CN115574853A - Method, system, equipment and medium for judging sensor abnormity - Google Patents
Method, system, equipment and medium for judging sensor abnormity Download PDFInfo
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Abstract
The invention discloses a method, a system, equipment and a medium for judging sensor abnormity, wherein a plurality of initial detection data and identification codes of a sensor are obtained according to a preset period, the difference value between two adjacent initial detection data is calculated, a plurality of target fluctuation value data are generated, the plurality of initial detection data, the identification codes and the target fluctuation value data are preprocessed, a plurality of modulation data to be analyzed are generated, the plurality of modulation data to be analyzed are subjected to reverse preprocessing, a plurality of target data to be analyzed are generated, each target data to be analyzed is screened by adopting a preset separation condition, a plurality of corresponding target data to be judged are determined, the difference value between two adjacent initial detection data in each target data to be judged and the associated target fluctuation value data are compared, and whether the sensor is abnormal or not is judged according to a comparison result; the technical problem that in a complex environment, if the sensor is abnormal, transmitted data are in error, and accuracy of transmitted data collection is affected is solved.
Description
Technical Field
The invention relates to the technical field of sensor detection, in particular to a method, a system, equipment and a medium for judging sensor abnormity.
Background
USRP is a general purpose software radio peripheral that enables a common computer to function as a high bandwidth software radio. USRP essentially acts as the digital baseband and intermediate frequency parts of a radio communication system, and engineers can use various software on the host CPU to perform all waveform-related processing. While high speed general purpose operations such as digital up-down conversion, sampling and interpolation are on the FPGA. Because of this feature, USRP can be made flexible to transmit using different modem methods for a plurality of data formats, and the budget and development time can be reduced.
In modern industrial processes, particularly automated processes, various sensors are used to monitor and control various parameters in the process. In addition, the sensor has many other applications in the fields of deepening material recognition, developing new energy, new materials and the like, particularly, in the research of various extreme technologies, the sensor needs to work in extreme monitoring environments such as ultrahigh temperature, ultralow temperature, ultrahigh pressure, ultrahigh vacuum and the like, and under the scene, besides certain requirements on the product quality and the bearing capacity of the sensor, certain requirements on the wiring of a cable for transmitting sensor data are also needed. If the sensor is in a corrosive environment, the best option is to have the sensor autonomously perform the electromagnetic wave based signal transmission.
At present, when a sensor transmits signals based on electromagnetic waves in a complex environment, if the sensor has an abnormal problem, transmitted data has errors, and accuracy of transmitted data collection is affected.
Disclosure of Invention
The invention provides a method, a system, equipment and a medium for judging sensor abnormity, which solve the technical problems that when a sensor transmits signals based on electromagnetic waves in a complex environment, if the sensor is abnormal, transmitted data has errors, and the accuracy of transmitted data collection is influenced.
The invention provides a method for judging sensor abnormity, which is applied to a USRP device, wherein a sensor is connected with the USRP device through a serial port switching device, and the method comprises the following steps:
acquiring a plurality of initial detection data and identification codes acquired by the sensor according to a preset period;
calculating a difference value between two adjacent initial detection data to generate a plurality of target fluctuation value data;
preprocessing the plurality of initial detection data, the identification codes and the target fluctuation value data to generate a plurality of modulated data to be analyzed;
carrying out inverse preprocessing on the plurality of modulated data to be analyzed to generate a plurality of target data to be analyzed;
screening each target data to be analyzed by adopting a preset separation condition, and determining a plurality of corresponding target data to be judged;
and comparing the difference value between two adjacent initial detection data in each target data to be judged with the associated target fluctuation value data, and judging whether the sensor is abnormal or not according to the comparison result.
Optionally, the step of preprocessing the plurality of initial detection data, the identification code, and the target fluctuation value data to generate a plurality of modulated data to be analyzed includes:
binary conversion is carried out on the plurality of initial detection data, and binary bit detection data corresponding to the number of the digits are generated according to the number of the digits in the initial detection data;
binary conversion is carried out on the target fluctuation value numbers to generate binary bit fluctuation data of a plurality of preset binary numbers;
sequencing the identification codes, the binary bit detection data and the binary bit fluctuation data according to a preset sequencing condition to construct a plurality of initial data to be analyzed;
and carrying out data modulation on each initial data to be analyzed to generate a plurality of corresponding data to be analyzed.
Optionally, the step of performing inverse preprocessing on the multiple pieces of modulation data to be analyzed to generate multiple pieces of target data to be analyzed includes:
demodulating according to the received multiple modulated data to be analyzed to generate multiple initial data to be analyzed;
and performing decimal conversion on the plurality of initial data to be analyzed to generate a plurality of target data to be analyzed.
Optionally, the step of screening each target data to be analyzed by using a preset separation condition to determine a plurality of corresponding target data to be determined includes:
screening the target data to be analyzed with consistent separators from the plurality of target data to be analyzed as initial data to be judged;
sequencing the plurality of initial data to be judged according to a data acquisition sequence to obtain a plurality of intermediate data to be judged;
taking the identification code in the intermediate data to be judged as a separator, and acquiring the number of the numbers to be judged between two adjacent separators;
comparing the number of the numbers to be judged with the number of preset standard numbers;
and if the number of all the numbers to be judged is consistent with the number of the standard numbers, taking the intermediate data to be judged as target data to be judged.
Optionally, the method further comprises:
and if any one of the numbers to be judged is inconsistent with the standard number, judging that the initial data to be judged related to the numbers to be judged is abnormal.
Optionally, the method further comprises:
when the number of times of the abnormal initial data to be judged is larger than a preset standard value, judging that the network environment at the current moment is unstable;
when the number of times of the abnormal initial data to be judged is less than or equal to a preset standard value, screening out the initial data to be judged related to the number of the numbers to be judged, and generating new intermediate data to be judged;
and skipping to execute the step of taking the identification code in the intermediate data to be judged as a separator and acquiring the number of the numbers to be judged between two adjacent separators.
Optionally, the step of comparing a difference between two adjacent initial detection data in each target data to be determined with the associated target fluctuation value data, and determining whether the sensor is abnormal according to a comparison result includes:
calculating a difference value between two adjacent initial detection data in each target data to be judged to obtain a first difference value;
comparing each of the first difference values with the associated target fluctuation value data;
if all the first difference values are consistent with the associated target fluctuation value data, judging that the sensor is not abnormal;
and if any first difference value is inconsistent with the associated target fluctuation value data, judging that the sensor is abnormal.
The system for judging the abnormality of the sensor provided by the second aspect of the invention is applied to a USRP device, the sensor is connected with the USRP device through a serial port switching device, and the system comprises:
the data acquisition module is used for acquiring a plurality of initial detection data and identification codes acquired by the sensor according to a preset period;
the target fluctuation value data acquisition module is used for calculating the difference value between two adjacent initial detection data and generating a plurality of target fluctuation value data;
the modulation data to be analyzed acquisition module is used for preprocessing the plurality of initial detection data, the identification codes and the target fluctuation value data to generate a plurality of modulation data to be analyzed;
the target data to be analyzed acquisition module is used for carrying out inverse preprocessing on the plurality of modulated data to be analyzed to generate a plurality of target data to be analyzed;
the target data to be judged acquisition module is used for screening the data to be analyzed of each target by adopting a preset separation condition and determining a plurality of corresponding data to be judged of the target;
and the abnormity judgment module is used for comparing the difference value between two adjacent initial detection data in the data to be judged of each target with the associated target fluctuation value data and judging whether the sensor is abnormal or not according to the comparison result.
An electronic device according to a third aspect of the present invention includes a memory and a processor, wherein the memory stores a computer program, and the computer program, when executed by the processor, causes the processor to execute the steps of the method for determining a sensor abnormality according to any one of the above-described methods.
A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed, implements the method for determining a sensor abnormality according to any one of the above.
According to the technical scheme, the invention has the following advantages:
acquiring a plurality of initial detection data and identification codes acquired by a sensor according to a preset period, calculating a difference value between two adjacent initial detection data, generating a plurality of target fluctuation value data, preprocessing the initial detection data, the identification codes and the target fluctuation value data, generating a plurality of modulation data to be analyzed, performing inverse preprocessing on the modulation data to be analyzed, generating a plurality of target data to be analyzed, screening the target data to be analyzed by adopting a preset separation condition, determining a plurality of corresponding target data to be judged, comparing the difference value between two adjacent initial detection data in the target data to be judged with the associated target fluctuation value data, and judging whether the sensor is abnormal or not according to a comparison result; the technical problem that when a sensor transmits signals based on electromagnetic waves in a complex environment, if the sensor is abnormal, transmitted data are in error, and accuracy of transmitted data collection is affected is solved; the method and the device realize the accurate judgment of whether the sensor is abnormal or not and the accuracy of data transmission of the sensor under the complex environment, and can judge the state of the current network environment and further search for the source causing the sensor to be abnormal.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a flowchart illustrating steps of a method for determining an abnormality of a sensor according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating steps of a method for determining an abnormal condition of a sensor according to a second embodiment of the present invention;
fig. 3 is a block diagram of a system for determining abnormality of a sensor according to a third embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a method, a system, equipment and a medium for judging sensor abnormity, which are used for solving the technical problems that when a sensor transmits signals based on electromagnetic waves in a complex environment, if the sensor is abnormal, transmitted data have errors, and the accuracy of transmitted data collection is influenced.
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a flowchart illustrating a method for determining an abnormality of a sensor according to an embodiment of the present invention.
The invention provides a method for judging sensor abnormity, which is applied to a USRP device, wherein a sensor is connected with the USRP device through a serial port switching device, and the method comprises the following steps:
The USRP device, which is a general software radio peripheral, enables a general computer to function as a high-bandwidth software radio. The USRP essentially acts as the digital baseband and intermediate frequency part of a radio communication system, and engineers can use various software on the host CPU to perform all waveform-related aspects of the processing.
And the serial port switching device is a switching device for connecting the sensor and the USRP device.
The initial detection data refers to the detection data collected by the sensor.
The identification code refers to address code data sent by the sensor to the USRP device and is used for distinguishing the source of transmitted data and screening out data belonging to the sensor in a complex wireless environment.
The preset period refers to a preset time period, and the specific period can be set according to requirements, which is not limited herein.
In the embodiment of the invention, the initial detection data collected by the sensor is obtained according to the time period set by preselection, and the identification code of the sensor is obtained simultaneously when the sensor transmits the initial detection data to the USRP device.
And 102, calculating a difference value between two adjacent initial detection data to generate a plurality of target fluctuation value data.
The target fluctuation value refers to a fluctuation value between the detection data according to a difference between two adjacent initial detection data.
In the embodiment of the invention, according to the acquired initial detection data acquired by the sensor, the initial detection data are sequenced according to the transmission time, the difference value between two adjacent initial detection data is calculated, and a plurality of target fluctuation value data are generated.
And 103, preprocessing the plurality of initial detection data, the identification codes and the target fluctuation value data to generate a plurality of modulated data to be analyzed.
Preprocessing refers to binary conversion, sorting, and modulation processing.
And modulating the data to be analyzed refers to data generated after preprocessing is performed according to the plurality of initial detection data, the identification codes and the target fluctuation value data, and is used for data subjected to inverse preprocessing.
In the embodiment of the invention, binary conversion, sorting and modulation processing are carried out on a plurality of initial detection data, a plurality of identification codes and a plurality of target fluctuation value data, and a plurality of modulated data to be analyzed are generated.
And 104, performing inverse preprocessing on the plurality of modulated data to be analyzed to generate a plurality of target data to be analyzed.
Inverse pre-processing, which refers to decimal conversion and modulation.
The target data to be analyzed refers to data generated after inverse preprocessing is performed on the plurality of modulated data to be analyzed, and the data is used for screening out the target data to be judged.
In the embodiment of the invention, decimal conversion and modulation are carried out on a plurality of modulated data to be analyzed to generate a plurality of target data to be analyzed.
And 105, screening the data to be analyzed of each target by adopting a preset separation condition, and determining a plurality of corresponding data to be judged of the target.
The preset separation condition refers to a condition for screening out target data to be judged from a plurality of target data to be analyzed.
The preset separation condition refers to whether the number of digits between two adjacent identification codes is equal to the standard number of digits.
In the embodiment of the invention, the target data to be judged is screened out from the plurality of target data to be analyzed according to the preset separation condition.
And 106, comparing the difference value between two adjacent initial detection data in the data to be judged of each target with the associated target fluctuation value data, and judging whether the sensor is abnormal or not according to the comparison result.
In the embodiment of the invention, according to target data to be judged obtained after inverse preprocessing and screening, the difference value between two adjacent initial detection data in the target data to be judged is calculated and compared with the associated target fluctuation value data obtained before inverse preprocessing, if all the first difference values are consistent with the associated target fluctuation value data, the sensor is judged not to be abnormal, and if any one of the first difference values is inconsistent with the associated target fluctuation value data, the sensor is judged to be abnormal.
In the embodiment of the invention, a plurality of initial detection data and identification codes acquired by a sensor are acquired according to a preset period, the difference value between two adjacent initial detection data is calculated to generate a plurality of target fluctuation value data, the initial detection data, the identification codes and the target fluctuation value data are preprocessed to generate a plurality of modulation data to be analyzed, the modulation data to be analyzed are subjected to inverse preprocessing to generate a plurality of target data to be analyzed, each target data to be analyzed is screened by adopting a preset separation condition, a plurality of corresponding target data to be judged are determined, the difference value between two adjacent initial detection data in each target data to be judged and the associated target fluctuation value data are compared, and whether the sensor is abnormal or not is judged according to a comparison result; the technical problem that when a sensor transmits signals based on electromagnetic waves in a complex environment, if the sensor is abnormal, transmitted data are in error, and accuracy of transmitted data collection is affected is solved; the method and the device realize the accurate judgment of whether the sensor is abnormal or not and the accuracy of data transmission of the sensor under the complex environment, and can judge the state of the current network environment and further search for the source causing the sensor to be abnormal.
Referring to fig. 2, fig. 2 is a flowchart illustrating a method for determining abnormality of a sensor according to a second embodiment of the present invention.
The invention provides a method for judging sensor abnormity, which is applied to a USRP device, wherein a sensor is connected with the USRP device through a serial port switching device, and the method comprises the following steps:
In the embodiment of the present invention, the specific implementation process of step 201 is similar to that of step 101, and is not described herein again.
It is worth mentioning that the identification code is used for distinguishing the source of the transmitted data, and screening out the data belonging to the sensor in a complex wireless environment, and there may be a plurality of data adopting the same modulation mode in a certain frequency band in an industrial scene, and the sources of the data do not necessarily belong to the sensor.
In an embodiment of the present invention, a sensor including a signal output interface and a USRP peripheral of model LWE310 are used. And the sensor is connected with the USRP by using an RS 485-USB interface.
The universal multifunctional sensor can support a modbus protocol, and after the sensor acquires monitoring data, a script which is configured in advance on an ARM system in the USRP device serving as a transmitting end can capture serial port data by adopting the protocol. An operator pre-configures rules for data screening and capturing in the script according to actual monitoring requirements and the technical indexes of the used sensor.
In one example of the invention, a certain sensor supports monitoring of four data of formaldehyde concentration, light intensity, temperature and humidity, a script inside the USRP acquires the data of the sensor through a modbus protocol, and a data structure is an array containing 4 elements. For example (here, by way of example only, the actual monitoring data may not be the same, but all are necessarily expressed in integer numbers): the formaldehyde concentration, the light intensity, the temperature and the humidity correspond to [120, 560, 242 and 317], and if the data that the operator needs to acquire is the temperature, the element with the index of 2 in the array, namely 242, is directly captured through the pre-configuration of the script. The scheme supports screening of a plurality of data, specifically screens out which data, and configures the script according to the actual configuration of an operator.
And 202, calculating a difference value between two adjacent initial detection data to generate a plurality of target fluctuation value data.
In the embodiment of the present invention, the specific implementation process of step 202 is similar to that of step 102, and is not described herein again.
Further, step 203 may comprise the sub-steps of:
and S11, carrying out binary conversion on the plurality of initial detection data, and generating binary bit detection data corresponding to the plurality of numbers according to the numbers in the initial detection data.
The number of digits refers to the number of times a digit appears in the detected data.
In the embodiment of the present invention, binary conversion is performed on a plurality of pieces of acquired initial detection data, and binary bit detection data corresponding to a plurality of numbers is generated according to the number of numbers included in the initial detection data.
In one example of the invention, the integer data obtained from the sensor is converted from decimal to binary, for example, the actual temperature is 24.2,usrp and the data after being captured and filtered by modbus protocol is 242. The data after the system conversion is:
decimal integer data: 242
Binary bit: 0010 0100 0010
And S12, carrying out binary conversion on the target fluctuation value numbers to generate binary bit fluctuation data with a plurality of preset binary numbers.
In the embodiment of the invention, binary conversion is carried out on the obtained multiple target fluctuation value numbers, and conversion is carried out according to the preset binary number to generate multiple binary bit fluctuation data with the preset binary number.
In one example of the present invention, the data captured for the first time is 21.1 degrees, the data captured for the second time is 23.1 degrees, and the temperature difference between the two is 2 degrees, so the tag value is 0000 0000 0010 0000, and four 4-bit binary books are used to represent one bit after hundred, ten, one and decimal point respectively. The binary bit fluctuation data may be configured according to the actual monitoring data.
It should be noted that the main purpose of decimal to binary conversion is to use QPSK modulation by default for subsequent modulation, that is, one subcarrier contains 2 bits of information, in combination with the above example, 0010 0100 0010 is split into 0010 0001 0010 for transmission, and the receiving end recovers data to 0010 0100 0010 after demodulation.
If 16QAM modulation is used, i.e. one subcarrier contains 4 bits of information, then the modulation is done directly. If low order BPSK modulation is used, i.e. one subcarrier contains 1 bit of information, the binary bits are modulated one by one in this case.
And S13, sequencing the identification codes, the binary bit detection data and the binary bit fluctuation data according to a preset sequencing condition, and constructing a plurality of initial data to be analyzed.
The preset ordering condition refers to ordering according to the sequence of the identification code, the binary bit detection data and the binary bit fluctuation data.
In the embodiment of the invention, the identification codes, the binary bit detection data and the binary bit fluctuation data are sequenced according to the preset sequencing conditions, and a plurality of initial data to be analyzed are constructed.
The specific embodiment mode of the initial data to be analyzed is as follows:
| identification code | Binary bit detection data | Binary bit wobble data |
It should be noted that the identification code is set at the front end of the binary bit detection data, and the main function of the identification code is to provide a special demodulation result to allow the receiving end to determine the initial position of the transmission data, and in the whole data transmission process, the data is continuously sent to the receiving end, so for the receiving end, a special value is necessarily needed to determine the starting point of each group of data to separate each sending.
In one example of the present invention, the identification code needs to be preset, and the configured data has a certain distinctive specificity compared to the initial detection data, and the identification code is not fixed, and is configured according to the actual monitoring data and the requirement, but must be in a binary bit form. For example, the data to be transmitted is temperature: 242 whose binary data is 0010 0100 0010, the identification code can be set to 1111 because 1111 is converted to decimal and is a two-digit number, in which case it must not be data representing temperature. The following is the processed data shown according to the example:
identification code binary bit detection data
1111 0010 0100 0010
It should be mentioned that binary bit fluctuation data is set at the back end of the binary bit detection data, and the binary bit detection data is generated by binary conversion of the difference between the current initial detection data and the previous initial detection data, where the difference is a signed integer and is represented in a complementary form when the difference is a negative number. The fluctuation value of the data acquired for the first time is 0 (the data acquired for the second time is required to satisfy the structure of identification code + binary bit detection data + binary bit fluctuation data, but the fluctuation value for the first time is 0).
In one example of the present invention, the last measured temperature is 242, the current measured temperature is 245, and the preprocessed data is:
binary bit fluctuation data of identification code binary bit detection data
1111 0010 0100 0010 0000 0000 0000 0011
And S14, carrying out data modulation on each initial data to be analyzed to generate a plurality of corresponding data to be analyzed.
In the embodiment of the invention, each initial data to be analyzed is subjected to data modulation, that is, the initial data to be analyzed is modulated and converted into a corresponding IQ signal, that is, a plurality of modulated data to be analyzed in a corresponding IQ signal form are generated, and are converted into electromagnetic waves through USRP hardware to be emitted.
And 204, demodulating according to the received multiple modulated data to be analyzed to generate multiple initial data to be analyzed.
In the embodiment of the invention, a plurality of pieces of initial data to be analyzed are generated by demodulating a plurality of pieces of modulated data to be analyzed received by a receiving end of the USRP device.
It should be noted that the receiving end of the USRP device can automatically receive the signal in the wireless environment and perform the demodulation step, and demodulate the received radio carrier, and the modulation and demodulation of the transmitting end of the USRP device are consistent.
It is worth mentioning that the initial data to be analyzed after demodulation is as follows: 0010 0100 0010 0000 0000 0000 0001 0010 0100 0100 0000 0000 0010 1111 0010 0100 0100 0000 0000 0000 1111 0010 0100 0100 0101.. The script of the receiving end distinguishes each transmission by the identification code 1111, except for distinguishing each transmission, the message source sensor can be distinguished by proper configuration.
And step 205, performing decimal conversion on the plurality of initial data to be analyzed to generate a plurality of target data to be analyzed.
In the embodiment of the invention, decimal conversion is carried out on a plurality of initial data to be analyzed to generate a plurality of target data to be analyzed.
And step 206, screening the data to be analyzed of each target by adopting a preset separation condition, and determining a plurality of corresponding data to be judged of the target.
Further, step 206 may comprise the following sub-steps:
s21, screening target data to be analyzed with consistent separators from the plurality of target data to be analyzed to serve as initial data to be judged.
And S22, sequencing the plurality of initial data to be judged according to the data acquisition sequence to obtain a plurality of intermediate data to be judged.
And S23, taking the identification code in the middle data to be judged as a separator, and acquiring the number of the numbers to be judged between two adjacent separators.
In one example of the invention, S21-S23 are of the form:
.., 2, 0, 1, 2, 4, 0, 2, 4, 0, 2.
And S24, comparing the number of the numbers to be judged with the number of the preset standard numbers.
The standard number refers to the number of standard numbers that should be obtained after decimal conversion of data between two separators.
It is worth mentioning that the standard number refers to the number of decimal digits.
In the embodiment of the invention, the number of the numbers to be judged is compared with the number of the preset standard numbers.
For example, the correct number after decimal conversion of the data between two separators should be the temperature + target fluctuation value data, with a 7 decimal number between the two separators.
And S25, if the number of all the numbers to be judged is consistent with the number of the standard numbers, taking the middle data to be judged as target data to be judged.
In the embodiment of the invention, if the number of all the numbers to be judged is consistent with the number of the standard numbers, the intermediate data to be judged is taken as the target data to be judged.
Further, step 206 may also include the following sub-steps:
and S26, if the number of any to-be-judged number is inconsistent with the number of the standard numbers, judging that the initial to-be-judged data related to the number of the to-be-judged numbers is abnormal.
In the embodiment of the invention, if any number to be judged is inconsistent with the standard number, the initial data to be judged related to the number of the numbers to be judged is judged to be abnormal.
Further, S26 may include the following sub-steps:
a1, when the number of times of the abnormal initial data to be judged is larger than a preset standard value, judging that the network environment at the current moment is unstable.
The preset standard value refers to a standard threshold value used for judging the number of times of abnormality of the initial data to be judged.
In the embodiment of the invention, when the number of times of the abnormal initial data to be judged is greater than the preset standard value, the network environment at the current moment is judged to be unstable.
It should be noted that, when it is determined that the network environment is unstable at the current time, the receiving end of the URSP device performs modulation negotiation with the transmitting end in another radio frequency channel, and the transmitting end and the receiving end perform order reduction processing on the modulation mode at the same time. Here, the device corresponding to the receiving end becomes the transmitting end, and the transmitting end (USRP of the connection sensor) becomes the receiving end. The reason why this can be done is mainly because the radio frequency architecture of LW-USRP supports multi-channel inter-frequency transceiving.
And A2, screening out the initial data to be judged related to the number of the numbers to be judged when the number of times of the abnormal initial data to be judged is less than or equal to a preset standard value, and generating new intermediate data to be judged.
In the embodiment of the invention, when the number of times of the abnormal initial data to be judged is less than or equal to the preset standard value, the initial data to be judged related to the number of the numbers to be judged is screened out, that is, the initial data to be judged is deleted from the original intermediate data to be judged, and new intermediate data to be judged is generated.
And A3, skipping to execute a step of taking the identification code in the middle data to be judged as a separator and acquiring the number of the numbers to be judged between two adjacent separators.
In the embodiment of the invention, the step of obtaining the number of the numbers to be judged between two adjacent separators by taking the identification code in the data to be judged in the middle as the separator is executed by jumping again.
And step 207, comparing the difference value between two adjacent initial detection data in the data to be judged of each target with the associated target fluctuation value data, and judging whether the sensor is abnormal or not according to the comparison result.
Further, step 207 may comprise the following sub-steps:
s31, calculating a difference value between two adjacent initial detection data in the data to be judged of each target to obtain a first difference value.
And S32, comparing each first difference value with the associated target fluctuation value data.
And S33, if all the first difference values are consistent with the associated target fluctuation value data, judging that the sensor is not abnormal.
And S34, if any first difference value is inconsistent with the associated target fluctuation value data, judging that the sensor is abnormal.
In the embodiment of the invention, the difference value between two adjacent initial detection data in each target data to be judged is calculated to obtain a first difference value, each first difference value is compared with the associated target fluctuation value data, if all the first difference values are consistent with the associated target fluctuation value data, the sensor is judged not to be abnormal, and if any first difference value is inconsistent with the associated target fluctuation value data, the sensor is judged to be abnormal.
In one example of the present invention, the target fluctuation value data obtained before the preprocessing is compared according to the difference between two adjacent initial detection data.
For the sake of brevity, the initial detection data is abbreviated as data, and the target fluctuation value data is abbreviated as fluctuation value, for example:
as shown above, the fluctuation value after each data is the difference between the current data and the previous data, and the software script at the receiving end can judge the integrity of the current data by comparing the difference and the fluctuation value of the data 2. The above example is a correct and normal data. For the case where the fluctuation value is negative, the sign may be represented by the fluctuation value leading bit. (the number of the fluctuation value can be configured freely according to the situation, and the complement is not adopted for the binary conversion of the signed data, but the positive and negative are judged through the digit of which the first digit does not participate in comparison.
Example of occurrence of error:
as shown above, it is obvious that the fluctuation value is completely different from the difference value between two adjacent data analyses, and at this time, it indicates that the data is erroneous, the erroneous data is discarded, and at the same time, it is determined that the sensor is abnormal.
It is worth mentioning that through serial port communication of USRP and sensor, the sensor does not need wiring, can monitor in high temperature and high corrosion environment, does not need external power supply simultaneously, and the start is operated promptly. Initialization parameters can be preset for different scenes; the initial detection data preprocessing and the inverse preprocessing of the sensor can flexibly use any communication protocol and modulation mode, and can self-adaptively adjust the modulation mode at the same time, thereby ensuring the integrity of data transmission. The system can flexibly adapt to various scenes and butt joint most of receiving end equipment; and the self-adaptive modulation and demodulation in the USRP is used for increasing and reducing the order, and a TCP/IP protocol is adopted in a data link in the USRP to ensure the integrity of the data link. And an error reporting and returning mode is used at the wireless end to replace error correction, so that the overall computational cost is reduced, and the stability is further improved.
In the embodiment of the invention, a plurality of initial detection data and identification codes acquired by a sensor are acquired according to a preset period, the difference value between two adjacent initial detection data is calculated to generate a plurality of target fluctuation value data, the initial detection data, the identification codes and the target fluctuation value data are preprocessed to generate a plurality of modulation data to be analyzed, the modulation data to be analyzed are subjected to inverse preprocessing to generate a plurality of target data to be analyzed, each target data to be analyzed is screened by adopting a preset separation condition, a plurality of corresponding target data to be judged are determined, the difference value between two adjacent initial detection data in each target data to be judged and the associated target fluctuation value data are compared, and whether the sensor is abnormal or not is judged according to a comparison result; the technical problem that when a sensor transmits signals based on electromagnetic waves in a complex environment, if the sensor is abnormal, transmitted data are in error, and accuracy of transmitted data collection is affected is solved; the method and the device realize the accurate judgment of whether the sensor is abnormal or not and the accuracy of data transmission of the sensor under the complex environment, and can judge the state of the current network environment and further search for the source causing the sensor to be abnormal.
Referring to fig. 3, fig. 3 is a block diagram illustrating a system for determining abnormality of a sensor according to a third embodiment of the present invention.
The embodiment of the invention provides a system for judging sensor abnormity, which is applied to a USRP device, wherein a sensor is connected with the USRP device through a serial port switching device, and the system comprises:
the data acquisition module 301 is configured to acquire a plurality of initial detection data and identification codes acquired by the sensor according to a preset period.
And a target fluctuation value data acquisition module 302 for calculating a difference between two adjacent initial detection data to generate a plurality of target fluctuation value data.
And a modulation data to be analyzed acquisition module 303, configured to pre-process the multiple initial detection data, the identification code, and the target fluctuation value data, and generate multiple modulation data to be analyzed.
The target data to be analyzed obtaining module 304 is configured to perform inverse preprocessing on the multiple modulated data to be analyzed, and generate multiple target data to be analyzed.
The target data to be determined obtaining module 305 is configured to screen each target data to be analyzed by using a preset separation condition, and determine a plurality of corresponding target data to be determined.
And the abnormity judging module 306 is used for comparing the difference value between two adjacent initial detection data in the data to be judged of each target with the associated target fluctuation value data and judging whether the sensor is abnormal according to the comparison result.
Further, the module 303 for acquiring modulated data to be analyzed includes:
and the binary bit detection data acquisition submodule is used for carrying out binary conversion on the plurality of initial detection data and generating binary bit detection data corresponding to the plurality of numbers according to the numbers in the initial detection data.
And the binary bit fluctuation data acquisition submodule is used for carrying out binary conversion on the plurality of target fluctuation value numbers to generate a plurality of binary bit fluctuation data with preset binary numbers.
And the initial data to be analyzed constructing submodule is used for sequencing the identification codes, the binary bit detection data and the binary bit fluctuation data according to preset sequencing conditions to construct a plurality of initial data to be analyzed.
And the data modulation acquisition submodule is used for carrying out data modulation on each initial data to be analyzed to generate a plurality of corresponding data to be analyzed.
Further, the target data to be analyzed acquisition module 304 includes:
and the data demodulation and acquisition submodule is used for demodulating according to the received multiple modulated data to be analyzed to generate multiple initial data to be analyzed.
And the data modulation acquisition submodule is used for performing decimal conversion on the plurality of initial data to be analyzed to generate a plurality of target data to be analyzed.
Further, the target data to be determined acquisition module 305 includes:
and the initial data to be judged acquisition submodule is used for screening the target data to be analyzed with consistent separators from the plurality of target data to be analyzed as the initial data to be judged.
And the intermediate data to be judged acquisition submodule is used for sequencing the plurality of initial data to be judged according to the data acquisition sequence to obtain a plurality of intermediate data to be judged.
And the number obtaining submodule for the numbers to be judged is used for obtaining the number of the numbers to be judged between two adjacent separators by taking the identification code in the middle data to be judged as the separator.
And the comparison submodule is used for comparing the number of the numbers to be judged with the number of the preset standard numbers.
And the first data processing submodule is used for taking the intermediate data to be judged as the target data to be judged if the number of all the numbers to be judged is consistent with the number of the standard numbers.
Further, the target data to be analyzed obtaining module 304 further includes:
and the second data processing submodule is used for judging that the initial data to be judged related to the number of the digits to be judged is abnormal if the number of any digit to be judged is inconsistent with the number of the standard digits.
Further, still include:
and the first judgment submodule is used for judging that the network environment at the current moment is unstable when the number of times of the abnormal initial data to be judged is greater than a preset standard value.
And the second judging submodule is used for screening out the initial data to be judged related to the number of the numbers to be judged and generating new intermediate data to be judged when the frequency of the abnormal initial data to be judged is less than or equal to a preset standard value.
And the skipping submodule is used for skipping and executing the step of taking the identification code in the middle data to be judged as the separator and acquiring the number of the numbers to be judged between two adjacent separators.
Further, the abnormality determining module 306 includes:
and the first difference acquisition submodule is used for calculating the difference between two adjacent initial detection data in the data to be judged of each target to obtain a first difference.
And the comparison submodule is used for comparing each first difference value with the associated target fluctuation value data.
And the first judgment submodule is used for judging that the sensor is not abnormal if all the first difference values are consistent with the associated target fluctuation value data.
And the second judgment submodule is used for judging that the sensor is abnormal if any first difference value is inconsistent with the associated target fluctuation value data.
In the embodiment of the invention, a plurality of initial detection data and identification codes acquired by a sensor are acquired according to a preset period, the difference value between two adjacent initial detection data is calculated to generate a plurality of target fluctuation value data, the initial detection data, the identification codes and the target fluctuation value data are preprocessed to generate a plurality of modulation data to be analyzed, the modulation data to be analyzed are subjected to inverse preprocessing to generate a plurality of target data to be analyzed, each target data to be analyzed is screened by adopting a preset separation condition, a plurality of corresponding target data to be judged are determined, the difference value between two adjacent initial detection data in each target data to be judged and the associated target fluctuation value data are compared, and whether the sensor is abnormal or not is judged according to a comparison result; the technical problem that when a sensor transmits signals based on electromagnetic waves in a complex environment, if the sensor is abnormal, transmitted data are in error, and accuracy of transmitted data collection is affected is solved; the method and the device realize the accurate judgment of whether the sensor is abnormal or not and the accuracy of data transmission of the sensor under the complex environment, and can judge the state of the current network environment and further search for the source causing the sensor to be abnormal.
An electronic device according to an embodiment of the present invention includes: the computer system comprises a memory and a processor, wherein a computer program is stored in the memory; the computer program, when executed by the processor, causes the processor to perform the method for determining abnormality of a sensor according to any one of the embodiments described above.
The memory may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read only memory), an EPROM, a hard disk, or a ROM. The memory has a storage space for program code for performing any of the method steps of the above-described method. For example, the memory space for the program code may comprise respective program codes for implementing the respective steps in the above method, respectively. The program code can be read from and written to one or more computer program products. These computer program products comprise a program code carrier such as a hard disk, a Compact Disc (CD), a memory card or a floppy disk. The program code may be compressed, for example, in a suitable form. The code, when executed by a computing processing device, causes the computing processing device to perform the steps of the method described above.
Embodiments of the present invention provide a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed, the method for determining abnormality of a sensor according to any embodiment of the present invention is implemented.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk, and various media capable of storing program codes.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for judging sensor abnormity is applied to a USRP device, a sensor is connected with the USRP device through a serial port switching device, and the method comprises the following steps:
acquiring a plurality of initial detection data and identification codes acquired by the sensor according to a preset period;
calculating a difference value between two adjacent initial detection data to generate a plurality of target fluctuation value data;
preprocessing the plurality of initial detection data, the identification codes and the target fluctuation value data to generate a plurality of pieces of modulation data to be analyzed;
carrying out inverse preprocessing on the plurality of modulated data to be analyzed to generate a plurality of target data to be analyzed;
screening each target data to be analyzed by adopting a preset separation condition, and determining a plurality of corresponding target data to be judged;
and comparing the difference value between two adjacent initial detection data in each target data to be judged with the associated target fluctuation value data, and judging whether the sensor is abnormal or not according to the comparison result.
2. The method of determining a sensor abnormality according to claim 1, wherein the step of preprocessing a plurality of the initial detection data, the identification code, and the target fluctuation value data to generate a plurality of modulated data to be analyzed includes:
binary conversion is carried out on the plurality of initial detection data, and binary bit detection data corresponding to the number of the digits are generated according to the number of the digits in the initial detection data;
binary conversion is carried out on the target fluctuation value numbers to generate binary bit fluctuation data of a plurality of preset binary numbers;
sequencing the identification codes, the binary bit detection data and the binary bit fluctuation data according to a preset sequencing condition to construct a plurality of initial data to be analyzed;
and carrying out data modulation on each initial data to be analyzed to generate a plurality of corresponding data to be analyzed.
3. The method for determining abnormality of a sensor according to claim 2, wherein the step of performing inverse preprocessing on the plurality of pieces of modulation data to be analyzed to generate a plurality of pieces of target data to be analyzed includes:
demodulating according to the received multiple modulated data to be analyzed to generate multiple initial data to be analyzed;
and performing decimal conversion on the plurality of initial data to be analyzed to generate a plurality of target data to be analyzed.
4. The method for determining abnormality of a sensor according to claim 3, wherein the step of screening each of the target data to be analyzed using a preset separation condition to determine a plurality of corresponding target data to be determined includes:
screening the target data to be analyzed with consistent separators from the plurality of target data to be analyzed as initial data to be judged;
sequencing the plurality of initial data to be judged according to a data acquisition sequence to obtain a plurality of intermediate data to be judged;
taking the identification code in the intermediate data to be judged as a separator, and acquiring the number of the numbers to be judged between two adjacent separators;
comparing the number of the numbers to be judged with the number of preset standard numbers;
and if the number of all the numbers to be judged is consistent with the number of the standard numbers, taking the intermediate data to be judged as target data to be judged.
5. The method of determining a sensor abnormality according to claim 4, further comprising:
and if any one of the numbers to be judged is inconsistent with the standard number, judging that the initial data to be judged related to the numbers to be judged is abnormal.
6. The method of determining a sensor abnormality according to claim 5, further comprising:
when the number of times of the abnormal initial data to be judged is larger than a preset standard value, judging that the network environment at the current moment is unstable;
when the number of times of the abnormal initial data to be judged is less than or equal to a preset standard value, screening out the initial data to be judged related to the number of the numbers to be judged, and generating new intermediate data to be judged;
and skipping to execute the step of taking the identification code in the intermediate data to be judged as a separator and acquiring the number of the numbers to be judged between two adjacent separators.
7. The method for determining abnormality of a sensor according to claim 1, wherein said step of comparing a difference value between two adjacent pieces of the initial detection data in each of the pieces of target data to be determined with the associated target fluctuation value data and determining whether or not abnormality of the sensor has occurred based on a result of the comparison includes:
calculating a difference value between two adjacent initial detection data in each target data to be judged to obtain a first difference value;
comparing each of the first difference values with the associated target fluctuation value data;
if all the first difference values are consistent with the associated target fluctuation value data, judging that the sensor is not abnormal;
and if any first difference value is inconsistent with the associated target fluctuation value data, judging that the sensor is abnormal.
8. The abnormal judgment system of the sensor is characterized in that the abnormal judgment system is applied to a USRP device, the sensor is connected with the USRP device through a serial port switching device, and the abnormal judgment system of the sensor comprises:
the data acquisition module is used for acquiring a plurality of initial detection data and identification codes acquired by the sensor according to a preset period;
the target fluctuation value data acquisition module is used for calculating the difference value between two adjacent initial detection data and generating a plurality of target fluctuation value data;
the modulation data to be analyzed acquisition module is used for preprocessing a plurality of initial detection data, the identification codes and the target fluctuation value data to generate a plurality of modulation data to be analyzed;
the target data to be analyzed acquisition module is used for carrying out inverse preprocessing on the plurality of modulated data to be analyzed to generate a plurality of target data to be analyzed;
the target data to be judged acquisition module is used for screening each target data to be analyzed by adopting a preset separation condition and determining a plurality of corresponding target data to be judged;
and the abnormity judgment module is used for comparing the difference value between two adjacent initial detection data in the data to be judged of each target with the associated target fluctuation value data and judging whether the sensor is abnormal or not according to the comparison result.
9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the computer program, when executed by the processor, causes the processor to perform the steps of the method for determining a sensor abnormality according to any one of claims 1 to 7.
10. A computer-readable storage medium on which a computer program is stored, the computer program, when executed, implementing a method of determining a sensor abnormality according to any one of claims 1 to 7.
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| CN117570375B (en) * | 2024-01-15 | 2024-04-02 | 唐山市开文水泥制品有限责任公司 | Pipe network visual management method, system, equipment and readable storage medium |
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