A Test Data Management System and Method for a Water-Control Explosion-Proof Electric Control Device

Abstract

The present invention discloses a test data management system and method for a water-controlled explosion-proof electric control device, relating to the technical field of test data management. The present invention collects the test data of the target device, and the interactive management terminal performs compression conversion on it. In this way, the situation of occupying too much local storage resources is avoided, and the transmission of the compressed test data effectively reduces the consumption of too much network resources during the transmission process; by dividing the test data after binary conversion, several groups of grouped strings and grouped sequences are obtained. At the same time, according to the occurrence frequencies of the grouped sequences and grouped strings, it is determined whether to perform binary mapping only on the grouped strings or to perform mapping on both the grouped sequences and grouped strings. This method not only considers the frequency of a single grouped string, but also considers the sequence frequency that appears after the combination of multiple grouped strings, thereby effectively reducing the capacity size of the transmitted data.

Description

Technical Field

[0001] The present invention relates to the technical field of test data management, and particularly to a test data management system and method for a water control explosion-proof electric control device. Background Art

[0002] A water control explosion-proof electric control device is a device specifically designed to achieve the explosion-proof function of electrical equipment by controlling water in an explosive hazardous environment;

[0003] In today's industrial field, especially in environments with explosion and fire risks such as oil, chemical, and coal mines, the reliability and safety of water control explosion-proof electric control devices are crucial;

[0004] With the continuous development of technology, the performance requirements for water control explosion-proof electric control devices are increasing day by day. To ensure their stable operation under harsh and dangerous working conditions, strict and comprehensive tests are required. During the test process, a large amount of test data will be generated, and this data contains key information about the device's performance, stability, safety, etc.;

[0005] However, due to the large amount of test data, storing and transmitting this data pose huge challenges. A large amount of data not only occupies a large amount of local storage space but also leads to low data transmission efficiency. Especially in some emergency situations, such as the moment when the device malfunctions, if the test data cannot be transmitted in real time quickly, it may delay the best opportunity for fault diagnosis and handling, thus triggering serious safety accidents;

[0006] For the large amount of test data, the current mainstream processing method is to compress it. By compressing, the data volume size is reduced to reduce its occupied space and shorten its transmission time. Currently, one compression method is to compress the test data volume based on frequency. For example, the dictionary algorithm uses shorter characters to replace frequently occurring words or phrases in the text to achieve efficient compression of the test data volume. However, this compression method does not consider the connection between words and phrases, and when there are words in a phrase, it can be further compressed;

[0007] To solve the above problems, the present invention proposes a solution. Summary of the Invention

[0008] The purpose of the present invention is to provide a test data management system and method for a water control explosion-proof electric control device to solve the problems raised in the above background art;

[0009] The purpose of the present invention can be achieved by the following technical solutions:

[0010] A test data management system for a water control explosion-proof electric control device, comprising:

[0011] An interaction management terminal for interactively managing the test data of a target device, where the test data includes multi-dimensional data of the target device under various test conditions;

[0012] After receiving the transmitted test data of the target device, the interaction management terminal performs binary conversion on it to obtain data to be mapped and converted;

[0013] Specify the grouping step size as 4, divide the data to be mapped and converted into several groups of grouped strings, and according to the positions of the several groups of grouped strings in the data to be mapped and converted, splice the grouped strings at two adjacent positions to obtain several grouped sequences;

[0014] Generate conversion data packets for several grouped strings according to the occurrence frequencies of several grouped strings and the occurrence frequencies of several grouped sequences according to a preset mapping conversion rule;

[0015] Transmit the conversion data packets of several grouped strings to the cloud test data management terminal in the order of generation of each conversion data packet, and the cloud test data management terminal restores and stores them.

[0016] Further, it further includes a test data acquisition terminal for acquiring the test data of the target device, and the multi-dimensions include pressure, temperature, humidity, current and voltage.

[0017] Further, the steps of dividing the data to be mapped and converted into several groups of grouped strings to obtain several grouped sequences are as follows:

[0018] S11: Perform binary conversion on the test data of the target device to obtain corresponding binary data, and re-label the binary data as the data to be mapped and converted;

[0019] S12: Specify the grouping step size as 4, and in the order from left to right, take every four characters of all the characters constituting the data to be mapped and converted as a group of grouped strings, and a group of grouped strings can be obtained;

[0020] S13: Mark the a groups of grouped strings as A1, A2,..., Aa in the order of their grouping, and then in the order of the grouped strings A1, A2,..., Aa, splice the grouped strings A1 and A2, A3 and A4,..., Aa-1 and Aa in sequence to obtain a corresponding grouped sequence;

[0021] Mark all the grouped sequences as D1, D2,..., Dd in the order of splicing of each grouped sequence. It should be noted here that the value of d is determined by a. If a is odd, the value of d is (a - 1) / 2, otherwise the value of d is a / 2.

[0022] A method for managing test data of a water control explosion-proof electric control device, comprising the following steps:

[0023] Step 1: The test data acquisition terminal acquires the test data of the target device and transmits it to the interaction management terminal;

[0024] Step 2: After receiving the test data of the target device, the interaction management terminal first performs a binary conversion on it to obtain the data to be mapped and converted;

[0025] Then, specifying the grouping step size as 4, the data to be mapped and converted is divided into several groups of grouped strings, and according to the positions of the several groups of grouped strings in the data to be mapped and converted, the grouped strings at two adjacent positions are spliced to obtain several grouped sequences;

[0026] After that, according to the occurrence frequencies of the several grouped strings and the occurrence frequencies of the several grouped sequences, conversion data packets of the several grouped strings are generated according to a preset mapping and conversion rule;

[0027] Finally, the conversion data packets of the several grouped strings are sequentially transmitted to the cloud test data management terminal according to the generation order of each conversion data packet;

[0028] Step 3: After receiving the transmission of several conversion data packets, the cloud test data management terminal restores and stores them.

[0029] Advantages of the present invention:

[0030] (1) In the present invention, the test data acquisition terminal acquires the test data of the target device, the interaction management terminal performs a binary conversion on the test data of the target device, and performs a compression conversion on the converted data, and transmits the compressed and converted data to the cloud test data management terminal for restoration and storage. In this way, it avoids the situation that too much local storage resources are occupied due to the large capacity of the test data, and the transmission of the compressed test data effectively reduces the consumption of too much network resources during the transmission process, reducing the transmission cost and time;

[0031] (2) When converting the test data in the present invention, by dividing the test data after binary conversion, several groups of grouped strings and grouped sequences are obtained. At the same time, according to the occurrence frequencies of the grouped sequences and the grouped strings, it is determined whether to perform only a binary mapping on the grouped strings, or to perform a mapping on both the grouped sequences and the grouped strings. This method not only considers the frequency of a single grouped string, but also considers the frequency of the sequence that appears after the combination of several grouped strings. Considering comprehensively, alternative characters are selected for compression, thereby effectively reducing the capacity size of the transmitted data and reducing the capacity size of the stored and transmitted test data volume. Description of the drawings

[0032] The present invention will be further described below in conjunction with the accompanying drawings.

[0033] Figure 1 is the system block diagram of the present invention;

[0034] Figure 2 is the method flowchart of the present invention. Specific embodiments

[0035] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0036] As Figure 1 、 2 shown, a test data management system and method for a water control explosion-proof electric control device include a test data acquisition terminal, an interactive management terminal, and a cloud test data management terminal;

[0037] The test data acquisition terminal is used to collect the test data of the target device. The test data includes multi-dimensional data of the target device under various test conditions, where the various test conditions are preset by the tester based on the application field of the target device;

[0038] In an embodiment of the present invention, the multi-dimensions include pressure, temperature, humidity, current, and voltage. In an embodiment of the present invention, the target device refers to a water control explosion-proof electric control device;

[0039] The test data acquisition terminal obtains the test data of the target device and transmits it to the interactive management terminal;

[0040] The interactive management terminal is used to perform interactive management on the test data of the target device. After receiving the transmitted test data of the target device, the interactive management terminal converts it according to the preset mapping conversion rules. The mapping conversion rules are as follows:

[0041] S11: Perform binary conversion on the test data of the target device to obtain the corresponding binary data, and re-label the binary data as the data to be mapped and converted;

[0042] S12: Specify the grouping step size as 4. In the order from left to right, group all the characters constituting the data to be mapped and converted into a group of character strings every four characters, and a group of grouping character strings can be obtained. It should be noted here that during the grouping process, if the number of remaining characters is less than 4, a group of conversion data packets is generated according to all the remaining characters;

[0043] S13: Mark the grouped strings in group a as A1, A2, ..., Aa in the order of their grouping. Then, in the order of the grouped strings A1, A2, ..., Aa, splice the grouped strings A1 and A2, A3 and A4, ..., Aa-1 and Aa successively to obtain a corresponding grouped sequence.

[0044] In the order of the splicing sequence of each grouped sequence, mark all the grouped sequences as D1, D2, ..., Dd successively. It should be noted here that the value of d is determined by a. If a is odd, the value of d is (a - 1) / 2. At this time, when splicing the grouped strings, up to Aa-2 and Aa, keep the grouped string Aa, and generate another set of conversion data packets according to the grouped string Aa. On the contrary, the value of d is a / 2, and the splicing ends at Aa-1 and Aa.

[0045] S14: Remove duplicates from the grouped sequences D1, D2, ..., Dd, and re-mark the remaining grouped sequences after deduplication as E1, E2, ..., Ee respectively, where 1 ≤ e ≤ d.

[0046] S15: Obtain the occurrence frequencies of the grouped sequences E1, E2, ..., Ee successively and mark them as F1, F2, ..., Fe. The occurrence frequencies of the grouped sequences E1, E2, ..., Ee refer to the number of grouped sequences that are consistent with the grouped sequences E1, E2, ..., Ee successively in the grouped sequences D1, D2, ..., Dd. Here, "consistent" means that the number of characters, content, and positions in the grouped sequences are all the same.

[0047] S16: Calculate and obtain the conjugate frequencies H1, H2, ..., He of the grouped sequences E1, E2, ..., Ee successively according to the preset calculation rules. The calculation rules are as follows:

[0048] S161: Obtain the occurrence frequency F1 of the grouped string that is consistent with the first four characters of the grouped sequence E1 in the order from left to right, and then obtain the occurrence frequency G1 of the grouped string that is consistent with the first four characters of the grouped sequence E1 in the order from right to left.

[0049] Calculate and obtain the conjugate frequency H1 of the grouped sequence E1 using the formula H1 = F1 * G1.

[0050] S162: Calculate and obtain the conjugate frequencies H1, H2, ..., He of the grouped sequences E1, E2, ..., Ee successively according to S161.

[0051] S17: Select the conjugate frequency with the largest value from the conjugate frequencies H1, H2, ..., He, and re-label it as Z1. Compare the magnitudes of Z1 and P1. If Z1 ≤ P1, generate a conversion data packet for the grouped strings A1, A2, ..., Aa according to a preset first generation rule. P1 is a preset conjugate frequency threshold, and the first generation rule is as follows:

[0052] S21: Remove duplicates from the grouped strings A1, A2, ..., Aa in S13, and re-label all the de-duplicated grouped strings as de-duplicated strings, denoted as Y1, Y2, ..., Yy, where y is the total number of de-duplicated grouped strings;

[0053] S22: Sequentially obtain the occurrence frequencies of the de-duplicated strings Y1, Y2, ..., Yy, and re-label the de-duplicated strings Y1, Y2, ..., Yy in descending order of occurrence frequency as X1, X2, ..., Xy. Here, it should be noted that in the case of a large batch of data, the value of y is default to be greater than or equal to 14. Therefore, in the following SS3, the association mapping is described with y being at least greater than 14;

[0054] S23: Establish an association mapping between the de-duplicated string X1 and the one-bit binary number 0, X2 and the one-bit binary number 1, X3 and the two-bit binary number 00, X4 and the two-bit binary number 01, X5 and the two-bit binary number 10, X6 and the two-bit binary number 11, X7 and the three-bit binary number 000, X8 and the three-bit binary number 001, X9 and the three-bit binary number 010, X10 and the three-bit binary number 011, X11 and the three-bit binary number 100, X12 and the three-bit binary number 101, X13 and the three-bit binary number 110, X14 and the three-bit binary number 111;

[0055] S24: Perform a consistency comparison between the grouped string A1 and the de-duplicated strings X1, X2, ..., Xy, obtain the de-duplicated string that is consistent with it, and determine whether an association mapping is established for the de-duplicated string. If there is a certain binary number in the de-duplicated string and its associated mapping, obtain the binary number corresponding to the de-duplicated string, and generate a conversion data packet for the grouped string A1 according to it. Otherwise, generate a conversion data packet for the grouped string A1 according to the grouped string A1 itself;

[0056] S25: Sequentially generate conversion data packets for the grouped strings A2, A3, ..., Aa in the order of the grouped strings A1, A2, ..., Aa;

[0057] The interactive management terminal sequentially transmits the conversion data packets of the grouped strings A1, A2, ..., Aa to the cloud test data management terminal in the order of the grouped strings A1, A2, ..., Aa;

[0058] S18: If Z1 > P1, at this time, generate conversion data packets for the grouped strings A1, A2, ..., Aa according to the preset second mapping rule;

[0059] S31: Select the conjugate frequencies with values greater than P1 from the conjugate frequencies H1, H2, ..., He, and obtain the quantity Q1 of the selected conjugate frequencies:

[0060] S32: Compare the magnitudes of Q1 and 2;

[0061] If Q1 ≥ 2, generate conversion data packets for the grouped strings A1, A2, ..., Aa according to the preset second generation rule. The second generation rule is as follows:

[0062] SS11: Then select the grouped sequences corresponding to the conjugate frequencies with the largest and second largest values from the conjugate frequencies H1, H2, ..., He as the first conversion sequence and the second conversion sequence;

[0063] Associate the first conversion sequence with a one-bit binary number 0, and associate the second conversion sequence with a one-bit binary number 1;

[0064] SS12: In the order from left to right, take the first 4 characters constituting the first conversion sequence as the leftward substring of the first conversion sequence, and take the last four characters as the rightward substring of the first conversion sequence. Similarly, obtain the leftward substring and the rightward substring of the second conversion sequence;

[0065] Associate the leftward substring of the first conversion sequence with a two-bit binary number 00, associate the rightward substring of the first conversion sequence with a two-bit binary number 01, associate the leftward substring of the second conversion sequence with a two-bit binary number 10, and associate the rightward substring of the second conversion sequence with a two-bit binary number 11;

[0066] SS13: Remove duplicates from the grouped strings A1, A2, ..., Aa in S13, re-label all the grouped strings after duplicate removal as de-duplicated strings, and mark them as Y1, Y2, ..., Yy, where y is the total number of grouped strings after duplicate removal;

[0067] SS14: Sequentially obtain the occurrence frequencies of the de-duplicated strings Y1, Y2, ..., Yy, and sequentially re-label the de-duplicated strings Y1, Y2, ..., Yy from largest to smallest occurrence frequency as X1, X2, ..., Xy. Here, it should be noted that in the case of a large batch of large-capacity data, the value of y is default to be greater than or equal to 14. Therefore, in the following SS3, the association mapping is described with y being at least greater than 14;

[0068] SS15: If any one of the left and right substrings of the deduplicated string X1 and the first conversion sequence, and the left and right substrings of the second conversion sequence is the same, no processing is performed. Otherwise, the deduplicated string X1 is associated and mapped with the three-bit binary number 000 in the order of the three-bit binary numbers 000, 001, 010, 011, 100, 101, 110, 111;

[0069] SS16: In the order of the deduplicated strings X1, X2,..., Xy, the deduplicated strings X1, X2,..., Xx, 1≤x≤y are sequentially associated and mapped;

[0070] SS17: The grouped string A1 is respectively compared with the deduplicated strings X1, X2,..., Xy for consistency, and the deduplicated strings that are the same as it are obtained, and it is determined whether to establish an associated mapping for the deduplicated strings. If there is a certain binary number in the deduplicated string that is associated and mapped with it, the binary number corresponding to the deduplicated string is obtained, and a conversion data packet of the grouped string A1 is generated according to it. Otherwise, a conversion data packet of the grouped string A1 is generated according to the grouped string A1 itself;

[0071] SS18: In the order of the grouped strings A1, A2,..., Aa, the conversion data packets of the grouped strings A2, A3,..., Aa are sequentially generated;

[0072] The interactive management terminal sequentially transmits the conversion data packets of the grouped strings A1, A2,..., Aa to the cloud test data management terminal in the order of the grouped strings A1, A2,..., Aa;

[0073] If Q1 = 1, the conversion data packets of the grouped strings A1, A2,..., Aa are generated according to the preset third generation rule. The third generation rule is as follows:

[0074] SS21: Then the grouped sequence corresponding to the conjugate frequency with the largest value among the conjugate frequencies H1, H2,..., He is selected as the first conversion sequence, and the first conversion sequence is associated and mapped with the one-bit binary number 0;

[0075] SS22: In the order from left to right, the first 4 characters constituting the first conversion sequence are used as the left substring of the first conversion sequence, and the last four characters are used as the right substring of the first conversion sequence;

[0076] The left substring of the first conversion sequence is associated and mapped with the two-bit binary number 00, and the right substring of the first conversion sequence is associated and mapped with the two-bit binary number 01;

[0077] SS23: Remove duplicates from the grouped strings A1, A2, ..., Aa in S13, and re-label all the de-duplicated grouped strings as de-duplicated strings, marked as Y1, Y2, ..., Yy, where y is the total number of de-duplicated grouped strings;

[0078] SS24: Sequentially obtain the occurrence frequencies of the de-duplicated strings Y1, Y2, ..., Yy, and re-label the de-duplicated strings Y1, Y2, ..., Yy as X1, X2, ..., Xy in descending order of the occurrence frequencies. It should be noted here that in the case of a large batch of large-capacity data, the value of y is default to be greater than or equal to 14. Therefore, in the following SS3, the association mapping is described with y being at least greater than 14;

[0079] SS25: If the de-duplicated string X1 is consistent with any one of the left and right substrings of the first conversion sequence, no processing is performed. Otherwise, in the order of one-bit binary number 1, two-bit binary numbers 10, 11, three-bit binary numbers 000, 001, 010, 011, 100, 101, 110, 111, first establish an association mapping between the de-duplicated string X1 and the three-bit binary number 000;

[0080] SS26: In the order of the de-duplicated strings X1, X2, ..., Xy, sequentially establish association mappings for the de-duplicated strings X1, X2, ..., Xx, where 1 ≤ x ≤ y;

[0081] SS27: Compare the grouped string A1 with the de-duplicated strings X1, X2, ..., Xy respectively to obtain the de-duplicated string that is consistent with it, and determine whether to establish an association mapping for the de-duplicated string. If there is a certain binary number associated with the de-duplicated string, obtain the binary number corresponding to the de-duplicated string, and generate a conversion data packet for the grouped string A1 according to it. Otherwise, generate a conversion data packet for the grouped string A1 according to the grouped string A1 itself;

[0082] SS28: In the order of the grouped strings A1, A2, ..., Aa, sequentially generate conversion data packets for the grouped strings A2, A3, ..., Aa;

[0083] The interactive management terminal sequentially transmits the conversion data packets of the grouped strings A1, A2, ..., Aa to the cloud test data management terminal in the order of the grouped strings A1, A2, ..., Aa;

[0084] A cloud test data management terminal is used to perform cloud storage management on the test data of a target device. After receiving the converted data packets of the transmitted packet strings A1, A2,..., Aa, the cloud test data management terminal obtains the data carried therein, splices the data in all the converted data packets in the order of reception, restores the spliced data to obtain the test data of the target device, and stores it, facilitating later testers to trace back and analyze the test data of the target device.

[0085] In the description of the specification, the description referring to terms such as "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0086] The above content is only an example and explanation of the present invention. Those skilled in the art of the present technology can make various modifications or supplements to the described specific embodiments or use similar methods for substitution, as long as they do not deviate from the invention or exceed the scope defined by the claims of the present invention, they should fall within the protection scope of the present invention.

[0087] The above has described in detail one embodiment of the present invention, but the content described is only the preferred embodiment of the present invention and cannot be considered as used to limit the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the application of the present invention should still fall within the scope covered by the patent of the present invention.

Claims

1. A test data management system for a water-controlled explosion-proof electric control device, characterized in that, Including: An interaction management terminal for interactively managing the test data of a target device, where the test data includes multi-dimensional data of the target device under various test conditions; After receiving the transmitted test data of the target device, the interaction management terminal performs base conversion on it to obtain data to be mapped and converted; Specify the grouping step size as 4, divide the data to be mapped and converted into several groups of grouped strings, and according to the positions of the several groups of grouped strings in the data to be mapped and converted, splice the grouped strings at two adjacent positions to obtain several grouped sequences; Generate conversion data packets for several grouped strings according to the occurrence frequencies of several grouped strings and the occurrence frequencies of several grouped sequences according to a preset mapping and conversion rule; Transmit the conversion data packets of several grouped strings to the cloud test data management terminal in the order of generation of each conversion data packet, and the cloud test data management terminal restores and stores them; The steps to obtain several grouped sequences are as follows: S11: Perform binary conversion on the test data of the target device to obtain corresponding binary data, and re-label the binary data as data to be mapped and converted; S12: Specify the grouping step size as 4, and in the order from left to right, group all the characters constituting the data to be mapped and converted into grouped strings with every four characters as a group, and a group of grouped strings can be obtained; S13: Mark the a groups of grouped strings as A1, A2,..., Aa in the order of their grouping, and then in the order of the grouped strings A1, A2,..., Aa, splice the grouped strings A1 and A2, A3 and A4,..., Aa-1 and Aa in sequence to obtain a corresponding grouped sequence; Mark all the grouped sequences as D1, D2,..., Dd in the order of splicing of each grouped sequence. Here, it should be noted that the value of d is determined by a. If a is odd, the value of d is (a - 1) / 2, otherwise the value of d is a / 2; S14: Remove duplicates from the grouped sequences D1, D2,..., Dd, and re-label the remaining all grouped sequences after deduplication as E1, E2,..., Ee, where 1 ≤ e ≤ d; S15: Obtain the occurrence frequencies of the grouped sequences E1, E2,..., Ee in sequence and mark them as F1, F2,..., Fe. The occurrence frequency of the grouped sequences E1, E2,..., Ee refers to the number of grouped sequences that are consistent with the grouped sequences E1, E2,..., Ee in sequence in the grouped sequences D1, D2,..., Dd, where being consistent means that the number, content, and position of the characters in the grouped sequence are all consistent; S16: Calculate and obtain the conjugate frequencies H1, H2,..., He of the grouped sequences E1, E2,..., Ee in sequence according to a preset calculation rule. The calculation rule is as follows: S161: In the order from left to right, obtain the occurrence frequency F1 of the grouped string that is consistent with the first four characters of the grouped sequence E1, and then in the order from right to left, obtain the occurrence frequency G1 of the grouped string that is consistent with the first four characters of the grouped sequence E1; Calculate and obtain the conjugate frequency H1 of the grouping sequence E1 using the formula H1 = F1 * G1; S162: Calculate and obtain the conjugate frequencies H1, H2,..., He of the grouping sequences E1, E2,..., Ee in sequence according to S161; S17: Select the conjugate frequency with the largest value from the conjugate frequencies H1, H2,..., He and relabel it as Z1. Compare the sizes of Z1 and P1. If Z1 ≤ P1, generate conversion data packets for the grouping strings A1, A2,..., Aa according to the preset first generation rule. P1 is the preset conjugate frequency threshold, and the first generation rule is as follows: S21: Remove duplicates from the grouping strings A1, A2,..., Aa in S13, and relabel all the de-duplicated grouping strings as de-duplicated strings, labeled as Y1, Y2,..., Yy, where y is the total number of de-duplicated grouping strings; S22: Obtain the occurrence frequencies of the de-duplicated strings Y1, Y2,..., Yy in sequence, and relabel the de-duplicated strings Y1, Y2,..., Yy in descending order of occurrence frequency as X1, X2,..., Xy. It should be noted here that in the case of batch large-capacity data, the value of y is default to be greater than or equal to 14. Therefore, in the following SS3, the association mapping is described with y being at least greater than 14; S23: Establish an association mapping between the de-duplicated string X1 and the one-bit binary number 0, X2 and the one-bit binary number 1, X3 and the two-bit binary number 00, X4 and the two-bit binary number 01, X5 and the two-bit binary number 10, X6 and the two-bit binary number 11, X7 and the three-bit binary number 000, X8 and the three-bit binary number 001, X9 and the three-bit binary number 010, X10 and the three-bit binary number 011, X11 and the three-bit binary number 100, X12 and the three-bit binary number 101, X13 and the three-bit binary number 110, X14 and the three-bit binary number 111; S24: Compare the grouping string A1 with the de-duplicated strings X1, X2,..., Xy for consistency, obtain the de-duplicated string that is consistent with it, and determine whether an association mapping is established for the de-duplicated string. If there is a certain binary number in the de-duplicated string that is associated with it, obtain the binary number corresponding to the de-duplicated string, and generate a conversion data packet for the grouping string A1 according to it. Otherwise, generate a conversion data packet for the grouping string A1 according to the grouping string A1 itself; S25: Generate conversion data packets for the grouping strings A2, A3,..., Aa in sequence according to the order of the grouping strings A1, A2,..., Aa; S18: If Z1 > P1, generate conversion data packets for the grouping strings A1, A2,..., Aa according to the preset second mapping rule at this time. The second mapping rule is as follows: S31: Select the conjugate frequencies greater than P1 from the conjugate frequencies H1, H2,..., He, and obtain the number Q1 of the selected conjugate frequencies; S32: Compare the sizes of Q1 and 2; If Q1 ≥ 2, then convert packets of the grouped strings A1, A2, ..., Aa are generated according to a preset second generation rule, and the second generation rule is as follows: SS11: Then select the grouped sequences corresponding to the conjugate frequencies with the largest and second largest values from the conjugate frequencies H1, H2, ..., He as the first conversion sequence and the second conversion sequence; Associate the first conversion sequence with a one-bit binary number 0, and associate the second conversion sequence with a one-bit binary data 1; SS12: In the order from left to right, use the first 4 characters that make up the first conversion sequence as the leftward substring of the first conversion sequence, and use the last four characters as the rightward substring of the first conversion sequence. Similarly, the leftward substring and the rightward substring of the second conversion sequence can be obtained; Associate the leftward substring of the first conversion sequence with a two-bit binary number 00, associate the rightward substring of the first conversion sequence with a two-bit binary number 01, associate the leftward substring of the second conversion sequence with a two-bit binary number 10, and associate the rightward substring of the second conversion sequence with a two-bit binary number 11; SS13: Remove duplicates from the grouped strings A1, A2, ..., Aa in S13, and re-label all the grouped strings after duplicate removal as de-duplicated strings, denoted as Y1, Y2, ..., Yy, where y is the total number of de-duplicated grouped strings; SS14: Obtain the occurrence frequencies of the de-duplicated strings Y1, Y2, ..., Yy in turn, and re-label the de-duplicated strings Y1, Y2, ..., Yy as X1, X2, ..., Xy in descending order of occurrence frequency. Here, it should be noted that in the case of batch large-capacity data, the value of y is default to be greater than or equal to 14. Therefore, in the following SS3, the association mapping is described with y being at least greater than 14; SS15: If the de-duplicated string X1 is consistent with any one of the left and right substrings of the first conversion sequence and the left and right substrings of the second conversion sequence, no processing is performed. Otherwise, in the order of three-bit binary numbers 000, 001, 010, 011, 100, 101, 110, 111, associate the de-duplicated string X1 with a three-bit binary number 000; SS16: In the order of the de-duplicated strings X1, X2, ..., Xy, perform association mapping on the de-duplicated strings X1, X2, ..., Xx, 1 ≤ x ≤ y in turn; SS17: Compare the grouped string A1 with the de-duplicated strings X1, X2, ..., Xy respectively to obtain the de-duplicated string that is consistent with it, and determine whether to establish an association mapping for the de-duplicated string. If there is a certain binary number associated with the de-duplicated string, obtain the binary number corresponding to the de-duplicated string, and generate a conversion packet of the grouped string A1 according to it. Otherwise, generate a conversion packet of the grouped string A1 according to the grouped string A1 itself; SS18: Generate conversion data packets for grouped strings A2, A3, ..., Aa in sequence according to the sequence of grouped strings A1, A2, ..., Aa. If Q1 = 1, generate conversion data packets for grouped strings A1, A2, ..., Aa according to a preset third generation rule.

2. The test data management system for a water-controlled explosion-proof electric control device according to claim 1, characterized in that It further includes a test data acquisition terminal for acquiring test data of the target device, and the multi-dimensions include pressure, temperature, humidity, current, and voltage.

3. A test data management method for a water-controlled explosion-proof electric control device, characterized in that, It includes the following steps: Step 1: The test data acquisition terminal acquires the test data of the target device and transmits it to the interaction management terminal. Step 2: After receiving the test data of the target device, the interaction management terminal first performs base conversion on it to obtain the data to be mapped and converted. Specify the grouping step size as 4, divide the data to be mapped and converted into several grouped strings, and according to the positions of the several grouped strings in the data to be mapped and converted, splice the grouped strings at two adjacent positions to obtain several grouped sequences. Generate conversion data packets for several grouped strings according to the occurrence frequencies of the several grouped strings and the occurrence frequencies of the several grouped sequences according to a preset mapping and conversion rule. Transmit the conversion data packets of several grouped strings to the cloud test data management terminal in sequence according to the generation order of each conversion data packet. Step 3: After receiving and transmitting several conversion data packets, the cloud test data management terminal restores and stores them. The steps to obtain several grouped sequences are as follows: S11: Perform binary conversion on the test data of the target device to obtain the corresponding binary data, and re-label the binary data as the data to be mapped and converted. S12: Specify the grouping step size as 4, and according to the order from left to right, group all the characters constituting the data to be mapped and converted into grouped strings with every four characters as a group, and a group of grouped strings can be obtained. S13: Mark the a groups of grouped strings as A1, A2, ..., Aa in sequence according to their grouping order, and then according to the order of grouped strings A1, A2, ..., Aa, splice grouped strings A1 and A2, A3 and A4, ..., Aa - 1 and Aa in sequence to obtain a corresponding grouped sequence. Mark all the grouped sequences as D1, D2, ..., Dd in sequence according to the sequence of splicing of each grouped sequence. It should be noted here that the value of d is determined by a. If a is odd, the value of d is (a - 1) / 2, otherwise the value of d is a / 2. S14: Remove duplicates from grouped sequences D1, D2, ..., Dd, and re-label the remaining all grouped sequences after deduplication as E1, E2, ..., Ee, where 1 ≤ e ≤ d. S15: Obtain the occurrence frequencies of the grouped sequences E1, E2, …, Ee in sequence and mark them as F1, F2, …, Fe. The occurrence frequencies of the grouped sequences E1, E2, …, Ee refer to the number of grouped sequences in the grouped sequences D1, D2, …, Dd that are successively consistent with the grouped sequences E1, E2, …, Ee. Here, being consistent means that the number of characters, content, and positions in the grouped sequences are all consistent; S16: Calculate and obtain the conjugate frequencies H1, H2, …, He of the grouped sequences E1, E2, …, Ee in sequence according to a preset calculation rule. The calculation rule is as follows: S161: Obtain the occurrence frequency F1 of the grouped string that is consistent with the first four characters of the grouped sequence E1 in the order from left to right, and then obtain the occurrence frequency G1 of the grouped string that is consistent with the first four characters of the grouped sequence E1 in the order from right to left; Calculate and obtain the conjugate frequency H1 of the grouped sequence E1 using the formula H1 = F1 * G1; S162: Calculate and obtain the conjugate frequencies H1, H2, …, He of the grouped sequences E1, E2, …, Ee in sequence according to S161; S17: Select the conjugate frequency with the largest value from the conjugate frequencies H1, H2, …, He and re - mark it as Z1. Compare the magnitudes of Z1 and P1. If Z1 ≤ P1, generate a conversion data packet for the grouped strings A1, A2, …, Aa according to a preset first generation rule. P1 is a preset conjugate frequency threshold. The first generation rule is as follows: S21: Remove duplicates from the grouped strings A1, A2, …, Aa in S13, and re - label all the de - duplicated grouped strings as de - duplicated strings, marked as Y1, Y2, …, Yy. y is the total number of de - duplicated grouped strings; S22: Obtain the occurrence frequencies of the de - duplicated strings Y1, Y2, …, Yy in sequence, and re - mark the de - duplicated strings Y1, Y2, …, Yy as X1, X2, …, Xy in the order from the largest to the smallest occurrence frequency. It should be noted that in the case of a large batch of data, the value of y is default greater than or equal to 14. Therefore, in the following SS3, the association mapping is described with y at least greater than 14; S23: Establish an association mapping between the de - duplicated string X1 and the one - bit binary number 0, X2 and the one - bit binary number 1, X3 and the two - bit binary number 00, X4 and the two - bit binary number 01, X5 and the two - bit binary number 10, X6 and the two - bit binary number 11, X7 and the three - bit binary number 000, X8 and the three - bit binary number 001, X9 and the three - bit binary number 010, X10 and the three - bit binary number 011, X11 and the three - bit binary number 100, X12 and the three - bit binary number 101, X13 and the three - bit binary number 110, X14 and the three - bit binary number 111; S24: Consistently compare the grouped string A1 with the deduplicated strings X1, X2, ..., Xy to obtain the deduplicated string that is consistent with it, and determine whether to establish an associated mapping for the deduplicated string. If there is a certain binary number in the deduplicated string and its associated mapping, obtain the binary number corresponding to the deduplicated string, and generate a conversion data packet for the grouped string A1 based on it. Otherwise, generate a conversion data packet for the grouped string A1 based on the grouped string A1 itself; S25: Generate conversion data packets for the grouped strings A2, A3, ..., Aa in sequence according to the order of the grouped strings A1, A2, ..., Aa; S18: If Z1 > P1, at this time, generate conversion data packets for the grouped strings A1, A2, ..., Aa according to the preset second mapping rule. The second mapping rule is as follows: S31: Select the conjugate frequencies with values greater than P1 from the conjugate frequencies H1, H2, ..., He, and obtain the quantity Q1 of the selected conjugate frequencies; S32: Compare the size of Q1 and 2; If Q1 ≥ 2, generate conversion data packets for the grouped strings A1, A2, ..., Aa according to the preset second generation rule. The second generation rule is as follows: SS11: Select the grouped sequences corresponding to the conjugate frequencies with the largest and second largest values from the conjugate frequencies H1, H2, ..., He as the first conversion sequence and the second conversion sequence; Establish an associated mapping between the first conversion sequence and a one-bit binary number 0, and establish an associated mapping between the second conversion sequence and a one-bit binary number 1; SS12: In the order from left to right, take the first 4 characters that make up the first conversion sequence as the leftward substring of the first conversion sequence, and take the last four characters as the rightward substring of the first conversion sequence. Similarly, obtain the leftward substring and the rightward substring of the second conversion sequence; Establish an associated mapping between the leftward substring of the first conversion sequence and a two-bit binary number 00, establish an associated mapping between the rightward substring of the first conversion sequence and a two-bit binary number 01, establish an associated mapping between the leftward substring of the second conversion sequence and a two-bit binary number 10, and establish an associated mapping between the rightward substring of the second conversion sequence and a two-bit binary number 11; SS13: Deduplicate the grouped strings A1, A2, ..., Aa in S13, and re-label all the deduplicated grouped strings as deduplicated strings, marked as Y1, Y2, ..., Yy, where y is the total number of deduplicated grouped strings; SS14: Sequentially obtain the occurrence frequencies of the deduplicated strings Y1, Y2, ..., Yy, and re-label the deduplicated strings Y1, Y2, ..., Yy in descending order of occurrence frequency as X1, X2, ..., Xy. Here, it should be noted that in the case of a large batch of large-capacity data, the value of y is default to be greater than or equal to 14. Therefore, in the following SS3, the establishment of the associated mapping is described with y being at least greater than 14; SS15: If any one of the left and right substrings of the deduplicated string X1 and the first conversion sequence, and the left and right substrings of the second conversion sequence is consistent, no processing is performed. Otherwise, the deduplicated string X1 is associated and mapped with the three-bit binary number 000 in the order of the three-bit binary numbers 000, 001, 010, 011, 100, 101, 110, 111; SS16: In the order of the deduplicated strings X1, X2,..., Xy, the deduplicated strings X1, X2,..., Xx, 1≤x≤y are sequentially associated and mapped; SS17: The grouped string A1 is compared with the deduplicated strings X1, X2,..., Xy for consistency respectively to obtain the deduplicated string that is consistent with it, and it is determined whether to establish an association mapping for the deduplicated string. If there is a certain binary number associated with the deduplicated string, the binary number corresponding to the deduplicated string is obtained, and the conversion data packet of the grouped string A1 is generated according to it. Otherwise, the conversion data packet of the grouped string A1 is generated according to the grouped string A1 itself; SS18: In the order of the grouped strings A1, A2,..., Aa, the conversion data packets of the grouped strings A2, A3,..., Aa are sequentially generated; If Q1 = 1, the conversion data packets of the grouped strings A1, A2,..., Aa are generated according to the preset third generation rule.

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