This invention discloses a work order requirement identification method and
system integrating
big data analysis, relating to the field of work order
data processing technology. It achieves accurate work order requirement identification through multi-module
collaboration and multi-
source data fusion. First, it obtains the original strings of multi-source candidate identifiers and converts them into half-
byte sequences. The half-
byte length is calculated, and the
tail padding type
label is determined based on the half-
byte length, while filtering out non-protocol pseudo-strings. The half-byte sequence is processed according to the
tail padding type
label to obtain a pure numeric half-byte sequence. A 14-bit numerical sequence is extracted, and a 15-bit standard IMEI is calculated. Then, a half-byte
verification sequence is generated in reverse, and a reversibility
verification flag is generated after comparison. Based on the reversibility
verification flag, the device
allocation code (TAC) is extracted, and the device information is obtained by querying the device
knowledge base in conjunction with the
tail padding type
label. The 15-bit standard IMEI, TAC, and device information are combined into a work order requirement identification triplet and written into the work order structured field, completing the work order requirement identification data encapsulation.