Data query method and medium based on micro-electro-mechanical system final test processor

Abstract

This invention discloses a data query method and medium based on a microelectromechanical system (MEMS) final test processor. The data query system based on the MEMS final test processor receives and parses the current data query command in real time to obtain the parsing result. It matches the identifier of the current data query final test processor with a Uniform Resource Locator (URI) mapping table to determine the target URI. Based on the embedded sensor information of each current data query, it queries a time-series server database to obtain the data for each embedded sensor, and then feeds this data back to the target web dashboard for display. The display results are then fed back to the target scanning terminal device. This solves the problem of difficult data querying caused by limitations such as the need for dedicated software interfaces and mobile applications for data retrieval, improving the efficiency, accuracy, and flexibility of test processor data querying.

Description

Technical Field

[0001] This invention relates to the field of data processing in semiconductor manufacturing equipment, and more particularly to a data query method and medium based on a microelectromechanical system final test processor. Background Technology

[0002] In the field of semiconductor manufacturing equipment data processing, semiconductor test processors are crucial for automating integrated circuit testing under operating conditions. In the case of micro-electro-mechanical systems (MEMS) devices that rely on physical movement or environmental interactions (e.g., changes in acceleration, rotation, or pressure), the accuracy of the test environment directly impacts measurement effectiveness. Even minute fluctuations in temperature, vibration, or humidity can lead to incorrect pass / fail decisions, calibration drift, or reduced yield.

[0003] In the process of developing this invention, the inventors discovered the following shortcomings in the existing technology: Currently, MEMS final test processors are equipped with embedded sensors to monitor key operating parameters, but existing systems for accessing data are significantly limited. This is because data is typically confined to proprietary software interfaces or local human-machine interfaces, requiring a physical presence for monitoring; for remote access, dedicated mobile applications, IP addresses, or complex application programming interfaces are also required, introducing operational friction and latency. Furthermore, in high-throughput MEMS production requiring nanometer-level precision, the inability to immediately assess device health when relevant data needs to be acquired increases the average time for identification problems and prolongs downtime, potentially leading to the scrapping of MEMS devices. Summary of the Invention

[0004] This invention provides a data query method and medium based on the final test processor of a microelectromechanical system, so as to improve the efficiency, accuracy and flexibility of test processor data query.

[0005] According to one aspect of the present invention, a data query method based on a microelectromechanical system final test processor is provided, comprising:

[0006] The data query system based on the microelectromechanical system final test processor receives the current data query instruction in real time, parses the current data query instruction, and obtains the parsing result of the current data query instruction.

[0007] The parsing result of the current data query instruction includes the identifier of the final test processor to be queried and at least one embedded sensor information to be queried.

[0008] Based on the current data to be queried, the final test processor identifier is matched with the pre-built identifier Uniform Resource Locator (URI) mapping table to determine the target URI;

[0009] Based on the current data to be queried, the embedded sensor information is queried in the pre-built time series server database, and the current embedded sensor data of each embedded sensor corresponding to the target final test processor corresponding to the target Uniform Resource Locator is obtained respectively.

[0010] The data from each of the currently embedded sensors is fed back to the target webpage dashboard, and the data from each of the currently embedded sensors is displayed on the target webpage dashboard in a preset visualization manner. The display results are then fed back to the target scanning terminal device.

[0011] According to another aspect of the present invention, a data query device based on a microelectromechanical system final test processor is provided, comprising:

[0012] The current data query instruction parsing result determination module is used to receive the current data query instruction in real time through the data query system based on the microelectromechanical system final test processor, and parse the current data query instruction to obtain the current data query instruction parsing result;

[0013] The parsing result of the current data query instruction includes the identifier of the final test processor to be queried and at least one embedded sensor information to be queried.

[0014] The target final test processor determination result is used to query the final test processor identifier based on the current data to be tested, match it with the pre-built identifier uniform resource locator mapping table, and determine the target uniform resource locator.

[0015] The current embedded sensor data acquisition module is used to query embedded sensor information based on the current data to be obtained, and to perform data query in a pre-built time series server database to obtain the current embedded sensor data of each embedded sensor corresponding to the target final test processor corresponding to the target Uniform Resource Locator.

[0016] The result feedback module is used to feed back the data of each currently embedded sensor to the target webpage dashboard, and display the data of each currently embedded sensor on the target webpage dashboard in a preset visualization method, and feed back the display results to the target scanning terminal device.

[0017] According to another aspect of the present invention, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the data query method based on the microelectromechanical system final test processor as described in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions, the computer instructions being configured to cause a processor to execute and implement the data query method based on a microelectromechanical system final test processor as described in any embodiment of the present invention.

[0019] The technical solution of this invention, through a data query system based on the final test processor of a microelectromechanical system (MEMS), receives current data query instructions in real time, parses these instructions to obtain the parsing results, matches the identifier of the final test processor with a pre-built identifier Uniform Resource Locator (URI) mapping table to determine the target URI, and queries a pre-built time-series server database based on the embedded sensor information of each current data query to obtain the current embedded sensor data corresponding to each embedded sensor of the target final test processor corresponding to the target URI. The current embedded sensor data is then fed back to a target webpage dashboard, displayed on the dashboard using a preset visualization method, and the display results are fed back to the target scanning terminal device. This solves the problem of difficult data querying caused by limitations such as the need for dedicated software interfaces and dedicated mobile applications for data retrieval, improves the efficiency, accuracy, and flexibility of test processor data querying, and allows for timely data feedback to ensure the security of the final test processor of the MEMS.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1This is a flowchart of a data query method based on a final test processor of a microelectromechanical system according to Embodiment 1 of the present invention;

[0023] Figure 2 This is a schematic diagram of a data query device based on a microelectromechanical system final test processor according to Embodiment 2 of the present invention;

[0024] Figure 3 This is a schematic diagram of the structure of an electronic device provided according to Embodiment 3 of the present invention. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "target," "current," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] It is worth noting that the information collected in the technical solution of this application is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data all comply with the relevant laws, regulations and standards of the relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entry points for users to choose to authorize or refuse; if the user chooses to refuse, the process will proceed to the expert decision-making process.

[0028] Example 1

[0029] Figure 1The flowchart of a data query method based on a microelectromechanical system final test processor is provided in Embodiment 1 of the present invention. This embodiment is applicable to situations where the microelectromechanical system final test processor performs timely and accurate data queries. The method can be executed by a data query device based on the microelectromechanical system final test processor, which can be implemented in hardware and / or software.

[0030] Correspondingly, such as Figure 1 As shown, the method includes:

[0031] S110. The data query system based on the microelectromechanical system final test processor receives the current data query instruction in real time, parses the current data query instruction, and obtains the parsing result of the current data query instruction.

[0032] The parsing result of the current data query instruction includes the identifier of the final test processor to be queried and at least one embedded sensor information to be queried.

[0033] In this embodiment, the data query system based on the final test processor of the microelectromechanical system can receive real-time component description data at the current moment and historical component description data at historical moments sent by different final test processors.

[0034] In addition, a QR code is printed on the exterior of each microelectromechanical system final test processor; this QR code can be printed on a durable industrial-grade adhesive label and permanently attached to a visible and accessible location on the exterior of the machine using tamper-evident adhesive or mechanical fasteners to ensure co-location and durability in industrial environments.

[0035] Optionally, before receiving the data query instruction in real time through the data query system based on the microelectromechanical system final test processor and parsing the data query instruction to obtain the data query instruction parsing result, the method further includes: instructing a target scanning terminal device to scan the current QR code on the current microelectromechanical system final test processor to obtain the current QR code scanning result; and generating the current data query instruction based on the acquired current data query embedded sensor information task and the current QR code scanning result.

[0036] In this embodiment, when a user needs to obtain temperature sensor data and component humidity sensor data from a specific microelectromechanical system (MEMS) final test processor, a corresponding task for querying embedded sensor information can be generated. Then, by scanning the current QR code on the current MEMS final test processor using a target scanning terminal device, the QR code scanning result can be obtained, which in turn generates a current data query instruction and sends it to the data query system based on the MEMS final test processor.

[0037] Optionally, parsing the current data query instruction to obtain the current data query instruction parsing result includes: parsing the current QR code scanning result corresponding to the current data query instruction to obtain the current data query final test processor identifier; parsing the current data query embedded sensor information task corresponding to the current data query instruction to obtain at least one current data query embedded sensor information; and obtaining the current data query instruction parsing result based on the current data query final test processor identifier and at least one current data query embedded sensor information.

[0038] In this embodiment, since each QR code corresponds to a unique identifier for the final test processor to be queried, it is necessary to parse the current QR code scanning result corresponding to the current data query instruction to obtain the identifier for the final test processor to be queried. Then, it is necessary to parse the task of querying embedded sensor information to obtain at least one piece of embedded sensor information, i.e., continuing the previous example, obtaining the information of the corresponding component temperature sensor and component humidity sensor. Therefore, the parsing result of the current data query instruction can include the identifier for the final test processor to be queried and the embedded sensor information for each component.

[0039] Optionally, it further includes: the data query system based on the microelectromechanical system final test processor, used to manage multiple microelectromechanical system final test processors; wherein each of the microelectromechanical system final test processors includes: an onboard communication module and multiple embedded sensors; each embedded sensor is used to collect real-time component description data of each test processor sub-component corresponding to the microelectromechanical system final test processor; and the real-time component description data is sent to the data query system based on the microelectromechanical system final test processor through the onboard communication module.

[0040] In this embodiment, each microelectromechanical system (MEMS) final test processor may include an onboard communication module and multiple embedded sensors. The onboard communication module can receive real-time component description data and historical component description data sent by each embedded sensor; and then, through the onboard communication module, transmit the received component description data to the data query system based on the MEMS final test processor wirelessly.

[0041] Accordingly, each embedded sensor is used to collect real-time component description data of the respective test processor sub-components corresponding to the final test processor of the microelectromechanical system. The types of embedded sensors may include component temperature sensors, component humidity sensors, component vibration sensors, component pressure sensors, and MEMS accelerometer sensors, etc.

[0042] Additionally, for the data query system based on the MEMS final test processor, the system is designed to be implemented within a dedicated network of the semiconductor manufacturing facility, thereby ensuring data security and low-latency communication. The core component is the semiconductor test processor, a pick-and-place MEMS final test processor for high-throughput testing of MEMS accelerometer sensors, gyroscopes, inertial measurement units, barometric pressure sensors, component humidity sensors, and electromagnetic sensors. Specifically, the pick-and-place processor is configured for high-throughput testing of equipment requiring thermal cycling between -40°C and 125°C.

[0043] Correspondingly, due to the physical nature of the MEMS final test processor, its electrical performance is highly sensitive to minute changes in temperature, mechanical vibration, humidity, and electromagnetic interference. Therefore, the final test processor must maintain excellent environmental stability throughout the entire testing cycle. To support this, one or more embedded sensors (such as the DS18B20 temperature sensor, BME280 environmental sensor, or ADXL345 accelerometer) are strategically placed within the final test processor to monitor critical areas, including the test chamber, thermal conditioning unit, and robotic actuator arm.

[0044] Furthermore, the embedded sensors can be connected to an onboard communication module. This onboard communication module includes a microcontroller and a wireless transceiver (e.g., Wi-Fi 6 or Ethernet) capable of connecting to a facility local area network. The onboard communication module is configured to package sensor readings (i.e., to send packetized real-time component description data) and transmit them at preset time intervals (e.g., every 1-5 seconds) to a predetermined network endpoint in a data query system corresponding to a microelectromechanical system-based final test processor.

[0045] Optionally, after sending the real-time component description data to the data query system based on the microelectromechanical system final test processor, the method further includes: receiving and parsing the real-time component description data corresponding to different microelectromechanical system final test processors in real time, parsing to obtain the data query final test processor identifier and the data values ​​of each embedded sensor corresponding to each microelectromechanical system final test processor; matching the corresponding Uniform Resource Locator (URL) according to each data query final test processor identifier, and generating an identifier URL mapping table; jointly storing each group of data query final test processor identifiers and embedded sensor data values, as well as the identifier URL mapping table, in a time series server database corresponding to the data query system based on the microelectromechanical system final test processor, thereby completing the construction of the time series server database.

[0046] In this embodiment, for the data query system based on the final test processor of the microelectromechanical system (MEMS), after receiving the real-time component description data, such as a temperature of 25 degrees Celsius and a humidity of 23%, the identifier of the final test processor for data query can be determined first based on the real-time component description data, assuming it is ZUCSCLQ01. Then, based on the specific parameter values: a temperature of 25 degrees Celsius and a humidity of 23%, the embedded sensor data values ​​are determined, specifically: the component temperature sensor data value is 25 degrees Celsius and the component humidity sensor data value is 23%. Additionally, each identifier of the final test processor for data query needs to be matched with a corresponding unique unified resource locator (URI), and an identifier-URI mapping table is generated.

[0047] Accordingly, the identifier ZUCSCLQ01 of the final test processor, along with the data value of 25 degrees Celsius from the component temperature sensor and 23% from the component humidity sensor, can be jointly stored in the time series server database. This allows data to be queried in the constructed time series server database using the identifier.

[0048] Optionally, before receiving the data query instruction in real time through the data query system based on the microelectromechanical system final test processor, and parsing the data query instruction to obtain the data query instruction parsing result, the method further includes: acquiring historical component description data corresponding to different microelectromechanical system final test processors at historical moments; parsing the historical component description data to obtain the data query final test processor identifier and historical embedded sensor data values ​​corresponding to each microelectromechanical system final test processor; and jointly storing each set of data query final test processor identifiers and historical embedded sensor data values ​​in a time series server database to achieve the updating and optimization of the constructed time series server database.

[0049] In this embodiment, it is also necessary to obtain historical component description data for each historical moment. Each historical component description data can be parsed to obtain the corresponding parsing results, which are then stored in the time series server database. Furthermore, for querying the final test processor identifier based on the data parsed from the historical component description data, it is necessary to determine whether it exists in the pre-stored identifier-uniform resource locator (URI) mapping table. If it exists, there is no need to add a new mapping between the final test processor identifier and the URI; if it does not exist, it needs to be added to the URI mapping table to update the URI mapping table.

[0050] S120. Query the final test processor identifier based on the current data to be retrieved, match it with the pre-built identifier Uniform Resource Locator (URI) mapping table, and determine the target URI.

[0051] In this embodiment, the target Uniform Resource Locator (URI) can be determined based on the final test processor identifier of the current data to be queried, according to the constructed identifier Uniform Resource Locator (URI) mapping table. This improves the security and accuracy of data querying.

[0052] S130. Query the embedded sensor information according to the current data to be queried, perform data query in the pre-built time series server database, and obtain the current embedded sensor data of each embedded sensor corresponding to the target final test processor corresponding to the target Uniform Resource Locator.

[0053] In this embodiment, the embedded sensor information of each current data to be queried can be obtained, such as the specific data values ​​of the temperature sensor and the capacitive humidity sensor, as well as their historical fluctuation trends. By querying the time series server database, the target final test processor corresponding to the target Uniform Resource Locator can be determined first, and then the current embedded sensor data of each embedded sensor corresponding to the target final test processor can be determined.

[0054] S140. Feed back the data of each currently embedded sensor to the target webpage dashboard, and display the data of each currently embedded sensor on the target webpage dashboard in a preset visualization manner, and feed back the display results to the target scanning terminal device.

[0055] The target webpage dashboard can be set on a data query system based on the final test processor of microelectromechanical systems, and can perform embedded sensor data reception, threshold comparison analysis and visualization operations.

[0056] Optionally, the step of feeding back each of the currently embedded sensor data to the target webpage dashboard and displaying each of the currently embedded sensor data on the target webpage dashboard through a preset visualization method includes: feeding back each of the currently embedded sensor data to the target webpage dashboard and obtaining the embedded sensor data thresholds corresponding to each of the embedded sensor data; wherein, the currently embedded sensor data includes at least one of the following: component vibration sensor data, component temperature sensor data, component humidity sensor data, and component machine status sensor data; comparing the component vibration sensor data, component temperature sensor data, component humidity sensor data, and component machine status sensor data with their respective corresponding embedded sensor data thresholds to obtain threshold comparison results; and generating display results on the target webpage dashboard through the visualization method based on the threshold comparison results and in combination with each of the currently embedded sensor data.

[0057] In this embodiment, different embedded sensor data thresholds are set for different embedded sensor data values. The target webpage dashboard compares the component vibration sensor data, component temperature sensor data, component humidity sensor data, and component machine status sensor data with their respective embedded sensor data thresholds to obtain threshold comparison results. For example, the threshold comparison result may be that the component vibration sensor data, component temperature sensor data, and component machine status sensor data all meet the embedded sensor data threshold requirements; however, the component humidity sensor data does not meet the embedded sensor data threshold requirements. The results of the non-compliance threshold comparison can be displayed, and the current embedded sensor data is also needed to generate a visualization on the target webpage dashboard. Additionally, historical embedded sensor data can be displayed in the results.

[0058] A concrete example is that, in operation, when operators, technicians, or engineers need to assess machine condition (such as verifying thermal stability or diagnosing suspected vibration problems before calibration runs), they can use the camera on their target scanning terminal device (e.g., a standard smartphone) to scan the current QR code on the current microelectromechanical system (MEMS) final test processor. The device's operating system decodes the final test processor identifier and matches it with a Uniform Resource Locator (URL), automatically launching a default web browser that navigates directly to a web dashboard. This dashboard is immediately displayed, showing real-time embedded sensor data, alarm status (which requires alarm handling if threshold comparison results are not met), and selectable trends in historical embedded sensor data.

[0059] Specific application scenarios include: Scenario 1: Temperature stability monitoring during thermal cycling tests. For example, a factory is using a MEMS final test processor to conduct thermal cycling tests at -40°C and 125°C on a batch of automotive inertial measurement units. During the test, the operator suspects that a certain device is experiencing temperature overshoot in the high-temperature range. He can simply scan the QR code on the machine's casing with his mobile phone to open the device's dedicated real-time web dashboard in his browser, showing whether the temperature inside the test chamber is within the ±0.5°C tolerance. If an anomaly is found, the machine can be stopped immediately for investigation, preventing misjudgment of the entire batch of products due to test condition failure. Scenario 2: Vibration anomaly diagnosis. For example, the yield of a processor used to test high-precision accelerometers has recently declined. After scanning the QR code, the engineer found that the web dashboard showed an abnormal spike of 0.1g in the vibration value near the robotic arm during the pickup action, indicating bearing wear. Maintenance was promptly arranged to prevent more chips from being incorrectly calibrated. Scenario 3 involves the renovation of outdated equipment. Specifically, a factory has 10 traditional final testing machines that are not equipped with remote monitoring capabilities. These machines can be upgraded at low cost to intelligent devices that support real-time monitoring, without the need to replace the entire machine.

[0060] The technical solution of this invention, through a data query system based on the final test processor of a microelectromechanical system (MEMS), receives current data query instructions in real time, parses these instructions to obtain the parsing results, matches the identifier of the final test processor with a pre-built identifier Uniform Resource Locator (URI) mapping table to determine the target URI, and queries a pre-built time-series server database based on the embedded sensor information of each current data query to obtain the current embedded sensor data corresponding to each embedded sensor of the target final test processor corresponding to the target URI. The current embedded sensor data is then fed back to a target webpage dashboard, displayed on the dashboard using a preset visualization method, and the display results are fed back to the target scanning terminal device. This solves the problem of difficult data querying caused by limitations such as the need for dedicated software interfaces and dedicated mobile applications for data retrieval, improves the efficiency, accuracy, and flexibility of test processor data querying, and allows for timely data feedback to ensure the security of the final test processor of the MEMS.

[0061] Example 2

[0062] Figure 2 This is a schematic diagram of a data query device based on a microelectromechanical system (MEMS) final test processor provided in Embodiment 2 of the present invention. The data query device based on a MEMS final test processor provided in this embodiment can be implemented by software and / or hardware, and can be configured in a terminal device or server to implement a data query method based on a MEMS final test processor according to an embodiment of the present invention. Figure 2 As shown, the device includes: a current data query instruction parsing result determination module 210, a target unified resource locator determination result 220, a current embedded sensor data acquisition module 230, and a display result feedback module 240.

[0063] The current data query instruction parsing result determination module 210 is used to receive the current data query instruction in real time through the data query system based on the microelectromechanical system final test processor, and parse the current data query instruction to obtain the current data query instruction parsing result.

[0064] The parsing result of the current data query instruction includes the identifier of the final test processor to be queried and at least one embedded sensor information to be queried.

[0065] The target Uniform Resource Locator (URI) determination result 220 is used to query the final test processor identifier based on the current data to be searched, and match it with the pre-built identifier URI mapping table to determine the target URI.

[0066] The embedded sensor data acquisition module 230 is used to query embedded sensor information based on the current data to be obtained, and to perform data query in a pre-built time series server database to obtain the current embedded sensor data of each embedded sensor corresponding to the target final test processor corresponding to the target Uniform Resource Locator.

[0067] The display result feedback module 240 is used to feed back the data of each currently embedded sensor to the target web page dashboard, display the data of each currently embedded sensor on the target web page dashboard in a preset visualization method, and feed back the display results to the target scanning terminal device.

[0068] The technical solution of this invention, through a data query system based on the final test processor of a microelectromechanical system (MEMS), receives current data query instructions in real time, parses these instructions to obtain the parsing results, matches the identifier of the final test processor with a pre-built identifier Uniform Resource Locator (URI) mapping table to determine the target URI, and queries a pre-built time-series server database based on the embedded sensor information of each current data query to obtain the current embedded sensor data corresponding to each embedded sensor of the target final test processor corresponding to the target URI. The current embedded sensor data is then fed back to a target webpage dashboard, displayed on the dashboard using a preset visualization method, and the display results are fed back to the target scanning terminal device. This solves the problem of difficult data querying caused by limitations such as the need for dedicated software interfaces and dedicated mobile applications for data retrieval, improves the efficiency, accuracy, and flexibility of test processor data querying, and allows for timely data feedback to ensure the security of the final test processor of the MEMS.

[0069] Based on the above embodiments, a current data query instruction generation module is further included, which can be specifically used to: before the data query system based on the microelectromechanical system final test processor receives the data query instruction in real time and parses the data query instruction to obtain the data query instruction parsing result, instruct the target scanning terminal device to scan the current QR code on the current microelectromechanical system final test processor to obtain the current QR code scanning result; wherein, a QR code is printed on the exterior of each microelectromechanical system final test processor; and generate the current data query instruction based on the obtained current data query embedded sensor information task and the current QR code scanning result.

[0070] Based on the above embodiments, it may further include: the data query system based on the microelectromechanical system final test processor, used to manage multiple microelectromechanical system final test processors; wherein each of the microelectromechanical system final test processors includes: an onboard communication module and multiple embedded sensors; each embedded sensor is used to collect real-time component description data of each test processor sub-component corresponding to the microelectromechanical system final test processor; and the real-time component description data is sent to the data query system based on the microelectromechanical system final test processor through the onboard communication module.

[0071] Based on the above embodiments, a time series server database construction module is further included, which can be specifically used to: after sending the real-time component description data to the data query system based on the microelectromechanical system final test processor, receive and parse the real-time component description data corresponding to different microelectromechanical system final test processors in real time, and parse to obtain the data query final test processor identifier and the data value of each embedded sensor corresponding to each microelectromechanical system final test processor; match the corresponding Uniform Resource Locator (URL) according to each data query final test processor identifier, and generate an identifier URL mapping table; jointly store each group of data query final test processor identifiers and embedded sensor data values, as well as the identifier URL mapping table, in the time series server database corresponding to the data query system based on the microelectromechanical system final test processor, so as to complete the construction of the time series server database.

[0072] Based on the above embodiments, the current data query instruction parsing result determination module 210 can be specifically used to: obtain the current data query final test processor identifier by parsing the current QR code scanning result corresponding to the current data query instruction; obtain at least one current data query embedded sensor information by parsing the current data query embedded sensor information task corresponding to the current data query instruction; and obtain the current data query instruction parsing result based on the current data query final test processor identifier and at least one current data query embedded sensor information.

[0073] Based on the above embodiments, a time series server database update and optimization module is also included, which can be specifically used to: before receiving the data query instruction in real time through the data query system based on the microelectromechanical system final test processor and parsing the data query instruction to obtain the data query instruction parsing result, obtain historical component description data corresponding to different microelectromechanical system final test processors at historical moments; based on the historical component description data, parse to obtain the data query final test processor identifier and historical embedded sensor data values ​​corresponding to each microelectromechanical system final test processor; and jointly store each set of data query final test processor identifiers and historical embedded sensor data values ​​in the time series server database to realize the update and optimization of the constructed time series server database.

[0074] Based on the above embodiments, the display result feedback module 240 can be specifically used to: feed back each of the current embedded sensor data to the target webpage dashboard, and obtain the embedded sensor data thresholds corresponding to each of the embedded sensor data; wherein, the current embedded sensor data includes at least one of the following: component vibration sensor data, component temperature sensor data, component humidity sensor data, and component machine status sensor data; compare the component vibration sensor data, component temperature sensor data, component humidity sensor data, and component machine status sensor data with their respective corresponding embedded sensor data thresholds to obtain threshold comparison results; and, based on the threshold comparison results and in combination with each of the current embedded sensor data, generate display results on the target webpage dashboard through visualization.

[0075] The data query device based on the final test processor of microelectromechanical systems provided in the embodiments of the present invention can execute the data query method based on the final test processor of microelectromechanical systems provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0076] Example 3

[0077] Figure 3 A schematic diagram of an electronic device 10, which can be used to implement Embodiment 3 of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0078] like Figure 3 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0079] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0080] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the data query method for the final test processor based on a microelectromechanical system.

[0081] In some embodiments, the data query method based on the microelectromechanical system final test processor can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the data query method based on the microelectromechanical system final test processor described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the data query method based on the microelectromechanical system final test processor by any other suitable means (e.g., by means of firmware).

[0082] The method includes: receiving current data query instructions in real time through a data query system based on a microelectromechanical system (MEMS) final test processor, parsing the current data query instructions to obtain a current data query instruction parsing result; wherein, the current data query instruction parsing result includes a current data query final test processor identifier and at least one current data query embedded sensor information; matching the current data query final test processor identifier with a pre-built identifier Uniform Resource Locator (URI) mapping table to determine a target URI; querying data in a pre-built time series server database based on each of the current data query embedded sensor information to obtain current embedded sensor data for each embedded sensor corresponding to the target final test processor corresponding to the target URI; feeding back each of the current embedded sensor data to a target webpage dashboard, displaying each of the current embedded sensor data on the target webpage dashboard using a preset visualization method, and feeding back the display result to the target scanning terminal device.

[0083] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0084] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0085] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0086] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0087] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0088] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0089] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0090] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

[0091] Example 4

[0092] Embodiment 4 of the present invention also provides a computer-readable storage medium, wherein the computer-readable instructions, when executed by a computer processor, are used to execute a data query method based on a microelectromechanical system final test processor. The method includes: receiving a current data query instruction in real time through a microelectromechanical system final test processor-based data query system, and parsing the current data query instruction to obtain a current data query instruction parsing result; wherein the current data query instruction parsing result includes a current data query final test processor identifier and at least one current data query embedded sensor information; matching the current data query final test processor identifier with a pre-built identifier uniform resource locator mapping table to determine a target uniform resource locator; performing a data query in a pre-built time series server database based on each of the current data query embedded sensor information to obtain current embedded sensor data corresponding to each embedded sensor of the target final test processor corresponding to the target uniform resource locator; feeding back each of the current embedded sensor data to a target webpage dashboard, displaying each of the current embedded sensor data on the target webpage dashboard using a preset visualization method, and feeding back the display result to a target scanning terminal device.

[0093] Of course, the computer-executable instructions provided in the embodiments of the present invention, which include a computer-readable storage medium, are not limited to the method operations described above, but can also perform related operations in data querying based on the microelectromechanical system final test processor provided in any embodiment of the present invention.

[0094] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0095] It is worth noting that in the above embodiment of data query based on the final test processor of microelectromechanical system, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of the present invention.

[0096] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A data query method based on a microelectromechanical system (MEMS) final test processor, characterized in that, include: The data query system based on the microelectromechanical system final test processor receives the current data query instruction in real time, parses the current data query instruction, and obtains the parsing result of the current data query instruction. The parsing result of the current data query instruction includes the identifier of the final test processor to be queried and at least one embedded sensor information to be queried. Based on the current data to be queried, the final test processor identifier is matched with the pre-built identifier Uniform Resource Locator (URI) mapping table to determine the target URI; Based on the current data to be queried, the embedded sensor information is queried in the pre-built time series server database, and the current embedded sensor data of each embedded sensor corresponding to the target final test processor corresponding to the target Uniform Resource Locator is obtained respectively. The data from each of the currently embedded sensors is fed back to the target webpage dashboard, and the data from each of the currently embedded sensors is displayed on the target webpage dashboard in a preset visualization manner. The display results are then fed back to the target scanning terminal device. The system also includes: a data query system based on the microelectromechanical system (MEMS) final test processor, used to manage multiple MEMS final test processors; wherein each MEMS final test processor includes: an onboard communication module and multiple embedded sensors; each embedded sensor is used to collect real-time component description data of each test processor sub-component corresponding to the MEMS final test processor; and the real-time component description data is sent to the data query system based on the MEMS final test processor through the onboard communication module. The process further includes, after sending the real-time component description data to the data query system based on the microelectromechanical system final test processor: Real-time reception and parsing of real-time component description data corresponding to different microelectromechanical system final test processors; parsing to obtain the data query final test processor identifier and data values ​​of each embedded sensor corresponding to each microelectromechanical system final test processor. Each data query retrieves the final test processor identifier to match the corresponding Uniform Resource Locator (URI), and generates an identifier-URI mapping table. The final test processor identifier and embedded sensor data values ​​for each group of data queries, along with the identifier Uniform Resource Locator (URL) mapping table, are jointly stored in a time series server database corresponding to the data query system based on the final test processor of the microelectromechanical system (MEMS), thereby completing the construction of the time series server database.

2. The method according to claim 1, characterized in that, Before the data query system based on the microelectromechanical system final test processor receives the data query instruction in real time, parses the data query instruction, and obtains the data query instruction parsing result, the following steps are also included: By instructing the target scanning terminal device to scan the current QR code on the final test processor of the current microelectromechanical system, the scanning result of the current QR code is obtained; Each microelectromechanical system (MEMS) final test processor has a QR code printed on its exterior. Based on the acquired task of querying embedded sensor information for the current data to be queried, and combined with the current QR code scanning result, a current data query instruction is generated.

3. The method according to claim 1 or 2, characterized in that, The step of parsing the current data query instruction to obtain the parsing result includes: By parsing the current QR code scanning result corresponding to the current data query instruction, the final test processor identifier for the current data query is obtained. By parsing the current data query embedded sensor information task corresponding to the current data query instruction, at least one current data query embedded sensor information is obtained. Based on the final test processor identifier of the current data to be queried and at least one embedded sensor information of the current data to be queried, the parsing result of the current data query instruction is obtained.

4. The method according to claim 3, characterized in that, Before the data query system based on the microelectromechanical system final test processor receives the data query instruction in real time, parses the data query instruction, and obtains the data query instruction parsing result, the following steps are also included: Obtain historical component description data for each historical moment corresponding to the final test processor of different microelectromechanical systems; Based on the description data of each historical component, the data query final test processor identifier and the data values ​​of each historical embedded sensor are obtained respectively for each microelectromechanical system final test processor; The final test processor identifier and historical embedded sensor data values ​​of each group of data are jointly stored in the time series server database to complete the update and optimization of the constructed time series server database.

5. The method according to claim 4, characterized in that, The step of feeding back the currently embedded sensor data to the target webpage dashboard and displaying the currently embedded sensor data on the target webpage dashboard using a preset visualization method includes: The current embedded sensor data is fed back to the target webpage dashboard, and the embedded sensor data threshold corresponding to each of the embedded sensor data is obtained; The currently embedded sensor data includes at least one of the following: component vibration sensor data, component temperature sensor data, component humidity sensor data, and component machine status sensor data; The vibration sensor data, temperature sensor data, humidity sensor data, and machine status sensor data of the component are compared with their respective embedded sensor data thresholds to obtain threshold comparison results. Based on the threshold comparison results and combined with the data from each currently embedded sensor, the results are displayed on the target webpage dashboard in real time through visualization.

6. A data query device based on a microelectromechanical system final test processor, characterized in that, include: The current data query instruction parsing result determination module is used to receive the current data query instruction in real time through the data query system based on the microelectromechanical system final test processor, and parse the current data query instruction to obtain the current data query instruction parsing result; The parsing result of the current data query instruction includes the identifier of the final test processor to be queried and at least one embedded sensor information to be queried. The target Uniform Resource Locator (URI) determination result is used to query the final test processor identifier based on the current data to be searched, and match it with the pre-built identifier URI mapping table to determine the target URI; The current embedded sensor data acquisition module is used to query embedded sensor information based on the current data to be obtained, and to perform data query in a pre-built time series server database to obtain the current embedded sensor data of each embedded sensor corresponding to the target final test processor corresponding to the target Uniform Resource Locator. The result feedback module is used to feed back the data of each currently embedded sensor to the target webpage dashboard, and display the data of each currently embedded sensor on the target webpage dashboard in a preset visualization method, and feed back the display results to the target scanning terminal device; The system also includes: a data query system based on the microelectromechanical system (MEMS) final test processor, used to manage multiple MEMS final test processors; wherein each MEMS final test processor includes: an onboard communication module and multiple embedded sensors; each embedded sensor is used to collect real-time component description data of each test processor sub-component corresponding to the MEMS final test processor; and the real-time component description data is sent to the data query system based on the MEMS final test processor through the onboard communication module. The system also includes a time-series server database construction module, used for: after sending the real-time component description data to the data query system based on the microelectromechanical system final test processor, receiving and parsing the real-time component description data corresponding to different microelectromechanical system final test processors in real time, parsing to obtain the data query final test processor identifier and the data values ​​of each embedded sensor corresponding to each microelectromechanical system final test processor; matching the corresponding Uniform Resource Locator (URI) according to each data query final test processor identifier, and generating an identifier URI mapping table; and jointly storing each group of data query final test processor identifiers and embedded sensor data values, as well as the identifier URI mapping table, in the time-series server database corresponding to the data query system based on the microelectromechanical system final test processor, thereby completing the construction of the time-series server database.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements a data query method based on a microelectromechanical system final test processor as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause the processor to execute a data query method for a microelectromechanical system final test processor as described in any one of claims 1-5.

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