Recyclable packaging appliance real-time monitoring system and method based on multi-sensor fusion

Abstract

The invention discloses a recyclable packaging appliance real-time monitoring system and method based on multi-sensor fusion, and relates to the technical field of Internet of Things. The method comprises the following steps: acquiring historical sensing data, acquiring an observed value # imgabs1 # of an acceleration sensor and an observed value # imgabs2 # of a vibration sensor at a # imgabs0 # moment, defining a motion state of a to-be-monitored recyclable packaging appliance, calculating a probability value when the to-be-monitored recyclable packaging appliance is in a # imgabs3 # motion state, and constructing a probability value of the to-be-monitored recyclable packaging appliance in different motion states. The first probability distribution of the observed value # imgabs4 # of the acceleration sensor and the second probability distribution of the observed value # imgabs5 # of the vibration sensor are obtained according to the obtained probability values, the first probability distribution and the second probability distribution; and calculating third probability distribution of the observation value # imgabs7 # of the acceleration sensor and the observation value # imgabs8 # of the vibration sensor, which are collected at the # imgabs6 # moment, in the # imgabs9 # motion state, and according to the obtained third probability distribution calculation result, judging the motion state of the recyclable packaging appliance to be monitored at the # imgabs10 # moment.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to a real-time monitoring system and method for recyclable packaging tools based on multi-sensor fusion. Background Art

[0002] With the rapid development of the logistics and supply chain industries, recyclable packaging is increasingly used in transportation and storage. In modern logistics and supply chain management, real-time monitoring of recyclable packaging is of great significance for improving transportation efficiency, ensuring cargo safety, and optimizing logistics costs.

[0003] However, existing technologies have many deficiencies in the management and monitoring of recyclable packaging equipment. The main manifestations are: traditional methods mainly rely on manual inspection or single sensor technology, which makes it difficult to achieve all-round real-time monitoring of packaging equipment. There are the following technical problems: 1) Insufficient monitoring accuracy: a single sensor can only provide limited information and it is difficult to fully reflect the movement status of the packaging equipment; 2) Weak anti-interference ability: in complex transportation and storage environments, a single sensor is easily affected by external interference, affecting the monitoring results and leading to misjudgment; 3) Inability to provide real-time feedback: existing technologies have delays in data fusion and processing, and cannot achieve real-time monitoring of the status of packaging equipment.

[0004] At present, the existing technology has applied multi-sensor fusion technology in the fields of autonomous driving, industrial automation, etc., but it has not been fully developed and utilized in the recyclable packaging equipment monitoring system. Therefore, how to achieve all-round real-time monitoring of recyclable packaging equipment through multi-sensor fusion technology and accurately determine its status is a technical problem that needs to be solved urgently. To this end, we propose a real-time monitoring system and method for recyclable packaging equipment based on multi-sensor fusion. Summary of the invention

[0005] The main purpose of the present invention is to provide a real-time monitoring system and method for recyclable packaging containers based on multi-sensor fusion, which can effectively solve the problems in the background technology.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is: The real-time monitoring method of recyclable packaging equipment based on multi-sensor fusion includes: Step 1: Collect historical sensor data of the recyclable packaging equipment to be monitored within the circulation period T at a fixed sampling frequency λ to obtain The observed value of the acceleration sensor at the moment and the observed values ​​of the vibration sensor ,in, ∈T; Step 2: Define the motion state of the recyclable packaging to be monitored as ={ , , , }, based on the historical sensor perception data obtained, calculate when the recyclable packaging device to be monitored is in the The probability value of the motion state ; Step 3: Construct the observed values ​​of the acceleration sensor under different motion states based on the historical sensor perception data obtained The first probability distribution and the observed values ​​of the vibration sensor The second probability distribution ; Step 4: Based on the obtained probability value , the first probability distribution and the second probability distribution , calculated when Observation values ​​of the acceleration sensor collected at all times and the observed values ​​of the vibration sensor The corresponding The third probability distribution under the motion state , the calculation formula is: = × × ; Step 5: According to the third probability distribution obtained The calculation results are determined in The movement status of the recyclable packaging device to be monitored at all times.

[0007] Real-time monitoring system for recyclable packaging based on multi-sensor fusion, including: The historical sensor perception data acquisition module is used to collect the historical sensor perception data of the recyclable packaging equipment to be monitored within the circulation period T at a fixed sampling frequency λ, and obtain The observed value of the acceleration sensor at the moment and the observed values ​​of the vibration sensor ; The motion state definition module is used to define the motion state of the recyclable packaging container to be monitored, wherein the motion state is ={ , , , }; The data processing module is used to calculate the time when the recyclable packaging device to be monitored is in the first The probability value of the motion state ; The first probability distribution calculation module is used to construct the observed values ​​of the acceleration sensor under different motion states according to the acquired historical sensor perception data. The first probability distribution ; The second probability distribution calculation module is used to construct the observation values ​​of the vibration sensor under different motion states according to the acquired historical sensor perception data. The second probability distribution ; Real-time data collection module, used to collect the data of recyclable packaging equipment to be monitored. Observation values ​​of the acceleration sensor collected at all times and the observed values ​​of the vibration sensor ; The third probability distribution calculation module is used to obtain the probability value , the first probability distribution and the second probability distribution , calculated when Observation values ​​of the acceleration sensor collected at all times and the observed values ​​of the vibration sensor The corresponding The third probability distribution under the motion state , the calculation formula is: = × × ; A motion state evaluation module is used to obtain a third probability distribution The calculation results are determined in The movement status of the recyclable packaging equipment to be monitored at all times; when When it is the maximum value among all the calculated results, it is determined that At this moment, the recyclable packaging equipment to be monitored is in the The possibility of this motion state is the greatest; when When it is the minimum value among all the calculated results, it is determined that At this moment, the recyclable packaging equipment to be monitored is in the The possibility of this motion state is the least.

[0008] The system also includes a memory, a processor, and a computer program stored on the memory and executable on the processor.

[0009] Furthermore, in step 2, the movement state classification principle of the recyclable packaging container to be monitored is: when = When , it indicates that the movement state of the recyclable packaging device to be monitored is static; when = When , it indicates that the motion state of the recyclable packaging device to be monitored is a uniform motion state; when = When , it indicates that the motion state of the recyclable packaging device to be monitored is a variable speed motion state; when = When , it indicates that the movement state of the recyclable packaging device to be monitored is the impact state.

[0010] Further, in step 2, the recyclable packaging device to be monitored is in the The probability value of the motion state The calculation formula is: =

[0011] In the formula, Indicates that the recyclable packaging equipment to be monitored is in the first The sampling frequency under various motion states; =1,2,3,4.

[0012] Furthermore, in step 3, the observed value of the acceleration sensor The first probability distribution The calculation formula is: = =

[0013] In the formula, is the probability density function that obeys the Gaussian distribution; Indicated as being in Observation values ​​of the acceleration sensor under various motion states The mean of Indicated as being in Observation values ​​of the acceleration sensor under various motion states The variance of is the ratio of pi.

[0014] Furthermore, in step 3, the observed value of the vibration sensor The second probability distribution The calculation formula is: = =

[0015] In the formula, is the probability density function that obeys the Gaussian distribution; Indicated as being in Observation values ​​of vibration sensors under various motion states The mean of Indicated as being in Observation values ​​of vibration sensors under various motion states The variance of is the ratio of pi.

[0016] Furthermore, in step five, The principle for determining the movement state of the recyclable packaging equipment to be monitored at the moment is: for =1,2,3,4; when When it is the maximum value among all the calculated results, it is determined that At this moment, the recyclable packaging equipment to be monitored is in the The possibility of this motion state is the greatest; when When it is the minimum value among all the calculated results, it is determined that At this moment, the recyclable packaging equipment to be monitored is in the The possibility of this motion state is the least.

[0017] The present invention has the following beneficial effects: Compared with the prior art, the technical solution of the present invention acquires the historical sensor perception data of the recyclable packaging equipment to be monitored within the circulation period T at a fixed sampling frequency λ. The observed value of the acceleration sensor at the moment and the observed values ​​of the vibration sensor , define the motion state of the recyclable packaging equipment to be monitored, and calculate the motion state of the recyclable packaging equipment to be monitored when it is in the first The probability value under different motion states is constructed to construct the observation value of the acceleration sensor under different motion states. The first probability distribution and the observed value of the vibration sensor The second probability distribution is calculated according to the obtained probability value, the first probability distribution and the second probability distribution. Observation values ​​of the acceleration sensor collected at all times and the observed values ​​of the vibration sensor The corresponding The third probability distribution under the motion state is obtained, and according to the calculation result of the third probability distribution, it is determined that The movement status of the recyclable packaging equipment to be monitored at all times can be realized, and all-round real-time monitoring of the recyclable packaging equipment can be achieved, and its status can be accurately determined, effectively solving technical problems in the existing technology, such as insufficient monitoring accuracy of a single sensor and weak anti-interference ability in complex transportation and storage environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic flow chart of a real-time monitoring method for recyclable packaging equipment based on multi-sensor fusion of the present invention; Figure 2 It is a structural schematic diagram of the real-time monitoring system for recyclable packaging tools based on multi-sensor fusion of the present invention. DETAILED DESCRIPTION

[0019] The present invention will be further described below in conjunction with specific implementation methods, wherein the accompanying drawings are only used for exemplary descriptions and represent only schematic diagrams rather than actual drawings, and should not be understood as limiting the present invention. In order to better illustrate the specific implementation methods of the present invention, some parts of the accompanying drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product.

[0020] The implementation process of the technical solution of the present invention includes the following steps: Step 1: Collect historical sensor data of the recyclable packaging equipment to be monitored within the circulation period T at a fixed sampling frequency λ to obtain The observed value of the acceleration sensor at the moment and the observed values ​​of the vibration sensor ,in, ∈T; It should be noted that for different sensor data, this solution mainly involves acceleration sensors and vibration sensors. When collecting sensor data, time synchronization processing is required. Specifically, a method combining hardware synchronization and software synchronization can be used.

[0021] 1) Hardware synchronization Hardware synchronization provides the same reference time for each sensor through a unified clock source, thereby achieving time synchronization at the hardware level. Common hardware synchronization methods include: GPS time synchronization: Using the high-precision time signal (such as PPS+NMEA) provided by GPS as a unified time source, each sensor calibrates its own clock according to the GPS time.

[0022] PTP protocol (IEEE 1588): It realizes sub-microsecond clock synchronization between multiple sensors and the host through Ethernet. The PTP protocol calculates network transmission delay and clock deviation through synchronization message interaction between master and slave devices, thereby achieving high-precision time synchronization.

[0023] 2) Software synchronization Software synchronization uses software algorithms to time-align sensor data, mainly using timestamps for matching. Common software synchronization methods include: Timestamp-based matching: Unify the data of each sensor to the sensor data with a longer scanning period (lower frequency). For example, if the lidar sampling frequency is 12.5Hz and the camera sampling frequency is 30Hz, then use the lidar sampling frequency as the benchmark to find the camera data closest to the lidar sampling time.

[0024] Interpolation method: For sensors with inconsistent sampling frequencies, the equivalent data at a certain moment is calculated through interpolation algorithms. For example, based on the radar data before and after the camera, the radar data corresponding to the camera sampling moment is calculated through linear interpolation.

[0025] 3) Combination of hardware synchronization and software synchronization In practical applications, hardware synchronization and software synchronization are usually used in combination to achieve more efficient time synchronization. For example: Hardware synchronization provides reference time: Provides a unified time reference for sensors through GPS or PTP protocol.

[0026] Software synchronization to handle time deviation: Based on hardware synchronization, the data of each sensor is further aligned through software algorithms to ensure the consistency of data in time.

[0027] Through the above steps, different sensor data can be synchronized in time and space to reflect the real state of the recyclable packaging device to be monitored at time t.

[0028] Step 2: Define the motion state of the recyclable packaging to be monitored as ={ , , , }, where = When , it indicates that the movement state of the recyclable packaging device to be monitored is static; when = When , it indicates that the motion state of the recyclable packaging equipment to be monitored is a uniform motion state; when = When , it indicates that the motion state of the recyclable packaging device to be monitored is the variable speed motion state; when = When , it indicates that the movement state of the recyclable packaging device to be monitored is the impact state.

[0029] Through the above steps, the motion state of the recyclable packaging equipment to be monitored can be classified, so as to facilitate the subsequent evaluation of the possibility of the motion state of the recyclable packaging equipment to be monitored. The specific definition method can adopt the manual calibration method, in which the historical sensor perception data is manually calibrated to form data sets under different motion states.

[0030] Step 3: Based on the historical sensor data obtained, calculate the time when the recyclable packaging device to be monitored is in the first The probability value of the motion state , the calculation formula is: =

[0031] In the formula, Indicates that the recyclable packaging equipment to be monitored is in the first The sampling frequency under various motion states; =1,2,3,4.

[0032] Step 4: Construct the observed values ​​of the acceleration sensor under different motion states based on the historical sensor perception data obtained The first probability distribution , the calculation formula is: = =

[0033] In the formula, is the probability density function that obeys the Gaussian distribution; Indicated as being in Observation values ​​of the acceleration sensor under various motion states The mean of Indicated as being in Observation values ​​of the acceleration sensor under various motion states The variance of is pi; It should be noted that in this solution, it is assumed that the observed values ​​of the acceleration sensor obey the Gaussian distribution. Specifically, the collected observed values ​​of the acceleration sensor need to be tested and confirmed. The test method is: through hypothesis testing (such as Shapiro-Wilk test) and frequency distribution histogram analysis, it can be determined whether the acceleration data obeys the Gaussian distribution.

[0034] Step 5: Construct the observation values ​​of the vibration sensor under different motion states based on the historical sensor perception data obtained The second probability distribution , the calculation formula is: = =

[0035] In the formula, is the probability density function that obeys the Gaussian distribution; Indicated as being in Observation values ​​of vibration sensors under various motion states The mean of Indicated as being in Observation values ​​of vibration sensors under various motion states The variance of is pi; It should be noted that the observed values ​​of the vibration sensor also need to be tested to confirm whether they obey the Gaussian distribution. The test method is the same as step 4 above and will not be repeated here.

[0036] Step 6: Collect At time , the observed value of the acceleration sensor of the recyclable packaging container to be monitored and the observed values ​​of the vibration sensor .

[0037] Step 7: Based on the obtained probability value , the first probability distribution and the second probability distribution , calculated when Observation values ​​of the acceleration sensor collected at all times and the observed values ​​of the vibration sensor The corresponding The third probability distribution under the motion state , the calculation formula is: = × × ; Step 8: According to the obtained third probability distribution The calculation results are determined in The movement state of the recyclable packaging equipment to be monitored at the moment; the principle for determining the movement state is: =1,2,3,4; when When it is the maximum value among all the calculated results, it is determined that At this moment, the recyclable packaging equipment to be monitored is in the The possibility of this motion state is the greatest; when When it is the minimum value among all the calculated results, it is determined that At this moment, the recyclable packaging equipment to be monitored is in the The possibility of this motion state is the least.

[0038] Specifically, for =1,2,3,4; the third probability distribution The calculation results include , , , ; If yes > > > , then in At this moment, the recyclable packaging equipment to be monitored is in the The possibility of this motion state is the greatest, The probability of the motion state is the smallest, that is, the probability of being in a static state is the largest, and the probability of being in a state of being impacted is the smallest; Similarly, if there is < < < , then in At this moment, the recyclable packaging equipment to be monitored is in the The possibility of this motion state is the smallest. The possibility of being in a state of motion is the greatest, that is, the possibility of being in a static state is the least, and the possibility of being in a state of being impacted is the greatest.

[0039] Step 9: Dynamic Update As the observation values ​​of the acceleration sensor and the vibration sensor are continuously collected and updated, the third probability distribution can be recursively updated, thereby achieving real-time estimation of the motion state of the device.

[0040] Through the above technical solution, it is possible to achieve all-round real-time monitoring of recyclable packaging containers and accurately determine their status, thereby effectively solving technical problems in the existing technology, such as insufficient monitoring accuracy of a single sensor and weak anti-interference ability in complex transportation and storage environments.

[0041] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A real-time monitoring method for recyclable packaging equipment based on multi-sensor fusion, characterized in that: include: Step 1: Collect historical sensor data of the recyclable packaging equipment to be monitored within the circulation period T at a fixed sampling frequency λ to obtain The observed value of the acceleration sensor at the moment and the observed values ​​of the vibration sensor ,in, ∈T; Step 2: Define the motion state of the recyclable packaging to be monitored as ={ , , , }, based on the historical sensor perception data obtained, calculate when the recyclable packaging device to be monitored is in the The probability value of the motion state ; Step 3: Construct the observed values ​​of the acceleration sensor under different motion states based on the historical sensor perception data obtained The first probability distribution and the observed values ​​of the vibration sensor The second probability distribution ; Step 4: Based on the obtained probability value , the first probability distribution and the second probability distribution , calculated when Observation values ​​of the acceleration sensor collected at all times and the observed values ​​of the vibration sensor The corresponding The third probability distribution under the motion state , the calculation formula is: = × × ; Step 5: According to the third probability distribution obtained The calculation results are as follows: The movement status of the recyclable packaging device to be monitored at all times.

2. The real-time monitoring method for recyclable packaging equipment based on multi-sensor fusion according to claim 1 is characterized in that: In step 2, the movement status classification principle of the recyclable packaging container to be monitored is: when = When , it indicates that the movement state of the recyclable packaging device to be monitored is static; when = When , it indicates that the motion state of the recyclable packaging device to be monitored is a uniform motion state; when = When , it indicates that the motion state of the recyclable packaging device to be monitored is a variable speed motion state; when = When , it indicates that the movement state of the recyclable packaging device to be monitored is the impact state.

3. The real-time monitoring method for recyclable packaging equipment based on multi-sensor fusion according to claim 1 is characterized in that: In step 2, the recyclable packaging to be monitored is in the The probability value of the motion state The calculation formula is: = In the formula, Indicates that the recyclable packaging equipment to be monitored is in the first The sampling frequency under various motion states; =1,2,3,4.

4. The real-time monitoring method for recyclable packaging equipment based on multi-sensor fusion according to claim 1 is characterized in that: In step 3, the observed value of the acceleration sensor The first probability distribution The calculation formula is: = = In the formula, is the probability density function that obeys the Gaussian distribution; Indicated as being in Observation values ​​of the acceleration sensor under various motion states The mean of Indicated as being in Observation values ​​of the acceleration sensor under various motion states The variance of is the ratio of pi.

5. The real-time monitoring method for recyclable packaging equipment based on multi-sensor fusion according to claim 1 is characterized in that: In step 3, the vibration sensor observations The second probability distribution The calculation formula is: = = In the formula, is the probability density function that obeys the Gaussian distribution; Indicated as being in Observation values ​​of vibration sensors under various motion states The mean of Indicated as being in Observation values ​​of vibration sensors under various motion states The variance of is the ratio of pi.

6. The real-time monitoring method for recyclable packaging based on multi-sensor fusion according to claim 1 is characterized in that: In step five, The principle for determining the movement state of the recyclable packaging equipment to be monitored at the moment is: for =1,2,3,4; when When it is the maximum value among all the calculated results, it is determined that At this moment, the recyclable packaging equipment to be monitored is in the The possibility of this motion state is the greatest; when When it is the minimum value among all the calculated results, it is determined that At this moment, the recyclable packaging equipment to be monitored is in the The possibility of this motion state is the least.

7. A real-time monitoring system for recyclable packaging tools based on multi-sensor fusion, applied to a real-time monitoring method for recyclable packaging tools based on multi-sensor fusion as claimed in any one of claims 1 to 6, characterized in that: include: The historical sensor perception data acquisition module is used to collect the historical sensor perception data of the recyclable packaging equipment to be monitored within the circulation period T at a fixed sampling frequency λ, and obtain The observed value of the acceleration sensor at the moment and the observed values ​​of the vibration sensor ,in, ∈T; The motion state definition module is used to define the motion state of the recyclable packaging container to be monitored, wherein the motion state is ={ , , , },when = When , it indicates that the movement state of the recyclable packaging device to be monitored is static; when = When , it indicates that the motion state of the recyclable packaging equipment to be monitored is a uniform motion state; when = When , it indicates that the motion state of the recyclable packaging device to be monitored is the variable speed motion state; when = When , it indicates that the movement state of the recyclable packaging device to be monitored is the impact state; The data processing module is used to calculate the time when the recyclable packaging device to be monitored is in the first The probability value of the motion state , the calculation formula is: = ; In the formula, Indicates that the recyclable packaging equipment to be monitored is in the first The sampling frequency under various motion states; =1,2,3,4; The first probability distribution calculation module is used to construct the observed values ​​of the acceleration sensor under different motion states according to the acquired historical sensor perception data. The first probability distribution , the calculation formula is: = = , where is the probability density function that obeys the Gaussian distribution; Indicated as being in Observation values ​​of the acceleration sensor under various motion states The mean of Indicated as being in Observation values ​​of the acceleration sensor under various motion states The variance of is pi; The second probability distribution calculation module is used to construct the observation values ​​of the vibration sensor under different motion states according to the acquired historical sensor perception data. The second probability distribution , the calculation formula is: = = ; In the formula, is the probability density function that obeys the Gaussian distribution; Indicated as being in Observation values ​​of vibration sensors under various motion states The mean of Indicated as being in Observation values ​​of vibration sensors under various motion states The variance of is the ratio of pi; Real-time data collection module, used to collect the data of recyclable packaging equipment to be monitored. Observation values ​​of the acceleration sensor collected at all times and the observed values ​​of the vibration sensor ; The third probability distribution calculation module is used to obtain the probability value , the first probability distribution and the second probability distribution , calculated when Observation values ​​of the acceleration sensor collected at all times and the observed values ​​of the vibration sensor The corresponding The third probability distribution under the motion state , the calculation formula is: = × × ; A motion state evaluation module is used to obtain a third probability distribution The calculation results are determined in The motion state of the recyclable packaging equipment to be monitored at the moment, wherein the motion state is determined according to the following principles: =1,2,3,4; when When it is the maximum value among all the calculated results, it is determined that At this moment, the recyclable packaging equipment to be monitored is in the The possibility of this motion state is the greatest; when When it is the minimum value among all the calculated results, it is determined that At this moment, the recyclable packaging equipment to be monitored is in the The possibility of this motion state is the least.

8. The real-time monitoring system for recyclable packaging tools based on multi-sensor fusion according to claim 7 is characterized in that: The system also includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, can implement the steps of the method for real-time monitoring of recyclable packaging containers based on multi-sensor fusion as described in any one of claims 1 to 6.

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