Laboratory intelligent equipment sensing system based on signal transmission

Abstract

The invention discloses a laboratory intelligent equipment sensing system based on signal transmission, and relates to the technical field of signal transmission, and the system comprises a data collection module which is used for collecting parameter information in a laboratory; the processing and analyzing module is used for analyzing and processing the parameters acquired by the data acquisition module and dispersing data processing tasks to the edge of a network; a communication management module; the communication management module is used for transmitting the analysis and processing result of the processing and analysis module to a mobile phone terminal of a laboratory supervisor, and the communication management module is also used for enhancing the security in the transmission process; the monitoring module is used for monitoring the transmission process of the communication management module and giving an alarm; the laboratory environment can be monitored and controlled more effectively, the accuracy and safety of data are improved, the energy consumption and the maintenance cost are reduced, and the intelligent level of a laboratory can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of signal transmission, and more specifically, to a laboratory intelligent equipment sensing system based on signal transmission. Background Art

[0002] The laboratory intelligent equipment perception system is mainly used to monitor the laboratory environment and equipment status. It can timely detect potential safety risks, such as fire, leakage, etc., and take preventive or response measures to reduce the probability of accidents. It can effectively track and manage the equipment, chemicals and other resources in the laboratory to ensure the rational use and storage of resources and reduce waste. The Chinese patent with publication number CN107623739A discloses an experimental teaching platform based on smart home perception and control, which transmits the collected environmental information data to the cloud platform server or local area network via a router, thereby realizing real-time data transmission. The cloud platform server and the user terminal module are connected via the Internet, which can view the environmental information data in the experiment in real time and control the equipment to perform actions; However, in actual use, the laboratory intelligent equipment perception system needs to use a variety of high-precision sensors to monitor the data in the laboratory. This will not only generate a large amount of detection data, which will bring difficulties to subsequent processing, but also these data need to rely on wireless sensor networks for data transmission. The stability and security of existing wireless networks are difficult to guarantee. Summary of the invention

[0003] In order to solve the above problems, the present invention provides a laboratory intelligent equipment perception system based on signal transmission.

[0004] A laboratory intelligent equipment perception system based on signal transmission is included, including a data acquisition module, wherein the data acquisition module is used to collect parameter information in the laboratory; A processing and analysis module, which is used to analyze and process the parameters collected by the data collection module and distribute the data processing tasks to the edge of the network; Communication management module; the communication management module is used to transmit the analysis results of the processing and analysis module to the mobile terminal of the laboratory supervisor, and the communication management module is also used to enhance the security during the transmission process; A monitoring module is used to monitor the transmission process of the communication management module and to generate an alarm.

[0005] Preferably, the data acquisition module further includes a preprocessing unit, which is used to pre-filter abnormal parameter information and fill in missing parameter information. The specific working method is as follows: Clean the collected parameter information; Perform outlier identification processing on the cleaned parameter information; Then the parameter information is processed for missing value identification; Perform feature extraction on the processed parameter information, and then perform compression processing on the extracted feature information; The compressed feature information is transmitted to the processing and analysis module.

[0006] Preferably, the specific process of extracting features from the processed parameter information is as follows: According to the formula , calculate and obtain the temperature uniformity of the laboratory ,in is the highest temperature measured for the i-th time, is the lowest temperature measured at the ith time, and n is the number of measurements; According to the formula , calculate and obtain the temperature fluctuation of the laboratory in and is the highest and lowest temperature measured at the test point at n times; According to the formula , calculate and obtain the humidity uniformity of the laboratory , among which and are the highest and lowest humidity measured at the i-th time, respectively, and m is the number of measurements; According to the formula , calculate and obtain the humidity fluctuation of the laboratory ,in are the highest and lowest humidity in m measurements, respectively; The temperature uniformity , Temperature Fluctuation , humidity uniformity and humidity fluctuations Marked as extracted features.

[0007] Preferably, the specific working mode of the processing and analysis module is as follows: Deploy edge nodes at the edge of the network; Perform data analysis on edge nodes; The data analysis includes decompressing the compressed characteristic information obtained after transmission; After decompression, the extracted feature information is analyzed.

[0008] Preferably, the specific working process of analyzing the extracted feature information is as follows: Pre-set temperature uniformity , Temperature Fluctuation , humidity uniformity and humidity fluctuations The corresponding control range; The calculated temperature uniformity , Temperature Fluctuation , humidity uniformity and humidity fluctuations Compare with the corresponding control range; If the temperature and humidity values ​​at all measurement points in the laboratory are within the preset range and the temperature uniformity is , Temperature Fluctuation , humidity uniformity and humidity fluctuations If both are within the control range, the laboratory environment is considered stable; otherwise, the laboratory environment is considered unstable. The determination result is transmitted to the communication module.

[0009] Preferably, the specific working method of extracting features from the processed parameter information also includes: Obtain parameter information and usage information of the device; Obtain the failure rate Y of laboratory equipment based on the equipment usage information; Obtain the usage frequency U of the laboratory equipment according to the usage information of the equipment; According to the equipment usage information, the average usage time P of the laboratory equipment is obtained; According to the parameter information of the equipment, the performance average value S of the laboratory equipment is obtained; The failure rate Y, usage frequency U, average usage time P and performance average S are marked as the extracted features.

[0010] Preferably, the specific working process of analyzing the extracted feature information also includes the following: The reliability index of the equipment in the laboratory is obtained by subtracting the failure rate Y from 1; The utilization efficiency of the equipment in the laboratory is obtained by dividing the average usage time P by the usage frequency U; The stability evaluation value of the equipment is obtained by dividing the performance average value S by the performance standard value of the equipment in the laboratory; The reliability, usage efficiency and stability evaluation values ​​of the equipment in the laboratory are transmitted to the communication management module as analysis results.

[0011] Preferably, the specific working mode of the communication management module is as follows: Before sending the analysis to the communication management module, the data is first encapsulated into a standard packet format; Receiving the analysis result of the data packet format, and marking the analysis result as data to be transmitted; Use a hash function to generate a summary of the data to be transmitted; Add a timestamp to the data to be transmitted; Transmitting the analysis result of the data packet format to the mobile terminal of the recipient; After receiving the analysis result of the data packet format, the receiver sends a confirmation message back to the communication management module; The receiver also records the analysis results, timestamp and verification results of the received data packet format.

[0012] Preferably, the specific working mode of the monitoring module is as follows: Capturing data packets transmitted in the communication management module network in real time; Generate a summary of the captured data packet content using the same hash function as the communication management module, and compare it with the summary value carried in the data packet to perform an integrity check; Check whether the timestamp in the data packet is consistent with the actual capture timestamp and perform timestamp verification; Monitor the transmission process of data packets; If any anomaly is found during integrity check, timestamp verification or data packet transmission, an alarm is triggered immediately. Send alarm information to laboratory supervisors through preset communication channels; All captured packets, generated hash values, signature verification results, and timestamps are recorded in the monitoring log.

[0013] Preferably, the specific process of the transmission process of the monitoring data packet is as follows: The transmission delay is obtained by recording the time required for the data packet to be transmitted from the communication management module to the receiving party; The probability that a data packet is successfully transmitted to the destination is obtained by dividing the number of successfully transmitted data packets by the total number of transmitted data packets, that is, the success rate. The transmission delay and the success rate are compared with a preset range. If the transmission delay and the success rate are within the preset range, the transmission process of the data packet is normal, otherwise the transmission process of the data packet is abnormal.

[0014] Beneficial effects: It can more effectively monitor and control the laboratory environment, improve the accuracy and security of data, while reducing energy consumption and maintenance costs, helping to improve the intelligence level of the laboratory. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flow chart of the control system of the present invention. DETAILED DESCRIPTION

[0016] The laboratory intelligent equipment perception system is mainly used to monitor the laboratory environment and equipment status. It can timely detect potential safety risks, such as fire, leakage, etc., and take preventive or response measures to reduce the probability of accidents. It can effectively track and manage the equipment, chemicals and other resources in the laboratory to ensure the rational use and storage of resources and reduce waste. However, in actual use, the laboratory intelligent equipment perception system needs to use a variety of high-precision sensors to monitor the data in the laboratory, which not only generates a large amount of detection data, which brings difficulties to subsequent processing, but also these data need to rely on wireless sensor networks for data transmission. The stability and security of the existing wireless network are difficult to guarantee; like Figure 1 As shown, a laboratory intelligent device perception system based on signal transmission includes a data acquisition module, and the data acquisition module is used to collect parameter information in the laboratory; it should be noted that in this embodiment, a high-precision, low-power sensor can be used, and an intelligent algorithm can be integrated to perform data preprocessing to reduce the transmission of invalid data, which can reduce the data transmission volume of the wireless network, reduce network congestion and improve data transmission efficiency; It should also be noted that, in this embodiment, the parameter information may be temperature, humidity, and gas hole; A processing and analysis module, which is used to analyze and process the parameters collected by the data collection module, and to distribute the data processing tasks to the edge of the network; it should be noted that localized processing reduces the data transmission requirements, improves the data processing speed and reduces the delay; Communication management module; the communication management module is used to transmit the analysis results of the processing and analysis module to the mobile terminal of the laboratory supervisor, and the communication management module is also used to enhance the security during the transmission process; it should be noted that the reliability and security of the wireless network are enhanced to ensure the integrity and confidentiality of the data during the transmission process; A monitoring module, which is used to monitor the transmission process of the communication management module and to raise an alarm; it should be noted that the safety monitoring capability of the laboratory is improved, and potential security threats are discovered and responded to in a timely manner; It should also be noted that through the comprehensive use of the above modules, the laboratory environment can be monitored and controlled more effectively, the accuracy and security of data can be improved, while energy consumption and maintenance costs can be reduced, which helps to improve the intelligence level of the laboratory.

[0017] As an optional embodiment: the data acquisition module further includes a preprocessing unit, which is used to pre-filter abnormal parameter information and fill in missing parameter information. The specific working method is as follows: Cleaning the collected parameter information; It should be noted that cleaning the collected raw data includes removing noise, filtering and removing outliers. In this embodiment, methods such as mean filtering, median filtering, and recursive average filtering can be used; Perform outlier identification processing on the cleaned parameter information; it should be noted that, in this embodiment, outliers can be identified by using a box plot (also known as a box-and-whisker plot), and the box plot determines the normal range of the data through the upper quartile (Q3), the lower quartile (Q1) and the interquartile range (IQR=Q3-Q1), and marks the values ​​exceeding the normal range as outliers; You can consider directly deleting data points containing outliers and replacing outliers with median or mean values; Then, the parameter information is processed for missing value identification. It should be noted that, in this embodiment, data exploration and visualization (such as heat map, missing value matrix) can be used to identify missing values ​​in the data, and the mean or median of all data can be used to fill the missing values. Perform feature extraction on the processed parameter information, and then perform compression processing on the extracted feature information; it should be noted that in order to reduce the transmission of invalid data, the data can be compressed, for example, by using the GZIP or LZMA algorithm to compress the data; The compressed characteristic information is transmitted to the processing and analysis module. It should be noted that the data transmission efficiency of the laboratory data acquisition module can be effectively improved, the transmission of invalid data can be reduced, network congestion can be reduced, and the overall data acquisition and processing performance can be improved.

[0018] As an optional embodiment: the specific process of extracting features from the processed parameter information is as follows: According to the formula , calculate and obtain the temperature uniformity of the laboratory ,in is the highest temperature measured for the i-th time, is the lowest temperature measured at the ith time, and n is the number of measurements; According to the formula , calculate and obtain the temperature fluctuation of the laboratory ,in and is the highest and lowest temperature measured at the test point at n times; According to the formula , calculate and obtain the humidity uniformity of the laboratory , among which and are the highest and lowest humidity measured at the i-th time, respectively, and m is the number of measurements; According to the formula , calculate and obtain the humidity fluctuation of the laboratory ,in are the highest and lowest humidity in m measurements, respectively; The temperature uniformity , Temperature Fluctuation , humidity uniformity and humidity fluctuations Marked as the extracted features. It should be noted that temperature uniformity It reflects the difference between the maximum and minimum temperature of each measuring point in the laboratory within a certain period of time. It is used to evaluate the consistency of temperature distribution in the laboratory and ensure the stability and repeatability of experimental conditions. For experiments that require precise temperature control, temperature uniformity is a key indicator. Temperature fluctuation It indicates the maximum fluctuation range of temperature in a single measurement cycle. It is used to evaluate the short-term stability of temperature in the laboratory. It is particularly important for experiments that require fast response and precise control. Humidity uniformity Similar to temperature uniformity, it reflects the difference between the maximum and minimum humidity values ​​at each measuring point in the laboratory. For experiments that require humidity control, such as plant growth experiments or certain chemical reactions, humidity uniformity is an important parameter to ensure experimental accuracy. Humidity fluctuation It indicates the maximum fluctuation range of humidity within a single measurement cycle. For experiments that require precise control of humidity, humidity fluctuation is a key indicator for evaluating short-term humidity stability in the laboratory. These calculated values ​​help laboratory managers monitor and adjust environmental conditions to ensure the accuracy and reliability of the experiment. By listing the above calculated values ​​as extracted features, it can facilitate subsequent analysis and processing.

[0019] As an optional embodiment: the specific working mode of the processing and analysis module is as follows: Deploy edge nodes at the edge of the network; it should be noted that in this embodiment, these nodes may be smart devices, edge servers or edge gateways; Perform data analysis on edge nodes; it should be noted that by distributing data processing tasks to the edge of the network, data transmission requirements can be reduced, data processing speed can be increased, and latency can be reduced; The data analysis includes decompressing the compressed characteristic information obtained after transmission; it should be noted that the decompression is performed by a decompression algorithm corresponding to the compression algorithm; After decompression, the extracted feature information is analyzed. It should be noted that the extracted feature information is analyzed to obtain the perception status of the equipment in the laboratory.

[0020] As an optional embodiment: the specific working process of analyzing the extracted feature information is as follows: Pre-set temperature uniformity , Temperature Fluctuation , humidity uniformity and humidity fluctuations Corresponding control range; It should be noted that the corresponding control range is determined according to the specific experimental requirements and safety standards of the laboratory, which is usually given by the experimental protocol, industry standards or safety specifications; The calculated temperature uniformity , Temperature Fluctuation , humidity uniformity and humidity fluctuations Compare with the corresponding control range; If the temperature and humidity values ​​at all measurement points in the laboratory are within the preset range and the temperature uniformity is , Temperature Fluctuation , humidity uniformity and humidity fluctuations If both are within the control range, the laboratory environment is considered stable; otherwise, the laboratory environment is considered unstable. The judgment result is transmitted to the communication module. It should be noted that by analyzing the extracted characteristic information, it is possible to perceive whether the working environment in the laboratory is stable.

[0021] As an optional embodiment: the specific working method of extracting features from the processed parameter information also includes: Obtaining parameter information and usage information of the equipment; it should be noted that, in this embodiment, the parameter information includes operating parameters, pressure, flow rate, voltage, current, etc. of the equipment in the laboratory, and the usage information includes the switch status and switch time of the laboratory equipment and historical fault information, and the historical fault information includes the number of faults, etc.; The failure rate Y of the laboratory equipment is obtained according to the usage information of the equipment; it should be noted that, in this embodiment, it is obtained by dividing the number of failures by the total operating time; The usage frequency U of the laboratory equipment is obtained according to the usage information of the equipment; it should be noted that in this embodiment, the usage frequency U is obtained by dividing the total number of startup times by the number of days observed; The average usage time P of the laboratory equipment is obtained according to the usage information of the equipment; it should be noted that, in this embodiment, it is obtained by dividing the total usage time during the observation period by the total number of startup times; The performance average value S of the laboratory equipment is obtained according to the parameter information of the equipment; it should be noted that, in this embodiment, by comprehensively calculating each performance indicator of the laboratory equipment, all measured values ​​are recorded and averaged, including the operating parameters, pressure, flow rate, voltage, current, etc. of the equipment in the laboratory; The failure rate Y, the usage frequency U, the average usage time P and the performance average S are marked as the extracted features. It should be noted that the extracted features are transmitted to the processing and analysis module; It should also be noted that key feature information can be extracted from the parameter information and usage information of laboratory equipment, which is helpful in evaluating the operating status, performance and reliability of the equipment, as well as formulating corresponding maintenance and improvement measures.

[0022] As an optional embodiment: the specific working process of analyzing the extracted feature information also includes the following: The reliability index of the equipment in the laboratory is obtained by subtracting the failure rate Y from 1; it should be noted that the reliability index is calculated using the failure rate, which reflects the probability of the equipment running without failure within a specified time; The utilization efficiency of the equipment in the laboratory is obtained by dividing the average usage time P by the usage frequency U. It should be noted that it reflects the average operating time of the equipment each time it is turned on; The stability evaluation value of the equipment is obtained by dividing the performance average value S by the pre-equipment performance standard value of the equipment in the laboratory. It should be noted that the performance stability index is calculated to evaluate whether the equipment performance meets the expected standards. The pre-equipment performance standard value can be obtained from the equipment manufacturer. The reliability, efficiency and stability evaluation values ​​of the equipment in the laboratory are transmitted to the communication management module as analysis results. It should be noted that the evaluation results of the laboratory equipment can be fully perceived and provide a basis for the maintenance and improvement of the equipment.

[0023] As an optional embodiment: the specific working mode of the communication management module is as follows: Before sending the analysis to the communication management module, the data is first packaged into a standard data packet format; it should be noted that, for example, JSON or XML, in order to facilitate parsing and processing; Receiving the analysis result of the data packet format, and marking the analysis result as data to be transmitted; Use a hash function to generate a summary of the data to be transmitted; it should be noted that the hash function (such as SHA-256) is combined with digital signature technology to ensure the integrity and source authentication of the data, so that even if the data is tampered with, the receiver can find data inconsistencies by comparing the summary value; Add a timestamp to the data to be transmitted; it should be noted that detailed logs are recorded to facilitate tracking and backtracking when necessary, enhancing non-repudiation; The analysis results in the data packet format are transmitted to the mobile phone terminal of the recipient; it should be noted that the transmission is performed through the laboratory's internal network or a secure communication channel. In this embodiment, the recipient is the laboratory staff; After receiving the analysis result of the data packet format, the receiver sends a confirmation message back to the communication management module; it should be noted that this is to ensure that the data packet has arrived successfully; The receiver also records the analysis results, timestamp and verification results of the received data packet format, which should be noted to facilitate future data analysis and backtracking.

[0024] As an optional embodiment: the specific working mode of the monitoring module is as follows: Capturing data packets transmitted in the communication management module network in real time; Generate a summary of the captured data packet content using the same hash function as the communication management module, and compare it with the summary value carried in the data packet to perform an integrity check; it should be noted that the data packet content is compared with the generated hash value; Check whether the timestamp in the data packet is consistent with the actual capture timestamp and perform timestamp verification; Monitoring the transmission process of the data packet; it should be noted that in this embodiment, it includes transmission speed, transmission delay and transmission success rate; If any anomaly is found during integrity check, timestamp verification or data packet transmission, an alarm is triggered immediately. Send the alarm information to the laboratory supervisor through a preset communication channel; it should be noted that the preset communication channel may be the contact information of the laboratory supervisor reserved in advance; All captured data packets, generated hash values, signature verification results, and timestamps are recorded in the monitoring log. It should be noted that this is helpful for subsequent inspections; It should also be noted that the monitoring module can effectively monitor the transmission process of the communication management module, ensure the security and reliability of data transmission, and promptly alarm when an abnormality is found.

[0025] As an optional embodiment: the specific process of the transmission process of the monitoring data packet is as follows: The transmission delay is obtained by recording the time required for the data packet to be transmitted from the communication management module to the receiving party; The probability that a data packet is successfully transmitted to the destination is obtained by dividing the number of successfully transmitted data packets by the total number of transmitted data packets, that is, the success rate. The transmission delay and the success rate are compared with a preset range. If the transmission delay and the success rate are within the preset range, the transmission process of the data packet is normal, otherwise the transmission process of the data packet is abnormal.

[0026] How it works The data acquisition module is used to collect parameter information in the laboratory; A processing and analysis module, which is used to analyze and process the parameters collected by the data collection module and distribute the data processing tasks to the edge of the network; Communication management module; the communication management module is used to transmit the analysis results of the processing and analysis module to the mobile terminal of the laboratory supervisor, and the communication management module is also used to enhance the security during the transmission process; A monitoring module, the monitoring module is used to monitor the transmission process of the communication management module and to give an alarm; Through the comprehensive use of the above modules, the laboratory environment can be monitored and controlled more effectively, the accuracy and security of data can be improved, while energy consumption and maintenance costs can be reduced, which helps to improve the intelligence level of the laboratory.

[0027] The above are only preferred implementations of the present invention. The protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technical staff in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of this template.

Claims

1. A laboratory intelligent equipment perception system based on signal transmission, characterized in that: It includes a data acquisition module, and the data acquisition module is used to collect parameter information in the laboratory; A processing and analysis module, which is used to analyze and process the parameters collected by the data collection module and distribute the data processing tasks to the edge of the network; Communication management module; the communication management module is used to transmit the analysis results of the processing and analysis module to the mobile terminal of the laboratory supervisor, and the communication management module is also used to enhance the security during the transmission process; A monitoring module, the monitoring module is used to monitor the transmission process of the communication management module and to give an alarm; The data acquisition module also includes a preprocessing unit, which is used to pre-filter abnormal parameter information and fill in missing parameter information. The specific working method is as follows: Clean the collected parameter information; Perform outlier identification processing on the cleaned parameter information; Then the parameter information is processed for missing value identification; Perform feature extraction on the processed parameter information, and then perform compression processing on the extracted feature information; Transmitting the compressed feature information to the processing and analysis module; The specific process of extracting features from the processed parameter information is as follows: According to the formula , calculate and obtain the temperature uniformity of the laboratory ,in is the highest temperature measured for the i-th time, is the lowest temperature measured at the ith time, and n is the number of measurements; According to the formula , calculate and obtain the temperature fluctuation of the laboratory ,in and is the highest and lowest temperature measured at the test point at n times; According to the formula , calculate and obtain the humidity uniformity of the laboratory ,in and are the highest and lowest humidity measured at the i-th time, respectively, and m is the number of measurements; According to the formula , calculate and obtain the humidity fluctuation of the laboratory ,in are the highest and lowest humidity in m measurements, respectively; The temperature uniformity , Temperature Fluctuation , humidity uniformity and humidity fluctuations Marked as extracted features.

2. According to claim 1, a laboratory intelligent device perception system based on signal transmission is characterized in that: The specific working mode of the processing and analysis module is as follows: Deploy edge nodes at the edge of the network; Perform data analysis on edge nodes; The data analysis includes decompressing the compressed characteristic information obtained after transmission; After decompression, the extracted feature information is analyzed.

3. According to claim 2, a laboratory intelligent device perception system based on signal transmission is characterized in that: The specific working process of analyzing the extracted feature information is as follows: Pre-set temperature uniformity , Temperature Fluctuation , humidity uniformity and humidity fluctuations The corresponding control range; The calculated temperature uniformity , Temperature Fluctuation , humidity uniformity and humidity fluctuations Compare with the corresponding control range; If the temperature and humidity values ​​at all measurement points in the laboratory are within the preset range and the temperature uniformity is , Temperature Fluctuation , humidity uniformity and humidity fluctuations If both are within the control range, the laboratory environment is considered stable; otherwise, the laboratory environment is considered unstable. The determination result is transmitted to the communication module.

4. According to claim 3, a laboratory intelligent device perception system based on signal transmission is characterized in that: The specific working method of extracting features from the processed parameter information also includes: Obtain parameter information and usage information of the device; Obtain the failure rate Y of laboratory equipment based on the equipment usage information; Obtain the usage frequency U of the laboratory equipment according to the usage information of the equipment; According to the equipment usage information, the average usage time P of the laboratory equipment is obtained; According to the parameter information of the equipment, the performance average value S of the laboratory equipment is obtained; The failure rate Y, usage frequency U, average usage time P and performance average S are marked as the extracted features.

5. According to claim 4, a laboratory intelligent device sensing system based on signal transmission is characterized in that: The specific working process of analyzing the extracted feature information also includes the following: The reliability index of the equipment in the laboratory is obtained by subtracting the failure rate Y from 1; The utilization efficiency of the equipment in the laboratory is obtained by dividing the average usage time P by the usage frequency U; The stability evaluation value of the equipment is obtained by dividing the performance average value S by the performance standard value of the equipment in the laboratory; The reliability, usage efficiency and stability evaluation values ​​of the equipment in the laboratory are transmitted to the communication management module as analysis results.

6. According to claim 1, a laboratory intelligent equipment perception system based on signal transmission is characterized in that: The specific working mode of the communication management module is as follows: Before sending the analysis to the communication management module, the data is first encapsulated into a standard packet format; Receiving the analysis result of the data packet format, and marking the analysis result as data to be transmitted; Use a hash function to generate a summary of the data to be transmitted; Add a timestamp to the data to be transmitted; Transmitting the analysis result of the data packet format to the mobile terminal of the recipient; After receiving the analysis result of the data packet format, the receiver sends a confirmation message back to the communication management module; The receiver also records the analysis results, timestamp and verification results of the received data packet format.

7. A laboratory intelligent equipment sensing system based on signal transmission according to claim 6, characterized in that: The specific working mode of the monitoring module is as follows: Capturing data packets transmitted in the communication management module network in real time; Generate a summary of the captured data packet content using the same hash function as the communication management module, and compare it with the summary value carried in the data packet to perform an integrity check; Check whether the timestamp in the data packet is consistent with the actual capture timestamp and perform timestamp verification; Monitor the transmission process of data packets; If any anomaly is found during integrity check, timestamp verification or monitoring of data packet transmission, an alarm is triggered immediately; Send alarm information to laboratory supervisors through preset communication channels; All captured packets, generated hash values, signature verification results, and timestamps are recorded in the monitoring log.

8. The laboratory intelligent equipment sensing system based on signal transmission according to claim 7 is characterized in that: The specific process of the transmission process of the monitoring data packet is as follows: The transmission delay is obtained by recording the time required for the data packet to be transmitted from the communication management module to the receiving party; The probability that a data packet is successfully transmitted to the destination is obtained by dividing the number of successfully transmitted data packets by the total number of transmitted data packets, that is, the success rate. The transmission delay and the success rate are compared with a preset range. If the transmission delay and the success rate are within the preset range, the transmission process of the data packet is normal, otherwise the transmission process of the data packet is abnormal.

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