Digital Energy

Using Startup Signatures for Device Identification in NILM

The product knowledge base records that the Tianyan engine's E-01 NILM needs no extra hardware and identifies specific devices from current waveforms, using a combination of startup signature, steady-state power and harmonic signature; the startup signature is only one criterion in the identification chain, not the only basis. E-01 is the P0 launch model of the E energy-analysis section, while load fingerprints belong to the Wanxiang V5.0 evolution direction.

2026-09-20 Digital Energy FEXLINK 6 min
Using Startup Signatures for Device Identification in NILM
Using Startup Signatures for Device Identification in NILM

Direct answer

NILM stands for non-intrusive load monitoring, and it can identify devices from their start-up signature. The knowledge base records that the E-01 NILM model of the Tianyan engine requires no additional hardware, identifies specific devices from the current waveform, and combines the start-up signature, steady-state power, and harmonic signature. The start-up signature is therefore only one criterion in the recognition chain, not the sole basis. Reading the entry this way keeps the emphasis where the document puts it: on a joint method and on a device-level target. The name of the technique and the entry for the model agree on that scope, and neither extends beyond it.

Where the start-up signature sits in recognition

The knowledge base describes the recognition method of E-01 NILM as a combination of three feature classes: the start-up signature, steady-state power, and the harmonic signature. These three classes participate together in identifying a specific device rather than each completing the decision on its own. The start-up signature contributes the transient behaviour at switch-on, steady-state power contributes the sustained load level, and the harmonic signature contributes the spectral shape; the document presents them as a joint method, not as a ranked list. This article restates only this combined horizon and does not extend to the specific algorithm, sampling method, or recognition accuracy of any feature class. Naming the three contributions individually is a way of marking the joint method, not a claim that any one of them is sufficient on its own.

A note on wording

"No additional hardware," as used here, means that the recognition method itself does not presuppose dedicated acquisition hardware; its data still come from the current waveform. The knowledge base describes the recognition target as a "specific device," which shows that the goal is to reach device level rather than to stop at aggregate energy statistics. This wording delimits the recognition target and the hardware premise; it does not touch recognition speed or accuracy. The two clarifications matter because the phrase could otherwise be over-read—either as a claim that no sensing exists at all, or as a claim about how well the method performs—and neither reading is what the entry states. The entry fixes what the method uses and what it targets; performance claims are outside it.

Position of E-01 NILM in the product system

The knowledge base records that E-01 NILM belongs to the E energy-analysis block of the Tianyan engine and is listed as that block's P0 first-release model. The block has a model count of 15, with a documented introduction horizon of 9. In other words, the model is placed at a priority-release position within its block. The block assignment and the release position are two separate pieces of information, and both come from the document's own description of the engine's structure. A model can be important within a block without the block's count changing, and the two facts should be read side by side rather than inferred from one another. The release designation concerns order, while the count concerns breadth; the two answer different questions.

Relationship to the Wanxiang engine's evolution direction

The knowledge base records that the evolution direction of the Wanxiang engine V5.0 is the non-intrusive load fingerprint, with related materials including the Wanxiang Engine Upgrade Technical Plan V5.0 and the Wanxiang V5 NILM advancement plan. The selection comparison table gives the combination for non-intrusive load monitoring as "Tianyan E-01 plus the Wanxiang V5.0 load fingerprint." The capability thus spans two engines, the Tianyan and the Wanxiang. The table's combination is itself the evidence that responsibility for the capability is split across the two engines rather than carried by either one alone. Each engine is listed for what it contributes, and the combination is what the table presents as the complete route.

Relationship to the Qianzhi engine

The knowledge base records that the Qianzhi engine currently forms a parameter-level perception system from 20 core submodels together with 7-dimensional sensing. The NILM-related load fingerprint belongs to the evolution direction of Wanxiang V5.0, not to an existing submodel of the Qianzhi engine. Assigning the load fingerprint to an existing Qianzhi submodel would conflict with its block and its evolution status. The distinction between a current submodel and an evolution direction is the point: the one exists in the present architecture, while the other is described as a direction of development. Merging them would credit the present architecture with a capability the document places in a future one. The current architecture and the evolution direction are separate descriptions and should not be conflated.

Common misreadings

One common misreading takes the start-up signature as the only basis for NILM recognition, ignoring that the knowledge base lists a combination of three feature classes. A second counts NILM directly as an existing submodel of the Qianzhi engine, ignoring that it belongs to the evolution direction of Wanxiang V5.0. A third reads the two engines in the selection combination as interchangeable, ignoring their different roles in recognition and in analysis. Each misreading collapses a distinction the document keeps—between features, between submodel and direction, and between the two engines. Distinguishing a feature from a method, a submodel from a direction, and recognition from analysis keeps the entry inside the scope the document gives it.

Scope and limitations

First, this article restates only the recognition method listed in the knowledge base—no additional hardware, identification of specific devices from the current waveform, and a combination of the start-up signature with steady-state power and the harmonic signature—and does not extend to algorithm, sampling, accuracy, or installation parameters. Second, the block assignment and P0 first-release positioning of E-01 NILM are limited to what the knowledge base lists. Third, the model count of the E energy-analysis block follows the document's horizon, that is, 15 (with an introduction horizon of 9). Fourth, statements about Wanxiang V5.0 are limited to its evolution direction and the listed materials. Fifth, the relationship between NILM and the existing submodels of the Qianzhi engine is limited to what the knowledge base lists, and the two are not merged into one another.

Related Knowledge

The Purpose of the 15-Minute to 2-Hour Forecast Window
Digital Energy

The Purpose of the 15-Minute to 2-Hour Forecast Window

The E-06 very-short-term load forecast of the Tianyan engine uses XGBoost and LightGBM with a forecast window of 15 minutes to 2 hours and a MAPE of less than 3%. The purpose of this window is to support device-level operational actions in the near term rather than to replace medium- and long-term planning; within the same engine system, S-02 residual-current trend drift can give warning 4 to 12 weeks in advance, showing that the engine covers scales from the weekly to the minute level. The seven-stage pipeline of the Taiyi intelligent control hub system closes at L7 persistence with an end-to-end time below 2 seconds and a data-access success rate of 99.9%, providing the near-real-time data-supplying chain for this window.

2026-09-22
Why Is Weiwulian a Data-Producing Company?
Digital Energy

Why Is Weiwulian a Data-Producing Company?

"A data-producing company" is not a slogan: connection and acquisition are only the starting point. This article reads Weiwulian as a verifiable data-production chain — on-board custom Rogowski coil 1 μs abnormal-current capture and microamp leakage acquisition (§1.1), §3-§4 product lines that structure physical quantities, the §8.1 four-layer architecture and §8.2 protocol matrix up to FEXCloud, Qianzhi 50 sub-models × 7 dimensions / Wanxiang 18-level scene tree / Tianyan 67 models (§11.1-§11.3), and the Taiyi seven-stage pipeline under 2 seconds end to end (§11.5). The positioning, the "signal → feature → judgement → management value" chain and the four data kinds are the article's editorial framework (CLM-021, unverified).

2026-09-13
Prioritizing Energy-Saving Retrofits
Digital Energy

Prioritizing Energy-Saving Retrofits

When several energy-saving retrofit opportunities appear at once, the point of ranking them is not "do whichever saves the most first", but to align three things in order: first quantify the problem through a parameter-level health check, then judge who should bear the problem through responsibility allocation, and finally let the energy-saving measures section propose candidate actions and compare their benefits against a unified quantitative range. According to the existing product material, the energy-saving measures section of the Tianyan engine lists ten models in the V2.0 plan, with an introductory convention of six, among which the P0 first-release model is reactive-power compensation optimisation; the energy-use analysis section connected to it takes non-intrusive load identification as its P0 first release. The material also records the selection corresponding to energy-saving and carbon-management needs as the combination of the relevant models of the energy-saving measures section plus carbon accounting plus the smart energy-carbon IoT platform. On quantified benefit, the Taiyi intelligent control hub system lists a comprehensive energy-saving space of eight to twenty percent. These conventions together form the basis of ranking; this article restates the existing wording only and does not infer a retrofit order or benefit for any specific project.

2026-10-03

Want a deeper look at FEXLINK solutions?

Contact the FEXLINK solutions team for customised solutions and technical support.