken lines M1 and M2 of the amplitude change of the transmitted audio information and the received audio information with time, and normalize the amplitude of each moment corresponding to the broken lines M1 and M2 to obtain the broken lines and ; The polyline On the polyline When above, the broken line With polyline The area between is the decline area, and the broken line On the polyline When it is below, the broken line With polyline The area between them is regarded as the rising area.

[0028] Step S320: Obtain the total area of ​​the decreasing area and the increasing area, add them together to get the sum of the area, and divide the two total areas by the sum of the area to get the weights corresponding to the two areas; divide the total time when the decreasing amplitude is greater than the amplitude threshold by the total decreasing time to get the deviation value Q of the decreasing area r , divide the total time when the increase is greater than the amplitude threshold by the total increase time to obtain the deviation value Q of the increase area i , and then get the abnormal coefficient C=K of the target data r *Q r +K i *Q i , and normalized, K r is the weight of the drop area, K i is the weight of the rising area.

[0029] Step S400: Set a target weight according to the communication distance corresponding to each target data, and obtain the device abnormality value of the target terminal device according to the abnormality coefficient. According to the device abnormality value, determine the abnormality of the communication component on the target terminal device.

[0030] According to step S100, the communication distance LT and characteristic range corresponding to a certain target data are obtained, and the area occupied by all the marking modules in the characteristic range is obtained, and the ratio h of the area of ​​the characteristic range is obtained to obtain the target weight W=e corresponding to the target data. -(k*LT / h) , where e is the natural logarithm, k is the weight coefficient, k>0, when h=0, let W=0; get the device abnormal value Z=∑G g=1C of the target terminal device g *W g , and normalized, G is the total number of target data, C g is the abnormal coefficient of the g-th target data, W g is the target weight of the g-th target data.

[0031] Since the device abnormality value ranges from [0, 1], the larger the value, the greater the abnormality of the communication component. In this embodiment, based on the device abnormality value, if the device abnormality value is in the range of [0, 0.3], it means that it can be used normally and does not need to be replaced. If the device abnormality value is in the range of [0.3, 0.6], it indicates that the device's communication component has a certain degree of abnormality and requires in-depth troubleshooting and prompt repair measures. If the device abnormality value is in the range of [0.6, 1], it means that the device's communication component is in a serious abnormal state and is no longer usable and needs to be replaced in a timely manner. This solution adds a judgment of environmental factors to the communication data of the characteristic terminal device and analyzes each target data. It has the advantages of intelligently analyzing the communication components, improving voice quality, and promptly detecting whether the communication components are abnormal.

[0032] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

Claims

1. A method for monitoring the operation status of terminal equipment based on big data, characterized in that: The following steps are involved: Step S100: Obtain historical communication data between the target terminal device and several characteristic terminal devices, perform preprocessing, analyze content integrity based on the sending and receiving signals in each communication data, and obtain characteristic distance of each terminal device; Step S200: extracting target data from the communication data corresponding to the target terminal device according to the communication data corresponding to each characteristic terminal device within the characteristic distance; Step S300: extracting features from the transmitted and received signals, calculating the signal similarity of the transmitted and received signals in each target data, and then obtaining the abnormal coefficient of each target data; Step S400: according to the communication distance corresponding to each target data, the target weight is set, and according to the abnormal coefficient, the device abnormal value of the target terminal device is obtained, and according to the device abnormal value, the abnormal situation of the communication component on the target terminal device is judged.

2. According to the big data-based terminal equipment operation status monitoring method of claim 1, it is characterized in that: Step S100 includes: Step S110: Acquire several characteristic terminal devices of the same model as the target terminal device, collect historical communication data between any two terminal devices, and extract the device sending signals, sending audio information, the device receiving signals, and receiving audio information from the communication data; Establish a three-dimensional model of the transmission space. In a communication data, the device that sends the signal is E1, and the device that receives the signal is E2. The positions of device E1 and device E2 in the three-dimensional model when sending and receiving audio information are respectively taken as P1 and P2; take position P1 as the starting point and position P2 as the end point, and get the vector V 12 ; The module with the highest height greater than the height threshold in the three-dimensional model is regarded as the characteristic building module and is connected with the vector V 12 The intersecting characteristic building modules are used as marking modules, and then all marking modules corresponding to a certain communication data are obtained; Step S120: Take a panoramic image of the transmission space and convert it into a plane image; take position P1 as the origin, vector V 12 The direction is the positive direction of the horizontal coordinate, vector V 12 The vertical direction is the positive direction of the ordinate, and a plane coordinate system is established; Get the circle centered at position P1, x 2 / a 2 +y 2 / b 2 <1 and x>0, and with position P2 as the center, (xL 12 ) 2 / a 2 +y 2 / b 2 <1 and x <L 12 The second characteristic range, L 12 is the straight-line distance between position P1 and position P2, where a is the first characteristic length, b is the second characteristic length, and 0 <b<L 12 / 2 <a<L 12 ; Get the total area M0 of the feature range, and the area M occupied by all the marking modules within the feature range a , the communication distance between device E1 and device E2 is L 12 (1+M a / M0); Step S130: taking the time when a terminal device sends a certain audio information as the sending time, and performing a first mark on all terminal devices that receive the certain audio information within a time period T after the sending time, and performing a second mark on all terminal devices that do not receive the certain audio information; Get the maximum communication distance L from the user manual of the terminal device max , if a terminal device has a first marking device and a second marking device at the same time after sending an audio message, the maximum value of the communication distance between the terminal device and each first marking device is taken as the distance LM1, and the minimum value of the communication distance between the terminal device and each second marking device is taken as the distance LM2. If the distance LM2 is not less than the distance LM1, the average value of the two distances is taken as the characteristic distance of the terminal device; Step S140: If the distance LM2 is smaller than the distance LM1, or the first marking device and the second marking device do not exist at the same time, the characteristic distance of a terminal device is obtained as L=min(k1*LM1, k2*LM2, K3*L max ), min() is to find the minimum value, k1, k2 and k3 are the first, second and third distance coefficients respectively; and so on, the characteristic distances of all terminal devices are obtained.

3. According to the big data-based terminal equipment operation status monitoring method of claim 2, it is characterized in that: Step S200 includes: Step S210: obtaining the communication distance between two terminal devices corresponding to a certain communication data, and the characteristic distances of the two terminal devices respectively, and when each characteristic distance is greater than the communication distance, converting both the transmitted audio information and the received audio information into a frequency spectrum, wherein if the amplitude difference of the frequency corresponding to a certain moment in the two frequency spectrums is greater than a difference threshold, the frequency corresponding to the certain moment is marked; If the number of times a certain frequency is marked is greater than the quantity threshold, the certain frequency is taken as the change frequency, and the amplitude difference extracted when the certain frequency is marked is averaged, and the average value is taken as the change amplitude value of the certain frequency; then all the change frequencies and the corresponding change amplitude values ​​are obtained, and according to each change frequency and the corresponding change amplitude value, a functional relationship diagram of the amplitude value changing with the frequency is established; Step S220: obtaining certain communication data corresponding to a target terminal device and a certain characteristic terminal device, obtaining a target spectrum diagram of the target terminal device at a certain time t; and adding and subtracting the amplitudes corresponding to each frequency in the target spectrum diagram and the function relationship diagram to obtain an addition spectrum diagram and a subtraction spectrum diagram; Then, the variances of the spectrum graph corresponding to a certain feature terminal device at a certain time t are obtained, namely, the addition spectrum graph, the subtraction spectrum graph and the target spectrum graph. If the minimum variance value is greater than the preset variance threshold, the certain time t is taken as the target time, and all target times are obtained; if the ratio of the sum of the target times to the total time period of sending audio information corresponding to a certain communication data is greater than the time ratio threshold, the certain communication data is taken as the target data.

4. According to the big data-based terminal equipment operation status monitoring method of claim 3, it is characterized in that: Step S300 includes: Step S310: respectively obtain the amplitude of the transmitted audio information and the received audio information in a certain target data at each moment, and establish the broken lines M1 and M2 of the amplitude variation with time in the transmitted audio information and the received audio information, and normalize the amplitude at each moment corresponding to the broken lines M1 and M2 to obtain the broken lines and ; The polyline On the polyline When above, the broken line With polyline The area between is taken as the decline area, and the broken line On the polyline When the line is below With polyline The area between is the rising area; Step S320: Obtain the total area of ​​the decreasing area and the increasing area, add them together to get the sum of the area, and divide the two total areas by the sum of the area to get the weights corresponding to the two areas; divide the total time when the decreasing amplitude is greater than the amplitude threshold by the total decreasing amplitude time to get the deviation value Q of the decreasing area r , divide the total time when the increase is greater than the amplitude threshold by the total increase time to obtain the deviation value Q of the increase area i , and then get the abnormal coefficient C=K of the target data r *Q r +K i *Q i , and normalized, K r is the weight of the drop area, K i is the weight of the rising area.

5. According to the big data-based terminal equipment operation status monitoring method of claim 4, it is characterized in that: Step S400 includes: according to step S100, obtaining the communication distance LT and the characteristic range corresponding to a certain target data, and obtaining the ratio h of the area occupied by all the marking modules in the characteristic range in the characteristic range to the area of ​​the characteristic range, and obtaining the target weight W=e corresponding to the certain target data -(k*LT / h) , where e is the natural logarithm, k is the weight coefficient, k>0, when h=0, let W=0; get the device abnormal value Z=∑G g=1C of the target terminal device g *W g , and normalized, G is the total number of target data, C g is the abnormal coefficient of the g-th target data, W g is the target weight of the g-th target data.

6. A terminal device operation status monitoring system, used to execute a terminal device operation status monitoring method based on big data as described in any one of claims 1 to 5, characterized in that: The system includes a feature distance obtaining module, a target data obtaining module, an abnormality coefficient calculation module and an abnormality judgment module; Obtaining characteristic distance module: used to obtain historical communication data between the target terminal device and several characteristic terminal devices, and perform preprocessing, analyze the content integrity according to the sending and receiving signals in each communication data, and obtain the characteristic distance of each terminal device; Obtaining target data module: used to extract target data from the communication data corresponding to the target terminal device according to the communication data corresponding to each characteristic terminal device within the characteristic distance; Anomaly coefficient calculation module: used to extract features of the transmitted and received signals, calculate the signal similarity of the transmitted and received signals in each target data, and then obtain the anomaly coefficient of each target data; Abnormal situation judgment module: used to set the target weight according to the communication distance corresponding to each target data, and obtain the device abnormal value of the target terminal device according to the abnormal coefficient, and judge the abnormal situation of the communication component on the target terminal device according to the device abnormal value.

7. A terminal device operation status monitoring system according to claim 6, characterized in that: The characteristic distance obtaining module comprises a marking module obtaining unit, a plane coordinate system establishing unit, a communication distance analyzing unit and a characteristic distance obtaining unit; Obtaining a marking module unit: used to obtain a number of characteristic terminal devices of the same model as the target terminal device; Establish a three-dimensional model of the transmission space, obtain all characteristic building modules therein, extract the marking modules therein, and obtain all marking modules corresponding to a certain communication data; A plane coordinate system establishing unit is used to capture a panoramic image of the transmission space and convert it into a plane figure; and obtain a first characteristic range and a second characteristic range corresponding to a certain communication data therein, and then obtain a communication distance; Communication distance analysis unit: used to obtain the maximum communication distance in the user manual corresponding to the terminal device. If a terminal device sends a certain audio message and there is a first marking device and a second marking device at the same time, each marking device is analyzed to obtain a characteristic distance of the terminal device; Obtain characteristic distance unit: used to obtain the characteristic distance of a terminal device.

8. A terminal device operation status monitoring system according to claim 7, characterized in that: The abnormal coefficient calculation module includes a drop-rise area judgment unit and an abnormal coefficient calculation unit; A decreasing and increasing amplitude region judgment unit is used to obtain the amplitude of the transmitted audio information and the received audio information in a certain target data at each moment, and to establish a broken line showing the amplitude change of the transmitted audio information and the received audio information with time, and to obtain the decreasing amplitude region and the increasing amplitude region according to the broken line; Abnormal coefficient calculation unit: used to obtain the weights corresponding to the two areas, the deviation value of the decreasing area and the deviation value of the increasing area; The abnormal coefficient of the target data is obtained.

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